diff --git a/annotated.html b/annotated.html index a32cb967e..c5ba60c95 100644 --- a/annotated.html +++ b/annotated.html @@ -138,41 +138,43 @@  Cunderlying_value_type< T, true >  CAppliedFunctionExpression referencing the result of a function call  CWrapFunctionWraps an std::function to return an expression - ▼NproximalHolds some standard proximals - ►Ndetails - CDelayedProximalFunctionExpression referencing a lazy proximal function call - CDelayedProximalEnveloppeFunctionExpression referencing a lazy function call to envelope proximal - CL1TightFrameL1 proximal, including linear transform - ►CL1L1 proximal, including linear transform - CBreaker - CDiagnosticHow did calling L1 go? - CDiagnosticAndResultResult from calling L1 - CFistaMixing - CNoMixing - CEuclidianNormProximal of euclidian norm - CL2NormProximal for the L2 norm - CL2BallProximal for indicator function of L2 ball - CWeightedL2Ball - CTranslationTranslation over proximal function - ▼Nutilities - Cbad_lexical_castException to be thrown by lexical_cast (below) - ▼Nwavelets - CSARASparsity Averaging Reweighted Analysis - ►CWaveletDataHolds wavelets coefficients - CDirectFilterHolds filters for direct transform - CWaveletPerforms direct and indirect wavelet transforms - ▼CConjugateGradientSolves $Ax = b$ for $x$, given $A$ and $b$ - CDiagnosticValues indicating how the algorithm ran - CDiagnosticAndResultValues indicating how the algorithm ran and its result; - CExceptionRoot exception for sopt - CLinearTransformJoins together direct and indirect operators - CORTsessionSopt interface class to hold a ONNXrt session - Cis_complexTrue if underlying type is complex - Cis_complex< std::complex< T >, void >True if underlying type is complex - CRelativeVariation - CScalarRelativeVariation - CSamplingAn operator that samples a set of measurements - CCData + ▼Nlogging + CLogLogging system for controlled & formatted writing to stdout + ▼NproximalHolds some standard proximals + ►Ndetails + CDelayedProximalFunctionExpression referencing a lazy proximal function call + CDelayedProximalEnveloppeFunctionExpression referencing a lazy function call to envelope proximal + CL1TightFrameL1 proximal, including linear transform + ►CL1L1 proximal, including linear transform + CBreaker + CDiagnosticHow did calling L1 go? + CDiagnosticAndResultResult from calling L1 + CFistaMixing + CNoMixing + CEuclidianNormProximal of euclidian norm + CL2NormProximal for the L2 norm + CL2BallProximal for indicator function of L2 ball + CWeightedL2Ball + CTranslationTranslation over proximal function + ▼Nutilities + Cbad_lexical_castException to be thrown by lexical_cast (below) + ▼Nwavelets + CSARASparsity Averaging Reweighted Analysis + ►CWaveletDataHolds wavelets coefficients + CDirectFilterHolds filters for direct transform + CWaveletPerforms direct and indirect wavelet transforms + ▼CConjugateGradientSolves $Ax = b$ for $x$, given $A$ and $b$ + CDiagnosticValues indicating how the algorithm ran + CDiagnosticAndResultValues indicating how the algorithm ran and its result; + CExceptionRoot exception for sopt + CLinearTransformJoins together direct and indirect operators + CORTsessionSopt interface class to hold a ONNXrt session + Cis_complexTrue if underlying type is complex + Cis_complex< std::complex< T >, void >True if underlying type is complex + CRelativeVariation + CScalarRelativeVariation + CSamplingAn operator that samples a set of measurements + CCData  ▼CDummyAlgorithmMinimum set of functions and type aliases needed by reweighting  CDiagnosticAndResult  CGProximal diff --git a/benchmarks_2conjugate__gradient_8cc.html b/benchmarks_2conjugate__gradient_8cc.html index d6fde807d..2e8d9eb42 100644 --- a/benchmarks_2conjugate__gradient_8cc.html +++ b/benchmarks_2conjugate__gradient_8cc.html @@ -91,29 +91,30 @@ diff --git a/benchmarks_2conjugate__gradient_8cc__incl.map b/benchmarks_2conjugate__gradient_8cc__incl.map index 0c5653d34..274f43bd2 100644 --- a/benchmarks_2conjugate__gradient_8cc__incl.map +++ b/benchmarks_2conjugate__gradient_8cc__incl.map @@ -1,25 +1,26 @@ - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/benchmarks_2conjugate__gradient_8cc__incl.md5 b/benchmarks_2conjugate__gradient_8cc__incl.md5 index 3eb9e262a..e24cf724b 100644 --- a/benchmarks_2conjugate__gradient_8cc__incl.md5 +++ b/benchmarks_2conjugate__gradient_8cc__incl.md5 @@ -1 +1 @@ -85ee390f6a9f0422840f445dd2435318 \ No newline at end of file +382fe7d9182a1421a71d9820eb6da66d \ No newline at end of file diff --git a/benchmarks_2conjugate__gradient_8cc__incl.png b/benchmarks_2conjugate__gradient_8cc__incl.png index 0b4212d5b..9ed6bc173 100644 Binary files a/benchmarks_2conjugate__gradient_8cc__incl.png and b/benchmarks_2conjugate__gradient_8cc__incl.png differ diff --git a/benchmarks_2l1__proximal_8cc.html b/benchmarks_2l1__proximal_8cc.html index f78ca0369..5ba7b9166 100644 --- a/benchmarks_2l1__proximal_8cc.html +++ b/benchmarks_2l1__proximal_8cc.html @@ -93,30 +93,31 @@ diff --git a/benchmarks_2l1__proximal_8cc__incl.map b/benchmarks_2l1__proximal_8cc__incl.map index f92d11fae..95b08dbe1 100644 --- a/benchmarks_2l1__proximal_8cc__incl.map +++ b/benchmarks_2l1__proximal_8cc__incl.map @@ -1,26 +1,27 @@ - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/benchmarks_2l1__proximal_8cc__incl.md5 b/benchmarks_2l1__proximal_8cc__incl.md5 index 87e0e65da..d3a39f3e4 100644 --- a/benchmarks_2l1__proximal_8cc__incl.md5 +++ b/benchmarks_2l1__proximal_8cc__incl.md5 @@ -1 +1 @@ -d2c7231b54c981605aa2a3d983016cb4 \ No newline at end of file +d02f63ed1328da758804a303724aec54 \ No newline at end of file diff --git a/benchmarks_2l1__proximal_8cc__incl.png b/benchmarks_2l1__proximal_8cc__incl.png index bdb11772a..793077acf 100644 Binary files a/benchmarks_2l1__proximal_8cc__incl.png and b/benchmarks_2l1__proximal_8cc__incl.png differ diff --git a/bisection__method_8cc.html b/bisection__method_8cc.html index 6c3ba81f8..d5e159265 100644 --- a/bisection__method_8cc.html +++ b/bisection__method_8cc.html @@ -95,25 +95,26 @@ @@ -278,15 +279,15 @@

Definition at line 16 of file bisection_method.cc.

16  {
17  using namespace sopt;
-
18  sopt::logging::set_level("debug");
+
18  sopt::logging::set_level("debug");
19  std::function<Scalar(Scalar)> const func = [](const Scalar &x) -> Scalar { return x * x * x; };
20  constexpr Scalar x0 = 0;
21  const Scalar x0_est = bisection_method(func(x0), func, a, b, tol);
22  CHECK(std::abs(x0_est - x0) <= tol);
23 }
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
-

References a, b, sopt::bisection_method(), sopt::logging::set_level(), and tol.

+

References a, b, sopt::bisection_method(), sopt::logging::set_level(), and tol.

diff --git a/bisection__method_8cc__incl.map b/bisection__method_8cc__incl.map index 6fac10b39..451aac92a 100644 --- a/bisection__method_8cc__incl.map +++ b/bisection__method_8cc__incl.map @@ -1,21 +1,22 @@ - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + diff --git a/bisection__method_8cc__incl.md5 b/bisection__method_8cc__incl.md5 index d2eab088b..801268855 100644 --- a/bisection__method_8cc__incl.md5 +++ b/bisection__method_8cc__incl.md5 @@ -1 +1 @@ -fd17cee29e121f2382d0373b1b14d42f \ No newline at end of file +f35b343675cbf5ec243e421161df7762 \ No newline at end of file diff --git a/bisection__method_8cc__incl.png b/bisection__method_8cc__incl.png index d7fa6ff48..ec17e1aac 100644 Binary files a/bisection__method_8cc__incl.png and b/bisection__method_8cc__incl.png differ diff --git a/bisection__method_8cc_source.html b/bisection__method_8cc_source.html index ced4a581b..6b3ace008 100644 --- a/bisection__method_8cc_source.html +++ b/bisection__method_8cc_source.html @@ -96,7 +96,7 @@
15 constexpr Scalar tol = 1e-4;
16 TEST_CASE("Bisection x^3") {
17  using namespace sopt;
-
18  sopt::logging::set_level("debug");
+
18  sopt::logging::set_level("debug");
19  std::function<Scalar(Scalar)> const func = [](const Scalar &x) -> Scalar { return x * x * x; };
20  constexpr Scalar x0 = 0;
21  const Scalar x0_est = bisection_method(func(x0), func, a, b, tol);
@@ -124,7 +124,7 @@
a
constexpr Scalar a
Definition: bisection_method.cc:13
t_Matrix
sopt::Matrix< Scalar > t_Matrix
Definition: bisection_method.cc:11
bisection_method.h
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
sopt::t_real
double t_real
Root of the type hierarchy for real numbers.
Definition: types.h:17
sopt::bisection_method
std::enable_if< std::is_same< t_real, K >::value, K >::type bisection_method(const K &function_value, const std::function< K(K)> &func, const K &a, const K &b, const t_real &rel_convergence=1e-4)
Find root to a function within an interval.
Definition: bisection_method.h:18
diff --git a/bisection__method_8h.html b/bisection__method_8h.html index f4e453a86..51813051b 100644 --- a/bisection__method_8h.html +++ b/bisection__method_8h.html @@ -95,21 +95,22 @@
diff --git a/bisection__method_8h__incl.map b/bisection__method_8h__incl.map index 8a0120c60..e715ac29e 100644 --- a/bisection__method_8h__incl.map +++ b/bisection__method_8h__incl.map @@ -1,17 +1,18 @@ - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + diff --git a/bisection__method_8h__incl.md5 b/bisection__method_8h__incl.md5 index 2fcde9cbe..0c10f518b 100644 --- a/bisection__method_8h__incl.md5 +++ b/bisection__method_8h__incl.md5 @@ -1 +1 @@ -289975a161f60be36c2016100ce236fe \ No newline at end of file +de192bf415453bf8ca33271e05402ef9 \ No newline at end of file diff --git a/bisection__method_8h__incl.png b/bisection__method_8h__incl.png index 497d1a706..e0c3c4c86 100644 Binary files a/bisection__method_8h__incl.png and b/bisection__method_8h__incl.png differ diff --git a/bisection__method_8h_source.html b/bisection__method_8h_source.html index c7e07ebff..b3e877c1e 100644 --- a/bisection__method_8h_source.html +++ b/bisection__method_8h_source.html @@ -143,7 +143,7 @@
SOPT_THROW
#define SOPT_THROW(MSG)
Definition: exception.h:46
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
sopt::t_real
double t_real
Root of the type hierarchy for real numbers.
Definition: types.h:17
sopt::bisection_method
std::enable_if< std::is_same< t_real, K >::value, K >::type bisection_method(const K &function_value, const std::function< K(K)> &func, const K &a, const K &b, const t_real &rel_convergence=1e-4)
Find root to a function within an interval.
Definition: bisection_method.h:18
diff --git a/cdata_8h.html b/cdata_8h.html index 5d071fcc4..43b08a6a8 100644 --- a/cdata_8h.html +++ b/cdata_8h.html @@ -93,27 +93,28 @@
diff --git a/cdata_8h__incl.map b/cdata_8h__incl.map index 6fea1d0da..dbf45eb3c 100644 --- a/cdata_8h__incl.map +++ b/cdata_8h__incl.map @@ -1,23 +1,24 @@ - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/cdata_8h__incl.md5 b/cdata_8h__incl.md5 index faa58eabf..6927639b8 100644 --- a/cdata_8h__incl.md5 +++ b/cdata_8h__incl.md5 @@ -1 +1 @@ -65fa3fd2ad7b0d356f8a500e8fcba742 \ No newline at end of file +2a997188ef28c8fd57f84f5661b68df2 \ No newline at end of file diff --git a/cdata_8h__incl.png b/cdata_8h__incl.png index d2f89988f..de7dc63d1 100644 Binary files a/cdata_8h__incl.png and b/cdata_8h__incl.png differ diff --git a/chained__operators_8cc.html b/chained__operators_8cc.html index 5145d6c86..3bc2a17ad 100644 --- a/chained__operators_8cc.html +++ b/chained__operators_8cc.html @@ -95,29 +95,30 @@ - - + + - - - - + + + + - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + +
diff --git a/chained__operators_8cc__incl.map b/chained__operators_8cc__incl.map index 35a3f790a..3205344b1 100644 --- a/chained__operators_8cc__incl.map +++ b/chained__operators_8cc__incl.map @@ -1,27 +1,28 @@ - - + + - - - - + + + + - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + diff --git a/chained__operators_8cc__incl.md5 b/chained__operators_8cc__incl.md5 index 91d3641c0..9d1e1c51e 100644 --- a/chained__operators_8cc__incl.md5 +++ b/chained__operators_8cc__incl.md5 @@ -1 +1 @@ -8d38b8709f212b888d20942fe61f9d99 \ No newline at end of file +dcd1eeaf9f280f15717716043ae21002 \ No newline at end of file diff --git a/chained__operators_8cc__incl.png b/chained__operators_8cc__incl.png index 86270f0b8..1b1d7fe36 100644 Binary files a/chained__operators_8cc__incl.png and b/chained__operators_8cc__incl.png differ diff --git a/classes.html b/classes.html index a9c9a146a..b3048a469 100644 --- a/classes.html +++ b/classes.html @@ -109,7 +109,7 @@
JointMAP (sopt::algorithm)
L
-
L1 (sopt::proximal)
L1GProximal (sopt::algorithm)
L1TightFrame (sopt::proximal)
L2Ball (sopt::proximal)
L2ForwardBackward (sopt::algorithm)
L2Norm (sopt::proximal)
LinearTransform (sopt)
+
L1 (sopt::proximal)
L1GProximal (sopt::algorithm)
L1TightFrame (sopt::proximal)
L2Ball (sopt::proximal)
L2ForwardBackward (sopt::algorithm)
L2Norm (sopt::proximal)
LinearTransform (sopt)
Log (sopt::logging)
M
MatrixAdjointToLinearTransform (sopt::details)
MatrixToLinearTransform (sopt::details)
diff --git a/classsopt_1_1RelativeVariation.html b/classsopt_1_1RelativeVariation.html index 4e08e7c4e..819fb04a8 100644 --- a/classsopt_1_1RelativeVariation.html +++ b/classsopt_1_1RelativeVariation.html @@ -353,9 +353,9 @@

119  SOPT_LOW_LOG(" - {} relative variation: {} <? {}", name(), std::sqrt(norm), tolerance());
120  return norm < tolerance() * tolerance();
121 }
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
-

References SOPT_LOW_LOG.

+

References SOPT_LOW_LOG.

diff --git a/classsopt_1_1ScalarRelativeVariation.html b/classsopt_1_1ScalarRelativeVariation.html index ac389c49b..8a8976179 100644 --- a/classsopt_1_1ScalarRelativeVariation.html +++ b/classsopt_1_1ScalarRelativeVariation.html @@ -441,10 +441,10 @@

137  previous_ = current;
138  return result;
139 }
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
sopt::gradient_operator::diff
Vector< T > diff(const Vector< T > &x)
Numerical derivative of 1d vector.
Definition: gradient_operator.h:11
-

References sopt::gradient_operator::diff(), and SOPT_LOW_LOG.

+

References sopt::gradient_operator::diff(), and SOPT_LOW_LOG.

diff --git a/classsopt_1_1algorithm_1_1JointMAP.html b/classsopt_1_1algorithm_1_1JointMAP.html index 3e2397b0b..4c6fdb56e 100644 --- a/classsopt_1_1algorithm_1_1JointMAP.html +++ b/classsopt_1_1algorithm_1_1JointMAP.html @@ -276,13 +276,13 @@

134  diagnostic.reg_term = gamma;
135  return diagnostic;
136  }
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
SOPT_ERROR
#define SOPT_ERROR(...)
\macro Something is definitely wrong, algorithm exits
Definition: logging.h:15
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
SOPT_ERROR
#define SOPT_ERROR(...)
\macro Something is definitely wrong, algorithm exits
Definition: logging.h:211
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::t_uint
size_t t_uint
Root of the type hierarchy for unsigned integers.
Definition: types.h:15
-

References sopt::algorithm::JointMAP< ALGORITHM >::DiagnosticAndResultReg::reg_good, sopt::algorithm::JointMAP< ALGORITHM >::DiagnosticAndResultReg::reg_niters, sopt::algorithm::JointMAP< ALGORITHM >::DiagnosticAndResultReg::reg_term, SOPT_ERROR, SOPT_HIGH_LOG, SOPT_LOW_LOG, and SOPT_MEDIUM_LOG.

+

References sopt::algorithm::JointMAP< ALGORITHM >::DiagnosticAndResultReg::reg_good, sopt::algorithm::JointMAP< ALGORITHM >::DiagnosticAndResultReg::reg_niters, sopt::algorithm::JointMAP< ALGORITHM >::DiagnosticAndResultReg::reg_term, SOPT_ERROR, SOPT_HIGH_LOG, SOPT_LOW_LOG, and SOPT_MEDIUM_LOG.

diff --git a/classsopt_1_1algorithm_1_1L1GProximal.html b/classsopt_1_1algorithm_1_1L1GProximal.html index e9cd87cbc..d731e26f1 100644 --- a/classsopt_1_1algorithm_1_1L1GProximal.html +++ b/classsopt_1_1algorithm_1_1L1GProximal.html @@ -469,9 +469,9 @@

49  {
50  SOPT_HIGH_LOG("Performing Forward Backward with L1 and L2 norms");
51  }
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
-

References SOPT_HIGH_LOG.

+

References SOPT_HIGH_LOG.

diff --git a/classsopt_1_1algorithm_1_1L2ForwardBackward.html b/classsopt_1_1algorithm_1_1L2ForwardBackward.html index 0ac4346da..e0345a358 100644 --- a/classsopt_1_1algorithm_1_1L2ForwardBackward.html +++ b/classsopt_1_1algorithm_1_1L2ForwardBackward.html @@ -1030,7 +1030,7 @@

References sopt::linear_transform().

-

Referenced by main().

+

Referenced by main().

diff --git a/classsopt_1_1algorithm_1_1PowerMethod.html b/classsopt_1_1algorithm_1_1PowerMethod.html index a1befd60c..ec06ba0d4 100644 --- a/classsopt_1_1algorithm_1_1PowerMethod.html +++ b/classsopt_1_1algorithm_1_1PowerMethod.html @@ -455,11 +455,11 @@

245 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::algorithm::PowerMethod::Real
typename real_type< Scalar >::type Real
Real type.
Definition: power_method.h:144
-
SOPT_WARN
#define SOPT_WARN(...)
\macro Something might be going wrong
Definition: logging.h:17
-
SOPT_INFO
#define SOPT_INFO(...)
\macro Verbose informational message about normal condition
Definition: logging.h:19
+
SOPT_WARN
#define SOPT_WARN(...)
\macro Something might be going wrong
Definition: logging.h:213
+
SOPT_INFO
#define SOPT_INFO(...)
\macro Verbose informational message about normal condition
Definition: logging.h:215
sopt::t_uint
size_t t_uint
Root of the type hierarchy for unsigned integers.
Definition: types.h:15
-

References SOPT_INFO, and SOPT_WARN.

+

References SOPT_INFO, and SOPT_WARN.

diff --git a/classsopt_1_1algorithm_1_1Reweighted.html b/classsopt_1_1algorithm_1_1Reweighted.html index 43f6f61c5..131f028df 100644 --- a/classsopt_1_1algorithm_1_1Reweighted.html +++ b/classsopt_1_1algorithm_1_1Reweighted.html @@ -941,13 +941,13 @@

234 }
sopt::algorithm::Reweighted::itermax
t_uint itermax() const
Maximum number of reweighted iterations.
Definition: reweighted.h:118
sopt::algorithm::Reweighted::update_delta
t_DeltaUpdate const & update_delta() const
Updates delta.
Definition: reweighted.h:155
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
SOPT_ERROR
#define SOPT_ERROR(...)
\macro Something is definitely wrong, algorithm exits
Definition: logging.h:15
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
SOPT_ERROR
#define SOPT_ERROR(...)
\macro Something is definitely wrong, algorithm exits
Definition: logging.h:211
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::standard_deviation
real_type< typename T::Scalar >::type standard_deviation(Eigen::ArrayBase< T > const &x)
Computes the standard deviation of a vector.
Definition: maths.h:16
-

References sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::algo, sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::good, sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::niters, SOPT_ERROR, SOPT_HIGH_LOG, SOPT_LOW_LOG, SOPT_MEDIUM_LOG, sopt::standard_deviation(), and sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::weights.

+

References sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::algo, sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::good, sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::niters, SOPT_ERROR, SOPT_HIGH_LOG, SOPT_LOW_LOG, SOPT_MEDIUM_LOG, sopt::standard_deviation(), and sopt::algorithm::Reweighted< ALGORITHM >::ReweightedResult::weights.

diff --git a/classsopt_1_1algorithm_1_1SDMM.html b/classsopt_1_1algorithm_1_1SDMM.html index 46d2b7615..95b77b4e5 100644 --- a/classsopt_1_1algorithm_1_1SDMM.html +++ b/classsopt_1_1algorithm_1_1SDMM.html @@ -952,11 +952,11 @@

a
constexpr Scalar a
Definition: bisection_method.cc:13
sopt::algorithm::SDMM::size
t_uint size() const
Number of terms.
Definition: sdmm.h:159
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
sopt::t_uint
size_t t_uint
Root of the type hierarchy for unsigned integers.
Definition: types.h:15
-

References a, SOPT_HIGH_LOG, and SOPT_LOW_LOG.

+

References a, SOPT_HIGH_LOG, and SOPT_LOW_LOG.

diff --git a/classsopt_1_1algorithm_1_1TFGProximal.html b/classsopt_1_1algorithm_1_1TFGProximal.html index 4220de81c..332c4079e 100644 --- a/classsopt_1_1algorithm_1_1TFGProximal.html +++ b/classsopt_1_1algorithm_1_1TFGProximal.html @@ -405,9 +405,9 @@

54  {
55  SOPT_HIGH_LOG("Performing Forward Backward TensorFlow model");
56  }
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
-

References SOPT_HIGH_LOG.

+

References SOPT_HIGH_LOG.

diff --git a/classsopt_1_1algorithm_1_1TVPrimalDual.html b/classsopt_1_1algorithm_1_1TVPrimalDual.html index 1e4f8d4ac..55f2a405f 100644 --- a/classsopt_1_1algorithm_1_1TVPrimalDual.html +++ b/classsopt_1_1algorithm_1_1TVPrimalDual.html @@ -995,7 +995,7 @@

References sopt::linear_transform().

-

Referenced by main(), and sopt::algorithm::TVPrimalDual< SCALAR >::operator()().

+

Referenced by main(), and sopt::algorithm::TVPrimalDual< SCALAR >::operator()().

@@ -1033,7 +1033,7 @@

References sopt::linear_transform().

-

Referenced by main().

+

Referenced by main().

@@ -1071,7 +1071,7 @@

259  }
sopt::algorithm::TVPrimalDual::residual_convergence
TVPrimalDual< Scalar > & residual_convergence(Real const &tolerance)
Helper function to set-up default residual convergence function.
Definition: tv_primal_dual.h:257
-

Referenced by main().

+

Referenced by main().

diff --git a/classsopt_1_1logging_1_1Log-members.html b/classsopt_1_1logging_1_1Log-members.html new file mode 100644 index 000000000..decd9d774 --- /dev/null +++ b/classsopt_1_1logging_1_1Log-members.html @@ -0,0 +1,115 @@ + + + + + + + +SOPT: Member List + + + + + + + + + + + + +
+
+ + + + + + + +
+
SOPT +
+
Sparse OPTimisation
+
+
+ + + + + + + + +
+
+ + +
+ +
+ + +
+
+
+
sopt::logging::Log Member List
+
+
+ +

This is the complete list of members for sopt::logging::Log, including all inherited members.

+ + + + + + + + + + + + + + + + + + + + + + + + + +
always enum valuesopt::logging::Log
ColorCodes typedefsopt::logging::Log
critical enum valuesopt::logging::Log
debug enum valuesopt::logging::Log
end_colorsopt::logging::Logstatic
error enum valuesopt::logging::Log
getLevel() constsopt::logging::Loginline
getLevelFromName(const std::string &level)sopt::logging::Logstatic
getLevelName(int level)sopt::logging::Logstatic
getLog(const std::string &name)sopt::logging::Logstatic
getName() constsopt::logging::Loginline
info enum valuesopt::logging::Log
isActive(int level) constsopt::logging::Loginline
Level enum namesopt::logging::Log
LevelMap typedefsopt::logging::Log
LogMap typedefsopt::logging::Log
operator<<(Log &log, int level)sopt::logging::Logfriend
setLevel(const std::string &name, int level)sopt::logging::Logstatic
setLevel(int level)sopt::logging::Loginline
setLevels(const LevelMap &logLevels)sopt::logging::Logstatic
setName(const std::string &name)sopt::logging::Loginline
trace enum valuesopt::logging::Log
warn enum valuesopt::logging::Log
warning enum valuesopt::logging::Log
+ +
+Generated by doxygen 1.9.1 +
+ + diff --git a/classsopt_1_1logging_1_1Log.html b/classsopt_1_1logging_1_1Log.html new file mode 100644 index 000000000..c73bce5ca --- /dev/null +++ b/classsopt_1_1logging_1_1Log.html @@ -0,0 +1,769 @@ + + + + + + + +SOPT: sopt::logging::Log Class Reference + + + + + + + + + + + + +
+
+ + + + + + + +
+
SOPT +
+
Sparse OPTimisation
+
+
+ + + + + + + + +
+
+ + +
+ +
+ + +
+
+
+Public Types | +Public Member Functions | +Static Public Member Functions | +Static Public Attributes | +Friends | +List of all members
+
+
sopt::logging::Log Class Reference
+
+
+ +

Logging system for controlled & formatted writing to stdout. + More...

+ +

#include <logging.h>

+ + + + + + + + + + + + + + +

+Public Types

enum  Level {
+  trace = 0 +, debug = 10 +, info = 20 +, warn = 30 +,
+  warning = 30 +, error = 40 +, critical = 50 +, always = 50 +
+ }
 Log priority levels. More...
 
using LogMap = std::map< std::string, Log >
 Typedef for a collection of named logs. More...
 
using LevelMap = std::map< std::string, int >
 Typedef for a collection of named log levels. More...
 
using ColorCodes = std::map< int, std::string >
 Typedef for a collection of shell color codes, accessed by log level. More...
 
+ + + + + + + + + + + + + + + + +

+Public Member Functions

int getLevel () const
 Get the priority level of this logger. More...
 
Log & setLevel (int level)
 Set the priority level of this logger. More...
 
std::string getName () const
 Get the name of this logger. More...
 
Log & setName (const std::string &name)
 Set the name of this logger. More...
 
bool isActive (int level) const
 Will this log level produce output on this logger at the moment? More...
 
+ + + + + + + + + + + + + + +

+Static Public Member Functions

static void setLevel (const std::string &name, int level)
 Set the log levels. More...
 
static void setLevels (const LevelMap &logLevels)
 
static Log & getLog (const std::string &name)
 
static Level getLevelFromName (const std::string &level)
 Get a log level enum from a string. More...
 
static std::string getLevelName (int level)
 Get the std::string representation of a log level. More...
 
+ + + + +

+Static Public Attributes

static const int end_color {-10}
 Special "level-like" code to end coloring. More...
 
+ + + + +

+Friends

std::ostream & operator<< (Log &log, int level)
 The streaming operator can use Log's internals. More...
 
+

Detailed Description

+

Logging system for controlled & formatted writing to stdout.

+ +

Definition at line 14 of file logging.h.

+

Member Typedef Documentation

+ +

◆ ColorCodes

+ +
+
+ + + + +
using sopt::logging::Log::ColorCodes = std::map<int, std::string>
+
+ +

Typedef for a collection of shell color codes, accessed by log level.

+ +

Definition at line 36 of file logging.h.

+ +
+
+ +

◆ LevelMap

+ +
+
+ + + + +
using sopt::logging::Log::LevelMap = std::map<std::string, int>
+
+ +

Typedef for a collection of named log levels.

+ +

Definition at line 33 of file logging.h.

+ +
+
+ +

◆ LogMap

+ +
+
+ + + + +
using sopt::logging::Log::LogMap = std::map<std::string, Log>
+
+ +

Typedef for a collection of named logs.

+ +

Definition at line 30 of file logging.h.

+ +
+
+

Member Enumeration Documentation

+ +

◆ Level

+ +
+
+ + + + +
enum sopt::logging::Log::Level
+
+ +

Log priority levels.

+ + + + + + + + + +
Enumerator
trace 
debug 
info 
warn 
warning 
error 
critical 
always 
+ +

Definition at line 18 of file logging.h.

+
18  {
+
19  trace = 0,
+
20  debug = 10,
+
21  info = 20,
+
22  warn = 30, warning = 30,
+
23  error = 40,
+
24  critical = 50, always = 50
+
25  };
+ + + + + + + + +
+
+
+

Member Function Documentation

+ +

◆ getLevel()

+ +
+
+ + + + + +
+ + + + + + + +
int sopt::logging::Log::getLevel () const
+ 		+inline
+
+ +

Get the priority level of this logger.

+ +

Definition at line 90 of file logging.h.

+
90  {
+
91  return _level;
+
92  }
+
+

Referenced by getLog().

+ +
+
+ +

◆ getLevelFromName()

+ +
+
+ + + + + +
+ + + + + + + + +
Log::Level sopt::logging::Log::getLevelFromName (const std::string & level)
+ 		+static
+
+ +

Get a log level enum from a string.

+ +

Definition at line 138 of file logging.cc.

+
138  {
+
139  if (level == "trace") return trace;
+
140  if (level == "debug") return debug;
+
141  if (level == "info") return info;
+
142  if (level == "warn") return warn;
+
143  if (level == "error") return error;
+
144  if (level == "critical") return critical;
+
145  SOPT_THROW("Couldn't create a log level from string '" + level + "'");
+
146  }
+
SOPT_THROW
#define SOPT_THROW(MSG)
Definition: exception.h:46
+
+

References SOPT_THROW.

+ +

Referenced by sopt::logging::set_level().

+ +
+
+ +

◆ getLevelName()

+ +
+
+ + + + + +
+ + + + + + + + +
string sopt::logging::Log::getLevelName (int level)
+ 		+static
+
+ +

Get the std::string representation of a log level.

+ +

Definition at line 95 of file logging.cc.

+
95  {
+
96  switch(level) {
+
97  case trace:
+
98  return "trace";
+
99  case debug:
+
100  return "debug";
+
101  case info:
+
102  return "info";
+
103  case warn:
+
104  return "warn";
+
105  case error:
+
106  return "error";
+
107  case critical:
+
108  return "critical";
+
109  default:
+
110  return "";
+
111  }
+
112  }
+
+
+
+ +

◆ getLog()

+ +
+
+ + + + + +
+ + + + + + + + +
Log & sopt::logging::Log::getLog (const std::string & name)
+ 		+static
+
+

Get a logger with the given name. The level will be taken from the "requestedLevels" static map or will be INFO by default.

+ +

Definition at line 57 of file logging.cc.

+
57  {
+
58  auto theLog = existingLogs.find(name);
+
59  if (theLog == existingLogs.end()) {
+
60  int level = info;
+
61  // Try running through all parent classes to find an existing level
+
62  string tmpname = name;
+
63  bool triedAllParents = false;
+
64  while (! triedAllParents) {
+
65  // Is there a default level?
+
66  if (defaultLevels.find(tmpname) != defaultLevels.end()) {
+
67  level = defaultLevels.find(tmpname)->second;
+
68  break;
+
69  }
+
70  // Is there already such a logger? (NB. tmpname != name in later iterations)
+
71  if (existingLogs.find(tmpname) != existingLogs.end()) {
+
72  level = existingLogs.find(tmpname)->second.getLevel();
+
73  break;
+
74  }
+
75  // Crop the string back to the next parent level
+
76  size_t lastDot = tmpname.find_last_of(".");
+
77  if (lastDot != string::npos) {
+
78  tmpname = tmpname.substr(0, lastDot);
+
79  } else {
+
80  triedAllParents = true;
+
81  }
+
82  }
+
83  // for (LevelMap::const_iterator l = defaultLevels.begin(); l != defaultLevels.end(); ++l) {
+
84  //
+
85  // }
+
86 
+
87  // emplace returns pair<iterator,bool>
+
88  auto result = existingLogs.emplace(name, Log(name, level));
+
89  theLog = result.first;
+
90  }
+
91  return theLog->second;
+
92  }
+
+

References getLevel().

+ +

Referenced by sopt::logging::getLog().

+ +
+
+ +

◆ getName()

+ +
+
+ + + + + +
+ + + + + + + +
std::string sopt::logging::Log::getName () const
+ 		+inline
+
+ +

Get the name of this logger.

+ +

Definition at line 107 of file logging.h.

+
107  {
+
108  return _name;
+
109  }
+
+
+
+ +

◆ isActive()

+ +
+
+ + + + + +
+ + + + + + + + +
bool sopt::logging::Log::isActive (int level) const
+ 		+inline
+
+ +

Will this log level produce output on this logger at the moment?

+ +

Definition at line 118 of file logging.h.

+
118  {
+
119  return (level >= _level);
+
120  }
+
+
+
+ +

◆ setLevel() [1/2]

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
static void sopt::logging::Log::setLevel (const std::string & name,
int level 
)
+ 		+static
+
+ +

Set the log levels.

+ +

Referenced by sopt::logging::set_level().

+ +
+
+ +

◆ setLevel() [2/2]

+ +
+
+ + + + + +
+ + + + + + + + +
Log& sopt::logging::Log::setLevel (int level)
+ 		+inline
+
+ +

Set the priority level of this logger.

+ +

Definition at line 95 of file logging.h.

+
95  {
+
96  _level = level;
+
97  return *this;
+
98  }
+
+
+
+ +

◆ setLevels()

+ +
+
+ + + + + +
+ + + + + + + + +
void sopt::logging::Log::setLevels (const LevelMap & logLevels)
+ 		+static
+
+ +

Definition at line 49 of file logging.cc.

+
49  {
+
50  for (LevelMap::const_iterator lev = logLevels.begin(); lev != logLevels.end(); ++lev) {
+
51  defaultLevels[lev->first] = lev->second;
+
52  }
+
53  _updateLevels(defaultLevels, existingLogs);
+
54  }
+
sopt::logging::_updateLevels
void _updateLevels(const Log::LevelMap &defaultLevels, Log::LogMap &existingLogs)
Definition: logging.cc:30
+
+

References sopt::logging::_updateLevels().

+ +
+
+ +

◆ setName()

+ +
+
+ + + + + +
+ + + + + + + + +
Log& sopt::logging::Log::setName (const std::string & name)
+ 		+inline
+
+ +

Set the name of this logger.

+ +

Definition at line 112 of file logging.h.

+
112  {
+
113  _name = name;
+
114  return *this;
+
115  }
+
+
+
+

Friends And Related Function Documentation

+ +

◆ operator<<

+ +
+
+ + + + + +
+ + + + + + + + + + + + + + + + + + +
std::ostream& operator<< (Log & log,
int level 
)
+ 		+friend
+
+ +

The streaming operator can use Log's internals.

+ +

Definition at line 190 of file logging.cc.

+
190  {
+
191  if (log.isActive(level)) {
+
192  if (level > Log::warning) {
+
193  cerr << log.formatMessage(level, "");
+
194  return cerr;
+
195  } else {
+
196  cout << log.formatMessage(level, "");
+
197  return cout;
+
198  }
+
199  } else {
+
200  static ostream devNull(nullptr);
+
201  return devNull;
+
202  }
+
203  }
+
+
+
+

Member Data Documentation

+ +

◆ end_color

+ +
+
+ + + + + +
+ + + + +
const int sopt::logging::Log::end_color {-10}
+ 		+static
+
+ +

Special "level-like" code to end coloring.

+ +

Definition at line 26 of file logging.h.

+ +
+
+
The documentation for this class was generated from the following files:
    +
  • /home/runner/work/sopt/sopt/cpp/sopt/logging.h
    • +
  • /home/runner/work/sopt/sopt/cpp/sopt/logging.cc
    • +
+
+ +
+Generated by doxygen 1.9.1 +
+ + diff --git a/classsopt_1_1proximal_1_1L1TightFrame.html b/classsopt_1_1proximal_1_1L1TightFrame.html index b2230852f..820f122ed 100644 --- a/classsopt_1_1proximal_1_1L1TightFrame.html +++ b/classsopt_1_1proximal_1_1L1TightFrame.html @@ -346,10 +346,10 @@

141  SOPT_LOW_LOG("Prox L1: objective = {}", objective(x, out, gamma));
142 }
sopt::proximal::L1TightFrame::objective
std::enable_if< is_complex< Scalar >::value==is_complex< typename T0::Scalar >::value and is_complex< Scalar >::value==is_complex< typename T1::Scalar >::value, Real >::type objective(Eigen::MatrixBase< T0 > const &x, Eigen::MatrixBase< T1 > const &z, Real const &gamma) const
Definition: l1_proximal.h:149
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
sopt::soft_threshhold
std::enable_if< std::is_arithmetic< SCALAR >::value or is_complex< SCALAR >::value, SCALAR >::type soft_threshhold(SCALAR const &x, typename real_type< SCALAR >::type const &threshhold)
abs(x) < threshhold ? 0: x - sgn(x) * threshhold
Definition: maths.h:29
-

References sopt::soft_threshhold(), and SOPT_LOW_LOG.

+

References sopt::soft_threshhold(), and SOPT_LOW_LOG.

Referenced by sopt::proximal::L1< SCALAR >::tight_frame().

diff --git a/classsopt_1_1wavelets_1_1SARA.html b/classsopt_1_1wavelets_1_1SARA.html index e744d64a4..742acfc04 100644 --- a/classsopt_1_1wavelets_1_1SARA.html +++ b/classsopt_1_1wavelets_1_1SARA.html @@ -467,11 +467,11 @@

144 
145  coeffs /= std::sqrt(size());
146 }
-
SOPT_TRACE
#define SOPT_TRACE(...)
Definition: logging.h:24
+
SOPT_TRACE
#define SOPT_TRACE(...)
Definition: logging.h:220
sopt::t_int
int t_int
Root of the type hierarchy for signed integers.
Definition: types.h:13
SOPT_WAVELET_ERROR_MACRO
#define SOPT_WAVELET_ERROR_MACRO(INPUT)
Definition: sara.h:119
-

References SOPT_TRACE, and SOPT_WAVELET_ERROR_MACRO.

+

References SOPT_TRACE, and SOPT_WAVELET_ERROR_MACRO.

@@ -632,7 +632,7 @@

176 }
sopt::wavelets::SARA::max_levels
t_uint max_levels() const
Number of levels over which to do transform.
Definition: sara.h:107
-

References max_levels(), SOPT_TRACE, and SOPT_WAVELET_ERROR_MACRO.

+

References max_levels(), SOPT_TRACE, and SOPT_WAVELET_ERROR_MACRO.

diff --git a/classsopt_1_1wavelets_1_1Wavelet.html b/classsopt_1_1wavelets_1_1Wavelet.html index 9e57b7361..0de390ba7 100644 --- a/classsopt_1_1wavelets_1_1Wavelet.html +++ b/classsopt_1_1wavelets_1_1Wavelet.html @@ -668,7 +668,7 @@

21  // Unknown input wavelet
22  throw std::exception();
23 }
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::wavelets::daubechies_data
WaveletData const & daubechies_data(t_uint n)
Factory function returning specific daubechie wavelet data.
Definition: wavelet_data.cc:1597
sopt::t_uint
size_t t_uint
Root of the type hierarchy for unsigned integers.
Definition: types.h:15
diff --git a/common__catch__main_8cc.html b/common__catch__main_8cc.html index 74ab7441d..39e50aefb 100644 --- a/common__catch__main_8cc.html +++ b/common__catch__main_8cc.html @@ -94,14 +94,18 @@ @@ -172,14 +176,11 @@

16  return returnCode;
17  mersenne.reset(new std::mt19937_64(session.configData().rngSeed));
18 
-
19  sopt::logging::initialize();
-
20 
-
21  return session.run();
-
22 }
+
19  return session.run();
+
20 }
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
-

References sopt::logging::initialize(), and mersenne().

+

References mersenne().

diff --git a/common__catch__main_8cc__incl.map b/common__catch__main_8cc__incl.map index ecaf8b2fc..19202a2f5 100644 --- a/common__catch__main_8cc__incl.map +++ b/common__catch__main_8cc__incl.map @@ -1,10 +1,14 @@ - - - - - - - - + + + + + + + + + + + + diff --git a/common__catch__main_8cc__incl.md5 b/common__catch__main_8cc__incl.md5 index a28078c9f..b450ef11d 100644 --- a/common__catch__main_8cc__incl.md5 +++ b/common__catch__main_8cc__incl.md5 @@ -1 +1 @@ -8e9473839420b21dad02707123867d04 \ No newline at end of file +1b0400968f5085c698b7168d9ac59f72 \ No newline at end of file diff --git a/common__catch__main_8cc__incl.png b/common__catch__main_8cc__incl.png index bef6ba9e0..589595739 100644 Binary files a/common__catch__main_8cc__incl.png and b/common__catch__main_8cc__incl.png differ diff --git a/common__catch__main_8cc_source.html b/common__catch__main_8cc_source.html index f67bdcc03..68fca8eef 100644 --- a/common__catch__main_8cc_source.html +++ b/common__catch__main_8cc_source.html @@ -97,14 +97,11 @@
16  return returnCode;
17  mersenne.reset(new std::mt19937_64(session.configData().rngSeed));
18 
-
19  sopt::logging::initialize();
-
20 
-
21  return session.run();
-
22 }
+
19  return session.run();
+
20 }
main
int main(int argc, char const **argv)
Definition: common_catch_main.cc:11
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
diff --git a/common__mpi__catch__main_8cc.html b/common__mpi__catch__main_8cc.html index 384df661a..f610c6697 100644 --- a/common__mpi__catch__main_8cc.html +++ b/common__mpi__catch__main_8cc.html @@ -97,17 +97,21 @@ @@ -204,18 +208,15 @@

45  return returnCode;
46  mersenne.reset(new std::mt19937_64(session.configData().rngSeed));
47 
-
48  sopt::logging::initialize();
+
48  auto const result = session.run();
49 
-
50  auto const result = session.run();
-
51 
-
52  return result;
-
53 }
+
50  return result;
+
51 }
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
cargs
std::vector< char const * > cargs
Definition: mpi_session.cc:10
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::mpi::init
std::shared_ptr< details::initializer > init(int argc, const char **argv)
Definition: session.cc:27
-

References cargs, sopt::mpi::init(), sopt::logging::initialize(), and mersenne().

+

References cargs, sopt::mpi::init(), and mersenne().

diff --git a/common__mpi__catch__main_8cc__incl.map b/common__mpi__catch__main_8cc__incl.map index 1a2c23b54..8448b7988 100644 --- a/common__mpi__catch__main_8cc__incl.map +++ b/common__mpi__catch__main_8cc__incl.map @@ -1,13 +1,17 @@ - - - - - - - - - - - + + + + + + + + + + + + + + + diff --git a/common__mpi__catch__main_8cc__incl.md5 b/common__mpi__catch__main_8cc__incl.md5 index ce591dc46..8fb9078bc 100644 --- a/common__mpi__catch__main_8cc__incl.md5 +++ b/common__mpi__catch__main_8cc__incl.md5 @@ -1 +1 @@ -194afaa79d61f33586f3a4884a623181 \ No newline at end of file +2c6bbf43bd406dacc3233d2f80d14096 \ No newline at end of file diff --git a/common__mpi__catch__main_8cc__incl.png b/common__mpi__catch__main_8cc__incl.png index 008accee6..93191e5c3 100644 Binary files a/common__mpi__catch__main_8cc__incl.png and b/common__mpi__catch__main_8cc__incl.png differ diff --git a/common__mpi__catch__main_8cc_source.html b/common__mpi__catch__main_8cc_source.html index 8eb024ead..8a7e79b81 100644 --- a/common__mpi__catch__main_8cc_source.html +++ b/common__mpi__catch__main_8cc_source.html @@ -126,17 +126,14 @@
45  return returnCode;
46  mersenne.reset(new std::mt19937_64(session.configData().rngSeed));
47 
-
48  sopt::logging::initialize();
+
48  auto const result = session.run();
49 
-
50  auto const result = session.run();
-
51 
-
52  return result;
-
53 }
+
50  return result;
+
51 }
main
int main(int argc, const char **argv)
Definition: common_mpi_catch_main.cc:14
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
cargs
std::vector< char const * > cargs
Definition: mpi_session.cc:10
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::mpi::init
std::shared_ptr< details::initializer > init(int argc, const char **argv)
Definition: session.cc:27
diff --git a/config_8in_8h.html b/config_8in_8h.html index 464527a9c..f3162a7d1 100644 --- a/config_8in_8h.html +++ b/config_8in_8h.html @@ -143,9 +143,6 @@ std::string sopt::default_logger_name ()  Default logger name. More...
  -constexpr bool sopt::color_logger () - Wether to add color to the logger. More...
-  constexpr std::size_t sopt::number_of_threads_in_tests ()  Number of threads used during testing. More...
  diff --git a/config_8in_8h_source.html b/config_8in_8h_source.html index 68604663f..a0e06def4 100644 --- a/config_8in_8h_source.html +++ b/config_8in_8h_source.html @@ -103,29 +103,34 @@
26 #include <tuple>
27 
28 namespace sopt {
-
30 inline std::string version() { return "@SOPT_VERSION@"; }
-
32 inline std::tuple<uint8_t, uint8_t, uint8_t> version_tuple() {
-
33  return std::tuple<uint8_t, uint8_t, uint8_t>(
-
34  @SOPT_VERSION_MAJOR@, @SOPT_VERSION_MINOR@, @SOPT_VERSION_PATCH@);
-
35 }
-
37 inline std::string gitref() { return "@SOPT_GITREF@"; }
-
39 inline std::string default_logging_level() { return "@SOPT_TEST_LOG_LEVEL@"; }
-
41 inline std::string default_logger_name() { return "@SOPT_LOGGER_NAME@"; }
-
43 inline constexpr bool color_logger() { return @SOPT_COLOR_LOGGING@; }
-
44 # ifdef SOPT_OPENMP
-
46 inline constexpr std::size_t number_of_threads_in_tests() { return @SOPT_DEFAULT_OPENMP_THREADS@; }
-
47 # endif
-
48 } // namespace sopt
-
49 
-
50 #endif
+
29 
+
31 inline std::string version() { return "@SOPT_VERSION@"; }
+
32 
+
34 inline std::tuple<uint8_t, uint8_t, uint8_t> version_tuple() {
+
35  return std::tuple<uint8_t, uint8_t, uint8_t>(
+
36  @SOPT_VERSION_MAJOR@, @SOPT_VERSION_MINOR@, @SOPT_VERSION_PATCH@);
+
37 }
+
38 
+
40 inline std::string gitref() { return "@SOPT_GITREF@"; }
+
41 
+
43 inline std::string default_logging_level() { return "@SOPT_TEST_LOG_LEVEL@"; }
+
44 
+
46 inline std::string default_logger_name() { return "@SOPT_LOGGER_NAME@"; }
+
47 
+
48 # ifdef SOPT_OPENMP
+
50 inline constexpr std::size_t number_of_threads_in_tests() { return @SOPT_DEFAULT_OPENMP_THREADS@; }
+
51 # endif
+
52 
+
53 } // namespace sopt
+
54 
+
55 #endif
-
sopt::version_tuple
std::tuple< uint8_t, uint8_t, uint8_t > version_tuple()
Returns library version.
Definition: config.in.h:32
-
sopt::default_logger_name
std::string default_logger_name()
Default logger name.
Definition: config.in.h:41
-
sopt::color_logger
constexpr bool color_logger()
Wether to add color to the logger.
Definition: config.in.h:43
-
sopt::default_logging_level
std::string default_logging_level()
Default logging level.
Definition: config.in.h:39
-
sopt::version
std::string version()
Returns library version.
Definition: config.in.h:30
-
sopt::number_of_threads_in_tests
constexpr std::size_t number_of_threads_in_tests()
Number of threads used during testing.
Definition: config.in.h:46
-
sopt::gitref
std::string gitref()
Returns library git reference, if known.
Definition: config.in.h:37
+
sopt::version_tuple
std::tuple< uint8_t, uint8_t, uint8_t > version_tuple()
Returns library version.
Definition: config.in.h:34
+
sopt::default_logger_name
std::string default_logger_name()
Default logger name.
Definition: config.in.h:46
+
sopt::default_logging_level
std::string default_logging_level()
Default logging level.
Definition: config.in.h:43
+
sopt::version
std::string version()
Returns library version.
Definition: config.in.h:31
+
sopt::number_of_threads_in_tests
constexpr std::size_t number_of_threads_in_tests()
Number of threads used during testing.
Definition: config.in.h:50
+
sopt::gitref
std::string gitref()
Returns library git reference, if known.
Definition: config.in.h:40
diff --git a/conjugate__gradient_8h.html b/conjugate__gradient_8h.html index 667a330b2..8cdd33e3f 100644 --- a/conjugate__gradient_8h.html +++ b/conjugate__gradient_8h.html @@ -96,27 +96,28 @@
diff --git a/conjugate__gradient_8h__incl.map b/conjugate__gradient_8h__incl.map index 6fed7895b..009f7d26f 100644 --- a/conjugate__gradient_8h__incl.map +++ b/conjugate__gradient_8h__incl.map @@ -1,23 +1,24 @@ - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/conjugate__gradient_8h__incl.md5 b/conjugate__gradient_8h__incl.md5 index 7d9db8327..67f5d672e 100644 --- a/conjugate__gradient_8h__incl.md5 +++ b/conjugate__gradient_8h__incl.md5 @@ -1 +1 @@ -969fa2c94930f7d9a73f8cda2dabeb5a \ No newline at end of file +173a7bb71dce42fdfc49a094b8647880 \ No newline at end of file diff --git a/conjugate__gradient_8h__incl.png b/conjugate__gradient_8h__incl.png index 1e28c7dff..20c823922 100644 Binary files a/conjugate__gradient_8h__incl.png and b/conjugate__gradient_8h__incl.png differ diff --git a/conjugate__gradient_8h_source.html b/conjugate__gradient_8h_source.html index 30b97d386..5970e4be0 100644 --- a/conjugate__gradient_8h_source.html +++ b/conjugate__gradient_8h_source.html @@ -201,7 +201,7 @@
sopt::ConjugateGradient::operator()
Diagnostic operator()(VECTOR &x, Eigen::MatrixBase< T1 > const &A, Eigen::MatrixBase< T2 > const &b) const
Computes $x$ for $Ax=b$.
Definition: conjugate_gradient.h:49
sopt::ConjugateGradient::operator()
DiagnosticAndResult< typename T0::Scalar > operator()(A_TYPE const &A, Eigen::MatrixBase< T0 > const &b) const
Computes $x$ for $Ax=b$.
Definition: conjugate_gradient.h:65
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
sopt::t_real
double t_real
Root of the type hierarchy for real numbers.
Definition: types.h:17
diff --git a/copy__tiff_8cc.html b/copy__tiff_8cc.html index 3733f3ed0..6592276c2 100644 --- a/copy__tiff_8cc.html +++ b/copy__tiff_8cc.html @@ -98,26 +98,29 @@
@@ -164,24 +167,19 @@

19  exit(0);

20  }
21 
-
22  // Initializes and sets logger (if compiled with logging)
-
23  // See set_level function for levels.
-
24  sopt::logging::initialize();
+
22  // Read input file
+
23  auto const image = sopt::notinstalled::read_standard_tiff(argv[1]);
+
24  sopt::utilities::write_tiff(image, argv[2]);
25 
-
26  // Read input file
-
27  auto const image = sopt::notinstalled::read_standard_tiff(argv[1]);
-
28  sopt::utilities::write_tiff(image, argv[2]);
-
29 
-
30  auto const reread = sopt::utilities::read_tiff(argv[2]);
-
31 
-
32  return 0;
-
33 }
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
+
26  auto const reread = sopt::utilities::read_tiff(argv[2]);
+
27 
+
28  return 0;
+
29 }
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::utilities::read_tiff
Image read_tiff(std::string const &filename)
Reads tiff image.
Definition: utilities.cc:38
-

References sopt::logging::initialize(), sopt::notinstalled::read_standard_tiff(), sopt::utilities::read_tiff(), and sopt::utilities::write_tiff().

+

References sopt::notinstalled::read_standard_tiff(), sopt::utilities::read_tiff(), and sopt::utilities::write_tiff().

diff --git a/copy__tiff_8cc__incl.map b/copy__tiff_8cc__incl.map index 2519cc081..1ed8b7159 100644 --- a/copy__tiff_8cc__incl.map +++ b/copy__tiff_8cc__incl.map @@ -1,22 +1,25 @@ - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + diff --git a/copy__tiff_8cc__incl.md5 b/copy__tiff_8cc__incl.md5 index fdea31249..f1da02514 100644 --- a/copy__tiff_8cc__incl.md5 +++ b/copy__tiff_8cc__incl.md5 @@ -1 +1 @@ -087736bdf9d4e512b407fae219b94f48 \ No newline at end of file +cc3a3286c9c84e6ab7769d30ce3bd1eb \ No newline at end of file diff --git a/copy__tiff_8cc__incl.png b/copy__tiff_8cc__incl.png index e1369bae4..57fb06df9 100644 Binary files a/copy__tiff_8cc__incl.png and b/copy__tiff_8cc__incl.png differ diff --git a/copy__tiff_8cc_source.html b/copy__tiff_8cc_source.html index e4a68a7a3..860c449d3 100644 --- a/copy__tiff_8cc_source.html +++ b/copy__tiff_8cc_source.html @@ -100,21 +100,16 @@
19  exit(0);
20  }
21 
-
22  // Initializes and sets logger (if compiled with logging)
-
23  // See set_level function for levels.
-
24  sopt::logging::initialize();
+
22  // Read input file
+
23  auto const image = sopt::notinstalled::read_standard_tiff(argv[1]);
+
24  sopt::utilities::write_tiff(image, argv[2]);
25 
-
26  // Read input file
-
27  auto const image = sopt::notinstalled::read_standard_tiff(argv[1]);
-
28  sopt::utilities::write_tiff(image, argv[2]);
-
29 
-
30  auto const reread = sopt::utilities::read_tiff(argv[2]);
-
31 
-
32  return 0;
-
33 }
+
26  auto const reread = sopt::utilities::read_tiff(argv[2]);
+
27 
+
28  return 0;
+
29 }
main
int main(int argc, char const **argv)
Definition: copy_tiff.cc:14
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::utilities::read_tiff
Image read_tiff(std::string const &filename)
Reads tiff image.
Definition: utilities.cc:38
diff --git a/cppflow__model_8cc.html b/cppflow__model_8cc.html index c14dc44e4..2b92b1c49 100644 --- a/cppflow__model_8cc.html +++ b/cppflow__model_8cc.html @@ -101,28 +101,32 @@ diff --git a/cppflow__model_8cc__incl.map b/cppflow__model_8cc__incl.map index 36bb89b34..25152721a 100644 --- a/cppflow__model_8cc__incl.map +++ b/cppflow__model_8cc__incl.map @@ -1,24 +1,28 @@ - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/cppflow__model_8cc__incl.md5 b/cppflow__model_8cc__incl.md5 index 7cb67e31c..2a8effe4d 100644 --- a/cppflow__model_8cc__incl.md5 +++ b/cppflow__model_8cc__incl.md5 @@ -1 +1 @@ -8fd2c046376d975698276b1e820a9b99 \ No newline at end of file +a36cd7da7f2450b44f6b4dfbe32e85eb \ No newline at end of file diff --git a/cppflow__model_8cc__incl.png b/cppflow__model_8cc__incl.png index b20ba74b7..2a65045fe 100644 Binary files a/cppflow__model_8cc__incl.png and b/cppflow__model_8cc__incl.png differ diff --git a/credible__region_8cc.html b/credible__region_8cc.html index 34744cca9..4abb8bea5 100644 --- a/credible__region_8cc.html +++ b/credible__region_8cc.html @@ -95,33 +95,34 @@ @@ -284,7 +285,7 @@

Definition at line 16 of file credible_region.cc.

16  {
-
17  sopt::logging::set_level("debug");
+
17  logging::set_level("debug");
18  const std::function<t_real(t_Vector)> energy_function = [](const t_Vector &input) -> t_real {
19  return 0.;
20  };
@@ -297,10 +298,10 @@

27  }

28 }
sopt::credible_region::compute_energy_upper_bound
t_real compute_energy_upper_bound(const t_real &alpha, const Eigen::MatrixBase< T > &solution, const std::function< t_real(typename T::PlainObject)> &objective_function)
Definition: credible_region.h:61
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
sopt::t_uint
size_t t_uint
Root of the type hierarchy for unsigned integers.
Definition: types.h:15
-

References sopt::credible_region::compute_energy_upper_bound(), N, and sopt::logging::set_level().

+

References sopt::credible_region::compute_energy_upper_bound(), N, and sopt::logging::set_level().

diff --git a/credible__region_8cc__incl.map b/credible__region_8cc__incl.map index def0b4ff7..b31094839 100644 --- a/credible__region_8cc__incl.map +++ b/credible__region_8cc__incl.map @@ -1,29 +1,30 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/credible__region_8cc__incl.md5 b/credible__region_8cc__incl.md5 index 3c5cc408e..73b0dacc9 100644 --- a/credible__region_8cc__incl.md5 +++ b/credible__region_8cc__incl.md5 @@ -1 +1 @@ -59be5ba3d153a89d04d877bedae5f65f \ No newline at end of file +75e204d7a9fd010368fa7c598747bc2d \ No newline at end of file diff --git a/credible__region_8cc__incl.png b/credible__region_8cc__incl.png index 7817885b4..391108f63 100644 Binary files a/credible__region_8cc__incl.png and b/credible__region_8cc__incl.png differ diff --git a/credible__region_8cc_source.html b/credible__region_8cc_source.html index da1be8ed9..5b8326b45 100644 --- a/credible__region_8cc_source.html +++ b/credible__region_8cc_source.html @@ -95,7 +95,7 @@
14 t_uint N = rows * cols;
15 
16 TEST_CASE("calculating gamma") {
-
17  sopt::logging::set_level("debug");
+
17  logging::set_level("debug");
18  const std::function<t_real(t_Vector)> energy_function = [](const t_Vector &input) -> t_real {
19  return 0.;
20  };
@@ -197,7 +197,7 @@
credible_region.h
sopt::credible_region::find_credible_interval
std::tuple< t_real, t_real, t_real > find_credible_interval(const Eigen::MatrixBase< T > &solution, const t_uint &rows, const t_uint &cols, const std::tuple< t_uint, t_uint, t_uint, t_uint > &region, const std::function< t_real(typename T::PlainObject)> &objective_function, const t_real &energy_upperbound)
Definition: credible_region.h:75
sopt::credible_region::compute_energy_upper_bound
t_real compute_energy_upper_bound(const t_real &alpha, const Eigen::MatrixBase< T > &solution, const std::function< t_real(typename T::PlainObject)> &objective_function)
Definition: credible_region.h:61
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
sopt::t_real
double t_real
Root of the type hierarchy for real numbers.
Definition: types.h:17
sopt::t_uint
size_t t_uint
Root of the type hierarchy for unsigned integers.
Definition: types.h:15
diff --git a/credible__region_8h.html b/credible__region_8h.html index 379664601..84c4fd3fc 100644 --- a/credible__region_8h.html +++ b/credible__region_8h.html @@ -100,25 +100,26 @@
diff --git a/credible__region_8h__incl.map b/credible__region_8h__incl.map index 9fdb8b56a..b7677a21b 100644 --- a/credible__region_8h__incl.map +++ b/credible__region_8h__incl.map @@ -1,21 +1,22 @@ - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + diff --git a/credible__region_8h__incl.md5 b/credible__region_8h__incl.md5 index 89741b2f4..9cd10af12 100644 --- a/credible__region_8h__incl.md5 +++ b/credible__region_8h__incl.md5 @@ -1 +1 @@ -275b6a04e80e9cab29090aa1752ecfbb \ No newline at end of file +67709ea4394910212f01493ca9a6c58f \ No newline at end of file diff --git a/credible__region_8h__incl.png b/credible__region_8h__incl.png index 8807149a8..d708be50f 100644 Binary files a/credible__region_8h__incl.png and b/credible__region_8h__incl.png differ diff --git a/credible__region_8h_source.html b/credible__region_8h_source.html index 9fd6fd7a4..4ef617045 100644 --- a/credible__region_8h_source.html +++ b/credible__region_8h_source.html @@ -286,8 +286,8 @@
SOPT_THROW
#define SOPT_THROW(MSG)
Definition: exception.h:46
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::credible_region
Definition: credible_region.h:16
sopt::credible_region::credible_interval_grid
std::enable_if< is_complex< K >::value or std::is_arithmetic< K >::value, std::tuple< Image< K >, Image< K >, Image< K > > >::type credible_interval_grid(const Eigen::MatrixBase< T > &solution, const t_uint &rows, const t_uint &cols, const t_uint &grid_pixel_size, const std::function< t_real(typename T::PlainObject)> &objective_function, const t_real &energy_upperbound)
Definition: credible_region.h:117
sopt::credible_region::find_credible_interval
std::tuple< t_real, t_real, t_real > find_credible_interval(const Eigen::MatrixBase< T > &solution, const t_uint &rows, const t_uint &cols, const std::tuple< t_uint, t_uint, t_uint, t_uint > &region, const std::function< t_real(typename T::PlainObject)> &objective_function, const t_real &energy_upperbound)
Definition: credible_region.h:75
diff --git a/dir_b02fe8fb06533d453d0d12b8152263dd.html b/dir_b02fe8fb06533d453d0d12b8152263dd.html index 59c3f7646..305159487 100644 --- a/dir_b02fe8fb06533d453d0d12b8152263dd.html +++ b/dir_b02fe8fb06533d453d0d12b8152263dd.html @@ -143,9 +143,7 @@   file  linear_transform.h [code]   -file  logging.disabled.h [code] -  -file  logging.enabled.h [code] +file  logging.cc [code]   file  logging.h [code]   diff --git a/examples_2conjugate__gradient_8cc.html b/examples_2conjugate__gradient_8cc.html index eca3fe3d9..89a7caf3a 100644 --- a/examples_2conjugate__gradient_8cc.html +++ b/examples_2conjugate__gradient_8cc.html @@ -91,28 +91,29 @@
diff --git a/examples_2conjugate__gradient_8cc__incl.map b/examples_2conjugate__gradient_8cc__incl.map index 4d5b6f86c..582f00771 100644 --- a/examples_2conjugate__gradient_8cc__incl.map +++ b/examples_2conjugate__gradient_8cc__incl.map @@ -1,24 +1,25 @@ - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2conjugate__gradient_8cc__incl.md5 b/examples_2conjugate__gradient_8cc__incl.md5 index cfbb58832..648bb695d 100644 --- a/examples_2conjugate__gradient_8cc__incl.md5 +++ b/examples_2conjugate__gradient_8cc__incl.md5 @@ -1 +1 @@ -e01a98be5bcb6584149f8fb8ba2252b3 \ No newline at end of file +9469e3b8e0ca32ccdd533cbd784b21fe \ No newline at end of file diff --git a/examples_2conjugate__gradient_8cc__incl.png b/examples_2conjugate__gradient_8cc__incl.png index a9ee278d5..d2553f348 100644 Binary files a/examples_2conjugate__gradient_8cc__incl.png and b/examples_2conjugate__gradient_8cc__incl.png differ diff --git a/examples_2forward__backward_2inpainting_8cc.html b/examples_2forward__backward_2inpainting_8cc.html index 0085fbef2..def78c65d 100644 --- a/examples_2forward__backward_2inpainting_8cc.html +++ b/examples_2forward__backward_2inpainting_8cc.html @@ -106,55 +106,56 @@
@@ -224,86 +225,85 @@

52 
53  // Initializes and sets logger (if compiled with logging)
54  // See set_level function for levels.
-
55  sopt::logging::initialize();
-
56  sopt::logging::set_level("debug");
-
57  SOPT_HIGH_LOG("Read input file {}", input);
-
58  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
59  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
-
60 
-
61  SOPT_HIGH_LOG("Initializing sensing operator");
-
62  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
-
63  sopt::LinearTransform<Vector> const sampling =
-
64  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
-
65  SOPT_HIGH_LOG("Initializing wavelets");
-
66  auto const wavelet = sopt::wavelets::factory("DB8", 4);
-
67 
-
68  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
-
69  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
-
70 
-
71  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
72  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
-
73 
-
74  SOPT_HIGH_LOG("Computing Forward Backward parameters");
-
75  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
76  auto constexpr snr = 30.0;
-
77  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
78  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
79 
-
80  SOPT_HIGH_LOG("Create dirty vector");
-
81  std::normal_distribution<> gaussian_dist(0, sigma);
-
82  Vector y(y0.size());
-
83  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
84  // Write dirty imagte to file
-
85  if (output != "none") {
-
86  Vector const dirty = sampling.adjoint() * y;
-
87  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
88  "dirty_" + output + ".tiff");
-
89  }
-
90 
-
91  sopt::t_real constexpr gamma = 18;
-
92  sopt::t_real const beta = sigma * sigma * 0.5;
-
93  SOPT_HIGH_LOG("Creating Foward Backward Functor");
-
94  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
-
95  .itermax(500)
-
96  .beta(beta) // stepsize
-
97  .sigma(sigma) // sigma
-
98  .gamma(gamma) // regularisation paramater
-
99  .relative_variation(1e-3)
-
100  .residual_tolerance(0)
-
101  .tight_frame(true)
-
102  .Phi(sampling);
-
103 
-
104  // Create a shared pointer to an instance of the L1GProximal class
-
105  // and set its properties
-
106  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
-
107  gp->l1_proximal_tolerance(1e-4)
-
108  .l1_proximal_nu(1)
-
109  .l1_proximal_itermax(50)
-
110  .l1_proximal_positivity_constraint(true)
-
111  .l1_proximal_real_constraint(true)
-
112  .Psi(psi);
-
113 
-
114  // Once the properties are set, inject it into the ImagingForwardBackward object
-
115  fb.g_proximal(gp);
-
116 
-
117  SOPT_HIGH_LOG("Starting Forward Backward");
-
118  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
-
119  // Here, we default to (y, Φx/ν - y)
-
120  auto const diagnostic = fb();
-
121  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
-
122 
-
123  if (output != "none")
-
124  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
-
125  output + ".tiff");
-
126  // diagnostic should tell us the function converged
-
127  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
128  // diagnostic from the last call to the conjugate gradient.
-
129  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
-
130 
-
131  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
-
132 
-
133  return 0;
-
134 }
+
55  sopt::logging::set_level("debug");
+
56  SOPT_HIGH_LOG("Read input file {}", input);
+
57  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
58  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
+
59 
+
60  SOPT_HIGH_LOG("Initializing sensing operator");
+
61  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
+
62  sopt::LinearTransform<Vector> const sampling =
+
63  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
64  SOPT_HIGH_LOG("Initializing wavelets");
+
65  auto const wavelet = sopt::wavelets::factory("DB8", 4);
+
66 
+
67  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
+
68  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
+
69 
+
70  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
+
71  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
+
72 
+
73  SOPT_HIGH_LOG("Computing Forward Backward parameters");
+
74  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
75  auto constexpr snr = 30.0;
+
76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
78 
+
79  SOPT_HIGH_LOG("Create dirty vector");
+
80  std::normal_distribution<> gaussian_dist(0, sigma);
+
81  Vector y(y0.size());
+
82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
83  // Write dirty imagte to file
+
84  if (output != "none") {
+
85  Vector const dirty = sampling.adjoint() * y;
+
86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
87  "dirty_" + output + ".tiff");
+
88  }
+
89 
+
90  sopt::t_real constexpr gamma = 18;
+
91  sopt::t_real const beta = sigma * sigma * 0.5;
+
92  SOPT_HIGH_LOG("Creating Foward Backward Functor");
+
93  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
+
94  .itermax(500)
+
95  .beta(beta) // stepsize
+
96  .sigma(sigma) // sigma
+
97  .gamma(gamma) // regularisation paramater
+
98  .relative_variation(1e-3)
+
99  .residual_tolerance(0)
+
100  .tight_frame(true)
+
101  .Phi(sampling);
+
102 
+
103  // Create a shared pointer to an instance of the L1GProximal class
+
104  // and set its properties
+
105  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
+
106  gp->l1_proximal_tolerance(1e-4)
+
107  .l1_proximal_nu(1)
+
108  .l1_proximal_itermax(50)
+
109  .l1_proximal_positivity_constraint(true)
+
110  .l1_proximal_real_constraint(true)
+
111  .Psi(psi);
+
112 
+
113  // Once the properties are set, inject it into the ImagingForwardBackward object
+
114  fb.g_proximal(gp);
+
115 
+
116  SOPT_HIGH_LOG("Starting Forward Backward");
+
117  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
+
118  // Here, we default to (y, Φx/ν - y)
+
119  auto const diagnostic = fb();
+
120  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
+
121 
+
122  if (output != "none")
+
123  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
+
124  output + ".tiff");
+
125  // diagnostic should tell us the function converged
+
126  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
127  // diagnostic from the last call to the conjugate gradient.
+
128  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
+
129 
+
130  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
+
131 
+
132  return 0;
+
133 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::LinearTransform
Joins together direct and indirect operators.
Definition: linear_transform.h:30
sopt::LinearTransform::adjoint
LinearTransform< VECTOR > adjoint() const
Indirect transform.
Definition: linear_transform.h:79
@@ -313,10 +313,9 @@

sopt::algorithm::ImagingForwardBackward::Phi
ImagingForwardBackward &::type Phi(ARGS &&... args)
Definition: imaging_forward_backward.h:202
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::wavelets::factory
Wavelet factory(const std::string &name, t_uint nlevels)
Creates a wavelet transform object.
Definition: wavelets.cc:8
@@ -332,7 +331,7 @@

Vector
sopt::Vector< Scalar > Vector
Definition: inpainting.cc:28
Matrix
sopt::Matrix< Scalar > Matrix
Definition: inpainting.cc:29
-

References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::algorithm::ImagingForwardBackward< SCALAR >::g_proximal(), sopt::logging::initialize(), mersenne(), sopt::algorithm::ImagingForwardBackward< SCALAR >::Phi(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

+

References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::algorithm::ImagingForwardBackward< SCALAR >::g_proximal(), mersenne(), sopt::algorithm::ImagingForwardBackward< SCALAR >::Phi(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

diff --git a/examples_2forward__backward_2inpainting_8cc__incl.map b/examples_2forward__backward_2inpainting_8cc__incl.map index 853957f83..b976563f2 100644 --- a/examples_2forward__backward_2inpainting_8cc__incl.map +++ b/examples_2forward__backward_2inpainting_8cc__incl.map @@ -1,51 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2forward__backward_2inpainting_8cc__incl.md5 b/examples_2forward__backward_2inpainting_8cc__incl.md5 index 55704f679..066a9f1c7 100644 --- a/examples_2forward__backward_2inpainting_8cc__incl.md5 +++ b/examples_2forward__backward_2inpainting_8cc__incl.md5 @@ -1 +1 @@ -7a62c16e3d23dfbd5b58c74579534022 \ No newline at end of file +56ccf4f3db93a6c7b48978f43b566bb5 \ No newline at end of file diff --git a/examples_2forward__backward_2inpainting_8cc__incl.png b/examples_2forward__backward_2inpainting_8cc__incl.png index 9f3ef85a0..1fcf7659e 100644 Binary files a/examples_2forward__backward_2inpainting_8cc__incl.png and b/examples_2forward__backward_2inpainting_8cc__incl.png differ diff --git a/examples_2forward__backward_2inpainting_8cc_source.html b/examples_2forward__backward_2inpainting_8cc_source.html index eeaffc623..ef8bde42b 100644 --- a/examples_2forward__backward_2inpainting_8cc_source.html +++ b/examples_2forward__backward_2inpainting_8cc_source.html @@ -133,86 +133,85 @@
52 
53  // Initializes and sets logger (if compiled with logging)
54  // See set_level function for levels.
-
55  sopt::logging::initialize();
-
56  sopt::logging::set_level("debug");
-
57  SOPT_HIGH_LOG("Read input file {}", input);
-
58  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
59  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
-
60 
-
61  SOPT_HIGH_LOG("Initializing sensing operator");
-
62  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
-
63  sopt::LinearTransform<Vector> const sampling =
-
64  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
-
65  SOPT_HIGH_LOG("Initializing wavelets");
-
66  auto const wavelet = sopt::wavelets::factory("DB8", 4);
-
67 
-
68  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
-
69  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
-
70 
-
71  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
72  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
-
73 
-
74  SOPT_HIGH_LOG("Computing Forward Backward parameters");
-
75  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
76  auto constexpr snr = 30.0;
-
77  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
78  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
79 
-
80  SOPT_HIGH_LOG("Create dirty vector");
-
81  std::normal_distribution<> gaussian_dist(0, sigma);
-
82  Vector y(y0.size());
-
83  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
84  // Write dirty imagte to file
-
85  if (output != "none") {
-
86  Vector const dirty = sampling.adjoint() * y;
-
87  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
88  "dirty_" + output + ".tiff");
-
89  }
-
90 
-
91  sopt::t_real constexpr gamma = 18;
-
92  sopt::t_real const beta = sigma * sigma * 0.5;
-
93  SOPT_HIGH_LOG("Creating Foward Backward Functor");
-
94  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
-
95  .itermax(500)
-
96  .beta(beta) // stepsize
-
97  .sigma(sigma) // sigma
-
98  .gamma(gamma) // regularisation paramater
-
99  .relative_variation(1e-3)
-
100  .residual_tolerance(0)
-
101  .tight_frame(true)
-
102  .Phi(sampling);
-
103 
-
104  // Create a shared pointer to an instance of the L1GProximal class
-
105  // and set its properties
-
106  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
-
107  gp->l1_proximal_tolerance(1e-4)
-
108  .l1_proximal_nu(1)
-
109  .l1_proximal_itermax(50)
-
110  .l1_proximal_positivity_constraint(true)
-
111  .l1_proximal_real_constraint(true)
-
112  .Psi(psi);
-
113 
-
114  // Once the properties are set, inject it into the ImagingForwardBackward object
-
115  fb.g_proximal(gp);
-
116 
-
117  SOPT_HIGH_LOG("Starting Forward Backward");
-
118  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
-
119  // Here, we default to (y, Φx/ν - y)
-
120  auto const diagnostic = fb();
-
121  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
-
122 
-
123  if (output != "none")
-
124  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
-
125  output + ".tiff");
-
126  // diagnostic should tell us the function converged
-
127  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
128  // diagnostic from the last call to the conjugate gradient.
-
129  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
-
130 
-
131  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
-
132 
-
133  return 0;
-
134 }
+
55  sopt::logging::set_level("debug");
+
56  SOPT_HIGH_LOG("Read input file {}", input);
+
57  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
58  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
+
59 
+
60  SOPT_HIGH_LOG("Initializing sensing operator");
+
61  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
+
62  sopt::LinearTransform<Vector> const sampling =
+
63  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
64  SOPT_HIGH_LOG("Initializing wavelets");
+
65  auto const wavelet = sopt::wavelets::factory("DB8", 4);
+
66 
+
67  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
+
68  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
+
69 
+
70  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
+
71  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
+
72 
+
73  SOPT_HIGH_LOG("Computing Forward Backward parameters");
+
74  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
75  auto constexpr snr = 30.0;
+
76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
78 
+
79  SOPT_HIGH_LOG("Create dirty vector");
+
80  std::normal_distribution<> gaussian_dist(0, sigma);
+
81  Vector y(y0.size());
+
82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
83  // Write dirty imagte to file
+
84  if (output != "none") {
+
85  Vector const dirty = sampling.adjoint() * y;
+
86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
87  "dirty_" + output + ".tiff");
+
88  }
+
89 
+
90  sopt::t_real constexpr gamma = 18;
+
91  sopt::t_real const beta = sigma * sigma * 0.5;
+
92  SOPT_HIGH_LOG("Creating Foward Backward Functor");
+
93  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
+
94  .itermax(500)
+
95  .beta(beta) // stepsize
+
96  .sigma(sigma) // sigma
+
97  .gamma(gamma) // regularisation paramater
+
98  .relative_variation(1e-3)
+
99  .residual_tolerance(0)
+
100  .tight_frame(true)
+
101  .Phi(sampling);
+
102 
+
103  // Create a shared pointer to an instance of the L1GProximal class
+
104  // and set its properties
+
105  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
+
106  gp->l1_proximal_tolerance(1e-4)
+
107  .l1_proximal_nu(1)
+
108  .l1_proximal_itermax(50)
+
109  .l1_proximal_positivity_constraint(true)
+
110  .l1_proximal_real_constraint(true)
+
111  .Psi(psi);
+
112 
+
113  // Once the properties are set, inject it into the ImagingForwardBackward object
+
114  fb.g_proximal(gp);
+
115 
+
116  SOPT_HIGH_LOG("Starting Forward Backward");
+
117  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
+
118  // Here, we default to (y, Φx/ν - y)
+
119  auto const diagnostic = fb();
+
120  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
+
121 
+
122  if (output != "none")
+
123  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
+
124  output + ".tiff");
+
125  // diagnostic should tell us the function converged
+
126  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
127  // diagnostic from the last call to the conjugate gradient.
+
128  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
+
129 
+
130  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
+
131 
+
132  return 0;
+
133 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::LinearTransform
Joins together direct and indirect operators.
Definition: linear_transform.h:30
sopt::LinearTransform::adjoint
LinearTransform< VECTOR > adjoint() const
Indirect transform.
Definition: linear_transform.h:79
@@ -226,11 +225,10 @@
imaging_forward_backward.h
l1_g_proximal.h
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::wavelets::factory
Wavelet factory(const std::string &name, t_uint nlevels)
Creates a wavelet transform object.
Definition: wavelets.cc:8
diff --git a/examples_2l1__proximal_8cc.html b/examples_2l1__proximal_8cc.html index 7a32d3575..cae05580b 100644 --- a/examples_2l1__proximal_8cc.html +++ b/examples_2l1__proximal_8cc.html @@ -91,29 +91,30 @@ @@ -153,57 +154,55 @@

Definition at line 5 of file l1_proximal.cc.

5  {
-
6  sopt::logging::initialize();
-
7 
-
8  using Scalar = sopt::t_complex;
-
9  using Real = sopt::real_type<Scalar>::type;
-
10  auto const input = sopt::Vector<Scalar>::Random(10).eval();
-
11  auto const Psi = sopt::Matrix<Scalar>::Random(input.size(), input.size() * 10).eval();
-
12  sopt::Vector<Real> const weights =
-
13  sopt::Vector<Scalar>::Random(Psi.cols()).normalized().array().abs();
-
14 
-
15  auto const l1 = sopt::proximal::L1<Scalar>()
-
16  .tolerance(1e-12)
-
17  .itermax(100)
-
18  .fista_mixing(true)
-
19  .positivity_constraint(true)
-
20  .nu(1)
-
21  .Psi(Psi)
-
22  .weights(weights);
-
23 
-
24  // gamma should be sufficiently small. Or is it nu should not be 1?
-
25  // In any case, this seems to work.
-
26  Real const gamma = 1e-2 / Psi.array().abs().sum();
-
27  auto const result = l1(gamma, input);
-
28 
-
29  if (not result.good) SOPT_THROW("Did not converge");
-
30 
-
31  // Check the proximal is a minimum in any allowed direction (positivity constraint)
-
32  Real constexpr eps = 1e-4;
-
33  for (size_t i(0); i < 10; ++i) {
-
34  sopt::Vector<Scalar> const dir = sopt::Vector<Scalar>::Random(input.size()).normalized() * eps;
-
35  sopt::Vector<Scalar> const position = sopt::positive_quadrant(result.proximal + dir);
-
36  Real const dobj = l1.objective(input, position, gamma);
-
37  // Fuzzy logic
-
38  if (dobj < result.objective - 1e-8)
-
39  SOPT_THROW("This is not the minimum we are looking for: ")
-
40  << dobj << " <~ " << result.objective;
-
41  }
-
42 
-
43  return 0;
-
44 }
+
6 
+
7  using Scalar = sopt::t_complex;
+
8  using Real = sopt::real_type<Scalar>::type;
+
9  auto const input = sopt::Vector<Scalar>::Random(10).eval();
+
10  auto const Psi = sopt::Matrix<Scalar>::Random(input.size(), input.size() * 10).eval();
+
11  sopt::Vector<Real> const weights =
+
12  sopt::Vector<Scalar>::Random(Psi.cols()).normalized().array().abs();
+
13 
+
14  auto const l1 = sopt::proximal::L1<Scalar>()
+
15  .tolerance(1e-12)
+
16  .itermax(100)
+
17  .fista_mixing(true)
+
18  .positivity_constraint(true)
+
19  .nu(1)
+
20  .Psi(Psi)
+
21  .weights(weights);
+
22 
+
23  // gamma should be sufficiently small. Or is it nu should not be 1?
+
24  // In any case, this seems to work.
+
25  Real const gamma = 1e-2 / Psi.array().abs().sum();
+
26  auto const result = l1(gamma, input);
+
27 
+
28  if (not result.good) SOPT_THROW("Did not converge");
+
29 
+
30  // Check the proximal is a minimum in any allowed direction (positivity constraint)
+
31  Real constexpr eps = 1e-4;
+
32  for (size_t i(0); i < 10; ++i) {
+
33  sopt::Vector<Scalar> const dir = sopt::Vector<Scalar>::Random(input.size()).normalized() * eps;
+
34  sopt::Vector<Scalar> const position = sopt::positive_quadrant(result.proximal + dir);
+
35  Real const dobj = l1.objective(input, position, gamma);
+
36  // Fuzzy logic
+
37  if (dobj < result.objective - 1e-8)
+
38  SOPT_THROW("This is not the minimum we are looking for: ")
+
39  << dobj << " <~ " << result.objective;
+
40  }
+
41 
+
42  return 0;
+
43 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::details::underlying_value_type
Computes inner-most element type.
Definition: real_type.h:42
sopt::proximal::L1::nu
Real nu() const
Bounds on the squared norm of the operator Ψ
Definition: l1_proximal.h:294
SOPT_THROW
#define SOPT_THROW(MSG)
Definition: exception.h:46
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::positive_quadrant
Eigen::CwiseUnaryOp< const details::ProjectPositiveQuadrant< typename T::Scalar >, const T > positive_quadrant(Eigen::DenseBase< T > const &input)
Expression to create projection onto positive quadrant.
Definition: maths.h:60
sopt::Vector
Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
A vector of a given type.
Definition: types.h:24
sopt::t_complex
std::complex< t_real > t_complex
Root of the type hierarchy for (real) complex numbers.
Definition: types.h:19
sopt::Matrix
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
A matrix of a given type.
Definition: types.h:29
-

References sopt::logging::initialize(), sopt::proximal::L1< SCALAR >::nu(), sopt::positive_quadrant(), and SOPT_THROW.

+

References sopt::proximal::L1< SCALAR >::nu(), sopt::positive_quadrant(), and SOPT_THROW.

diff --git a/examples_2l1__proximal_8cc__incl.map b/examples_2l1__proximal_8cc__incl.map index d53183e0b..dfba3a4ba 100644 --- a/examples_2l1__proximal_8cc__incl.map +++ b/examples_2l1__proximal_8cc__incl.map @@ -1,25 +1,26 @@ - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2l1__proximal_8cc__incl.md5 b/examples_2l1__proximal_8cc__incl.md5 index 46093df87..32b8c3049 100644 --- a/examples_2l1__proximal_8cc__incl.md5 +++ b/examples_2l1__proximal_8cc__incl.md5 @@ -1 +1 @@ -e90dfce1a98b9f728bcba1a9349802c7 \ No newline at end of file +6128f2f574950265506534543b783929 \ No newline at end of file diff --git a/examples_2l1__proximal_8cc__incl.png b/examples_2l1__proximal_8cc__incl.png index a290d3ca0..824114155 100644 Binary files a/examples_2l1__proximal_8cc__incl.png and b/examples_2l1__proximal_8cc__incl.png differ diff --git a/examples_2l1__proximal_8cc_source.html b/examples_2l1__proximal_8cc_source.html index f30577166..f3d9e309e 100644 --- a/examples_2l1__proximal_8cc_source.html +++ b/examples_2l1__proximal_8cc_source.html @@ -84,45 +84,44 @@
3 #include "sopt/types.h"
4 
5 int main(int, char const **) {
-
6  sopt::logging::initialize();
-
7 
-
8  using Scalar = sopt::t_complex;
-
9  using Real = sopt::real_type<Scalar>::type;
-
10  auto const input = sopt::Vector<Scalar>::Random(10).eval();
-
11  auto const Psi = sopt::Matrix<Scalar>::Random(input.size(), input.size() * 10).eval();
-
12  sopt::Vector<Real> const weights =
-
13  sopt::Vector<Scalar>::Random(Psi.cols()).normalized().array().abs();
-
14 
-
15  auto const l1 = sopt::proximal::L1<Scalar>()
-
16  .tolerance(1e-12)
-
17  .itermax(100)
-
18  .fista_mixing(true)
-
19  .positivity_constraint(true)
-
20  .nu(1)
-
21  .Psi(Psi)
-
22  .weights(weights);
-
23 
-
24  // gamma should be sufficiently small. Or is it nu should not be 1?
-
25  // In any case, this seems to work.
-
26  Real const gamma = 1e-2 / Psi.array().abs().sum();
-
27  auto const result = l1(gamma, input);
-
28 
-
29  if (not result.good) SOPT_THROW("Did not converge");
-
30 
-
31  // Check the proximal is a minimum in any allowed direction (positivity constraint)
-
32  Real constexpr eps = 1e-4;
-
33  for (size_t i(0); i < 10; ++i) {
-
34  sopt::Vector<Scalar> const dir = sopt::Vector<Scalar>::Random(input.size()).normalized() * eps;
-
35  sopt::Vector<Scalar> const position = sopt::positive_quadrant(result.proximal + dir);
-
36  Real const dobj = l1.objective(input, position, gamma);
-
37  // Fuzzy logic
-
38  if (dobj < result.objective - 1e-8)
-
39  SOPT_THROW("This is not the minimum we are looking for: ")
-
40  << dobj << " <~ " << result.objective;
-
41  }
-
42 
-
43  return 0;
-
44 }
+
6 
+
7  using Scalar = sopt::t_complex;
+
8  using Real = sopt::real_type<Scalar>::type;
+
9  auto const input = sopt::Vector<Scalar>::Random(10).eval();
+
10  auto const Psi = sopt::Matrix<Scalar>::Random(input.size(), input.size() * 10).eval();
+
11  sopt::Vector<Real> const weights =
+
12  sopt::Vector<Scalar>::Random(Psi.cols()).normalized().array().abs();
+
13 
+
14  auto const l1 = sopt::proximal::L1<Scalar>()
+
15  .tolerance(1e-12)
+
16  .itermax(100)
+
17  .fista_mixing(true)
+
18  .positivity_constraint(true)
+
19  .nu(1)
+
20  .Psi(Psi)
+
21  .weights(weights);
+
22 
+
23  // gamma should be sufficiently small. Or is it nu should not be 1?
+
24  // In any case, this seems to work.
+
25  Real const gamma = 1e-2 / Psi.array().abs().sum();
+
26  auto const result = l1(gamma, input);
+
27 
+
28  if (not result.good) SOPT_THROW("Did not converge");
+
29 
+
30  // Check the proximal is a minimum in any allowed direction (positivity constraint)
+
31  Real constexpr eps = 1e-4;
+
32  for (size_t i(0); i < 10; ++i) {
+
33  sopt::Vector<Scalar> const dir = sopt::Vector<Scalar>::Random(input.size()).normalized() * eps;
+
34  sopt::Vector<Scalar> const position = sopt::positive_quadrant(result.proximal + dir);
+
35  Real const dobj = l1.objective(input, position, gamma);
+
36  // Fuzzy logic
+
37  if (dobj < result.objective - 1e-8)
+
38  SOPT_THROW("This is not the minimum we are looking for: ")
+
39  << dobj << " <~ " << result.objective;
+
40  }
+
41 
+
42  return 0;
+
43 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::details::underlying_value_type
Computes inner-most element type.
Definition: real_type.h:42
@@ -131,7 +130,6 @@
SOPT_THROW
#define SOPT_THROW(MSG)
Definition: exception.h:46
l1_proximal.h
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::positive_quadrant
Eigen::CwiseUnaryOp< const details::ProjectPositiveQuadrant< typename T::Scalar >, const T > positive_quadrant(Eigen::DenseBase< T > const &input)
Expression to create projection onto positive quadrant.
Definition: maths.h:60
sopt::Vector
Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
A vector of a given type.
Definition: types.h:24
sopt::t_complex
std::complex< t_real > t_complex
Root of the type hierarchy for (real) complex numbers.
Definition: types.h:19
diff --git a/examples_2power__method_8cc.html b/examples_2power__method_8cc.html index 588cc69aa..ae977a337 100644 --- a/examples_2power__method_8cc.html +++ b/examples_2power__method_8cc.html @@ -91,33 +91,34 @@ diff --git a/examples_2power__method_8cc__incl.map b/examples_2power__method_8cc__incl.map index 021e207f6..0ac6d5f37 100644 --- a/examples_2power__method_8cc__incl.map +++ b/examples_2power__method_8cc__incl.map @@ -1,29 +1,30 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2power__method_8cc__incl.md5 b/examples_2power__method_8cc__incl.md5 index cf7f38a82..e79b94dd3 100644 --- a/examples_2power__method_8cc__incl.md5 +++ b/examples_2power__method_8cc__incl.md5 @@ -1 +1 @@ -e83a54ae985348c163af27406b348a1b \ No newline at end of file +0e5afcda8acb89bf67074bf27e9d839e \ No newline at end of file diff --git a/examples_2power__method_8cc__incl.png b/examples_2power__method_8cc__incl.png index 518bd4820..b69a72efb 100644 Binary files a/examples_2power__method_8cc__incl.png and b/examples_2power__method_8cc__incl.png differ diff --git a/examples_2primal__dual_2inpainting_8cc.html b/examples_2primal__dual_2inpainting_8cc.html index b7a8636b1..b5c27655d 100644 --- a/examples_2primal__dual_2inpainting_8cc.html +++ b/examples_2primal__dual_2inpainting_8cc.html @@ -109,55 +109,56 @@ @@ -227,77 +228,73 @@

57  std::srand(static_cast<unsigned int>(seed));
58  std::mt19937 mersenne(std::time(nullptr));
59 
-
60  // Initializes and sets logger (if compiled with logging)
-
61  // See set_level function for levels.
-
62  sopt::logging::initialize();
-
63 
-
64  SOPT_HIGH_LOG("Read input file {}", input);
-
65  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
66 
-
67  SOPT_HIGH_LOG("Initializing sensing operator");
-
68  sopt::t_uint const nmeasure = 0.33 * image.size();
-
69  auto const sampling =
-
70  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
60  SOPT_HIGH_LOG("Read input file {}", input);
+
61  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
62 
+
63  SOPT_HIGH_LOG("Initializing sensing operator");
+
64  sopt::t_uint const nmeasure = 0.33 * image.size();
+
65  auto const sampling =
+
66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
67 
+
68  SOPT_HIGH_LOG("Initializing wavelets");
+
69  // Below we define a simple wavelet set for testing
+
70  auto const wavelet = sopt::wavelets::factory("DB4", 4);
71 
-
72  SOPT_HIGH_LOG("Initializing wavelets");
-
73  // Below we define a simple wavelet set for testing
-
74  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
75 
-
76  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
-
77  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
-
78 
-
79  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
80 
-
81  SOPT_HIGH_LOG("Computing primal-dual parameters");
-
82  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
72  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
+
73  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
+
74 
+
75  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
+
76 
+
77  SOPT_HIGH_LOG("Computing primal-dual parameters");
+
78  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
79 
+
80  auto constexpr snr = 30.0;
+
81  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
82  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
83 
-
84  auto constexpr snr = 30.0;
-
85  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
86  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
87 
-
88  SOPT_HIGH_LOG("Create dirty vector");
-
89  std::normal_distribution<> gaussian_dist(0, sigma);
-
90  Vector y(y0.size());
-
91  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
92  // Write dirty image to file
-
93  if (output != "none") {
-
94  Vector const dirty = sampling.adjoint() * y;
-
95  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
96  "dirty_" + output + ".tiff");
-
97  }
-
98  sopt::t_real const gamma = (psi.adjoint() * (sampling.adjoint() * y)).real().maxCoeff() * 1e-2;
-
99 
-
100  SOPT_HIGH_LOG("Creating primal-dual Functor");
-
101  auto const pd = sopt::algorithm::ImagingPrimalDual<Scalar>(y)
-
102  .itermax(500)
-
103  .gamma(gamma)
-
104  .tau(0.5)
-
105  .l2ball_proximal_epsilon(epsilon)
-
106  .Psi(psi)
-
107  .Phi(sampling)
-
108  .relative_variation(5e-4)
-
109  .residual_convergence(epsilon)
-
110  .positivity_constraint(true);
-
111 
-
112  SOPT_HIGH_LOG("Starting primal dual");
-
113  // Alternatively, pd can be called with a tuple (x, residual) as argument
-
114  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
-
115  auto const diagnostic = pd();
-
116  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
-
117 
-
118  // diagnostic should tell us the function converged
-
119  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
120  // diagnostic from the last call to the conjugate gradient.
-
121  if (not diagnostic.good) {
-
122  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
-
123  // throw std::runtime_error("Did not converge!");
-
124  }
-
125  if (output != "none")
-
126  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
-
127  output + ".tiff");
-
128 
-
129  return 0;
-
130 }
+
84  SOPT_HIGH_LOG("Create dirty vector");
+
85  std::normal_distribution<> gaussian_dist(0, sigma);
+
86  Vector y(y0.size());
+
87  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
88  // Write dirty image to file
+
89  if (output != "none") {
+
90  Vector const dirty = sampling.adjoint() * y;
+
91  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
92  "dirty_" + output + ".tiff");
+
93  }
+
94  sopt::t_real const gamma = (psi.adjoint() * (sampling.adjoint() * y)).real().maxCoeff() * 1e-2;
+
95 
+
96  SOPT_HIGH_LOG("Creating primal-dual Functor");
+
97  auto const pd = sopt::algorithm::ImagingPrimalDual<Scalar>(y)
+
98  .itermax(500)
+
99  .gamma(gamma)
+
100  .tau(0.5)
+
101  .l2ball_proximal_epsilon(epsilon)
+
102  .Psi(psi)
+
103  .Phi(sampling)
+
104  .relative_variation(5e-4)
+
105  .residual_convergence(epsilon)
+
106  .positivity_constraint(true);
+
107 
+
108  SOPT_HIGH_LOG("Starting primal dual");
+
109  // Alternatively, pd can be called with a tuple (x, residual) as argument
+
110  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
+
111  auto const diagnostic = pd();
+
112  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
+
113 
+
114  // diagnostic should tell us the function converged
+
115  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
116  // diagnostic from the last call to the conjugate gradient.
+
117  if (not diagnostic.good) {
+
118  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
+
119  // throw std::runtime_error("Did not converge!");
+
120  }
+
121  if (output != "none")
+
122  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
+
123  output + ".tiff");
+
124 
+
125  return 0;
+
126 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -306,8 +303,7 @@

sopt::algorithm::ImagingPrimalDual::Phi
ImagingPrimalDual &::type Phi(ARGS &&... args)
Definition: imaging_primal_dual.h:219
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::wavelets::factory
Wavelet factory(const std::string &name, t_uint nlevels)
Creates a wavelet transform object.
Definition: wavelets.cc:8
@@ -323,7 +319,7 @@

Vector
sopt::Vector< Scalar > Vector
Definition: inpainting.cc:28
Matrix
sopt::Matrix< Scalar > Matrix
Definition: inpainting.cc:29
-

References sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::logging::initialize(), mersenne(), sopt::algorithm::ImagingPrimalDual< SCALAR >::Phi(), sopt::algorithm::ImagingPrimalDual< SCALAR >::Psi(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::ImagingPrimalDual< SCALAR >::residual_convergence(), sopt::sigma(), SOPT_HIGH_LOG, and sopt::utilities::write_tiff().

+

References sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), mersenne(), sopt::algorithm::ImagingPrimalDual< SCALAR >::Phi(), sopt::algorithm::ImagingPrimalDual< SCALAR >::Psi(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::ImagingPrimalDual< SCALAR >::residual_convergence(), sopt::sigma(), SOPT_HIGH_LOG, and sopt::utilities::write_tiff().

diff --git a/examples_2primal__dual_2inpainting_8cc__incl.map b/examples_2primal__dual_2inpainting_8cc__incl.map index 8b6104942..49ec6d007 100644 --- a/examples_2primal__dual_2inpainting_8cc__incl.map +++ b/examples_2primal__dual_2inpainting_8cc__incl.map @@ -1,51 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2primal__dual_2inpainting_8cc__incl.md5 b/examples_2primal__dual_2inpainting_8cc__incl.md5 index 97c253e51..091cbdebb 100644 --- a/examples_2primal__dual_2inpainting_8cc__incl.md5 +++ b/examples_2primal__dual_2inpainting_8cc__incl.md5 @@ -1 +1 @@ -e9ade8f8df4e2743ba31069e08a954e5 \ No newline at end of file +88415a9020bb632717f285359b4003f7 \ No newline at end of file diff --git a/examples_2primal__dual_2inpainting_8cc__incl.png b/examples_2primal__dual_2inpainting_8cc__incl.png index 284f5457d..2b5ba953f 100644 Binary files a/examples_2primal__dual_2inpainting_8cc__incl.png and b/examples_2primal__dual_2inpainting_8cc__incl.png differ diff --git a/examples_2primal__dual_2inpainting_8cc_source.html b/examples_2primal__dual_2inpainting_8cc_source.html index afc37e4e0..d0251825b 100644 --- a/examples_2primal__dual_2inpainting_8cc_source.html +++ b/examples_2primal__dual_2inpainting_8cc_source.html @@ -138,77 +138,73 @@
57  std::srand(static_cast<unsigned int>(seed));
58  std::mt19937 mersenne(std::time(nullptr));
59 
-
60  // Initializes and sets logger (if compiled with logging)
-
61  // See set_level function for levels.
-
62  sopt::logging::initialize();
-
63 
-
64  SOPT_HIGH_LOG("Read input file {}", input);
-
65  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
66 
-
67  SOPT_HIGH_LOG("Initializing sensing operator");
-
68  sopt::t_uint const nmeasure = 0.33 * image.size();
-
69  auto const sampling =
-
70  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
60  SOPT_HIGH_LOG("Read input file {}", input);
+
61  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
62 
+
63  SOPT_HIGH_LOG("Initializing sensing operator");
+
64  sopt::t_uint const nmeasure = 0.33 * image.size();
+
65  auto const sampling =
+
66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
67 
+
68  SOPT_HIGH_LOG("Initializing wavelets");
+
69  // Below we define a simple wavelet set for testing
+
70  auto const wavelet = sopt::wavelets::factory("DB4", 4);
71 
-
72  SOPT_HIGH_LOG("Initializing wavelets");
-
73  // Below we define a simple wavelet set for testing
-
74  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
75 
-
76  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
-
77  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
-
78 
-
79  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
80 
-
81  SOPT_HIGH_LOG("Computing primal-dual parameters");
-
82  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
72  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
+
73  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
+
74 
+
75  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
+
76 
+
77  SOPT_HIGH_LOG("Computing primal-dual parameters");
+
78  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
79 
+
80  auto constexpr snr = 30.0;
+
81  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
82  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
83 
-
84  auto constexpr snr = 30.0;
-
85  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
86  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
87 
-
88  SOPT_HIGH_LOG("Create dirty vector");
-
89  std::normal_distribution<> gaussian_dist(0, sigma);
-
90  Vector y(y0.size());
-
91  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
92  // Write dirty image to file
-
93  if (output != "none") {
-
94  Vector const dirty = sampling.adjoint() * y;
-
95  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
96  "dirty_" + output + ".tiff");
-
97  }
-
98  sopt::t_real const gamma = (psi.adjoint() * (sampling.adjoint() * y)).real().maxCoeff() * 1e-2;
-
99 
-
100  SOPT_HIGH_LOG("Creating primal-dual Functor");
-
101  auto const pd = sopt::algorithm::ImagingPrimalDual<Scalar>(y)
-
102  .itermax(500)
-
103  .gamma(gamma)
-
104  .tau(0.5)
-
105  .l2ball_proximal_epsilon(epsilon)
-
106  .Psi(psi)
-
107  .Phi(sampling)
-
108  .relative_variation(5e-4)
-
109  .residual_convergence(epsilon)
-
110  .positivity_constraint(true);
-
111 
-
112  SOPT_HIGH_LOG("Starting primal dual");
-
113  // Alternatively, pd can be called with a tuple (x, residual) as argument
-
114  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
-
115  auto const diagnostic = pd();
-
116  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
-
117 
-
118  // diagnostic should tell us the function converged
-
119  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
120  // diagnostic from the last call to the conjugate gradient.
-
121  if (not diagnostic.good) {
-
122  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
-
123  // throw std::runtime_error("Did not converge!");
-
124  }
-
125  if (output != "none")
-
126  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
-
127  output + ".tiff");
-
128 
-
129  return 0;
-
130 }
+
84  SOPT_HIGH_LOG("Create dirty vector");
+
85  std::normal_distribution<> gaussian_dist(0, sigma);
+
86  Vector y(y0.size());
+
87  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
88  // Write dirty image to file
+
89  if (output != "none") {
+
90  Vector const dirty = sampling.adjoint() * y;
+
91  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
92  "dirty_" + output + ".tiff");
+
93  }
+
94  sopt::t_real const gamma = (psi.adjoint() * (sampling.adjoint() * y)).real().maxCoeff() * 1e-2;
+
95 
+
96  SOPT_HIGH_LOG("Creating primal-dual Functor");
+
97  auto const pd = sopt::algorithm::ImagingPrimalDual<Scalar>(y)
+
98  .itermax(500)
+
99  .gamma(gamma)
+
100  .tau(0.5)
+
101  .l2ball_proximal_epsilon(epsilon)
+
102  .Psi(psi)
+
103  .Phi(sampling)
+
104  .relative_variation(5e-4)
+
105  .residual_convergence(epsilon)
+
106  .positivity_constraint(true);
+
107 
+
108  SOPT_HIGH_LOG("Starting primal dual");
+
109  // Alternatively, pd can be called with a tuple (x, residual) as argument
+
110  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
+
111  auto const diagnostic = pd();
+
112  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
+
113 
+
114  // diagnostic should tell us the function converged
+
115  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
116  // diagnostic from the last call to the conjugate gradient.
+
117  if (not diagnostic.good) {
+
118  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
+
119  // throw std::runtime_error("Did not converge!");
+
120  }
+
121  if (output != "none")
+
122  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
+
123  output + ".tiff");
+
124 
+
125  return 0;
+
126 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -220,9 +216,8 @@
main
int main(int argc, char const **argv)
Definition: inpainting.cc:24
imaging_primal_dual.h
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::wavelets::factory
Wavelet factory(const std::string &name, t_uint nlevels)
Creates a wavelet transform object.
Definition: wavelets.cc:8
diff --git a/examples_2proximal__admm_2inpainting_8cc.html b/examples_2proximal__admm_2inpainting_8cc.html index 7d80b6a86..b2c052b34 100644 --- a/examples_2proximal__admm_2inpainting_8cc.html +++ b/examples_2proximal__admm_2inpainting_8cc.html @@ -105,53 +105,54 @@ @@ -219,85 +220,82 @@

49  std::srand(static_cast<unsigned int>(seed));
50  std::mt19937 mersenne(std::time(nullptr));
51 
-
52  // Initializes and sets logger (if compiled with logging)
-
53  // See set_level function for levels.
-
54  sopt::logging::initialize();
-
55  sopt::logging::set_level("debug");
-
56 
-
57  SOPT_HIGH_LOG("Read input file {}", input);
-
58  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
59 
-
60  SOPT_HIGH_LOG("Initializing sensing operator");
-
61  sopt::t_uint const nmeasure = 0.33 * image.size();
-
62  auto const sampling =
-
63  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
-
64 
-
65  SOPT_HIGH_LOG("Initializing wavelets");
-
66  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
67  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
68 
-
69  SOPT_HIGH_LOG("Computing proximal-ADMM parameters");
-
70  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
71  auto constexpr snr = 30.0;
-
72  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
73  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
74 
-
75  SOPT_HIGH_LOG("Create dirty vector");
-
76  std::normal_distribution<> gaussian_dist(0, sigma);
-
77  Vector y(y0.size());
-
78  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
79  // Write dirty imagte to file
-
80  if (output != "none") {
-
81  Vector const dirty = sampling.adjoint() * y;
-
82  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
83  "dirty_" + output + ".tiff");
-
84  }
-
85 
-
86  SOPT_HIGH_LOG("Creating proximal-ADMM Functor");
-
87  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
-
88  .itermax(500)
-
89  .gamma(1e-1)
-
90  .relative_variation(5e-4)
-
91  .l2ball_proximal_epsilon(epsilon)
-
92  .tight_frame(false)
-
93  .l1_proximal_tolerance(1e-2)
-
94  .l1_proximal_nu(1)
-
95  .l1_proximal_itermax(50)
-
96  .l1_proximal_positivity_constraint(true)
-
97  .l1_proximal_real_constraint(true)
-
98  .residual_convergence(epsilon * 1.001)
-
99  .lagrange_update_scale(0.9)
-
100  .nu(1e0)
-
101  .Psi(psi)
-
102  .Phi(sampling);
-
103 
-
104  SOPT_HIGH_LOG("Starting proximal-ADMM");
-
105  // Alternatively, padmm can be called with a tuple (x, residual) as argument
-
106  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
-
107  auto const diagnostic = padmm();
-
108  SOPT_HIGH_LOG("proximal-ADMM returned {}", diagnostic.good);
-
109 
-
110  // diagnostic should tell us the function converged
-
111  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
112  // diagnostic from the last call to the conjugate gradient.
-
113  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
-
114 
-
115  SOPT_HIGH_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
-
116  if (output != "none")
-
117  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
-
118  output + ".tiff");
-
119 
-
120  return 0;
-
121 }
+
52  // See set_level function for levels.
+
53  sopt::logging::set_level("debug");
+
54 
+
55  SOPT_HIGH_LOG("Read input file {}", input);
+
56  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
57 
+
58  SOPT_HIGH_LOG("Initializing sensing operator");
+
59  sopt::t_uint const nmeasure = 0.33 * image.size();
+
60  auto const sampling =
+
61  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
62 
+
63  SOPT_HIGH_LOG("Initializing wavelets");
+
64  auto const wavelet = sopt::wavelets::factory("DB4", 4);
+
65  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
+
66 
+
67  SOPT_HIGH_LOG("Computing proximal-ADMM parameters");
+
68  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
69  auto constexpr snr = 30.0;
+
70  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
71  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
72 
+
73  SOPT_HIGH_LOG("Create dirty vector");
+
74  std::normal_distribution<> gaussian_dist(0, sigma);
+
75  Vector y(y0.size());
+
76  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
77  // Write dirty imagte to file
+
78  if (output != "none") {
+
79  Vector const dirty = sampling.adjoint() * y;
+
80  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
81  "dirty_" + output + ".tiff");
+
82  }
+
83 
+
84  SOPT_HIGH_LOG("Creating proximal-ADMM Functor");
+
85  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
+
86  .itermax(500)
+
87  .gamma(1e-1)
+
88  .relative_variation(5e-4)
+
89  .l2ball_proximal_epsilon(epsilon)
+
90  .tight_frame(false)
+
91  .l1_proximal_tolerance(1e-2)
+
92  .l1_proximal_nu(1)
+
93  .l1_proximal_itermax(50)
+
94  .l1_proximal_positivity_constraint(true)
+
95  .l1_proximal_real_constraint(true)
+
96  .residual_convergence(epsilon * 1.001)
+
97  .lagrange_update_scale(0.9)
+
98  .nu(1e0)
+
99  .Psi(psi)
+
100  .Phi(sampling);
+
101 
+
102  SOPT_HIGH_LOG("Starting proximal-ADMM");
+
103  // Alternatively, padmm can be called with a tuple (x, residual) as argument
+
104  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
+
105  auto const diagnostic = padmm();
+
106  SOPT_HIGH_LOG("proximal-ADMM returned {}", diagnostic.good);
+
107 
+
108  // diagnostic should tell us the function converged
+
109  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
110  // diagnostic from the last call to the conjugate gradient.
+
111  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
+
112 
+
113  SOPT_HIGH_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
+
114  if (output != "none")
+
115  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
+
116  output + ".tiff");
+
117 
+
118  return 0;
+
119 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
sopt::algorithm::ImagingProximalADMM::residual_convergence
ImagingProximalADMM< Scalar > & residual_convergence(Real const &tolerance)
Helper function to set-up default residual convergence function.
Definition: imaging_padmm.h:236
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::wavelets::factory
Wavelet factory(const std::string &name, t_uint nlevels)
Creates a wavelet transform object.
Definition: wavelets.cc:8
@@ -312,7 +310,7 @@

Vector
sopt::Vector< Scalar > Vector
Definition: inpainting.cc:28
Matrix
sopt::Matrix< Scalar > Matrix
Definition: inpainting.cc:29
-

References sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::logging::initialize(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::ImagingProximalADMM< SCALAR >::residual_convergence(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, and sopt::utilities::write_tiff().

+

References sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::ImagingProximalADMM< SCALAR >::residual_convergence(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, and sopt::utilities::write_tiff().

diff --git a/examples_2proximal__admm_2inpainting_8cc__incl.map b/examples_2proximal__admm_2inpainting_8cc__incl.map index d6577e34a..a96b59d17 100644 --- a/examples_2proximal__admm_2inpainting_8cc__incl.map +++ b/examples_2proximal__admm_2inpainting_8cc__incl.map @@ -1,49 +1,50 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2proximal__admm_2inpainting_8cc__incl.md5 b/examples_2proximal__admm_2inpainting_8cc__incl.md5 index e172367db..24c966abb 100644 --- a/examples_2proximal__admm_2inpainting_8cc__incl.md5 +++ b/examples_2proximal__admm_2inpainting_8cc__incl.md5 @@ -1 +1 @@ -476e3369680ff4bc02d7a8262d8d5fb8 \ No newline at end of file +9f5c19ddd658c80937358cfbc0f396bf \ No newline at end of file diff --git a/examples_2proximal__admm_2inpainting_8cc__incl.png b/examples_2proximal__admm_2inpainting_8cc__incl.png index 3455c8dba..e75cd7634 100644 Binary files a/examples_2proximal__admm_2inpainting_8cc__incl.png and b/examples_2proximal__admm_2inpainting_8cc__incl.png differ diff --git a/examples_2proximal__admm_2inpainting_8cc_source.html b/examples_2proximal__admm_2inpainting_8cc_source.html index e2cd41a0d..1566190ad 100644 --- a/examples_2proximal__admm_2inpainting_8cc_source.html +++ b/examples_2proximal__admm_2inpainting_8cc_source.html @@ -130,76 +130,74 @@
49  std::srand(static_cast<unsigned int>(seed));
50  std::mt19937 mersenne(std::time(nullptr));
51 
-
52  // Initializes and sets logger (if compiled with logging)
-
53  // See set_level function for levels.
-
54  sopt::logging::initialize();
-
55  sopt::logging::set_level("debug");
-
56 
-
57  SOPT_HIGH_LOG("Read input file {}", input);
-
58  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
59 
-
60  SOPT_HIGH_LOG("Initializing sensing operator");
-
61  sopt::t_uint const nmeasure = 0.33 * image.size();
-
62  auto const sampling =
-
63  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
-
64 
-
65  SOPT_HIGH_LOG("Initializing wavelets");
-
66  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
67  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
68 
-
69  SOPT_HIGH_LOG("Computing proximal-ADMM parameters");
-
70  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
71  auto constexpr snr = 30.0;
-
72  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
73  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
74 
-
75  SOPT_HIGH_LOG("Create dirty vector");
-
76  std::normal_distribution<> gaussian_dist(0, sigma);
-
77  Vector y(y0.size());
-
78  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
79  // Write dirty imagte to file
-
80  if (output != "none") {
-
81  Vector const dirty = sampling.adjoint() * y;
-
82  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
83  "dirty_" + output + ".tiff");
-
84  }
-
85 
-
86  SOPT_HIGH_LOG("Creating proximal-ADMM Functor");
-
87  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
-
88  .itermax(500)
-
89  .gamma(1e-1)
-
90  .relative_variation(5e-4)
-
91  .l2ball_proximal_epsilon(epsilon)
-
92  .tight_frame(false)
-
93  .l1_proximal_tolerance(1e-2)
-
94  .l1_proximal_nu(1)
-
95  .l1_proximal_itermax(50)
-
96  .l1_proximal_positivity_constraint(true)
-
97  .l1_proximal_real_constraint(true)
-
98  .residual_convergence(epsilon * 1.001)
-
99  .lagrange_update_scale(0.9)
-
100  .nu(1e0)
-
101  .Psi(psi)
-
102  .Phi(sampling);
-
103 
-
104  SOPT_HIGH_LOG("Starting proximal-ADMM");
-
105  // Alternatively, padmm can be called with a tuple (x, residual) as argument
-
106  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
-
107  auto const diagnostic = padmm();
-
108  SOPT_HIGH_LOG("proximal-ADMM returned {}", diagnostic.good);
-
109 
-
110  // diagnostic should tell us the function converged
-
111  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
112  // diagnostic from the last call to the conjugate gradient.
-
113  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
-
114 
-
115  SOPT_HIGH_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
-
116  if (output != "none")
-
117  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
-
118  output + ".tiff");
-
119 
-
120  return 0;
-
121 }
+
52  // See set_level function for levels.
+
53  sopt::logging::set_level("debug");
+
54 
+
55  SOPT_HIGH_LOG("Read input file {}", input);
+
56  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
57 
+
58  SOPT_HIGH_LOG("Initializing sensing operator");
+
59  sopt::t_uint const nmeasure = 0.33 * image.size();
+
60  auto const sampling =
+
61  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
62 
+
63  SOPT_HIGH_LOG("Initializing wavelets");
+
64  auto const wavelet = sopt::wavelets::factory("DB4", 4);
+
65  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
+
66 
+
67  SOPT_HIGH_LOG("Computing proximal-ADMM parameters");
+
68  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
69  auto constexpr snr = 30.0;
+
70  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
71  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
72 
+
73  SOPT_HIGH_LOG("Create dirty vector");
+
74  std::normal_distribution<> gaussian_dist(0, sigma);
+
75  Vector y(y0.size());
+
76  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
77  // Write dirty imagte to file
+
78  if (output != "none") {
+
79  Vector const dirty = sampling.adjoint() * y;
+
80  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
81  "dirty_" + output + ".tiff");
+
82  }
+
83 
+
84  SOPT_HIGH_LOG("Creating proximal-ADMM Functor");
+
85  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
+
86  .itermax(500)
+
87  .gamma(1e-1)
+
88  .relative_variation(5e-4)
+
89  .l2ball_proximal_epsilon(epsilon)
+
90  .tight_frame(false)
+
91  .l1_proximal_tolerance(1e-2)
+
92  .l1_proximal_nu(1)
+
93  .l1_proximal_itermax(50)
+
94  .l1_proximal_positivity_constraint(true)
+
95  .l1_proximal_real_constraint(true)
+
96  .residual_convergence(epsilon * 1.001)
+
97  .lagrange_update_scale(0.9)
+
98  .nu(1e0)
+
99  .Psi(psi)
+
100  .Phi(sampling);
+
101 
+
102  SOPT_HIGH_LOG("Starting proximal-ADMM");
+
103  // Alternatively, padmm can be called with a tuple (x, residual) as argument
+
104  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
+
105  auto const diagnostic = padmm();
+
106  SOPT_HIGH_LOG("proximal-ADMM returned {}", diagnostic.good);
+
107 
+
108  // diagnostic should tell us the function converged
+
109  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
110  // diagnostic from the last call to the conjugate gradient.
+
111  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
+
112 
+
113  SOPT_HIGH_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
+
114  if (output != "none")
+
115  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
+
116  output + ".tiff");
+
117 
+
118  return 0;
+
119 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -209,10 +207,9 @@
main
int main(int argc, char const **argv)
Definition: inpainting.cc:24
imaging_padmm.h
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
-
sopt::logging::set_level
void set_level(std::string const &, std::string const &)
Sets loggin level.
Definition: logging.disabled.h:16
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
+
sopt::logging::set_level
void set_level(const std::string &level)
Method to set the logging level of the default Log object.
Definition: logging.h:154
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::wavelets::factory
Wavelet factory(const std::string &name, t_uint nlevels)
Creates a wavelet transform object.
Definition: wavelets.cc:8
diff --git a/examples_2proximal__admm_2reweighted_8cc.html b/examples_2proximal__admm_2reweighted_8cc.html index daf63ca70..515461195 100644 --- a/examples_2proximal__admm_2reweighted_8cc.html +++ b/examples_2proximal__admm_2reweighted_8cc.html @@ -108,55 +108,56 @@ @@ -224,80 +225,76 @@

52  std::srand(static_cast<unsigned int>(seed));
53  std::mt19937 mersenne(std::time(nullptr));
54 
-
55  // Initializes and sets logger (if compiled with logging)
-
56  // See set_level function for levels.
-
57  sopt::logging::initialize();
-
58 
-
59  SOPT_MEDIUM_LOG("Read input file {}", input);
-
60  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
61 
-
62  SOPT_MEDIUM_LOG("Initializing sensing operator");
-
63  sopt::t_uint const nmeasure = 0.33 * image.size();
-
64  auto const sampling =
-
65  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
-
66 
-
67  SOPT_MEDIUM_LOG("Initializing wavelets");
-
68  sopt::wavelets::SARA const sara{std::make_tuple(std::string{"DB3"}, 1u),
-
69  std::make_tuple(std::string{"DB1"}, 2u),
-
70  std::make_tuple(std::string{"DB1"}, 3u)};
-
71  auto const psi = sopt::linear_transform<Scalar>(sara, image.rows(), image.cols());
-
72 
-
73  SOPT_MEDIUM_LOG("Computing proximal-ADMM parameters");
-
74  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
75  auto constexpr snr = 30.0;
-
76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
78 
-
79  SOPT_MEDIUM_LOG("Create dirty vector");
-
80  std::normal_distribution<> gaussian_dist(0, sigma);
-
81  Vector y(y0.size());
-
82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
83  // Write dirty imagte to file
-
84  if (output != "none") {
-
85  Vector const dirty = sampling.adjoint() * y;
-
86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
87  "dirty_" + output + ".tiff");
-
88  }
-
89 
-
90  SOPT_MEDIUM_LOG("Creating proximal-ADMM Functor");
-
91  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
-
92  .itermax(500)
-
93  .gamma(1e-1)
-
94  .relative_variation(5e-4)
-
95  .l2ball_proximal_epsilon(epsilon)
-
96  .tight_frame(false)
-
97  .l1_proximal_tolerance(1e-2)
-
98  .l1_proximal_nu(1)
-
99  .l1_proximal_itermax(50)
-
100  .l1_proximal_positivity_constraint(true)
-
101  .l1_proximal_real_constraint(true)
-
102  .residual_convergence(epsilon * 1.001)
-
103  .lagrange_update_scale(0.9)
-
104  .nu(1e0)
-
105  .Psi(psi)
-
106  .Phi(sampling);
-
107 
-
108  SOPT_MEDIUM_LOG("Creating the reweighted algorithm");
-
109  // positive_quadrant projects the result of PADMM on the positive quadrant.
-
110  // This follows the reweighted algorithm for SDMM
-
111  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
-
112  auto const reweighted =
-
113  sopt::algorithm::reweighted(padmm).itermax(5).min_delta(min_delta).is_converged(
-
114  sopt::RelativeVariation<Scalar>(1e-3));
-
115 
-
116  SOPT_MEDIUM_LOG("Starting proximal-ADMM");
-
117  // Alternatively, padmm can be called with a tuple (x, residual) as argument
-
118  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
-
119  auto const diagnostic = reweighted();
-
120  SOPT_MEDIUM_LOG("proximal-ADMM returned {}", diagnostic.good);
-
121 
-
122  SOPT_MEDIUM_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
-
123  if (output != "none")
-
124  sopt::utilities::write_tiff(Matrix::Map(diagnostic.algo.x.data(), image.rows(), image.cols()),
-
125  output + ".tiff");
-
126 
-
127  return 0;
-
128 }
+
55  SOPT_MEDIUM_LOG("Read input file {}", input);
+
56  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
57 
+
58  SOPT_MEDIUM_LOG("Initializing sensing operator");
+
59  sopt::t_uint const nmeasure = 0.33 * image.size();
+
60  auto const sampling =
+
61  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
62 
+
63  SOPT_MEDIUM_LOG("Initializing wavelets");
+
64  sopt::wavelets::SARA const sara{std::make_tuple(std::string{"DB3"}, 1u),
+
65  std::make_tuple(std::string{"DB1"}, 2u),
+
66  std::make_tuple(std::string{"DB1"}, 3u)};
+
67  auto const psi = sopt::linear_transform<Scalar>(sara, image.rows(), image.cols());
+
68 
+
69  SOPT_MEDIUM_LOG("Computing proximal-ADMM parameters");
+
70  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
71  auto constexpr snr = 30.0;
+
72  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
73  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
74 
+
75  SOPT_MEDIUM_LOG("Create dirty vector");
+
76  std::normal_distribution<> gaussian_dist(0, sigma);
+
77  Vector y(y0.size());
+
78  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
79  // Write dirty imagte to file
+
80  if (output != "none") {
+
81  Vector const dirty = sampling.adjoint() * y;
+
82  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
83  "dirty_" + output + ".tiff");
+
84  }
+
85 
+
86  SOPT_MEDIUM_LOG("Creating proximal-ADMM Functor");
+
87  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
+
88  .itermax(500)
+
89  .gamma(1e-1)
+
90  .relative_variation(5e-4)
+
91  .l2ball_proximal_epsilon(epsilon)
+
92  .tight_frame(false)
+
93  .l1_proximal_tolerance(1e-2)
+
94  .l1_proximal_nu(1)
+
95  .l1_proximal_itermax(50)
+
96  .l1_proximal_positivity_constraint(true)
+
97  .l1_proximal_real_constraint(true)
+
98  .residual_convergence(epsilon * 1.001)
+
99  .lagrange_update_scale(0.9)
+
100  .nu(1e0)
+
101  .Psi(psi)
+
102  .Phi(sampling);
+
103 
+
104  SOPT_MEDIUM_LOG("Creating the reweighted algorithm");
+
105  // positive_quadrant projects the result of PADMM on the positive quadrant.
+
106  // This follows the reweighted algorithm for SDMM
+
107  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
+
108  auto const reweighted =
+
109  sopt::algorithm::reweighted(padmm).itermax(5).min_delta(min_delta).is_converged(
+
110  sopt::RelativeVariation<Scalar>(1e-3));
+
111 
+
112  SOPT_MEDIUM_LOG("Starting proximal-ADMM");
+
113  // Alternatively, padmm can be called with a tuple (x, residual) as argument
+
114  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
+
115  auto const diagnostic = reweighted();
+
116  SOPT_MEDIUM_LOG("proximal-ADMM returned {}", diagnostic.good);
+
117 
+
118  SOPT_MEDIUM_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
+
119  if (output != "none")
+
120  sopt::utilities::write_tiff(Matrix::Map(diagnostic.algo.x.data(), image.rows(), image.cols()),
+
121  output + ".tiff");
+
122 
+
123  return 0;
+
124 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -306,9 +303,8 @@

sopt::wavelets::SARA
Sparsity Averaging Reweighted Analysis.
Definition: sara.h:20
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::algorithm::reweighted
Reweighted< ALGORITHM > reweighted(ALGORITHM const &algo, typename Reweighted< ALGORITHM >::t_SetWeights const &set_weights, typename Reweighted< ALGORITHM >::t_Reweightee const &reweightee)
Factory function to create an l0-approximation by reweighting an l1 norm.
Definition: reweighted.h:238
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::t_int
int t_int
Root of the type hierarchy for signed integers.
Definition: types.h:13
@@ -322,7 +318,7 @@

Vector
sopt::Vector< Scalar > Vector
Definition: inpainting.cc:28
Matrix
sopt::Matrix< Scalar > Matrix
Definition: inpainting.cc:29
-

References sopt::dirty(), sopt::epsilon(), sopt::logging::initialize(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::ImagingProximalADMM< SCALAR >::residual_convergence(), sopt::algorithm::reweighted(), sopt::sigma(), SOPT_MEDIUM_LOG, and sopt::utilities::write_tiff().

+

References sopt::dirty(), sopt::epsilon(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::ImagingProximalADMM< SCALAR >::residual_convergence(), sopt::algorithm::reweighted(), sopt::sigma(), SOPT_MEDIUM_LOG, and sopt::utilities::write_tiff().

diff --git a/examples_2proximal__admm_2reweighted_8cc__incl.map b/examples_2proximal__admm_2reweighted_8cc__incl.map index 7d981ff40..7d8d214ca 100644 --- a/examples_2proximal__admm_2reweighted_8cc__incl.map +++ b/examples_2proximal__admm_2reweighted_8cc__incl.map @@ -1,51 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2proximal__admm_2reweighted_8cc__incl.md5 b/examples_2proximal__admm_2reweighted_8cc__incl.md5 index 54a21376d..9a1224064 100644 --- a/examples_2proximal__admm_2reweighted_8cc__incl.md5 +++ b/examples_2proximal__admm_2reweighted_8cc__incl.md5 @@ -1 +1 @@ -b916e81040b0eb10b7b61b0d2eae1f2d \ No newline at end of file +a0122d4d0c7335685ef4ad732ca4cf49 \ No newline at end of file diff --git a/examples_2proximal__admm_2reweighted_8cc__incl.png b/examples_2proximal__admm_2reweighted_8cc__incl.png index 71ab3c564..6626836bb 100644 Binary files a/examples_2proximal__admm_2reweighted_8cc__incl.png and b/examples_2proximal__admm_2reweighted_8cc__incl.png differ diff --git a/examples_2proximal__admm_2reweighted_8cc_source.html b/examples_2proximal__admm_2reweighted_8cc_source.html index dcc02e765..a53befb6d 100644 --- a/examples_2proximal__admm_2reweighted_8cc_source.html +++ b/examples_2proximal__admm_2reweighted_8cc_source.html @@ -133,80 +133,76 @@
52  std::srand(static_cast<unsigned int>(seed));
53  std::mt19937 mersenne(std::time(nullptr));
54 
-
55  // Initializes and sets logger (if compiled with logging)
-
56  // See set_level function for levels.
-
57  sopt::logging::initialize();
-
58 
-
59  SOPT_MEDIUM_LOG("Read input file {}", input);
-
60  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
61 
-
62  SOPT_MEDIUM_LOG("Initializing sensing operator");
-
63  sopt::t_uint const nmeasure = 0.33 * image.size();
-
64  auto const sampling =
-
65  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
-
66 
-
67  SOPT_MEDIUM_LOG("Initializing wavelets");
-
68  sopt::wavelets::SARA const sara{std::make_tuple(std::string{"DB3"}, 1u),
-
69  std::make_tuple(std::string{"DB1"}, 2u),
-
70  std::make_tuple(std::string{"DB1"}, 3u)};
-
71  auto const psi = sopt::linear_transform<Scalar>(sara, image.rows(), image.cols());
-
72 
-
73  SOPT_MEDIUM_LOG("Computing proximal-ADMM parameters");
-
74  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
75  auto constexpr snr = 30.0;
-
76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
78 
-
79  SOPT_MEDIUM_LOG("Create dirty vector");
-
80  std::normal_distribution<> gaussian_dist(0, sigma);
-
81  Vector y(y0.size());
-
82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
83  // Write dirty imagte to file
-
84  if (output != "none") {
-
85  Vector const dirty = sampling.adjoint() * y;
-
86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
87  "dirty_" + output + ".tiff");
-
88  }
-
89 
-
90  SOPT_MEDIUM_LOG("Creating proximal-ADMM Functor");
-
91  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
-
92  .itermax(500)
-
93  .gamma(1e-1)
-
94  .relative_variation(5e-4)
-
95  .l2ball_proximal_epsilon(epsilon)
-
96  .tight_frame(false)
-
97  .l1_proximal_tolerance(1e-2)
-
98  .l1_proximal_nu(1)
-
99  .l1_proximal_itermax(50)
-
100  .l1_proximal_positivity_constraint(true)
-
101  .l1_proximal_real_constraint(true)
-
102  .residual_convergence(epsilon * 1.001)
-
103  .lagrange_update_scale(0.9)
-
104  .nu(1e0)
-
105  .Psi(psi)
-
106  .Phi(sampling);
-
107 
-
108  SOPT_MEDIUM_LOG("Creating the reweighted algorithm");
-
109  // positive_quadrant projects the result of PADMM on the positive quadrant.
-
110  // This follows the reweighted algorithm for SDMM
-
111  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
-
112  auto const reweighted =
-
113  sopt::algorithm::reweighted(padmm).itermax(5).min_delta(min_delta).is_converged(
-
114  sopt::RelativeVariation<Scalar>(1e-3));
-
115 
-
116  SOPT_MEDIUM_LOG("Starting proximal-ADMM");
-
117  // Alternatively, padmm can be called with a tuple (x, residual) as argument
-
118  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
-
119  auto const diagnostic = reweighted();
-
120  SOPT_MEDIUM_LOG("proximal-ADMM returned {}", diagnostic.good);
-
121 
-
122  SOPT_MEDIUM_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
-
123  if (output != "none")
-
124  sopt::utilities::write_tiff(Matrix::Map(diagnostic.algo.x.data(), image.rows(), image.cols()),
-
125  output + ".tiff");
-
126 
-
127  return 0;
-
128 }
+
55  SOPT_MEDIUM_LOG("Read input file {}", input);
+
56  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
57 
+
58  SOPT_MEDIUM_LOG("Initializing sensing operator");
+
59  sopt::t_uint const nmeasure = 0.33 * image.size();
+
60  auto const sampling =
+
61  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
62 
+
63  SOPT_MEDIUM_LOG("Initializing wavelets");
+
64  sopt::wavelets::SARA const sara{std::make_tuple(std::string{"DB3"}, 1u),
+
65  std::make_tuple(std::string{"DB1"}, 2u),
+
66  std::make_tuple(std::string{"DB1"}, 3u)};
+
67  auto const psi = sopt::linear_transform<Scalar>(sara, image.rows(), image.cols());
+
68 
+
69  SOPT_MEDIUM_LOG("Computing proximal-ADMM parameters");
+
70  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
71  auto constexpr snr = 30.0;
+
72  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
73  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
74 
+
75  SOPT_MEDIUM_LOG("Create dirty vector");
+
76  std::normal_distribution<> gaussian_dist(0, sigma);
+
77  Vector y(y0.size());
+
78  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
79  // Write dirty imagte to file
+
80  if (output != "none") {
+
81  Vector const dirty = sampling.adjoint() * y;
+
82  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
83  "dirty_" + output + ".tiff");
+
84  }
+
85 
+
86  SOPT_MEDIUM_LOG("Creating proximal-ADMM Functor");
+
87  auto const padmm = sopt::algorithm::ImagingProximalADMM<Scalar>(y)
+
88  .itermax(500)
+
89  .gamma(1e-1)
+
90  .relative_variation(5e-4)
+
91  .l2ball_proximal_epsilon(epsilon)
+
92  .tight_frame(false)
+
93  .l1_proximal_tolerance(1e-2)
+
94  .l1_proximal_nu(1)
+
95  .l1_proximal_itermax(50)
+
96  .l1_proximal_positivity_constraint(true)
+
97  .l1_proximal_real_constraint(true)
+
98  .residual_convergence(epsilon * 1.001)
+
99  .lagrange_update_scale(0.9)
+
100  .nu(1e0)
+
101  .Psi(psi)
+
102  .Phi(sampling);
+
103 
+
104  SOPT_MEDIUM_LOG("Creating the reweighted algorithm");
+
105  // positive_quadrant projects the result of PADMM on the positive quadrant.
+
106  // This follows the reweighted algorithm for SDMM
+
107  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
+
108  auto const reweighted =
+
109  sopt::algorithm::reweighted(padmm).itermax(5).min_delta(min_delta).is_converged(
+
110  sopt::RelativeVariation<Scalar>(1e-3));
+
111 
+
112  SOPT_MEDIUM_LOG("Starting proximal-ADMM");
+
113  // Alternatively, padmm can be called with a tuple (x, residual) as argument
+
114  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
+
115  auto const diagnostic = reweighted();
+
116  SOPT_MEDIUM_LOG("proximal-ADMM returned {}", diagnostic.good);
+
117 
+
118  SOPT_MEDIUM_LOG("SOPT-proximal-ADMM converged in {} iterations", diagnostic.niters);
+
119  if (output != "none")
+
120  sopt::utilities::write_tiff(Matrix::Map(diagnostic.algo.x.data(), image.rows(), image.cols()),
+
121  output + ".tiff");
+
122 
+
123  return 0;
+
124 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -218,10 +214,9 @@
main
int main(int argc, char const **argv)
Definition: reweighted.cc:26
imaging_padmm.h
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::algorithm::reweighted
Reweighted< ALGORITHM > reweighted(ALGORITHM const &algo, typename Reweighted< ALGORITHM >::t_SetWeights const &set_weights, typename Reweighted< ALGORITHM >::t_Reweightee const &reweightee)
Factory function to create an l0-approximation by reweighting an l1 norm.
Definition: reweighted.h:238
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
sopt::t_int
int t_int
Root of the type hierarchy for signed integers.
Definition: types.h:13
diff --git a/examples_2sara_8cc.html b/examples_2sara_8cc.html index db4f6a6c2..1dcf3bb39 100644 --- a/examples_2sara_8cc.html +++ b/examples_2sara_8cc.html @@ -89,29 +89,33 @@ diff --git a/examples_2sara_8cc__incl.map b/examples_2sara_8cc__incl.map index 75949b84c..c1ab234a5 100644 --- a/examples_2sara_8cc__incl.map +++ b/examples_2sara_8cc__incl.map @@ -1,25 +1,29 @@ - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2sara_8cc__incl.md5 b/examples_2sara_8cc__incl.md5 index 28388c99d..6aade317c 100644 --- a/examples_2sara_8cc__incl.md5 +++ b/examples_2sara_8cc__incl.md5 @@ -1 +1 @@ -810a5c838a765708e1790e01122ec425 \ No newline at end of file +f17e9756690b5c7263cca4d5e5cd7b86 \ No newline at end of file diff --git a/examples_2sara_8cc__incl.png b/examples_2sara_8cc__incl.png index c5635284f..6c9faf7d1 100644 Binary files a/examples_2sara_8cc__incl.png and b/examples_2sara_8cc__incl.png differ diff --git a/examples_2sdmm_2inpainting_8cc.html b/examples_2sdmm_2inpainting_8cc.html index 613ca6eac..fd57f5d87 100644 --- a/examples_2sdmm_2inpainting_8cc.html +++ b/examples_2sdmm_2inpainting_8cc.html @@ -105,52 +105,53 @@ @@ -218,81 +219,77 @@

49  std::srand(static_cast<unsigned int>(seed));
50  std::mt19937 mersenne(std::time(nullptr));
51 
-
52  // Initializes and sets logger (if compiled with logging)
-
53  // See set_level function for levels.
-
54  sopt::logging::initialize();
-
55 
-
56  SOPT_HIGH_LOG("Read input file {}", input);
-
57  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
58 
-
59  SOPT_HIGH_LOG("Initializing sensing operator");
-
60  sopt::t_uint const nmeasure = 0.33 * image.size();
-
61  auto const sampling =
-
62  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
52  SOPT_HIGH_LOG("Read input file {}", input);
+
53  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
54 
+
55  SOPT_HIGH_LOG("Initializing sensing operator");
+
56  sopt::t_uint const nmeasure = 0.33 * image.size();
+
57  auto const sampling =
+
58  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
59 
+
60  SOPT_HIGH_LOG("Initializing wavelets");
+
61  auto const wavelet = sopt::wavelets::factory("DB4", 4);
+
62  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
63 
-
64  SOPT_HIGH_LOG("Initializing wavelets");
-
65  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
66  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
67 
-
68  SOPT_HIGH_LOG("Computing sdmm parameters");
-
69  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
70  auto constexpr snr = 30.0;
-
71  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
72  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
73 
-
74  SOPT_HIGH_LOG("Create dirty vector");
-
75  std::normal_distribution<> gaussian_dist(0, sigma);
-
76  Vector y(y0.size());
-
77  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
78  // Write dirty imagte to file
-
79  if (output != "none") {
-
80  Vector const dirty = sampling.adjoint() * y;
-
81  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
82  "dirty_" + output + ".tiff");
-
83  }
-
84 
-
85  SOPT_HIGH_LOG("Initializing convergence function");
-
86  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
-
87  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
-
88  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
-
89  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
-
90  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
-
91  return relvar(x);
-
92  };
-
93 
-
94  SOPT_HIGH_LOG("Creating SDMM Functor");
-
95  auto const sdmm =
-
96  sopt::algorithm::SDMM<Scalar>()
-
97  .itermax(3000)
-
98  .gamma(0.1)
-
99  .conjugate_gradient(200, 1e-8)
-
100  .is_converged(convergence)
-
101  // Any number of (proximal g_i, L_i) pairs can be added
-
102  // ||Psi^dagger x||_1
-
103  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
-
104  // ||y - A x|| < epsilon
-
105  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
-
106  // x in positive quadrant
-
107  .append(sopt::proximal::positive_quadrant<Scalar>);
-
108 
-
109  SOPT_HIGH_LOG("Allocating result vector");
-
110  Vector result(image.size());
-
111  SOPT_HIGH_LOG("Starting SDMM");
-
112  auto const diagnostic = sdmm(result, Vector::Zero(image.size()));
-
113  SOPT_HIGH_LOG("SDMM returned {}", diagnostic.good);
-
114 
-
115  // diagnostic should tell us the function converged
-
116  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
117  // diagnostic from the last call to the conjugate gradient.
-
118  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
-
119 
-
120  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", diagnostic.niters);
-
121  if (output != "none")
-
122  sopt::utilities::write_tiff(Matrix::Map(result.data(), image.rows(), image.cols()),
-
123  output + ".tiff");
-
124 
-
125  return 0;
-
126 }
+
64  SOPT_HIGH_LOG("Computing sdmm parameters");
+
65  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
66  auto constexpr snr = 30.0;
+
67  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
68  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
69 
+
70  SOPT_HIGH_LOG("Create dirty vector");
+
71  std::normal_distribution<> gaussian_dist(0, sigma);
+
72  Vector y(y0.size());
+
73  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
74  // Write dirty imagte to file
+
75  if (output != "none") {
+
76  Vector const dirty = sampling.adjoint() * y;
+
77  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
78  "dirty_" + output + ".tiff");
+
79  }
+
80 
+
81  SOPT_HIGH_LOG("Initializing convergence function");
+
82  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
+
83  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
+
84  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
+
85  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
+
86  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
+
87  return relvar(x);
+
88  };
+
89 
+
90  SOPT_HIGH_LOG("Creating SDMM Functor");
+
91  auto const sdmm =
+
92  sopt::algorithm::SDMM<Scalar>()
+
93  .itermax(3000)
+
94  .gamma(0.1)
+
95  .conjugate_gradient(200, 1e-8)
+
96  .is_converged(convergence)
+
97  // Any number of (proximal g_i, L_i) pairs can be added
+
98  // ||Psi^dagger x||_1
+
99  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
+
100  // ||y - A x|| < epsilon
+
101  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
+
102  // x in positive quadrant
+
103  .append(sopt::proximal::positive_quadrant<Scalar>);
+
104 
+
105  SOPT_HIGH_LOG("Allocating result vector");
+
106  Vector result(image.size());
+
107  SOPT_HIGH_LOG("Starting SDMM");
+
108  auto const diagnostic = sdmm(result, Vector::Zero(image.size()));
+
109  SOPT_HIGH_LOG("SDMM returned {}", diagnostic.good);
+
110 
+
111  // diagnostic should tell us the function converged
+
112  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
113  // diagnostic from the last call to the conjugate gradient.
+
114  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
+
115 
+
116  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", diagnostic.niters);
+
117  if (output != "none")
+
118  sopt::utilities::write_tiff(Matrix::Map(result.data(), image.rows(), image.cols()),
+
119  output + ".tiff");
+
120 
+
121  return 0;
+
122 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -302,9 +299,8 @@

sopt::proximal::L2Ball
Proximal for indicator function of L2 ball.
Definition: proximal.h:182
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::proximal::translate
Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
Translates given proximal by given vector.
Definition: proximal.h:362
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
@@ -321,7 +317,7 @@

Vector
sopt::Vector< Scalar > Vector
Definition: inpainting.cc:28
Matrix
sopt::Matrix< Scalar > Matrix
Definition: inpainting.cc:29
-

References sopt::algorithm::SDMM< SCALAR >::conjugate_gradient(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::logging::initialize(), sopt::algorithm::SDMM< SCALAR >::is_converged(), sopt::l1_norm(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_MEDIUM_LOG, sopt::proximal::translate(), and sopt::utilities::write_tiff().

+

References sopt::algorithm::SDMM< SCALAR >::conjugate_gradient(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::algorithm::SDMM< SCALAR >::is_converged(), sopt::l1_norm(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_MEDIUM_LOG, sopt::proximal::translate(), and sopt::utilities::write_tiff().

diff --git a/examples_2sdmm_2inpainting_8cc__incl.map b/examples_2sdmm_2inpainting_8cc__incl.map index 3de9cd5ba..134a8a023 100644 --- a/examples_2sdmm_2inpainting_8cc__incl.map +++ b/examples_2sdmm_2inpainting_8cc__incl.map @@ -1,48 +1,49 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2sdmm_2inpainting_8cc__incl.md5 b/examples_2sdmm_2inpainting_8cc__incl.md5 index b696aa94f..8f820c496 100644 --- a/examples_2sdmm_2inpainting_8cc__incl.md5 +++ b/examples_2sdmm_2inpainting_8cc__incl.md5 @@ -1 +1 @@ -cb70ec12d2785550bc5bd258b21b5521 \ No newline at end of file +ad6a490e10d5061b3d63ca4f06e3a0a0 \ No newline at end of file diff --git a/examples_2sdmm_2inpainting_8cc__incl.png b/examples_2sdmm_2inpainting_8cc__incl.png index 97d8f2981..3ad9cfe5d 100644 Binary files a/examples_2sdmm_2inpainting_8cc__incl.png and b/examples_2sdmm_2inpainting_8cc__incl.png differ diff --git a/examples_2sdmm_2inpainting_8cc_source.html b/examples_2sdmm_2inpainting_8cc_source.html index 887a8ef7f..8f576c77c 100644 --- a/examples_2sdmm_2inpainting_8cc_source.html +++ b/examples_2sdmm_2inpainting_8cc_source.html @@ -130,81 +130,77 @@
49  std::srand(static_cast<unsigned int>(seed));
50  std::mt19937 mersenne(std::time(nullptr));
51 
-
52  // Initializes and sets logger (if compiled with logging)
-
53  // See set_level function for levels.
-
54  sopt::logging::initialize();
-
55 
-
56  SOPT_HIGH_LOG("Read input file {}", input);
-
57  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
58 
-
59  SOPT_HIGH_LOG("Initializing sensing operator");
-
60  sopt::t_uint const nmeasure = 0.33 * image.size();
-
61  auto const sampling =
-
62  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
52  SOPT_HIGH_LOG("Read input file {}", input);
+
53  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
54 
+
55  SOPT_HIGH_LOG("Initializing sensing operator");
+
56  sopt::t_uint const nmeasure = 0.33 * image.size();
+
57  auto const sampling =
+
58  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
59 
+
60  SOPT_HIGH_LOG("Initializing wavelets");
+
61  auto const wavelet = sopt::wavelets::factory("DB4", 4);
+
62  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
63 
-
64  SOPT_HIGH_LOG("Initializing wavelets");
-
65  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
66  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
67 
-
68  SOPT_HIGH_LOG("Computing sdmm parameters");
-
69  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
70  auto constexpr snr = 30.0;
-
71  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
72  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
73 
-
74  SOPT_HIGH_LOG("Create dirty vector");
-
75  std::normal_distribution<> gaussian_dist(0, sigma);
-
76  Vector y(y0.size());
-
77  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
78  // Write dirty imagte to file
-
79  if (output != "none") {
-
80  Vector const dirty = sampling.adjoint() * y;
-
81  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
82  "dirty_" + output + ".tiff");
-
83  }
-
84 
-
85  SOPT_HIGH_LOG("Initializing convergence function");
-
86  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
-
87  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
-
88  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
-
89  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
-
90  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
-
91  return relvar(x);
-
92  };
-
93 
-
94  SOPT_HIGH_LOG("Creating SDMM Functor");
-
95  auto const sdmm =
-
96  sopt::algorithm::SDMM<Scalar>()
-
97  .itermax(3000)
-
98  .gamma(0.1)
-
99  .conjugate_gradient(200, 1e-8)
-
100  .is_converged(convergence)
-
101  // Any number of (proximal g_i, L_i) pairs can be added
-
102  // ||Psi^dagger x||_1
-
103  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
-
104  // ||y - A x|| < epsilon
-
105  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
-
106  // x in positive quadrant
-
107  .append(sopt::proximal::positive_quadrant<Scalar>);
-
108 
-
109  SOPT_HIGH_LOG("Allocating result vector");
-
110  Vector result(image.size());
-
111  SOPT_HIGH_LOG("Starting SDMM");
-
112  auto const diagnostic = sdmm(result, Vector::Zero(image.size()));
-
113  SOPT_HIGH_LOG("SDMM returned {}", diagnostic.good);
-
114 
-
115  // diagnostic should tell us the function converged
-
116  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
-
117  // diagnostic from the last call to the conjugate gradient.
-
118  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
-
119 
-
120  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", diagnostic.niters);
-
121  if (output != "none")
-
122  sopt::utilities::write_tiff(Matrix::Map(result.data(), image.rows(), image.cols()),
-
123  output + ".tiff");
-
124 
-
125  return 0;
-
126 }
+
64  SOPT_HIGH_LOG("Computing sdmm parameters");
+
65  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
66  auto constexpr snr = 30.0;
+
67  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
68  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
69 
+
70  SOPT_HIGH_LOG("Create dirty vector");
+
71  std::normal_distribution<> gaussian_dist(0, sigma);
+
72  Vector y(y0.size());
+
73  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
74  // Write dirty imagte to file
+
75  if (output != "none") {
+
76  Vector const dirty = sampling.adjoint() * y;
+
77  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
78  "dirty_" + output + ".tiff");
+
79  }
+
80 
+
81  SOPT_HIGH_LOG("Initializing convergence function");
+
82  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
+
83  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
+
84  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
+
85  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
+
86  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
+
87  return relvar(x);
+
88  };
+
89 
+
90  SOPT_HIGH_LOG("Creating SDMM Functor");
+
91  auto const sdmm =
+
92  sopt::algorithm::SDMM<Scalar>()
+
93  .itermax(3000)
+
94  .gamma(0.1)
+
95  .conjugate_gradient(200, 1e-8)
+
96  .is_converged(convergence)
+
97  // Any number of (proximal g_i, L_i) pairs can be added
+
98  // ||Psi^dagger x||_1
+
99  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
+
100  // ||y - A x|| < epsilon
+
101  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
+
102  // x in positive quadrant
+
103  .append(sopt::proximal::positive_quadrant<Scalar>);
+
104 
+
105  SOPT_HIGH_LOG("Allocating result vector");
+
106  Vector result(image.size());
+
107  SOPT_HIGH_LOG("Starting SDMM");
+
108  auto const diagnostic = sdmm(result, Vector::Zero(image.size()));
+
109  SOPT_HIGH_LOG("SDMM returned {}", diagnostic.good);
+
110 
+
111  // diagnostic should tell us the function converged
+
112  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
+
113  // diagnostic from the last call to the conjugate gradient.
+
114  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
+
115 
+
116  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", diagnostic.niters);
+
117  if (output != "none")
+
118  sopt::utilities::write_tiff(Matrix::Map(result.data(), image.rows(), image.cols()),
+
119  output + ".tiff");
+
120 
+
121  return 0;
+
122 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -216,10 +212,9 @@
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
main
int main(int argc, char const **argv)
Definition: inpainting.cc:24
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::proximal::translate
Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
Translates given proximal by given vector.
Definition: proximal.h:362
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
diff --git a/examples_2sdmm_2reweighted_8cc.html b/examples_2sdmm_2reweighted_8cc.html index f4b8571d9..a421f30ba 100644 --- a/examples_2sdmm_2reweighted_8cc.html +++ b/examples_2sdmm_2reweighted_8cc.html @@ -107,54 +107,55 @@ @@ -222,104 +223,100 @@

53  std::srand(static_cast<unsigned int>(seed));
54  std::mt19937 mersenne(std::time(nullptr));
55 
-
56  // Initializes and sets logger (if compiled with logging)
-
57  // See set_level function for levels.
-
58  sopt::logging::initialize();
-
59 
-
60  SOPT_HIGH_LOG("Read input file {}", input);
-
61  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
62 
-
63  SOPT_HIGH_LOG("Initializing sensing operator");
-
64  sopt::t_uint const nmeasure = 0.33 * image.size();
-
65  auto const sampling =
-
66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
56  SOPT_HIGH_LOG("Read input file {}", input);
+
57  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
58 
+
59  SOPT_HIGH_LOG("Initializing sensing operator");
+
60  sopt::t_uint const nmeasure = 0.33 * image.size();
+
61  auto const sampling =
+
62  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
63 
+
64  SOPT_HIGH_LOG("Initializing wavelets");
+
65  auto const wavelet = sopt::wavelets::factory("DB4", 4);
+
66  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
67 
-
68  SOPT_HIGH_LOG("Initializing wavelets");
-
69  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
70  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
71 
-
72  SOPT_HIGH_LOG("Computing sdmm parameters");
-
73  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
74  auto constexpr snr = 30.0;
-
75  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
76  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
77 
-
78  SOPT_HIGH_LOG("Create dirty vector");
-
79  std::normal_distribution<> gaussian_dist(0, sigma);
-
80  Vector y(y0.size());
-
81  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
82  // Write dirty imagte to file
-
83  if (output != "none") {
-
84  Vector const dirty = sampling.adjoint() * y;
-
85  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
86  "dirty_" + output + ".tiff");
-
87  }
-
88 
-
89  SOPT_HIGH_LOG("Initializing convergence function");
-
90  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
-
91  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
-
92  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
-
93  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
-
94  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
-
95  return relvar(x);
-
96  };
-
97 
-
98  SOPT_HIGH_LOG("Creating SDMM Functor");
-
99  auto const sdmm =
-
100  sopt::algorithm::SDMM<Scalar>()
-
101  .itermax(3000)
-
102  .gamma(0.1)
-
103  .conjugate_gradient(200, 1e-8)
-
104  .is_converged(convergence)
-
105  // Any number of (proximal g_i, L_i) pairs can be added
-
106  // ||Psi^dagger x||_1
-
107  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
-
108  // ||y - A x|| < epsilon
-
109  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
-
110  // x in positive quadrant
-
111  .append(sopt::proximal::positive_quadrant<Scalar>);
-
112 
-
113  SOPT_HIGH_LOG("Creating the reweighted algorithm");
-
114  // positive_quadrant projects the result of SDMM on the positive quadrant.
-
115  // This follows the reweighted algorithm in the original C implementation.
-
116  auto const posq = positive_quadrant(sdmm);
-
117  using t_PosQuadSDMM = std::remove_const<decltype(posq)>::type;
-
118  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
-
119  // Sets weight after each sdmm iteration.
-
120  // In practice, this means replacing the proximal of the l1 objective function.
-
121  auto set_weights = [](t_PosQuadSDMM &sdmm, Vector const &weights) {
-
122  sdmm.algorithm().proximals(0) = [weights](Vector &out, Scalar gamma, Vector const &x) {
-
123  out = sopt::soft_threshhold(x, gamma * weights);
-
124  };
-
125  };
-
126  auto call_PsiT = [&psi](t_PosQuadSDMM const &, Vector const &x) -> Vector {
-
127  return psi.adjoint() * x;
-
128  };
-
129  auto const reweighted = sopt::algorithm::reweighted(posq, set_weights, call_PsiT)
-
130  .itermax(5)
-
131  .min_delta(min_delta)
-
132  .is_converged(sopt::RelativeVariation<Scalar>(1e-3));
-
133 
-
134  SOPT_HIGH_LOG("Computing warm-start SDMM");
-
135  auto warm_start = sdmm(Vector::Zero(image.size()));
-
136  warm_start.x = sopt::positive_quadrant(warm_start.x);
-
137  SOPT_HIGH_LOG("SDMM returned {}", warm_start.good);
-
138 
-
139  SOPT_HIGH_LOG("Computing warm-start SDMM");
-
140  auto const result = reweighted(warm_start);
-
141 
-
142  // result should tell us the function converged
-
143  // it also contains result.niters - the number of iterations, and cg_diagnostic - the
-
144  // result from the last call to the conjugate gradient.
-
145  if (not result.good) throw std::runtime_error("Did not converge!");
-
146 
-
147  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", result.niters);
-
148  if (output != "none")
-
149  sopt::utilities::write_tiff(Matrix::Map(result.algo.x.data(), image.rows(), image.cols()),
-
150  output + ".tiff");
-
151 
-
152  return 0;
-
153 }
+
68  SOPT_HIGH_LOG("Computing sdmm parameters");
+
69  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
70  auto constexpr snr = 30.0;
+
71  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
72  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
73 
+
74  SOPT_HIGH_LOG("Create dirty vector");
+
75  std::normal_distribution<> gaussian_dist(0, sigma);
+
76  Vector y(y0.size());
+
77  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
78  // Write dirty imagte to file
+
79  if (output != "none") {
+
80  Vector const dirty = sampling.adjoint() * y;
+
81  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
82  "dirty_" + output + ".tiff");
+
83  }
+
84 
+
85  SOPT_HIGH_LOG("Initializing convergence function");
+
86  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
+
87  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
+
88  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
+
89  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
+
90  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
+
91  return relvar(x);
+
92  };
+
93 
+
94  SOPT_HIGH_LOG("Creating SDMM Functor");
+
95  auto const sdmm =
+
96  sopt::algorithm::SDMM<Scalar>()
+
97  .itermax(3000)
+
98  .gamma(0.1)
+
99  .conjugate_gradient(200, 1e-8)
+
100  .is_converged(convergence)
+
101  // Any number of (proximal g_i, L_i) pairs can be added
+
102  // ||Psi^dagger x||_1
+
103  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
+
104  // ||y - A x|| < epsilon
+
105  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
+
106  // x in positive quadrant
+
107  .append(sopt::proximal::positive_quadrant<Scalar>);
+
108 
+
109  SOPT_HIGH_LOG("Creating the reweighted algorithm");
+
110  // positive_quadrant projects the result of SDMM on the positive quadrant.
+
111  // This follows the reweighted algorithm in the original C implementation.
+
112  auto const posq = positive_quadrant(sdmm);
+
113  using t_PosQuadSDMM = std::remove_const<decltype(posq)>::type;
+
114  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
+
115  // Sets weight after each sdmm iteration.
+
116  // In practice, this means replacing the proximal of the l1 objective function.
+
117  auto set_weights = [](t_PosQuadSDMM &sdmm, Vector const &weights) {
+
118  sdmm.algorithm().proximals(0) = [weights](Vector &out, Scalar gamma, Vector const &x) {
+
119  out = sopt::soft_threshhold(x, gamma * weights);
+
120  };
+
121  };
+
122  auto call_PsiT = [&psi](t_PosQuadSDMM const &, Vector const &x) -> Vector {
+
123  return psi.adjoint() * x;
+
124  };
+
125  auto const reweighted = sopt::algorithm::reweighted(posq, set_weights, call_PsiT)
+
126  .itermax(5)
+
127  .min_delta(min_delta)
+
128  .is_converged(sopt::RelativeVariation<Scalar>(1e-3));
+
129 
+
130  SOPT_HIGH_LOG("Computing warm-start SDMM");
+
131  auto warm_start = sdmm(Vector::Zero(image.size()));
+
132  warm_start.x = sopt::positive_quadrant(warm_start.x);
+
133  SOPT_HIGH_LOG("SDMM returned {}", warm_start.good);
+
134 
+
135  SOPT_HIGH_LOG("Computing warm-start SDMM");
+
136  auto const result = reweighted(warm_start);
+
137 
+
138  // result should tell us the function converged
+
139  // it also contains result.niters - the number of iterations, and cg_diagnostic - the
+
140  // result from the last call to the conjugate gradient.
+
141  if (not result.good) throw std::runtime_error("Did not converge!");
+
142 
+
143  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", result.niters);
+
144  if (output != "none")
+
145  sopt::utilities::write_tiff(Matrix::Map(result.algo.x.data(), image.rows(), image.cols()),
+
146  output + ".tiff");
+
147 
+
148  return 0;
+
149 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -329,10 +326,9 @@

sopt::proximal::L2Ball
Proximal for indicator function of L2 ball.
Definition: proximal.h:182
mersenne
std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::algorithm::reweighted
Reweighted< ALGORITHM > reweighted(ALGORITHM const &algo, typename Reweighted< ALGORITHM >::t_SetWeights const &set_weights, typename Reweighted< ALGORITHM >::t_Reweightee const &reweightee)
Factory function to create an l0-approximation by reweighting an l1 norm.
Definition: reweighted.h:238
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::proximal::translate
Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
Translates given proximal by given vector.
Definition: proximal.h:362
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
@@ -351,7 +347,7 @@

Vector
sopt::Vector< Scalar > Vector
Definition: inpainting.cc:28
Matrix
sopt::Matrix< Scalar > Matrix
Definition: inpainting.cc:29
-

References sopt::algorithm::SDMM< SCALAR >::conjugate_gradient(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::logging::initialize(), sopt::algorithm::SDMM< SCALAR >::is_converged(), sopt::l1_norm(), mersenne(), sopt::positive_quadrant(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::reweighted(), sopt::sigma(), sopt::soft_threshhold(), SOPT_HIGH_LOG, SOPT_MEDIUM_LOG, sopt::proximal::translate(), and sopt::utilities::write_tiff().

+

References sopt::algorithm::SDMM< SCALAR >::conjugate_gradient(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::algorithm::SDMM< SCALAR >::is_converged(), sopt::l1_norm(), mersenne(), sopt::positive_quadrant(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::reweighted(), sopt::sigma(), sopt::soft_threshhold(), SOPT_HIGH_LOG, SOPT_MEDIUM_LOG, sopt::proximal::translate(), and sopt::utilities::write_tiff().

diff --git a/examples_2sdmm_2reweighted_8cc__incl.map b/examples_2sdmm_2reweighted_8cc__incl.map index cc505d7c7..cfa402048 100644 --- a/examples_2sdmm_2reweighted_8cc__incl.map +++ b/examples_2sdmm_2reweighted_8cc__incl.map @@ -1,50 +1,51 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/examples_2sdmm_2reweighted_8cc__incl.md5 b/examples_2sdmm_2reweighted_8cc__incl.md5 index c0358ce4e..f9e7115bb 100644 --- a/examples_2sdmm_2reweighted_8cc__incl.md5 +++ b/examples_2sdmm_2reweighted_8cc__incl.md5 @@ -1 +1 @@ -5428e5d389a98ba3ee5e1459fb8009b4 \ No newline at end of file +3ad0506af7995aaed26044c8f8afab8b \ No newline at end of file diff --git a/examples_2sdmm_2reweighted_8cc__incl.png b/examples_2sdmm_2reweighted_8cc__incl.png index 6c33b903e..03bf49d2e 100644 Binary files a/examples_2sdmm_2reweighted_8cc__incl.png and b/examples_2sdmm_2reweighted_8cc__incl.png differ diff --git a/examples_2sdmm_2reweighted_8cc_source.html b/examples_2sdmm_2reweighted_8cc_source.html index d5fc5d88c..a6d86f551 100644 --- a/examples_2sdmm_2reweighted_8cc_source.html +++ b/examples_2sdmm_2reweighted_8cc_source.html @@ -134,104 +134,100 @@
53  std::srand(static_cast<unsigned int>(seed));
54  std::mt19937 mersenne(std::time(nullptr));
55 
-
56  // Initializes and sets logger (if compiled with logging)
-
57  // See set_level function for levels.
-
58  sopt::logging::initialize();
-
59 
-
60  SOPT_HIGH_LOG("Read input file {}", input);
-
61  Image const image = sopt::notinstalled::read_standard_tiff(input);
-
62 
-
63  SOPT_HIGH_LOG("Initializing sensing operator");
-
64  sopt::t_uint const nmeasure = 0.33 * image.size();
-
65  auto const sampling =
-
66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
56  SOPT_HIGH_LOG("Read input file {}", input);
+
57  Image const image = sopt::notinstalled::read_standard_tiff(input);
+
58 
+
59  SOPT_HIGH_LOG("Initializing sensing operator");
+
60  sopt::t_uint const nmeasure = 0.33 * image.size();
+
61  auto const sampling =
+
62  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
+
63 
+
64  SOPT_HIGH_LOG("Initializing wavelets");
+
65  auto const wavelet = sopt::wavelets::factory("DB4", 4);
+
66  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
67 
-
68  SOPT_HIGH_LOG("Initializing wavelets");
-
69  auto const wavelet = sopt::wavelets::factory("DB4", 4);
-
70  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
-
71 
-
72  SOPT_HIGH_LOG("Computing sdmm parameters");
-
73  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
-
74  auto constexpr snr = 30.0;
-
75  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
-
76  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
-
77 
-
78  SOPT_HIGH_LOG("Create dirty vector");
-
79  std::normal_distribution<> gaussian_dist(0, sigma);
-
80  Vector y(y0.size());
-
81  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
-
82  // Write dirty imagte to file
-
83  if (output != "none") {
-
84  Vector const dirty = sampling.adjoint() * y;
-
85  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
-
86  "dirty_" + output + ".tiff");
-
87  }
-
88 
-
89  SOPT_HIGH_LOG("Initializing convergence function");
-
90  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
-
91  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
-
92  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
-
93  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
-
94  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
-
95  return relvar(x);
-
96  };
-
97 
-
98  SOPT_HIGH_LOG("Creating SDMM Functor");
-
99  auto const sdmm =
-
100  sopt::algorithm::SDMM<Scalar>()
-
101  .itermax(3000)
-
102  .gamma(0.1)
-
103  .conjugate_gradient(200, 1e-8)
-
104  .is_converged(convergence)
-
105  // Any number of (proximal g_i, L_i) pairs can be added
-
106  // ||Psi^dagger x||_1
-
107  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
-
108  // ||y - A x|| < epsilon
-
109  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
-
110  // x in positive quadrant
-
111  .append(sopt::proximal::positive_quadrant<Scalar>);
-
112 
-
113  SOPT_HIGH_LOG("Creating the reweighted algorithm");
-
114  // positive_quadrant projects the result of SDMM on the positive quadrant.
-
115  // This follows the reweighted algorithm in the original C implementation.
-
116  auto const posq = positive_quadrant(sdmm);
-
117  using t_PosQuadSDMM = std::remove_const<decltype(posq)>::type;
-
118  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
-
119  // Sets weight after each sdmm iteration.
-
120  // In practice, this means replacing the proximal of the l1 objective function.
-
121  auto set_weights = [](t_PosQuadSDMM &sdmm, Vector const &weights) {
-
122  sdmm.algorithm().proximals(0) = [weights](Vector &out, Scalar gamma, Vector const &x) {
-
123  out = sopt::soft_threshhold(x, gamma * weights);
-
124  };
-
125  };
-
126  auto call_PsiT = [&psi](t_PosQuadSDMM const &, Vector const &x) -> Vector {
-
127  return psi.adjoint() * x;
-
128  };
-
129  auto const reweighted = sopt::algorithm::reweighted(posq, set_weights, call_PsiT)
-
130  .itermax(5)
-
131  .min_delta(min_delta)
-
132  .is_converged(sopt::RelativeVariation<Scalar>(1e-3));
-
133 
-
134  SOPT_HIGH_LOG("Computing warm-start SDMM");
-
135  auto warm_start = sdmm(Vector::Zero(image.size()));
-
136  warm_start.x = sopt::positive_quadrant(warm_start.x);
-
137  SOPT_HIGH_LOG("SDMM returned {}", warm_start.good);
-
138 
-
139  SOPT_HIGH_LOG("Computing warm-start SDMM");
-
140  auto const result = reweighted(warm_start);
-
141 
-
142  // result should tell us the function converged
-
143  // it also contains result.niters - the number of iterations, and cg_diagnostic - the
-
144  // result from the last call to the conjugate gradient.
-
145  if (not result.good) throw std::runtime_error("Did not converge!");
-
146 
-
147  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", result.niters);
-
148  if (output != "none")
-
149  sopt::utilities::write_tiff(Matrix::Map(result.algo.x.data(), image.rows(), image.cols()),
-
150  output + ".tiff");
-
151 
-
152  return 0;
-
153 }
+
68  SOPT_HIGH_LOG("Computing sdmm parameters");
+
69  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
+
70  auto constexpr snr = 30.0;
+
71  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
+
72  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
+
73 
+
74  SOPT_HIGH_LOG("Create dirty vector");
+
75  std::normal_distribution<> gaussian_dist(0, sigma);
+
76  Vector y(y0.size());
+
77  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
+
78  // Write dirty imagte to file
+
79  if (output != "none") {
+
80  Vector const dirty = sampling.adjoint() * y;
+
81  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
+
82  "dirty_" + output + ".tiff");
+
83  }
+
84 
+
85  SOPT_HIGH_LOG("Initializing convergence function");
+
86  auto relvar = sopt::RelativeVariation<Scalar>(5e-2);
+
87  auto convergence = [&y, &sampling, &psi, &relvar](sopt::Vector<Scalar> const &x) -> bool {
+
88  SOPT_MEDIUM_LOG("||x - y||_2: {}", (y - sampling * x).stableNorm());
+
89  SOPT_MEDIUM_LOG("||Psi^Tx||_1: {}", sopt::l1_norm(psi.adjoint() * x));
+
90  SOPT_MEDIUM_LOG("||abs(x) - x||_2: {}", (x.array().abs().matrix() - x).stableNorm());
+
91  return relvar(x);
+
92  };
+
93 
+
94  SOPT_HIGH_LOG("Creating SDMM Functor");
+
95  auto const sdmm =
+
96  sopt::algorithm::SDMM<Scalar>()
+
97  .itermax(3000)
+
98  .gamma(0.1)
+
99  .conjugate_gradient(200, 1e-8)
+
100  .is_converged(convergence)
+
101  // Any number of (proximal g_i, L_i) pairs can be added
+
102  // ||Psi^dagger x||_1
+
103  .append(sopt::proximal::l1_norm<Scalar>, psi.adjoint(), psi)
+
104  // ||y - A x|| < epsilon
+
105  .append(sopt::proximal::translate(sopt::proximal::L2Ball<Scalar>(epsilon), -y), sampling)
+
106  // x in positive quadrant
+
107  .append(sopt::proximal::positive_quadrant<Scalar>);
+
108 
+
109  SOPT_HIGH_LOG("Creating the reweighted algorithm");
+
110  // positive_quadrant projects the result of SDMM on the positive quadrant.
+
111  // This follows the reweighted algorithm in the original C implementation.
+
112  auto const posq = positive_quadrant(sdmm);
+
113  using t_PosQuadSDMM = std::remove_const<decltype(posq)>::type;
+
114  auto const min_delta = sigma * std::sqrt(y.size()) / std::sqrt(8 * image.size());
+
115  // Sets weight after each sdmm iteration.
+
116  // In practice, this means replacing the proximal of the l1 objective function.
+
117  auto set_weights = [](t_PosQuadSDMM &sdmm, Vector const &weights) {
+
118  sdmm.algorithm().proximals(0) = [weights](Vector &out, Scalar gamma, Vector const &x) {
+
119  out = sopt::soft_threshhold(x, gamma * weights);
+
120  };
+
121  };
+
122  auto call_PsiT = [&psi](t_PosQuadSDMM const &, Vector const &x) -> Vector {
+
123  return psi.adjoint() * x;
+
124  };
+
125  auto const reweighted = sopt::algorithm::reweighted(posq, set_weights, call_PsiT)
+
126  .itermax(5)
+
127  .min_delta(min_delta)
+
128  .is_converged(sopt::RelativeVariation<Scalar>(1e-3));
+
129 
+
130  SOPT_HIGH_LOG("Computing warm-start SDMM");
+
131  auto warm_start = sdmm(Vector::Zero(image.size()));
+
132  warm_start.x = sopt::positive_quadrant(warm_start.x);
+
133  SOPT_HIGH_LOG("SDMM returned {}", warm_start.good);
+
134 
+
135  SOPT_HIGH_LOG("Computing warm-start SDMM");
+
136  auto const result = reweighted(warm_start);
+
137 
+
138  // result should tell us the function converged
+
139  // it also contains result.niters - the number of iterations, and cg_diagnostic - the
+
140  // result from the last call to the conjugate gradient.
+
141  if (not result.good) throw std::runtime_error("Did not converge!");
+
142 
+
143  SOPT_HIGH_LOG("SOPT-SDMM converged in {} iterations", result.niters);
+
144  if (output != "none")
+
145  sopt::utilities::write_tiff(Matrix::Map(result.algo.x.data(), image.rows(), image.cols()),
+
146  output + ".tiff");
+
147 
+
148  return 0;
+
149 }
Scalar
sopt::t_real Scalar
Definition: bisection_method.cc:9
sopt::Sampling
An operator that samples a set of measurements.
Definition: sampling.h:17
@@ -243,11 +239,10 @@
Image
sopt::Image< Scalar > Image
Definition: cppflow_model.cc:20
main
int main(int argc, char const **argv)
Definition: reweighted.cc:26
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::algorithm::reweighted
Reweighted< ALGORITHM > reweighted(ALGORITHM const &algo, typename Reweighted< ALGORITHM >::t_SetWeights const &set_weights, typename Reweighted< ALGORITHM >::t_Reweightee const &reweightee)
Factory function to create an l0-approximation by reweighting an l1 norm.
Definition: reweighted.h:238
-
sopt::logging::initialize
std::shared_ptr< int > initialize(std::string const &)
Initializes a logger.
Definition: logging.disabled.h:12
sopt::notinstalled::read_standard_tiff
Image read_standard_tiff(std::string const &name)
Reads tiff image from sopt data directory if it exists.
Definition: tiffwrappers.cc:9
sopt::proximal::translate
Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
Translates given proximal by given vector.
Definition: proximal.h:362
sopt::utilities::write_tiff
void write_tiff(Image<> const &image, std::string const &filename)
Writes a tiff greyscale file.
Definition: utilities.cc:68
diff --git a/exception_8h.html b/exception_8h.html index ed502d6b7..1f1b90572 100644 --- a/exception_8h.html +++ b/exception_8h.html @@ -108,56 +108,56 @@ diff --git a/exception_8h__dep__incl.map b/exception_8h__dep__incl.map index dabfc4370..0c1e89a98 100644 --- a/exception_8h__dep__incl.map +++ b/exception_8h__dep__incl.map @@ -1,52 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/exception_8h__dep__incl.md5 b/exception_8h__dep__incl.md5 index bf2e287cd..0d67d50cf 100644 --- a/exception_8h__dep__incl.md5 +++ b/exception_8h__dep__incl.md5 @@ -1 +1 @@ -d98d579a1e022294f0984193bb0213e8 \ No newline at end of file +47d8e4e4a723a927464af30132629415 \ No newline at end of file diff --git a/exception_8h__dep__incl.png b/exception_8h__dep__incl.png index 5b647beb7..a7a83ef82 100644 Binary files a/exception_8h__dep__incl.png and b/exception_8h__dep__incl.png differ diff --git a/files.html b/files.html index 9937ddeda..27d4e625a 100644 --- a/files.html +++ b/files.html @@ -146,31 +146,30 @@  l2_forward_backward.h  l2_primal_dual.h  linear_transform.h - logging.disabled.h - logging.enabled.h - logging.h - maths.h - objective_functions.h - ort_session.h - padmm.h - positive_quadrant.h - power_method.h - primal_dual.h - proximal.h - proximal_expression.h - real_type.h - relative_variation.h - reweighted.h - sampling.cc - sampling.h - sdmm.h - tf_g_proximal.h - tv_primal_dual.h - types.h - utilities.cc - utilities.h - wavelets.h - wrapper.h + logging.cc + logging.h + maths.h + objective_functions.h + ort_session.h + padmm.h + positive_quadrant.h + power_method.h + primal_dual.h + proximal.h + proximal_expression.h + real_type.h + relative_variation.h + reweighted.h + sampling.cc + sampling.h + sdmm.h + tf_g_proximal.h + tv_primal_dual.h + types.h + utilities.cc + utilities.h + wavelets.h + wrapper.h  ► tests  bisection_method.cc  chained_operators.cc diff --git a/forward__backward_8cc.html b/forward__backward_8cc.html index a280b82ee..fb0bd3c21 100644 --- a/forward__backward_8cc.html +++ b/forward__backward_8cc.html @@ -103,44 +103,45 @@ diff --git a/forward__backward_8cc__incl.map b/forward__backward_8cc__incl.map index 39e43f45e..2fdb73508 100644 --- a/forward__backward_8cc__incl.map +++ b/forward__backward_8cc__incl.map @@ -1,40 +1,41 @@ - + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/forward__backward_8cc__incl.md5 b/forward__backward_8cc__incl.md5 index 3ae147f47..0363674aa 100644 --- a/forward__backward_8cc__incl.md5 +++ b/forward__backward_8cc__incl.md5 @@ -1 +1 @@ -2780bcd1fa6b8c5246b61c3e0989efb9 \ No newline at end of file +52930a891a7eb4ce6eb05cebb10462c4 \ No newline at end of file diff --git a/forward__backward_8cc__incl.png b/forward__backward_8cc__incl.png index 3fdd7f5a5..7ca422b7d 100644 Binary files a/forward__backward_8cc__incl.png and b/forward__backward_8cc__incl.png differ diff --git a/forward__backward_8h.html b/forward__backward_8h.html index e4f7dfe93..00aa44aba 100644 --- a/forward__backward_8h.html +++ b/forward__backward_8h.html @@ -99,29 +99,30 @@
diff --git a/forward__backward_8h__incl.map b/forward__backward_8h__incl.map index 522f163a9..14cb2b3b9 100644 --- a/forward__backward_8h__incl.map +++ b/forward__backward_8h__incl.map @@ -1,25 +1,26 @@ - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/forward__backward_8h__incl.md5 b/forward__backward_8h__incl.md5 index 2efc81a87..0ed5f3bc4 100644 --- a/forward__backward_8h__incl.md5 +++ b/forward__backward_8h__incl.md5 @@ -1 +1 @@ -1970530e1ef1b65d4caf5240957cfc1c \ No newline at end of file +8b82692fb3bfbab645ee3d9cd956ea60 \ No newline at end of file diff --git a/forward__backward_8h__incl.png b/forward__backward_8h__incl.png index fe782d90b..87b9b9984 100644 Binary files a/forward__backward_8h__incl.png and b/forward__backward_8h__incl.png differ diff --git a/forward__backward_8h_source.html b/forward__backward_8h_source.html index ae4d9c39f..1f796d464 100644 --- a/forward__backward_8h_source.html +++ b/forward__backward_8h_source.html @@ -343,11 +343,11 @@
t_real
sopt::t_real t_real
Definition: forward_backward.cc:27
linear_transform.h
-
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:31
-
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:27
-
SOPT_ERROR
#define SOPT_ERROR(...)
\macro Something is definitely wrong, algorithm exits
Definition: logging.h:15
-
SOPT_WARN
#define SOPT_WARN(...)
\macro Something might be going wrong
Definition: logging.h:17
-
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:29
+
SOPT_LOW_LOG
#define SOPT_LOW_LOG(...)
Low priority message.
Definition: logging.h:227
+
SOPT_HIGH_LOG
#define SOPT_HIGH_LOG(...)
High priority message.
Definition: logging.h:223
+
SOPT_ERROR
#define SOPT_ERROR(...)
\macro Something is definitely wrong, algorithm exits
Definition: logging.h:211
+
SOPT_WARN
#define SOPT_WARN(...)
\macro Something might be going wrong
Definition: logging.h:213
+
SOPT_MEDIUM_LOG
#define SOPT_MEDIUM_LOG(...)
Medium priority message.
Definition: logging.h:225
sopt::linear_transform
LinearTransform< VECTOR > linear_transform(OperatorFunction< VECTOR > const &direct, OperatorFunction< VECTOR > const &indirect, std::array< t_int, 3 > const &sizes={{1, 1, 0}})
Definition: linear_transform.h:101
sopt::t_real
double t_real
Root of the type hierarchy for real numbers.
Definition: types.h:17
diff --git a/functions.html b/functions.html index fb9eb919c..76d28f5fe 100644 --- a/functions.html +++ b/functions.html @@ -96,13 +96,16 @@

- a -

diff --git a/functions_func_i.html b/functions_func_i.html index 87eece437..1d0403d4c 100644 --- a/functions_func_i.html +++ b/functions_func_i.html @@ -96,17 +96,20 @@

- i -

diff --git a/functions_s.html b/functions_s.html index cff57276e..8357978b9 100644 --- a/functions_s.html +++ b/functions_s.html @@ -102,7 +102,7 @@

- s -

    , sopt::ScalarRelativeVariation< TYPE >
  • ScalarRelativeVariation() -: sopt::ScalarRelativeVariation< TYPE > +: sopt::ScalarRelativeVariation< TYPE >
  • SDMM() : sopt::algorithm::SDMM< SCALAR > @@ -111,6 +111,15 @@

    - s -

      : DummyAlgorithm , sopt::algorithm::Reweighted< ALGORITHM > +
    • setLevel() +: sopt::logging::Log +
      • +
    • setLevels() +: sopt::logging::Log +
      • +
    • setName() +: sopt::logging::Log +
    • size() : sopt::algorithm::SDMM< SCALAR >
      • @@ -118,11 +127,11 @@

      - s -

        : sopt::details::WrapFunction< VECTOR >
      • SOPT_MACRO() -: sopt::algorithm::ForwardBackward< SCALAR > -, sopt::algorithm::ImagingForwardBackward< SCALAR > +: sopt::algorithm::ForwardBackward< SCALAR > +, sopt::algorithm::ImagingForwardBackward< SCALAR > , sopt::algorithm::ImagingPrimalDual< SCALAR > , sopt::algorithm::ImagingProximalADMM< SCALAR > -, sopt::algorithm::JointMAP< ALGORITHM > +, sopt::algorithm::JointMAP< ALGORITHM > , sopt::algorithm::L1GProximal< SCALAR > , sopt::algorithm::L2ForwardBackward< SCALAR > , sopt::algorithm::PrimalDual< SCALAR > diff --git a/functions_t.html b/functions_t.html index 087b2bb9e..6fc6133f6 100644 --- a/functions_t.html +++ b/functions_t.html @@ -173,7 +173,7 @@

        - t -

          , sopt::algorithm::ImagingPrimalDual< SCALAR > , sopt::algorithm::ImagingProximalADMM< SCALAR > , sopt::algorithm::L2ForwardBackward< SCALAR > -, sopt::algorithm::PrimalDual< SCALAR > +, sopt::algorithm::PrimalDual< SCALAR > , sopt::algorithm::ProximalADMM< SCALAR > , sopt::algorithm::TVPrimalDual< SCALAR > @@ -191,6 +191,9 @@

          - t -

            , sopt::proximal::L1< SCALAR >::Breaker , sopt::RelativeVariation< TYPE > +
          • trace +: sopt::logging::Log +
          • transform : sopt::CData< T >
            • diff --git a/functions_type.html b/functions_type.html index 5136f52f3..0543f5dfb 100644 --- a/functions_type.html +++ b/functions_type.html @@ -81,6 +81,13 @@

            - a -

            +

            - c -

            + +

            - d -

            • Diagnostic : sopt::algorithm::PositiveQuadrant< ALGORITHM > @@ -118,6 +125,16 @@

              - i -

              +

              - l -

              + +

              - p -

              • PlainObject : sopt::details::AppliedFunction< FUNCTION, DERIVED > diff --git a/functions_vars.html b/functions_vars.html index f423e3a50..197cbafc9 100644 --- a/functions_vars.html +++ b/functions_vars.html @@ -119,6 +119,9 @@

                - e -

                diff --git a/functions_w.html b/functions_w.html index c3fb64364..8538dfed3 100644 --- a/functions_w.html +++ b/functions_w.html @@ -74,8 +74,14 @@
                Here is a list of all class members with links to the classes they belong to:

                - w -

                  +
                • warn +: sopt::logging::Log +
                  • +
                • warning +: sopt::logging::Log +
                • WaveletData() -: sopt::wavelets::WaveletData +: sopt::wavelets::WaveletData
                • WeightedL2Ball() : sopt::proximal::WeightedL2Ball< T > @@ -83,7 +89,7 @@

                  - w -

                  -
                  conan install .. -of . --build missing -o openmp=off -o mpi=off -pr:h=default -pr:b=default
                  +
                  conan install .. -of . --build missing -o openmp=on -o dompi=on
                  conan build .. -of .

                  Using CMake

                  If the dependencies are already available on your system, you can also install SOPT manually like so

                  @@ -145,10 +143,8 @@

                  Using Conan v2 (recommended)

                  make -j
                  make -j install

                  On MacOS, you can also install most of the dependencies with Homebrew e.g.

                  -
                  brew install libtensorflow eigen tiff spdlog catch2
                  +
                  brew install libtensorflow eigen tiff catch2

                  Note that the ONNXruntime interface is currently only supported when compiling with Clang on MacOS, but not with g++

                  -

                  Common errors

                  -

                  If you are using the g++ compiler and get an error to do with the package spdlog, try adding the option -s compiler.libcxx=libstdc++11 to the conan build command. This option is also necessary when building with gcc on MacOS.

                  Conan tips

                  You can set commonly used options, choices of compilers etc. in a conan profile. You can list profiles available on your system using conan profile list and select the profile you want to use with conan install with conan install .. -pr my_profile. CMake build options can also be added to the profile under [options]. Here is an example of a conan profile for building with a homebrew installed gcc 11 on MacOS.

                  [settings]
                  @@ -184,7 +180,7 @@

                  References and citation

                  License

                  -

                  SOPT: Sparse OPTimisation package Copyright (C) 2013-2023

                  +

                  SOPT: Sparse OPTimisation package Copyright (C) 2013-2024

                  This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

                  This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details (LICENSE.txt).

                  You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.

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+ diff --git a/inherit_graph_61.md5 b/inherit_graph_61.md5 index b11769ed9..47aed0f12 100644 --- a/inherit_graph_61.md5 +++ b/inherit_graph_61.md5 @@ -1 +1 @@ -e113160e310399bceb6e5ad10bb6b4f4 \ No newline at end of file +73c6d0360cbedee6ea236ffb077d2a72 \ No newline at end of file diff --git a/inherit_graph_61.png b/inherit_graph_61.png index e79b9ef2f..27f5a39de 100644 Binary files a/inherit_graph_61.png and b/inherit_graph_61.png differ diff --git a/inherit_graph_62.map b/inherit_graph_62.map index 206a3b123..413d0e9ca 100644 --- a/inherit_graph_62.map +++ b/inherit_graph_62.map @@ -1,3 +1,3 @@ - + diff --git a/inherit_graph_62.md5 b/inherit_graph_62.md5 index 3a7a6ca50..b11769ed9 100644 --- a/inherit_graph_62.md5 +++ b/inherit_graph_62.md5 @@ -1 +1 @@ -8a68193a03579142a7a935c2c66efc61 \ No newline at end of file +e113160e310399bceb6e5ad10bb6b4f4 \ No newline at end of file diff --git a/inherit_graph_62.png b/inherit_graph_62.png index 5225b739c..e79b9ef2f 100644 Binary files a/inherit_graph_62.png and b/inherit_graph_62.png differ diff --git a/inherit_graph_63.map b/inherit_graph_63.map index 605988267..206a3b123 100644 --- a/inherit_graph_63.map +++ b/inherit_graph_63.map @@ -1,4 +1,3 @@ - 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+ + + + + + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + diff --git a/inpainting_8h.html b/inpainting_8h.html index 2aa7eefc6..693275539 100644 --- a/inpainting_8h.html +++ b/inpainting_8h.html @@ -93,28 +93,29 @@
                  diff --git a/inpainting_8h__incl.map b/inpainting_8h__incl.map index d72fba03b..d526c58f9 100644 --- a/inpainting_8h__incl.map +++ b/inpainting_8h__incl.map @@ -1,24 +1,25 @@ - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + diff --git a/inpainting_8h__incl.md5 b/inpainting_8h__incl.md5 index 67661cb8c..c0109f4a4 100644 --- a/inpainting_8h__incl.md5 +++ b/inpainting_8h__incl.md5 @@ -1 +1 @@ -1c78e3461b4b2f8acdd8d1993812ddd7 \ No newline at end of file +eb60eed5b37946ad72c12e37454aad62 \ No newline at end of file diff --git a/inpainting_8h__incl.png b/inpainting_8h__incl.png index 62adca910..1799a81bd 100644 Binary files a/inpainting_8h__incl.png and b/inpainting_8h__incl.png differ diff --git a/inpainting__credible__interval_8cc.html b/inpainting__credible__interval_8cc.html index 0b6e8977e..03724ceb1 100644 --- a/inpainting__credible__interval_8cc.html +++ b/inpainting__credible__interval_8cc.html @@ -107,56 +107,56 @@
                  @@ -224,115 +224,113 @@

                  51  std::srand(static_cast<unsigned int>(seed));
                  52  std::mt19937 mersenne(std::time(nullptr));
                  53 
                  -
                  54  // Initializes and sets logger (if compiled with logging)
                  -
                  55  // See set_level function for levels.
                  -
                  56  sopt::logging::initialize();
                  -
                  57  sopt::logging::set_level("debug");
                  -
                  58  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  59  const Image image = sopt::notinstalled::read_standard_tiff(input) /
                  -
                  60  sopt::notinstalled::read_standard_tiff(input).cwiseAbs().maxCoeff();
                  -
                  61  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  -
                  62 
                  -
                  63  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  64  sopt::t_uint const nmeasure = std::floor(0.33 * image.size());
                  -
                  65  sopt::LinearTransform<Vector> const sampling =
                  -
                  66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  67  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  68  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  -
                  69 
                  -
                  70  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  -
                  71  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  -
                  72 
                  -
                  73  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  -
                  74  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  -
                  75 
                  -
                  76  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  -
                  77  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  78  auto constexpr snr = 30.0;
                  -
                  79  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  80  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(nmeasure)) * sigma;
                  -
                  81 
                  -
                  82  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  83  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  84  Vector y(y0.size());
                  -
                  85  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  86  // Write dirty imagte to file
                  -
                  87  if (output != "none") {
                  -
                  88  Vector const dirty = sampling.adjoint() * y;
                  -
                  89  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  90  "dirty_" + output + ".tiff");
                  -
                  91  }
                  -
                  92 
                  -
                  93  sopt::t_real constexpr gamma = 18;
                  -
                  94  sopt::t_real const beta = sigma * sigma;
                  -
                  95  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  -
                  96  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
                  -
                  97  .itermax(500)
                  -
                  98  .beta(beta)
                  -
                  99  .sigma(sigma)
                  -
                  100  .gamma(gamma)
                  -
                  101  .relative_variation(5e-4)
                  -
                  102  .residual_tolerance(0)
                  -
                  103  .tight_frame(true)
                  -
                  104  .Phi(sampling);
                  -
                  105 
                  -
                  106  // Create a shared pointer to an instance of the L1GProximal class
                  -
                  107  // and set its properties
                  -
                  108  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  -
                  109  gp->l1_proximal_tolerance(1e-4)
                  -
                  110  .l1_proximal_nu(1)
                  -
                  111  .l1_proximal_itermax(50)
                  -
                  112  .l1_proximal_positivity_constraint(true)
                  -
                  113  .l1_proximal_real_constraint(true)
                  -
                  114  .Psi(psi);
                  -
                  115 
                  -
                  116  // Once the properties are set, inject it into the ImagingForwardBackward object
                  -
                  117  fb.g_proximal(gp);
                  -
                  118 
                  -
                  119  SOPT_HIGH_LOG("Starting Forward Backward");
                  -
                  120  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  -
                  121  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  -
                  122  auto const diagnostic = fb();
                  -
                  123  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  -
                  124 
                  -
                  125  if (output != "none")
                  -
                  126  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  127  output + ".tiff");
                  -
                  128  // diagnostic should tell us the function converged
                  -
                  129  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  130  // diagnostic from the last call to the conjugate gradient.
                  -
                  131  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  54  // See set_level function for levels.
                  +
                  55  sopt::logging::set_level("debug");
                  +
                  56  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  57  const Image image = sopt::notinstalled::read_standard_tiff(input) /
                  +
                  58  sopt::notinstalled::read_standard_tiff(input).cwiseAbs().maxCoeff();
                  +
                  59  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  +
                  60 
                  +
                  61  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  62  sopt::t_uint const nmeasure = std::floor(0.33 * image.size());
                  +
                  63  sopt::LinearTransform<Vector> const sampling =
                  +
                  64  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  65  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  66  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  +
                  67 
                  +
                  68  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  +
                  69  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  +
                  70 
                  +
                  71  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  +
                  72  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  +
                  73 
                  +
                  74  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  +
                  75  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  +
                  76  auto constexpr snr = 30.0;
                  +
                  77  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  78  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(nmeasure)) * sigma;
                  +
                  79 
                  +
                  80  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  81  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  82  Vector y(y0.size());
                  +
                  83  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  84  // Write dirty imagte to file
                  +
                  85  if (output != "none") {
                  +
                  86  Vector const dirty = sampling.adjoint() * y;
                  +
                  87  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  88  "dirty_" + output + ".tiff");
                  +
                  89  }
                  +
                  90 
                  +
                  91  sopt::t_real constexpr gamma = 18;
                  +
                  92  sopt::t_real const beta = sigma * sigma;
                  +
                  93  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  +
                  94  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
                  +
                  95  .itermax(500)
                  +
                  96  .beta(beta)
                  +
                  97  .sigma(sigma)
                  +
                  98  .gamma(gamma)
                  +
                  99  .relative_variation(5e-4)
                  +
                  100  .residual_tolerance(0)
                  +
                  101  .tight_frame(true)
                  +
                  102  .Phi(sampling);
                  +
                  103 
                  +
                  104  // Create a shared pointer to an instance of the L1GProximal class
                  +
                  105  // and set its properties
                  +
                  106  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  +
                  107  gp->l1_proximal_tolerance(1e-4)
                  +
                  108  .l1_proximal_nu(1)
                  +
                  109  .l1_proximal_itermax(50)
                  +
                  110  .l1_proximal_positivity_constraint(true)
                  +
                  111  .l1_proximal_real_constraint(true)
                  +
                  112  .Psi(psi);
                  +
                  113 
                  +
                  114  // Once the properties are set, inject it into the ImagingForwardBackward object
                  +
                  115  fb.g_proximal(gp);
                  +
                  116 
                  +
                  117  SOPT_HIGH_LOG("Starting Forward Backward");
                  +
                  118  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  +
                  119  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  +
                  120  auto const diagnostic = fb();
                  +
                  121  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  +
                  122 
                  +
                  123  if (output != "none")
                  +
                  124  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  125  output + ".tiff");
                  +
                  126  // diagnostic should tell us the function converged
                  +
                  127  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  128  // diagnostic from the last call to the conjugate gradient.
                  +
                  129  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  130 
                  +
                  131  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  132 
                  -
                  133  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  -
                  134 
                  -
                  135  constexpr sopt::t_real alpha = 0.99;
                  -
                  136  const sopt::t_uint grid_pixel_size = image.rows() / 16;
                  -
                  137  SOPT_HIGH_LOG("Finding credible interval");
                  -
                  138  const std::function<Scalar(Vector)> objective_function = [gamma, sigma, &y, &sampling,
                  -
                  139  &psi](const Vector &x) {
                  -
                  140  return sopt::l1_norm(psi.adjoint() * x) * gamma +
                  -
                  141  0.5 * std::pow(sopt::l2_norm(sampling * x - y), 2) / (sigma * sigma);
                  -
                  142  };
                  -
                  143 
                  -
                  144  sopt::Image<sopt::t_real> lower_error;
                  -
                  145  sopt::Image<sopt::t_real> upper_error;
                  -
                  146  sopt::Image<sopt::t_real> mean_solution;
                  -
                  147  std::tie(lower_error, mean_solution, upper_error) =
                  -
                  148  sopt::credible_region::credible_interval<sopt::Vector<sopt::t_real>, sopt::t_real>(
                  -
                  149  diagnostic.x, image.rows(), image.cols(), grid_pixel_size, objective_function, alpha);
                  -
                  150  if (output != "none") {
                  -
                  151  sopt::utilities::write_tiff(
                  -
                  152  Matrix::Map(upper_error.data(), upper_error.rows(), upper_error.cols()),
                  -
                  153  output + "_upper_error.tiff");
                  -
                  154  sopt::utilities::write_tiff(
                  -
                  155  Matrix::Map(mean_solution.data(), mean_solution.rows(), mean_solution.cols()),
                  -
                  156  output + "_mean_solution.tiff");
                  -
                  157  sopt::utilities::write_tiff(
                  -
                  158  Matrix::Map(lower_error.data(), lower_error.rows(), lower_error.cols()),
                  -
                  159  output + "_lower_error.tiff");
                  -
                  160  }
                  -
                  161  return 0;
                  -
                  162 }
                  +
                  133  constexpr sopt::t_real alpha = 0.99;
                  +
                  134  const sopt::t_uint grid_pixel_size = image.rows() / 16;
                  +
                  135  SOPT_HIGH_LOG("Finding credible interval");
                  +
                  136  const std::function<Scalar(Vector)> objective_function = [gamma, sigma, &y, &sampling,
                  +
                  137  &psi](const Vector &x) {
                  +
                  138  return sopt::l1_norm(psi.adjoint() * x) * gamma +
                  +
                  139  0.5 * std::pow(sopt::l2_norm(sampling * x - y), 2) / (sigma * sigma);
                  +
                  140  };
                  +
                  141 
                  +
                  142  sopt::Image<sopt::t_real> lower_error;
                  +
                  143  sopt::Image<sopt::t_real> upper_error;
                  +
                  144  sopt::Image<sopt::t_real> mean_solution;
                  +
                  145  std::tie(lower_error, mean_solution, upper_error) =
                  +
                  146  sopt::credible_region::credible_interval<sopt::Vector<sopt::t_real>, sopt::t_real>(
                  +
                  147  diagnostic.x, image.rows(), image.cols(), grid_pixel_size, objective_function, alpha);
                  +
                  148  if (output != "none") {
                  +
                  149  sopt::utilities::write_tiff(
                  +
                  150  Matrix::Map(upper_error.data(), upper_error.rows(), upper_error.cols()),
                  +
                  151  output + "_upper_error.tiff");
                  +
                  152  sopt::utilities::write_tiff(
                  +
                  153  Matrix::Map(mean_solution.data(), mean_solution.rows(), mean_solution.cols()),
                  +
                  154  output + "_mean_solution.tiff");
                  +
                  155  sopt::utilities::write_tiff(
                  +
                  156  Matrix::Map(lower_error.data(), lower_error.rows(), lower_error.cols()),
                  +
                  157  output + "_lower_error.tiff");
                  +
                  158  }
                  +
                  159  return 0;
                  +
                  160 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::LinearTransform
                  Joins together direct and indirect operators.
                  Definition: linear_transform.h:30
                  sopt::LinearTransform::adjoint
                  LinearTransform< VECTOR > adjoint() const
                  Indirect transform.
                  Definition: linear_transform.h:79
                  @@ -342,10 +340,9 @@

                  sopt::algorithm::ImagingForwardBackward::Phi
                  ImagingForwardBackward &::type Phi(ARGS &&... args)
                  Definition: imaging_forward_backward.h:202
                  mersenne
                  std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  +
                  sopt::logging::set_level
                  void set_level(const std::string &level)
                  Method to set the logging level of the default Log object.
                  Definition: logging.h:154
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  @@ -363,7 +360,7 @@

                  Vector
                  sopt::Vector< Scalar > Vector
                  Definition: inpainting.cc:28
                  Matrix
                  sopt::Matrix< Scalar > Matrix
                  Definition: inpainting.cc:29
                  -

                  References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::algorithm::ImagingForwardBackward< SCALAR >::g_proximal(), sopt::logging::initialize(), sopt::l1_norm(), sopt::l2_norm(), mersenne(), sopt::algorithm::ImagingForwardBackward< SCALAR >::Phi(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

                  +

                  References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::algorithm::ImagingForwardBackward< SCALAR >::g_proximal(), sopt::l1_norm(), sopt::l2_norm(), mersenne(), sopt::algorithm::ImagingForwardBackward< SCALAR >::Phi(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

                  diff --git a/inpainting__credible__interval_8cc__incl.map b/inpainting__credible__interval_8cc__incl.map index e72ad6c22..1fc2911e2 100644 --- a/inpainting__credible__interval_8cc__incl.map +++ b/inpainting__credible__interval_8cc__incl.map @@ -1,52 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/inpainting__credible__interval_8cc__incl.md5 b/inpainting__credible__interval_8cc__incl.md5 index f51771325..5aa728809 100644 --- a/inpainting__credible__interval_8cc__incl.md5 +++ b/inpainting__credible__interval_8cc__incl.md5 @@ -1 +1 @@ -2a42057ffb0acc6429847f6deb0d0d68 \ No newline at end of file +79931274a39660b043156f2b5c956ed6 \ No newline at end of file diff --git a/inpainting__credible__interval_8cc__incl.png b/inpainting__credible__interval_8cc__incl.png index 67f6cf793..0c1183289 100644 Binary files a/inpainting__credible__interval_8cc__incl.png and b/inpainting__credible__interval_8cc__incl.png differ diff --git a/inpainting__credible__interval_8cc_source.html b/inpainting__credible__interval_8cc_source.html index 51953a3cb..1c8c70da7 100644 --- a/inpainting__credible__interval_8cc_source.html +++ b/inpainting__credible__interval_8cc_source.html @@ -132,115 +132,113 @@
                  51  std::srand(static_cast<unsigned int>(seed));
                  52  std::mt19937 mersenne(std::time(nullptr));
                  53 
                  -
                  54  // Initializes and sets logger (if compiled with logging)
                  -
                  55  // See set_level function for levels.
                  -
                  56  sopt::logging::initialize();
                  -
                  57  sopt::logging::set_level("debug");
                  -
                  58  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  59  const Image image = sopt::notinstalled::read_standard_tiff(input) /
                  -
                  60  sopt::notinstalled::read_standard_tiff(input).cwiseAbs().maxCoeff();
                  -
                  61  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  -
                  62 
                  -
                  63  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  64  sopt::t_uint const nmeasure = std::floor(0.33 * image.size());
                  -
                  65  sopt::LinearTransform<Vector> const sampling =
                  -
                  66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  67  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  68  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  -
                  69 
                  -
                  70  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  -
                  71  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  -
                  72 
                  -
                  73  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  -
                  74  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  -
                  75 
                  -
                  76  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  -
                  77  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  78  auto constexpr snr = 30.0;
                  -
                  79  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  80  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(nmeasure)) * sigma;
                  -
                  81 
                  -
                  82  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  83  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  84  Vector y(y0.size());
                  -
                  85  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  86  // Write dirty imagte to file
                  -
                  87  if (output != "none") {
                  -
                  88  Vector const dirty = sampling.adjoint() * y;
                  -
                  89  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  90  "dirty_" + output + ".tiff");
                  -
                  91  }
                  -
                  92 
                  -
                  93  sopt::t_real constexpr gamma = 18;
                  -
                  94  sopt::t_real const beta = sigma * sigma;
                  -
                  95  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  -
                  96  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
                  -
                  97  .itermax(500)
                  -
                  98  .beta(beta)
                  -
                  99  .sigma(sigma)
                  -
                  100  .gamma(gamma)
                  -
                  101  .relative_variation(5e-4)
                  -
                  102  .residual_tolerance(0)
                  -
                  103  .tight_frame(true)
                  -
                  104  .Phi(sampling);
                  -
                  105 
                  -
                  106  // Create a shared pointer to an instance of the L1GProximal class
                  -
                  107  // and set its properties
                  -
                  108  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  -
                  109  gp->l1_proximal_tolerance(1e-4)
                  -
                  110  .l1_proximal_nu(1)
                  -
                  111  .l1_proximal_itermax(50)
                  -
                  112  .l1_proximal_positivity_constraint(true)
                  -
                  113  .l1_proximal_real_constraint(true)
                  -
                  114  .Psi(psi);
                  -
                  115 
                  -
                  116  // Once the properties are set, inject it into the ImagingForwardBackward object
                  -
                  117  fb.g_proximal(gp);
                  -
                  118 
                  -
                  119  SOPT_HIGH_LOG("Starting Forward Backward");
                  -
                  120  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  -
                  121  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  -
                  122  auto const diagnostic = fb();
                  -
                  123  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  -
                  124 
                  -
                  125  if (output != "none")
                  -
                  126  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  127  output + ".tiff");
                  -
                  128  // diagnostic should tell us the function converged
                  -
                  129  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  130  // diagnostic from the last call to the conjugate gradient.
                  -
                  131  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  54  // See set_level function for levels.
                  +
                  55  sopt::logging::set_level("debug");
                  +
                  56  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  57  const Image image = sopt::notinstalled::read_standard_tiff(input) /
                  +
                  58  sopt::notinstalled::read_standard_tiff(input).cwiseAbs().maxCoeff();
                  +
                  59  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  +
                  60 
                  +
                  61  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  62  sopt::t_uint const nmeasure = std::floor(0.33 * image.size());
                  +
                  63  sopt::LinearTransform<Vector> const sampling =
                  +
                  64  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  65  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  66  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  +
                  67 
                  +
                  68  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  +
                  69  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  +
                  70 
                  +
                  71  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  +
                  72  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  +
                  73 
                  +
                  74  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  +
                  75  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  +
                  76  auto constexpr snr = 30.0;
                  +
                  77  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  78  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(nmeasure)) * sigma;
                  +
                  79 
                  +
                  80  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  81  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  82  Vector y(y0.size());
                  +
                  83  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  84  // Write dirty imagte to file
                  +
                  85  if (output != "none") {
                  +
                  86  Vector const dirty = sampling.adjoint() * y;
                  +
                  87  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  88  "dirty_" + output + ".tiff");
                  +
                  89  }
                  +
                  90 
                  +
                  91  sopt::t_real constexpr gamma = 18;
                  +
                  92  sopt::t_real const beta = sigma * sigma;
                  +
                  93  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  +
                  94  auto fb = sopt::algorithm::ImagingForwardBackward<Scalar>(y)
                  +
                  95  .itermax(500)
                  +
                  96  .beta(beta)
                  +
                  97  .sigma(sigma)
                  +
                  98  .gamma(gamma)
                  +
                  99  .relative_variation(5e-4)
                  +
                  100  .residual_tolerance(0)
                  +
                  101  .tight_frame(true)
                  +
                  102  .Phi(sampling);
                  +
                  103 
                  +
                  104  // Create a shared pointer to an instance of the L1GProximal class
                  +
                  105  // and set its properties
                  +
                  106  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  +
                  107  gp->l1_proximal_tolerance(1e-4)
                  +
                  108  .l1_proximal_nu(1)
                  +
                  109  .l1_proximal_itermax(50)
                  +
                  110  .l1_proximal_positivity_constraint(true)
                  +
                  111  .l1_proximal_real_constraint(true)
                  +
                  112  .Psi(psi);
                  +
                  113 
                  +
                  114  // Once the properties are set, inject it into the ImagingForwardBackward object
                  +
                  115  fb.g_proximal(gp);
                  +
                  116 
                  +
                  117  SOPT_HIGH_LOG("Starting Forward Backward");
                  +
                  118  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  +
                  119  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  +
                  120  auto const diagnostic = fb();
                  +
                  121  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  +
                  122 
                  +
                  123  if (output != "none")
                  +
                  124  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  125  output + ".tiff");
                  +
                  126  // diagnostic should tell us the function converged
                  +
                  127  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  128  // diagnostic from the last call to the conjugate gradient.
                  +
                  129  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  130 
                  +
                  131  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  132 
                  -
                  133  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  -
                  134 
                  -
                  135  constexpr sopt::t_real alpha = 0.99;
                  -
                  136  const sopt::t_uint grid_pixel_size = image.rows() / 16;
                  -
                  137  SOPT_HIGH_LOG("Finding credible interval");
                  -
                  138  const std::function<Scalar(Vector)> objective_function = [gamma, sigma, &y, &sampling,
                  -
                  139  &psi](const Vector &x) {
                  -
                  140  return sopt::l1_norm(psi.adjoint() * x) * gamma +
                  -
                  141  0.5 * std::pow(sopt::l2_norm(sampling * x - y), 2) / (sigma * sigma);
                  -
                  142  };
                  -
                  143 
                  -
                  144  sopt::Image<sopt::t_real> lower_error;
                  -
                  145  sopt::Image<sopt::t_real> upper_error;
                  -
                  146  sopt::Image<sopt::t_real> mean_solution;
                  -
                  147  std::tie(lower_error, mean_solution, upper_error) =
                  -
                  148  sopt::credible_region::credible_interval<sopt::Vector<sopt::t_real>, sopt::t_real>(
                  -
                  149  diagnostic.x, image.rows(), image.cols(), grid_pixel_size, objective_function, alpha);
                  -
                  150  if (output != "none") {
                  -
                  151  sopt::utilities::write_tiff(
                  -
                  152  Matrix::Map(upper_error.data(), upper_error.rows(), upper_error.cols()),
                  -
                  153  output + "_upper_error.tiff");
                  -
                  154  sopt::utilities::write_tiff(
                  -
                  155  Matrix::Map(mean_solution.data(), mean_solution.rows(), mean_solution.cols()),
                  -
                  156  output + "_mean_solution.tiff");
                  -
                  157  sopt::utilities::write_tiff(
                  -
                  158  Matrix::Map(lower_error.data(), lower_error.rows(), lower_error.cols()),
                  -
                  159  output + "_lower_error.tiff");
                  -
                  160  }
                  -
                  161  return 0;
                  -
                  162 }
                  +
                  133  constexpr sopt::t_real alpha = 0.99;
                  +
                  134  const sopt::t_uint grid_pixel_size = image.rows() / 16;
                  +
                  135  SOPT_HIGH_LOG("Finding credible interval");
                  +
                  136  const std::function<Scalar(Vector)> objective_function = [gamma, sigma, &y, &sampling,
                  +
                  137  &psi](const Vector &x) {
                  +
                  138  return sopt::l1_norm(psi.adjoint() * x) * gamma +
                  +
                  139  0.5 * std::pow(sopt::l2_norm(sampling * x - y), 2) / (sigma * sigma);
                  +
                  140  };
                  +
                  141 
                  +
                  142  sopt::Image<sopt::t_real> lower_error;
                  +
                  143  sopt::Image<sopt::t_real> upper_error;
                  +
                  144  sopt::Image<sopt::t_real> mean_solution;
                  +
                  145  std::tie(lower_error, mean_solution, upper_error) =
                  +
                  146  sopt::credible_region::credible_interval<sopt::Vector<sopt::t_real>, sopt::t_real>(
                  +
                  147  diagnostic.x, image.rows(), image.cols(), grid_pixel_size, objective_function, alpha);
                  +
                  148  if (output != "none") {
                  +
                  149  sopt::utilities::write_tiff(
                  +
                  150  Matrix::Map(upper_error.data(), upper_error.rows(), upper_error.cols()),
                  +
                  151  output + "_upper_error.tiff");
                  +
                  152  sopt::utilities::write_tiff(
                  +
                  153  Matrix::Map(mean_solution.data(), mean_solution.rows(), mean_solution.cols()),
                  +
                  154  output + "_mean_solution.tiff");
                  +
                  155  sopt::utilities::write_tiff(
                  +
                  156  Matrix::Map(lower_error.data(), lower_error.rows(), lower_error.cols()),
                  +
                  157  output + "_lower_error.tiff");
                  +
                  158  }
                  +
                  159  return 0;
                  +
                  160 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::LinearTransform
                  Joins together direct and indirect operators.
                  Definition: linear_transform.h:30
                  sopt::LinearTransform::adjoint
                  LinearTransform< VECTOR > adjoint() const
                  Indirect transform.
                  Definition: linear_transform.h:79
                  @@ -255,11 +253,10 @@
                  main
                  int main(int argc, char const **argv)
                  Definition: inpainting_credible_interval.cc:25
                  l1_g_proximal.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  sopt::logging::set_level
                  void set_level(const std::string &level)
                  Method to set the logging level of the default Log object.
                  Definition: logging.h:154
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  diff --git a/inpainting__joint__map_8cc.html b/inpainting__joint__map_8cc.html index c7473b31d..ce7324647 100644 --- a/inpainting__joint__map_8cc.html +++ b/inpainting__joint__map_8cc.html @@ -107,56 +107,56 @@ @@ -224,96 +224,94 @@

                  51  std::srand(static_cast<unsigned int>(seed));
                  52  std::mt19937 mersenne(std::time(nullptr));
                  53 
                  -
                  54  // Initializes and sets logger (if compiled with logging)
                  -
                  55  // See set_level function for levels.
                  -
                  56  sopt::logging::initialize();
                  -
                  57  sopt::logging::set_level("debug");
                  -
                  58  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  59  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  -
                  60  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  -
                  61 
                  -
                  62  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  63  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  -
                  64  sopt::LinearTransform<Vector> const sampling =
                  -
                  65  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  66  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  67  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  -
                  68 
                  -
                  69  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  -
                  70  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  -
                  71 
                  -
                  72  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  -
                  73  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  -
                  74 
                  -
                  75  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  -
                  76  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  77  auto constexpr snr = 30.0;
                  -
                  78  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  79  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  -
                  80 
                  -
                  81  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  82  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  83  Vector y(y0.size());
                  -
                  84  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  85  // Write dirty imagte to file
                  -
                  86  if (output != "none") {
                  -
                  87  Vector const dirty = sampling.adjoint() * y;
                  -
                  88  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  89  "dirty_" + output + ".tiff");
                  -
                  90  }
                  -
                  91 
                  -
                  92  sopt::t_real constexpr gamma = 0;
                  -
                  93  sopt::t_real const beta = sigma * sigma * 0.5;
                  -
                  94  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  -
                  95  auto fb = std::make_shared<sopt::algorithm::ImagingForwardBackward<Scalar>>(y);
                  -
                  96  fb->itermax(500)
                  -
                  97  .beta(beta) // stepsize
                  -
                  98  .sigma(sigma) // sigma
                  -
                  99  .gamma(gamma) // regularisation paramater
                  -
                  100  .relative_variation(1e-3)
                  -
                  101  .residual_tolerance(0)
                  -
                  102  .tight_frame(true)
                  -
                  103  .Phi(sampling);
                  -
                  104 
                  -
                  105  // Create a shared pointer to an instance of the L1GProximal class
                  -
                  106  // and set its properties
                  -
                  107  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  -
                  108  gp->l1_proximal_tolerance(1e-4)
                  -
                  109  .l1_proximal_nu(1)
                  -
                  110  .l1_proximal_itermax(50)
                  -
                  111  .l1_proximal_positivity_constraint(true)
                  -
                  112  .l1_proximal_real_constraint(true)
                  -
                  113  .Psi(psi);
                  -
                  114 
                  -
                  115  // Once the properties are set, inject it into the ImagingForwardBackward object
                  -
                  116  fb->g_proximal(gp);
                  -
                  117 
                  -
                  118  SOPT_HIGH_LOG("Starting Forward Backward");
                  -
                  119  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  -
                  120  // Here, we default to (y, Φx/ν - y)
                  -
                  121  auto l1_norm = [psi](const Vector &x) { return sopt::l1_norm(psi.adjoint() * x); };
                  -
                  122  const sopt::t_uint number_of_wavelet_coefficients = image.size();
                  -
                  123  auto joint_map = sopt::algorithm::JointMAP<sopt::algorithm::ImagingForwardBackward<Scalar>>(
                  -
                  124  fb, l1_norm, number_of_wavelet_coefficients)
                  -
                  125  .alpha(1)
                  -
                  126  .beta(1)
                  -
                  127  .k(1)
                  -
                  128  .relative_variation(1e-3)
                  -
                  129  .objective_variation(1e-3);
                  -
                  130  auto diagnostic = joint_map();
                  -
                  131  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  -
                  132  if (output != "none")
                  -
                  133  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  134  output + ".tiff");
                  -
                  135  // diagnostic should tell us the function converged
                  -
                  136  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  137  // diagnostic from the last call to the conjugate gradient.
                  -
                  138  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  54  // See set_level function for levels.
                  +
                  55  sopt::logging::set_level("debug");
                  +
                  56  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  57  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  +
                  58  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  +
                  59 
                  +
                  60  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  61  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  +
                  62  sopt::LinearTransform<Vector> const sampling =
                  +
                  63  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  64  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  65  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  +
                  66 
                  +
                  67  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  +
                  68  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  +
                  69 
                  +
                  70  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  +
                  71  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  +
                  72 
                  +
                  73  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  +
                  74  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  +
                  75  auto constexpr snr = 30.0;
                  +
                  76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  +
                  78 
                  +
                  79  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  80  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  81  Vector y(y0.size());
                  +
                  82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  83  // Write dirty imagte to file
                  +
                  84  if (output != "none") {
                  +
                  85  Vector const dirty = sampling.adjoint() * y;
                  +
                  86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  87  "dirty_" + output + ".tiff");
                  +
                  88  }
                  +
                  89 
                  +
                  90  sopt::t_real constexpr gamma = 0;
                  +
                  91  sopt::t_real const beta = sigma * sigma * 0.5;
                  +
                  92  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  +
                  93  auto fb = std::make_shared<sopt::algorithm::ImagingForwardBackward<Scalar>>(y);
                  +
                  94  fb->itermax(500)
                  +
                  95  .beta(beta) // stepsize
                  +
                  96  .sigma(sigma) // sigma
                  +
                  97  .gamma(gamma) // regularisation paramater
                  +
                  98  .relative_variation(1e-3)
                  +
                  99  .residual_tolerance(0)
                  +
                  100  .tight_frame(true)
                  +
                  101  .Phi(sampling);
                  +
                  102 
                  +
                  103  // Create a shared pointer to an instance of the L1GProximal class
                  +
                  104  // and set its properties
                  +
                  105  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  +
                  106  gp->l1_proximal_tolerance(1e-4)
                  +
                  107  .l1_proximal_nu(1)
                  +
                  108  .l1_proximal_itermax(50)
                  +
                  109  .l1_proximal_positivity_constraint(true)
                  +
                  110  .l1_proximal_real_constraint(true)
                  +
                  111  .Psi(psi);
                  +
                  112 
                  +
                  113  // Once the properties are set, inject it into the ImagingForwardBackward object
                  +
                  114  fb->g_proximal(gp);
                  +
                  115 
                  +
                  116  SOPT_HIGH_LOG("Starting Forward Backward");
                  +
                  117  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  +
                  118  // Here, we default to (y, Φx/ν - y)
                  +
                  119  auto l1_norm = [psi](const Vector &x) { return sopt::l1_norm(psi.adjoint() * x); };
                  +
                  120  const sopt::t_uint number_of_wavelet_coefficients = image.size();
                  +
                  121  auto joint_map = sopt::algorithm::JointMAP<sopt::algorithm::ImagingForwardBackward<Scalar>>(
                  +
                  122  fb, l1_norm, number_of_wavelet_coefficients)
                  +
                  123  .alpha(1)
                  +
                  124  .beta(1)
                  +
                  125  .k(1)
                  +
                  126  .relative_variation(1e-3)
                  +
                  127  .objective_variation(1e-3);
                  +
                  128  auto diagnostic = joint_map();
                  +
                  129  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  +
                  130  if (output != "none")
                  +
                  131  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  132  output + ".tiff");
                  +
                  133  // diagnostic should tell us the function converged
                  +
                  134  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  135  // diagnostic from the last call to the conjugate gradient.
                  +
                  136  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  137 
                  +
                  138  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  139 
                  -
                  140  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  -
                  141 
                  -
                  142  return 0;
                  -
                  143 }
                  +
                  140  return 0;
                  +
                  141 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::LinearTransform
                  Joins together direct and indirect operators.
                  Definition: linear_transform.h:30
                  sopt::LinearTransform::adjoint
                  LinearTransform< VECTOR > adjoint() const
                  Indirect transform.
                  Definition: linear_transform.h:79
                  @@ -321,10 +319,9 @@

                  sopt::algorithm::JointMAP
                  Definition: joint_map.h:19
                  mersenne
                  std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  +
                  sopt::logging::set_level
                  void set_level(const std::string &level)
                  Method to set the logging level of the default Log object.
                  Definition: logging.h:154
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  @@ -341,7 +338,7 @@

                  Vector
                  sopt::Vector< Scalar > Vector
                  Definition: inpainting.cc:28
                  Matrix
                  sopt::Matrix< Scalar > Matrix
                  Definition: inpainting.cc:29
                  -

                  References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::logging::initialize(), sopt::l1_norm(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

                  +

                  References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::l1_norm(), mersenne(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

                  diff --git a/inpainting__joint__map_8cc__incl.map b/inpainting__joint__map_8cc__incl.map index 632e07feb..2ba2af8c2 100644 --- a/inpainting__joint__map_8cc__incl.map +++ b/inpainting__joint__map_8cc__incl.map @@ -1,52 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/inpainting__joint__map_8cc__incl.md5 b/inpainting__joint__map_8cc__incl.md5 index 2e530bed4..d52a184be 100644 --- a/inpainting__joint__map_8cc__incl.md5 +++ b/inpainting__joint__map_8cc__incl.md5 @@ -1 +1 @@ -a360c1a10d559293d7a595bfb8f79d25 \ No newline at end of file +c46719b84821bced2c5c558646888bae \ No newline at end of file diff --git a/inpainting__joint__map_8cc__incl.png b/inpainting__joint__map_8cc__incl.png index 007d6001a..608c4cd0a 100644 Binary files a/inpainting__joint__map_8cc__incl.png and b/inpainting__joint__map_8cc__incl.png differ diff --git a/inpainting__joint__map_8cc_source.html b/inpainting__joint__map_8cc_source.html index 32800f0ff..2f4d42f2a 100644 --- a/inpainting__joint__map_8cc_source.html +++ b/inpainting__joint__map_8cc_source.html @@ -132,96 +132,94 @@
                  51  std::srand(static_cast<unsigned int>(seed));
                  52  std::mt19937 mersenne(std::time(nullptr));
                  53 
                  -
                  54  // Initializes and sets logger (if compiled with logging)
                  -
                  55  // See set_level function for levels.
                  -
                  56  sopt::logging::initialize();
                  -
                  57  sopt::logging::set_level("debug");
                  -
                  58  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  59  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  -
                  60  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  -
                  61 
                  -
                  62  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  63  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  -
                  64  sopt::LinearTransform<Vector> const sampling =
                  -
                  65  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  66  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  67  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  -
                  68 
                  -
                  69  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  -
                  70  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  -
                  71 
                  -
                  72  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  -
                  73  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  -
                  74 
                  -
                  75  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  -
                  76  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  77  auto constexpr snr = 30.0;
                  -
                  78  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  79  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  -
                  80 
                  -
                  81  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  82  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  83  Vector y(y0.size());
                  -
                  84  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  85  // Write dirty imagte to file
                  -
                  86  if (output != "none") {
                  -
                  87  Vector const dirty = sampling.adjoint() * y;
                  -
                  88  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  89  "dirty_" + output + ".tiff");
                  -
                  90  }
                  -
                  91 
                  -
                  92  sopt::t_real constexpr gamma = 0;
                  -
                  93  sopt::t_real const beta = sigma * sigma * 0.5;
                  -
                  94  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  -
                  95  auto fb = std::make_shared<sopt::algorithm::ImagingForwardBackward<Scalar>>(y);
                  -
                  96  fb->itermax(500)
                  -
                  97  .beta(beta) // stepsize
                  -
                  98  .sigma(sigma) // sigma
                  -
                  99  .gamma(gamma) // regularisation paramater
                  -
                  100  .relative_variation(1e-3)
                  -
                  101  .residual_tolerance(0)
                  -
                  102  .tight_frame(true)
                  -
                  103  .Phi(sampling);
                  -
                  104 
                  -
                  105  // Create a shared pointer to an instance of the L1GProximal class
                  -
                  106  // and set its properties
                  -
                  107  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  -
                  108  gp->l1_proximal_tolerance(1e-4)
                  -
                  109  .l1_proximal_nu(1)
                  -
                  110  .l1_proximal_itermax(50)
                  -
                  111  .l1_proximal_positivity_constraint(true)
                  -
                  112  .l1_proximal_real_constraint(true)
                  -
                  113  .Psi(psi);
                  -
                  114 
                  -
                  115  // Once the properties are set, inject it into the ImagingForwardBackward object
                  -
                  116  fb->g_proximal(gp);
                  -
                  117 
                  -
                  118  SOPT_HIGH_LOG("Starting Forward Backward");
                  -
                  119  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  -
                  120  // Here, we default to (y, Φx/ν - y)
                  -
                  121  auto l1_norm = [psi](const Vector &x) { return sopt::l1_norm(psi.adjoint() * x); };
                  -
                  122  const sopt::t_uint number_of_wavelet_coefficients = image.size();
                  -
                  123  auto joint_map = sopt::algorithm::JointMAP<sopt::algorithm::ImagingForwardBackward<Scalar>>(
                  -
                  124  fb, l1_norm, number_of_wavelet_coefficients)
                  -
                  125  .alpha(1)
                  -
                  126  .beta(1)
                  -
                  127  .k(1)
                  -
                  128  .relative_variation(1e-3)
                  -
                  129  .objective_variation(1e-3);
                  -
                  130  auto diagnostic = joint_map();
                  -
                  131  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  -
                  132  if (output != "none")
                  -
                  133  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  134  output + ".tiff");
                  -
                  135  // diagnostic should tell us the function converged
                  -
                  136  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  137  // diagnostic from the last call to the conjugate gradient.
                  -
                  138  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  54  // See set_level function for levels.
                  +
                  55  sopt::logging::set_level("debug");
                  +
                  56  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  57  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  +
                  58  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  +
                  59 
                  +
                  60  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  61  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  +
                  62  sopt::LinearTransform<Vector> const sampling =
                  +
                  63  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  64  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  65  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  +
                  66 
                  +
                  67  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  +
                  68  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  +
                  69 
                  +
                  70  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  +
                  71  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  +
                  72 
                  +
                  73  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  +
                  74  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  +
                  75  auto constexpr snr = 30.0;
                  +
                  76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  +
                  78 
                  +
                  79  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  80  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  81  Vector y(y0.size());
                  +
                  82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  83  // Write dirty imagte to file
                  +
                  84  if (output != "none") {
                  +
                  85  Vector const dirty = sampling.adjoint() * y;
                  +
                  86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  87  "dirty_" + output + ".tiff");
                  +
                  88  }
                  +
                  89 
                  +
                  90  sopt::t_real constexpr gamma = 0;
                  +
                  91  sopt::t_real const beta = sigma * sigma * 0.5;
                  +
                  92  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  +
                  93  auto fb = std::make_shared<sopt::algorithm::ImagingForwardBackward<Scalar>>(y);
                  +
                  94  fb->itermax(500)
                  +
                  95  .beta(beta) // stepsize
                  +
                  96  .sigma(sigma) // sigma
                  +
                  97  .gamma(gamma) // regularisation paramater
                  +
                  98  .relative_variation(1e-3)
                  +
                  99  .residual_tolerance(0)
                  +
                  100  .tight_frame(true)
                  +
                  101  .Phi(sampling);
                  +
                  102 
                  +
                  103  // Create a shared pointer to an instance of the L1GProximal class
                  +
                  104  // and set its properties
                  +
                  105  auto gp = std::make_shared<sopt::algorithm::L1GProximal<Scalar>>(false);
                  +
                  106  gp->l1_proximal_tolerance(1e-4)
                  +
                  107  .l1_proximal_nu(1)
                  +
                  108  .l1_proximal_itermax(50)
                  +
                  109  .l1_proximal_positivity_constraint(true)
                  +
                  110  .l1_proximal_real_constraint(true)
                  +
                  111  .Psi(psi);
                  +
                  112 
                  +
                  113  // Once the properties are set, inject it into the ImagingForwardBackward object
                  +
                  114  fb->g_proximal(gp);
                  +
                  115 
                  +
                  116  SOPT_HIGH_LOG("Starting Forward Backward");
                  +
                  117  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  +
                  118  // Here, we default to (y, Φx/ν - y)
                  +
                  119  auto l1_norm = [psi](const Vector &x) { return sopt::l1_norm(psi.adjoint() * x); };
                  +
                  120  const sopt::t_uint number_of_wavelet_coefficients = image.size();
                  +
                  121  auto joint_map = sopt::algorithm::JointMAP<sopt::algorithm::ImagingForwardBackward<Scalar>>(
                  +
                  122  fb, l1_norm, number_of_wavelet_coefficients)
                  +
                  123  .alpha(1)
                  +
                  124  .beta(1)
                  +
                  125  .k(1)
                  +
                  126  .relative_variation(1e-3)
                  +
                  127  .objective_variation(1e-3);
                  +
                  128  auto diagnostic = joint_map();
                  +
                  129  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  +
                  130  if (output != "none")
                  +
                  131  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  132  output + ".tiff");
                  +
                  133  // diagnostic should tell us the function converged
                  +
                  134  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  135  // diagnostic from the last call to the conjugate gradient.
                  +
                  136  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  137 
                  +
                  138  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  139 
                  -
                  140  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  -
                  141 
                  -
                  142  return 0;
                  -
                  143 }
                  +
                  140  return 0;
                  +
                  141 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::LinearTransform
                  Joins together direct and indirect operators.
                  Definition: linear_transform.h:30
                  sopt::LinearTransform::adjoint
                  LinearTransform< VECTOR > adjoint() const
                  Indirect transform.
                  Definition: linear_transform.h:79
                  @@ -234,11 +232,10 @@
                  joint_map.h
                  l1_g_proximal.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  sopt::logging::set_level
                  void set_level(const std::string &level)
                  Method to set the logging level of the default Log object.
                  Definition: logging.h:154
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  diff --git a/joint__map_8h.html b/joint__map_8h.html index 12174062d..e99e9933b 100644 --- a/joint__map_8h.html +++ b/joint__map_8h.html @@ -101,36 +101,37 @@
                  diff --git a/joint__map_8h__incl.map b/joint__map_8h__incl.map index bd64332c4..6ebcb4535 100644 --- a/joint__map_8h__incl.map +++ b/joint__map_8h__incl.map @@ -1,32 +1,33 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/joint__map_8h__incl.md5 b/joint__map_8h__incl.md5 index a00a80dac..5093cb26c 100644 --- a/joint__map_8h__incl.md5 +++ b/joint__map_8h__incl.md5 @@ -1 +1 @@ -e39924f64e5c815f2794a63dff1ab131 \ No newline at end of file +4737a1a792027505438ae74d7824342e \ No newline at end of file diff --git a/joint__map_8h__incl.png b/joint__map_8h__incl.png index d226ea3a3..c14b393c1 100644 Binary files a/joint__map_8h__incl.png and b/joint__map_8h__incl.png differ diff --git a/joint__map_8h_source.html b/joint__map_8h_source.html index 0742ebc9f..9f1aff048 100644 --- a/joint__map_8h_source.html +++ b/joint__map_8h_source.html @@ -223,10 +223,10 @@
                  imaging_forward_backward.h
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  +
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:211
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::t_real
                  double t_real
                  Root of the type hierarchy for real numbers.
                  Definition: types.h:17
                  sopt::t_uint
                  size_t t_uint
                  Root of the type hierarchy for unsigned integers.
                  Definition: types.h:15
                  diff --git a/l1__g__proximal_8h.html b/l1__g__proximal_8h.html index 3fdcd9ae5..019856d6c 100644 --- a/l1__g__proximal_8h.html +++ b/l1__g__proximal_8h.html @@ -103,36 +103,37 @@
                  diff --git a/l1__g__proximal_8h__incl.map b/l1__g__proximal_8h__incl.map index 005b64b6d..61fd9006f 100644 --- a/l1__g__proximal_8h__incl.map +++ b/l1__g__proximal_8h__incl.map @@ -1,32 +1,33 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/l1__g__proximal_8h__incl.md5 b/l1__g__proximal_8h__incl.md5 index 9d91038a3..6679cf997 100644 --- a/l1__g__proximal_8h__incl.md5 +++ b/l1__g__proximal_8h__incl.md5 @@ -1 +1 @@ -3adc05fd11ea6588bfbe5d1f8d00fa32 \ No newline at end of file +8897030deb060106aee2ca42ab05405c \ No newline at end of file diff --git a/l1__g__proximal_8h__incl.png b/l1__g__proximal_8h__incl.png index 9a34e8661..a3722de63 100644 Binary files a/l1__g__proximal_8h__incl.png and b/l1__g__proximal_8h__incl.png differ diff --git a/l1__g__proximal_8h_source.html b/l1__g__proximal_8h_source.html index 6c28574a8..9b3ebc5ff 100644 --- a/l1__g__proximal_8h_source.html +++ b/l1__g__proximal_8h_source.html @@ -256,7 +256,7 @@
                  l1_proximal.h
                  linear_transform.h
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  sopt::t_uint
                  size_t t_uint
                  Root of the type hierarchy for unsigned integers.
                  Definition: types.h:15
                  sopt::Vector
                  Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
                  A vector of a given type.
                  Definition: types.h:24
                  diff --git a/l1__proximal_8h.html b/l1__proximal_8h.html index 9fba70ffa..fc8812c12 100644 --- a/l1__proximal_8h.html +++ b/l1__proximal_8h.html @@ -98,28 +98,29 @@
                  diff --git a/l1__proximal_8h__incl.map b/l1__proximal_8h__incl.map index 54b3fdf9a..72ad70281 100644 --- a/l1__proximal_8h__incl.map +++ b/l1__proximal_8h__incl.map @@ -1,24 +1,25 @@ - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + diff --git a/l1__proximal_8h__incl.md5 b/l1__proximal_8h__incl.md5 index e98ba3b49..ef5248b1a 100644 --- a/l1__proximal_8h__incl.md5 +++ b/l1__proximal_8h__incl.md5 @@ -1 +1 @@ -2f5c3722897a01afb183f22c95eb85f7 \ No newline at end of file +89df40061c3facf7d8fc4b9b82a705a6 \ No newline at end of file diff --git a/l1__proximal_8h__incl.png b/l1__proximal_8h__incl.png index 35ccc0c0d..acfc452ae 100644 Binary files a/l1__proximal_8h__incl.png and b/l1__proximal_8h__incl.png differ diff --git a/l1__proximal_8h_source.html b/l1__proximal_8h_source.html index 7dc8d4ddb..c6c3b6656 100644 --- a/l1__proximal_8h_source.html +++ b/l1__proximal_8h_source.html @@ -537,10 +537,10 @@
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  -
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:17
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:211
                  +
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:213
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::proximal
                  Holds some standard proximals.
                  Definition: l1_proximal.h:17
                  diff --git a/l2__forward__backward_8h.html b/l2__forward__backward_8h.html index c7d4d724f..e1df8f8cc 100644 --- a/l2__forward__backward_8h.html +++ b/l2__forward__backward_8h.html @@ -102,34 +102,35 @@
                  diff --git a/l2__forward__backward_8h__incl.map b/l2__forward__backward_8h__incl.map index da61ed31f..f88389ef9 100644 --- a/l2__forward__backward_8h__incl.map +++ b/l2__forward__backward_8h__incl.map @@ -1,30 +1,31 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/l2__forward__backward_8h__incl.md5 b/l2__forward__backward_8h__incl.md5 index d8a5d9dc2..249fe73ff 100644 --- a/l2__forward__backward_8h__incl.md5 +++ b/l2__forward__backward_8h__incl.md5 @@ -1 +1 @@ -97d6ca00ecb32188735974c52a428c67 \ No newline at end of file +644f5c01737410f30b87cf39d6feda78 \ No newline at end of file diff --git a/l2__forward__backward_8h__incl.png b/l2__forward__backward_8h__incl.png index f699696d4..fc94d552a 100644 Binary files a/l2__forward__backward_8h__incl.png and b/l2__forward__backward_8h__incl.png differ diff --git a/l2__forward__backward_8h_source.html b/l2__forward__backward_8h_source.html index 4dd41af6a..6c76b48bc 100644 --- a/l2__forward__backward_8h_source.html +++ b/l2__forward__backward_8h_source.html @@ -418,8 +418,8 @@
                  SOPT_MACRO
                  #define SOPT_MACRO(NAME, TYPE)
                  Definition: l2_forward_backward.h:84
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  sopt::proximal::l2_norm
                  void l2_norm(Eigen::DenseBase< T0 > &out, typename real_type< typename T0::Scalar >::type gamma, Eigen::DenseBase< T1 > const &x)
                  Proximal of the l2 norm (note this is different from the l2 ball indicator function)
                  Definition: proximal.h:84
                  diff --git a/l2__inpainting_8cc.html b/l2__inpainting_8cc.html index 046d49287..be708b25d 100644 --- a/l2__inpainting_8cc.html +++ b/l2__inpainting_8cc.html @@ -87,6 +87,7 @@ #include <iostream>
                  #include <random>
                  #include <vector>
                  +#include <ctime>
                  #include "sopt/l2_forward_backward.h"
                  #include "sopt/logging.h"
                  #include "sopt/maths.h"
                  @@ -104,51 +105,53 @@
                  @@ -186,108 +189,106 @@

                  -

                  Definition at line 22 of file l2_inpainting.cc.

                  -
                  22  {
                  -
                  23  // Some type aliases for simplicity
                  -
                  24  using Scalar = double;
                  -
                  25  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  -
                  26  // type expected by Forward Backward
                  -
                  27  using Vector = sopt::Vector<Scalar>;
                  -
                  28  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  -
                  29  // type expected by Forward Backward
                  -
                  30  using Matrix = sopt::Matrix<Scalar>;
                  -
                  31  // Image - 2D array - A * x is a coefficient-wise multiplication
                  -
                  32  // Type expected by wavelets and image write/read functions
                  -
                  33  using Image = sopt::Image<Scalar>;
                  -
                  34 
                  -
                  35  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  -
                  36  std::string const output = argc == 3 ? argv[2] : "none";
                  -
                  37  if (argc > 3) {
                  -
                  38  std::cout << "Usage:\n"
                  -
                  39  "$ "
                  -
                  40  << argv[0]
                  -
                  41  << " [input [output]]\n\n"
                  -
                  42  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  -
                  43  "- output: filename pattern for output image\n";
                  -
                  44  exit(0);
                  -
                  45  }
                  -
                  46  // Set up random numbers for C and C++
                  -
                  47  auto const seed = std::time(nullptr);
                  -
                  48  std::srand(static_cast<unsigned int>(seed));
                  -
                  49  std::mt19937 mersenne(std::time(nullptr));
                  -
                  50 
                  -
                  51  // Initializes and sets logger (if compiled with logging)
                  +

                  Definition at line 23 of file l2_inpainting.cc.

                  +
                  23  {
                  +
                  24  // Some type aliases for simplicity
                  +
                  25  using Scalar = double;
                  +
                  26  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  +
                  27  // type expected by Forward Backward
                  +
                  28  using Vector = sopt::Vector<Scalar>;
                  +
                  29  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  +
                  30  // type expected by Forward Backward
                  +
                  31  using Matrix = sopt::Matrix<Scalar>;
                  +
                  32  // Image - 2D array - A * x is a coefficient-wise multiplication
                  +
                  33  // Type expected by wavelets and image write/read functions
                  +
                  34  using Image = sopt::Image<Scalar>;
                  +
                  35 
                  +
                  36  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  +
                  37  std::string const output = argc == 3 ? argv[2] : "none";
                  +
                  38  if (argc > 3) {
                  +
                  39  std::cout << "Usage:\n"
                  +
                  40  "$ "
                  +
                  41  << argv[0]
                  +
                  42  << " [input [output]]\n\n"
                  +
                  43  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  +
                  44  "- output: filename pattern for output image\n";
                  +
                  45  exit(0);
                  +
                  46  }
                  +
                  47  // Set up random numbers for C and C++
                  +
                  48  auto const seed = std::time(nullptr);
                  +
                  49  std::srand(static_cast<unsigned int>(seed));
                  +
                  50  std::mt19937 mersenne(std::time(nullptr));
                  +
                  51 
                  52  // See set_level function for levels.
                  -
                  53  sopt::logging::initialize();
                  -
                  54  sopt::logging::set_level("debug");
                  -
                  55  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  56  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  -
                  57  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  -
                  58 
                  -
                  59  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  60  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  -
                  61  sopt::LinearTransform<Vector> const sampling =
                  -
                  62  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  63  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  64  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  -
                  65 
                  -
                  66  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  -
                  67  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  -
                  68 
                  -
                  69  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  -
                  70  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  -
                  71 
                  -
                  72  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  -
                  73  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  74  auto constexpr snr = 30.0;
                  -
                  75  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  76  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  -
                  77 
                  -
                  78  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  79  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  80  Vector y(y0.size());
                  -
                  81  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  82  // Write dirty imagte to file
                  -
                  83  if (output != "none") {
                  -
                  84  Vector const dirty = sampling.adjoint() * y;
                  -
                  85  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  86  "dirty_" + output + ".tiff");
                  -
                  87  }
                  -
                  88  constexpr sopt::t_real x_sigma = 1.;
                  -
                  89  sopt::t_real constexpr gamma = 1. / (x_sigma * x_sigma * 2);
                  -
                  90  sopt::t_real const beta = sigma * sigma * 0.5;
                  -
                  91  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  -
                  92  auto const fb = sopt::algorithm::L2ForwardBackward<Scalar>(y)
                  -
                  93  .itermax(500)
                  -
                  94  .beta(beta) // stepsize
                  -
                  95  .sigma(sigma) // sigma
                  -
                  96  .gamma(gamma) // regularisation paramater
                  -
                  97  .relative_variation(1e-3)
                  -
                  98  .residual_tolerance(0)
                  -
                  99  .tight_frame(true)
                  -
                  100  .Phi(sampling);
                  -
                  101 
                  -
                  102  SOPT_HIGH_LOG("Starting Forward Backward");
                  -
                  103  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  -
                  104  // Here, we default to (y, Φx/ν - y)
                  -
                  105  Vector const init_map = Vector::Ones(image.size()) * x_sigma;
                  -
                  106  Vector const init_res = y - (sampling * init_map);
                  -
                  107  const std::tuple<Vector, Vector> warm_start = {init_map, init_res};
                  -
                  108  auto const diagnostic = fb();
                  -
                  109  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  -
                  110 
                  -
                  111  if (output != "none")
                  -
                  112  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  113  output + ".tiff");
                  -
                  114  // diagnostic should tell us the function converged
                  -
                  115  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  116  // diagnostic from the last call to the conjugate gradient.
                  -
                  117  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  -
                  118 
                  -
                  119  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  -
                  120 
                  -
                  121  return 0;
                  -
                  122 }
                  +
                  53  sopt::logging::set_level("debug");
                  +
                  54  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  55  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  +
                  56  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  +
                  57 
                  +
                  58  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  59  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  +
                  60  sopt::LinearTransform<Vector> const sampling =
                  +
                  61  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  62  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  63  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  +
                  64 
                  +
                  65  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  +
                  66  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  +
                  67 
                  +
                  68  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  +
                  69  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  +
                  70 
                  +
                  71  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  +
                  72  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  +
                  73  auto constexpr snr = 30.0;
                  +
                  74  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  75  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  +
                  76 
                  +
                  77  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  78  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  79  Vector y(y0.size());
                  +
                  80  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  81  // Write dirty imagte to file
                  +
                  82  if (output != "none") {
                  +
                  83  Vector const dirty = sampling.adjoint() * y;
                  +
                  84  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  85  "dirty_" + output + ".tiff");
                  +
                  86  }
                  +
                  87  constexpr sopt::t_real x_sigma = 1.;
                  +
                  88  sopt::t_real constexpr gamma = 1. / (x_sigma * x_sigma * 2);
                  +
                  89  sopt::t_real const beta = sigma * sigma * 0.5;
                  +
                  90  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  +
                  91  auto const fb = sopt::algorithm::L2ForwardBackward<Scalar>(y)
                  +
                  92  .itermax(500)
                  +
                  93  .beta(beta) // stepsize
                  +
                  94  .sigma(sigma) // sigma
                  +
                  95  .gamma(gamma) // regularisation paramater
                  +
                  96  .relative_variation(1e-3)
                  +
                  97  .residual_tolerance(0)
                  +
                  98  .tight_frame(true)
                  +
                  99  .Phi(sampling);
                  +
                  100 
                  +
                  101  SOPT_HIGH_LOG("Starting Forward Backward");
                  +
                  102  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  +
                  103  // Here, we default to (y, Φx/ν - y)
                  +
                  104  Vector const init_map = Vector::Ones(image.size()) * x_sigma;
                  +
                  105  Vector const init_res = y - (sampling * init_map);
                  +
                  106  const std::tuple<Vector, Vector> warm_start = {init_map, init_res};
                  +
                  107  auto const diagnostic = fb();
                  +
                  108  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  +
                  109 
                  +
                  110  if (output != "none")
                  +
                  111  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  112  output + ".tiff");
                  +
                  113  // diagnostic should tell us the function converged
                  +
                  114  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  115  // diagnostic from the last call to the conjugate gradient.
                  +
                  116  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  117 
                  +
                  118  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  +
                  119 
                  +
                  120  return 0;
                  +
                  121 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::LinearTransform
                  Joins together direct and indirect operators.
                  Definition: linear_transform.h:30
                  sopt::LinearTransform::adjoint
                  LinearTransform< VECTOR > adjoint() const
                  Indirect transform.
                  Definition: linear_transform.h:79
                  @@ -296,10 +297,9 @@

                  sopt::algorithm::L2ForwardBackward::Phi
                  L2ForwardBackward &::type Phi(ARGS &&... args)
                  Definition: l2_forward_backward.h:197

                  mersenne
                  std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  +
                  sopt::logging::set_level
                  void set_level(const std::string &level)
                  Method to set the logging level of the default Log object.
                  Definition: logging.h:154
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  @@ -315,7 +315,7 @@

                  Vector
                  sopt::Vector< Scalar > Vector
                  Definition: inpainting.cc:28

                  Matrix
                  sopt::Matrix< Scalar > Matrix
                  Definition: inpainting.cc:29

                  -

                  References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), sopt::logging::initialize(), mersenne(), sopt::algorithm::L2ForwardBackward< SCALAR >::Phi(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

                  +

                  References sopt::LinearTransform< VECTOR >::adjoint(), sopt::dirty(), sopt::epsilon(), sopt::wavelets::factory(), mersenne(), sopt::algorithm::L2ForwardBackward< SCALAR >::Phi(), sopt::notinstalled::read_standard_tiff(), sopt::logging::set_level(), sopt::sigma(), SOPT_HIGH_LOG, SOPT_LOW_LOG, and sopt::utilities::write_tiff().

                  diff --git a/l2__inpainting_8cc__incl.map b/l2__inpainting_8cc__incl.map index bc9b2acd7..c2bee5490 100644 --- a/l2__inpainting_8cc__incl.map +++ b/l2__inpainting_8cc__incl.map @@ -1,47 +1,49 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/l2__inpainting_8cc__incl.md5 b/l2__inpainting_8cc__incl.md5 index 9ae23f57a..c143f86d4 100644 --- a/l2__inpainting_8cc__incl.md5 +++ b/l2__inpainting_8cc__incl.md5 @@ -1 +1 @@ -c178eaa93358d6c13e98d1efb68a3690 \ No newline at end of file +3b67e3275aca81140085291ebd927052 \ No newline at end of file diff --git a/l2__inpainting_8cc__incl.png b/l2__inpainting_8cc__incl.png index e17b4f605..0b97a799c 100644 Binary files a/l2__inpainting_8cc__incl.png and b/l2__inpainting_8cc__incl.png differ diff --git a/l2__inpainting_8cc_source.html b/l2__inpainting_8cc_source.html index 66251a62c..2bede99fc 100644 --- a/l2__inpainting_8cc_source.html +++ b/l2__inpainting_8cc_source.html @@ -85,122 +85,121 @@
                  4 #include <iostream>
                  5 #include <random>
                  6 #include <vector>
                  -
                  7 
                  -
                  8 #include "sopt/l2_forward_backward.h"
                  -
                  9 #include "sopt/logging.h"
                  -
                  10 #include "sopt/maths.h"
                  -
                  11 #include "sopt/relative_variation.h"
                  -
                  12 #include "sopt/sampling.h"
                  -
                  13 #include "sopt/types.h"
                  -
                  14 #include "sopt/utilities.h"
                  -
                  15 #include "sopt/wavelets.h"
                  -
                  16 // This header is not part of the installed sopt interface
                  -
                  17 // It is only present in tests
                  -
                  18 #include "tools_for_tests/directories.h"
                  -
                  19 #include "tools_for_tests/tiffwrappers.h"
                  -
                  20 
                  -
                  21 // \min_{x} ||\Psi^Tx||_1 \quad \mbox{s.t.} \quad ||y - Ax||_2 < \epsilon and x \geq 0
                  -
                  22 int main(int argc, char const **argv) {
                  -
                  23  // Some type aliases for simplicity
                  -
                  24  using Scalar = double;
                  -
                  25  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  -
                  26  // type expected by Forward Backward
                  -
                  27  using Vector = sopt::Vector<Scalar>;
                  -
                  28  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  -
                  29  // type expected by Forward Backward
                  -
                  30  using Matrix = sopt::Matrix<Scalar>;
                  -
                  31  // Image - 2D array - A * x is a coefficient-wise multiplication
                  -
                  32  // Type expected by wavelets and image write/read functions
                  -
                  33  using Image = sopt::Image<Scalar>;
                  -
                  34 
                  -
                  35  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  -
                  36  std::string const output = argc == 3 ? argv[2] : "none";
                  -
                  37  if (argc > 3) {
                  -
                  38  std::cout << "Usage:\n"
                  -
                  39  "$ "
                  -
                  40  << argv[0]
                  -
                  41  << " [input [output]]\n\n"
                  -
                  42  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  -
                  43  "- output: filename pattern for output image\n";
                  -
                  44  exit(0);
                  -
                  45  }
                  -
                  46  // Set up random numbers for C and C++
                  -
                  47  auto const seed = std::time(nullptr);
                  -
                  48  std::srand(static_cast<unsigned int>(seed));
                  -
                  49  std::mt19937 mersenne(std::time(nullptr));
                  -
                  50 
                  -
                  51  // Initializes and sets logger (if compiled with logging)
                  +
                  7 #include <ctime>
                  +
                  8 
                  +
                  9 #include "sopt/l2_forward_backward.h"
                  +
                  10 #include "sopt/logging.h"
                  +
                  11 #include "sopt/maths.h"
                  +
                  12 #include "sopt/relative_variation.h"
                  +
                  13 #include "sopt/sampling.h"
                  +
                  14 #include "sopt/types.h"
                  +
                  15 #include "sopt/utilities.h"
                  +
                  16 #include "sopt/wavelets.h"
                  +
                  17 // This header is not part of the installed sopt interface
                  +
                  18 // It is only present in tests
                  +
                  19 #include "tools_for_tests/directories.h"
                  +
                  20 #include "tools_for_tests/tiffwrappers.h"
                  +
                  21 
                  +
                  22 // \min_{x} ||\Psi^Tx||_1 \quad \mbox{s.t.} \quad ||y - Ax||_2 < \epsilon and x \geq 0
                  +
                  23 int main(int argc, char const **argv) {
                  +
                  24  // Some type aliases for simplicity
                  +
                  25  using Scalar = double;
                  +
                  26  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  +
                  27  // type expected by Forward Backward
                  +
                  28  using Vector = sopt::Vector<Scalar>;
                  +
                  29  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  +
                  30  // type expected by Forward Backward
                  +
                  31  using Matrix = sopt::Matrix<Scalar>;
                  +
                  32  // Image - 2D array - A * x is a coefficient-wise multiplication
                  +
                  33  // Type expected by wavelets and image write/read functions
                  +
                  34  using Image = sopt::Image<Scalar>;
                  +
                  35 
                  +
                  36  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  +
                  37  std::string const output = argc == 3 ? argv[2] : "none";
                  +
                  38  if (argc > 3) {
                  +
                  39  std::cout << "Usage:\n"
                  +
                  40  "$ "
                  +
                  41  << argv[0]
                  +
                  42  << " [input [output]]\n\n"
                  +
                  43  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  +
                  44  "- output: filename pattern for output image\n";
                  +
                  45  exit(0);
                  +
                  46  }
                  +
                  47  // Set up random numbers for C and C++
                  +
                  48  auto const seed = std::time(nullptr);
                  +
                  49  std::srand(static_cast<unsigned int>(seed));
                  +
                  50  std::mt19937 mersenne(std::time(nullptr));
                  +
                  51 
                  52  // See set_level function for levels.
                  -
                  53  sopt::logging::initialize();
                  -
                  54  sopt::logging::set_level("debug");
                  -
                  55  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  56  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  -
                  57  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  -
                  58 
                  -
                  59  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  60  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  -
                  61  sopt::LinearTransform<Vector> const sampling =
                  -
                  62  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  63  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  64  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  -
                  65 
                  -
                  66  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  -
                  67  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  -
                  68 
                  -
                  69  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  -
                  70  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  -
                  71 
                  -
                  72  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  -
                  73  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  74  auto constexpr snr = 30.0;
                  -
                  75  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  76  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  -
                  77 
                  -
                  78  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  79  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  80  Vector y(y0.size());
                  -
                  81  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  82  // Write dirty imagte to file
                  -
                  83  if (output != "none") {
                  -
                  84  Vector const dirty = sampling.adjoint() * y;
                  -
                  85  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  86  "dirty_" + output + ".tiff");
                  -
                  87  }
                  -
                  88  constexpr sopt::t_real x_sigma = 1.;
                  -
                  89  sopt::t_real constexpr gamma = 1. / (x_sigma * x_sigma * 2);
                  -
                  90  sopt::t_real const beta = sigma * sigma * 0.5;
                  -
                  91  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  -
                  92  auto const fb = sopt::algorithm::L2ForwardBackward<Scalar>(y)
                  -
                  93  .itermax(500)
                  -
                  94  .beta(beta) // stepsize
                  -
                  95  .sigma(sigma) // sigma
                  -
                  96  .gamma(gamma) // regularisation paramater
                  -
                  97  .relative_variation(1e-3)
                  -
                  98  .residual_tolerance(0)
                  -
                  99  .tight_frame(true)
                  -
                  100  .Phi(sampling);
                  -
                  101 
                  -
                  102  SOPT_HIGH_LOG("Starting Forward Backward");
                  -
                  103  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  -
                  104  // Here, we default to (y, Φx/ν - y)
                  -
                  105  Vector const init_map = Vector::Ones(image.size()) * x_sigma;
                  -
                  106  Vector const init_res = y - (sampling * init_map);
                  -
                  107  const std::tuple<Vector, Vector> warm_start = {init_map, init_res};
                  -
                  108  auto const diagnostic = fb();
                  -
                  109  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  -
                  110 
                  -
                  111  if (output != "none")
                  -
                  112  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  113  output + ".tiff");
                  -
                  114  // diagnostic should tell us the function converged
                  -
                  115  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  116  // diagnostic from the last call to the conjugate gradient.
                  -
                  117  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  -
                  118 
                  -
                  119  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  -
                  120 
                  -
                  121  return 0;
                  -
                  122 }
                  +
                  53  sopt::logging::set_level("debug");
                  +
                  54  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  55  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  +
                  56  SOPT_HIGH_LOG("Image size: {} x {} = {}", image.cols(), image.rows(), image.size());
                  +
                  57 
                  +
                  58  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  59  sopt::t_uint const nmeasure = std::floor(0.5 * image.size());
                  +
                  60  sopt::LinearTransform<Vector> const sampling =
                  +
                  61  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  62  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  63  auto const wavelet = sopt::wavelets::factory("DB8", 4);
                  +
                  64 
                  +
                  65  // sopt::wavelets::SARA const wavelet{std::make_tuple("db1", 4u), std::make_tuple("db2", 4u),
                  +
                  66  // std::make_tuple("db3", 4u), std::make_tuple("db4", 4u)};
                  +
                  67 
                  +
                  68  auto const psi = sopt::linear_transform<Scalar>(wavelet, image.rows(), image.cols());
                  +
                  69  SOPT_LOW_LOG("Wavelet coefficients: {}", (psi.adjoint() * image).size());
                  +
                  70 
                  +
                  71  SOPT_HIGH_LOG("Computing Forward Backward parameters");
                  +
                  72  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  +
                  73  auto constexpr snr = 30.0;
                  +
                  74  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  75  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  +
                  76 
                  +
                  77  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  78  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  79  Vector y(y0.size());
                  +
                  80  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  81  // Write dirty imagte to file
                  +
                  82  if (output != "none") {
                  +
                  83  Vector const dirty = sampling.adjoint() * y;
                  +
                  84  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  85  "dirty_" + output + ".tiff");
                  +
                  86  }
                  +
                  87  constexpr sopt::t_real x_sigma = 1.;
                  +
                  88  sopt::t_real constexpr gamma = 1. / (x_sigma * x_sigma * 2);
                  +
                  89  sopt::t_real const beta = sigma * sigma * 0.5;
                  +
                  90  SOPT_HIGH_LOG("Creating Foward Backward Functor");
                  +
                  91  auto const fb = sopt::algorithm::L2ForwardBackward<Scalar>(y)
                  +
                  92  .itermax(500)
                  +
                  93  .beta(beta) // stepsize
                  +
                  94  .sigma(sigma) // sigma
                  +
                  95  .gamma(gamma) // regularisation paramater
                  +
                  96  .relative_variation(1e-3)
                  +
                  97  .residual_tolerance(0)
                  +
                  98  .tight_frame(true)
                  +
                  99  .Phi(sampling);
                  +
                  100 
                  +
                  101  SOPT_HIGH_LOG("Starting Forward Backward");
                  +
                  102  // Alternatively, forward-backward can be called with a tuple (x, residual) as argument
                  +
                  103  // Here, we default to (y, Φx/ν - y)
                  +
                  104  Vector const init_map = Vector::Ones(image.size()) * x_sigma;
                  +
                  105  Vector const init_res = y - (sampling * init_map);
                  +
                  106  const std::tuple<Vector, Vector> warm_start = {init_map, init_res};
                  +
                  107  auto const diagnostic = fb();
                  +
                  108  SOPT_HIGH_LOG("Forward backward returned {}", diagnostic.good);
                  +
                  109 
                  +
                  110  if (output != "none")
                  +
                  111  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  112  output + ".tiff");
                  +
                  113  // diagnostic should tell us the function converged
                  +
                  114  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  115  // diagnostic from the last call to the conjugate gradient.
                  +
                  116  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  117 
                  +
                  118  SOPT_HIGH_LOG("SOPT-Forward Backward converged in {} iterations", diagnostic.niters);
                  +
                  119 
                  +
                  120  return 0;
                  +
                  121 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::LinearTransform
                  Joins together direct and indirect operators.
                  Definition: linear_transform.h:30
                  sopt::LinearTransform::adjoint
                  LinearTransform< VECTOR > adjoint() const
                  Indirect transform.
                  Definition: linear_transform.h:79
                  @@ -210,13 +209,12 @@
                  mersenne
                  std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  l2_forward_backward.h
                  -
                  main
                  int main(int argc, char const **argv)
                  Definition: l2_inpainting.cc:22
                  +
                  main
                  int main(int argc, char const **argv)
                  Definition: l2_inpainting.cc:23
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  sopt::logging::set_level
                  void set_level(const std::string &level)
                  Method to set the logging level of the default Log object.
                  Definition: logging.h:154
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  diff --git a/l2__primal__dual_8h.html b/l2__primal__dual_8h.html index 0794590e9..4e1be15c7 100644 --- a/l2__primal__dual_8h.html +++ b/l2__primal__dual_8h.html @@ -102,34 +102,35 @@
                  diff --git a/l2__primal__dual_8h__incl.map b/l2__primal__dual_8h__incl.map index 9b063d1b0..1d410c303 100644 --- a/l2__primal__dual_8h__incl.map +++ b/l2__primal__dual_8h__incl.map @@ -1,30 +1,31 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/l2__primal__dual_8h__incl.md5 b/l2__primal__dual_8h__incl.md5 index 3d06ee34e..e06cd7658 100644 --- a/l2__primal__dual_8h__incl.md5 +++ b/l2__primal__dual_8h__incl.md5 @@ -1 +1 @@ -e1e4554f3855af20bc2750834c931f02 \ No newline at end of file +97ff14168b6d4ed352eee428b3559f03 \ No newline at end of file diff --git a/l2__primal__dual_8h__incl.png b/l2__primal__dual_8h__incl.png index 7d395c07c..f7bf99001 100644 Binary files a/l2__primal__dual_8h__incl.png and b/l2__primal__dual_8h__incl.png differ diff --git a/l2__primal__dual_8h_source.html b/l2__primal__dual_8h_source.html index a805a1346..a4ee8b9cb 100644 --- a/l2__primal__dual_8h_source.html +++ b/l2__primal__dual_8h_source.html @@ -479,8 +479,8 @@
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  sopt::proximal::l2_norm
                  void l2_norm(Eigen::DenseBase< T0 > &out, typename real_type< typename T0::Scalar >::type gamma, Eigen::DenseBase< T1 > const &x)
                  Proximal of the l2 norm (note this is different from the l2 ball indicator function)
                  Definition: proximal.h:84
                  sopt::linear_transform
                  LinearTransform< VECTOR > linear_transform(OperatorFunction< VECTOR > const &direct, OperatorFunction< VECTOR > const &indirect, std::array< t_int, 3 > const &sizes={{1, 1, 0}})
                  Definition: linear_transform.h:101
                  diff --git a/linear__transform_8cc.html b/linear__transform_8cc.html index 387762f2d..1aa6fc3b6 100644 --- a/linear__transform_8cc.html +++ b/linear__transform_8cc.html @@ -92,29 +92,30 @@ diff --git a/linear__transform_8cc__incl.map b/linear__transform_8cc__incl.map index 780047a94..4f66eaa32 100644 --- a/linear__transform_8cc__incl.map +++ b/linear__transform_8cc__incl.map @@ -1,25 +1,26 @@ - + - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/linear__transform_8cc__incl.md5 b/linear__transform_8cc__incl.md5 index a70df23e0..6cb966c85 100644 --- a/linear__transform_8cc__incl.md5 +++ b/linear__transform_8cc__incl.md5 @@ -1 +1 @@ -6a8706597801453aac1be5707756bb3f \ No newline at end of file +05945f7e6ab2dc6229030122f7c5d4c1 \ No newline at end of file diff --git a/linear__transform_8cc__incl.png b/linear__transform_8cc__incl.png index b8fe68df9..708ed04ad 100644 Binary files a/linear__transform_8cc__incl.png and b/linear__transform_8cc__incl.png differ diff --git a/linear__transform_8h.html b/linear__transform_8h.html index d529e271c..82c0a105d 100644 --- a/linear__transform_8h.html +++ b/linear__transform_8h.html @@ -100,26 +100,27 @@
                  diff --git a/linear__transform_8h__incl.map b/linear__transform_8h__incl.map index 99b9e5baa..7102d27f8 100644 --- a/linear__transform_8h__incl.map +++ b/linear__transform_8h__incl.map @@ -1,22 +1,23 @@ - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + diff --git a/linear__transform_8h__incl.md5 b/linear__transform_8h__incl.md5 index fe08bea44..e925dc89e 100644 --- a/linear__transform_8h__incl.md5 +++ b/linear__transform_8h__incl.md5 @@ -1 +1 @@ -8b7bc10905e04ef89e03e7a14772751d \ No newline at end of file +4db4e04d4e79c8dd82b2624a5b5c7bbe \ No newline at end of file diff --git a/linear__transform_8h__incl.png b/linear__transform_8h__incl.png index cbb299d61..352051b96 100644 Binary files a/linear__transform_8h__incl.png and b/linear__transform_8h__incl.png differ diff --git a/logging_8cc.html b/logging_8cc.html new file mode 100644 index 000000000..3b654384f --- /dev/null +++ b/logging_8cc.html @@ -0,0 +1,137 @@ + + + + + + + +SOPT: /home/runner/work/sopt/sopt/cpp/sopt/logging.cc File Reference + + + + + + + + + + + + +
                  +
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                  SOPT +
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                  +Namespaces | +Functions
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                  logging.cc File Reference
                  +
                  +
                  +
                  #include "sopt/logging.h"
                  +#include <ctime>
                  +#include <iostream>
                  +#include <ostream>
                  +#include <unistd.h>
                  +
                  + + Include dependency graph for logging.cc:
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                  Go to the source code of this file.

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                   sopt
                   
                   sopt::logging
                   
                  + + + + + + +

                  +Functions

                  void sopt::logging::_updateLevels (const Log::LevelMap &defaultLevels, Log::LogMap &existingLogs)
                   
                  ostream & sopt::logging::operator<< (Log &log, int level)
                   Streaming output to a logger must have a Log::Level/int as its first argument. More...
                   
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                  + + diff --git a/logging_8cc__incl.map b/logging_8cc__incl.map new file mode 100644 index 000000000..1aeaba5a9 --- /dev/null +++ b/logging_8cc__incl.map @@ -0,0 +1,16 @@ + + + + + + + + + + + + + + + + diff --git a/logging_8cc__incl.md5 b/logging_8cc__incl.md5 new file mode 100644 index 000000000..b2a3bc704 --- /dev/null +++ b/logging_8cc__incl.md5 @@ -0,0 +1 @@ +5a709de0893e29e134fc043fb4efe5ba \ No newline at end of file diff --git a/logging_8cc__incl.png b/logging_8cc__incl.png new file mode 100644 index 000000000..ebc90c0d3 Binary files /dev/null and b/logging_8cc__incl.png differ diff --git a/logging_8cc_source.html b/logging_8cc_source.html new file mode 100644 index 000000000..e4c5edb23 --- /dev/null +++ b/logging_8cc_source.html @@ -0,0 +1,304 @@ + + + + + + + +SOPT: /home/runner/work/sopt/sopt/cpp/sopt/logging.cc Source File + + + + + + + + + + + + +
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                  Sparse OPTimisation
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                  logging.cc
                  +
                  +
                  +Go to the documentation of this file.
                  1 #include "sopt/logging.h"
                  +
                  2 #include <ctime>
                  +
                  3 #include <iostream>
                  +
                  4 #include <ostream>
                  +
                  5 #include <unistd.h>
                  +
                  6 
                  +
                  7 using namespace std;
                  +
                  8 
                  +
                  9 namespace sopt::logging {
                  +
                  10 
                  +
                  11 
                  +
                  12  thread_local Log::LogMap Log::existingLogs;
                  +
                  13  thread_local Log::LevelMap Log::defaultLevels;
                  +
                  14  bool Log::showTimestamp = false;
                  +
                  15  bool Log::showLogLevel = true;
                  +
                  16  bool Log::showLoggerName = true;
                  +
                  17  bool Log::useShellColors = true;
                  +
                  18  const int Log::end_color;
                  +
                  19 
                  +
                  20 
                  +
                  21  Log::Log(const string& name)
                  +
                  22  : _name(name), _level(info) { }
                  +
                  23 
                  +
                  24 
                  +
                  25  Log::Log(const string& name, int level)
                  +
                  26  : _name(name), _level(level) { }
                  +
                  27 
                  +
                  28 
                  +
                  30  void _updateLevels(const Log::LevelMap& defaultLevels, Log::LogMap& existingLogs) {
                  +
                  32  for (Log::LevelMap::const_iterator lev = defaultLevels.begin(); lev != defaultLevels.end(); ++lev) {
                  +
                  33  for (Log::LogMap::iterator log = existingLogs.begin(); log != existingLogs.end(); ++log) {
                  +
                  34  if (log->first.find(lev->first) == 0) {
                  +
                  35  log->second.setLevel(lev->second);
                  +
                  36  }
                  +
                  37  }
                  +
                  38  }
                  +
                  39  }
                  +
                  40 
                  +
                  41 
                  +
                  42  void Log::setLevel(const string& name, int level) {
                  +
                  43  defaultLevels[name] = level;
                  +
                  44  //cout << name << " -> " << level << '\n';
                  +
                  45  _updateLevels(defaultLevels, existingLogs);
                  +
                  46  }
                  +
                  47 
                  +
                  48 
                  +
                  49  void Log::setLevels(const LevelMap& logLevels) {
                  +
                  50  for (LevelMap::const_iterator lev = logLevels.begin(); lev != logLevels.end(); ++lev) {
                  +
                  51  defaultLevels[lev->first] = lev->second;
                  +
                  52  }
                  +
                  53  _updateLevels(defaultLevels, existingLogs);
                  +
                  54  }
                  +
                  55 
                  +
                  56 
                  +
                  57  Log& Log::getLog(const string& name) {
                  +
                  58  auto theLog = existingLogs.find(name);
                  +
                  59  if (theLog == existingLogs.end()) {
                  +
                  60  int level = info;
                  +
                  61  // Try running through all parent classes to find an existing level
                  +
                  62  string tmpname = name;
                  +
                  63  bool triedAllParents = false;
                  +
                  64  while (! triedAllParents) {
                  +
                  65  // Is there a default level?
                  +
                  66  if (defaultLevels.find(tmpname) != defaultLevels.end()) {
                  +
                  67  level = defaultLevels.find(tmpname)->second;
                  +
                  68  break;
                  +
                  69  }
                  +
                  70  // Is there already such a logger? (NB. tmpname != name in later iterations)
                  +
                  71  if (existingLogs.find(tmpname) != existingLogs.end()) {
                  +
                  72  level = existingLogs.find(tmpname)->second.getLevel();
                  +
                  73  break;
                  +
                  74  }
                  +
                  75  // Crop the string back to the next parent level
                  +
                  76  size_t lastDot = tmpname.find_last_of(".");
                  +
                  77  if (lastDot != string::npos) {
                  +
                  78  tmpname = tmpname.substr(0, lastDot);
                  +
                  79  } else {
                  +
                  80  triedAllParents = true;
                  +
                  81  }
                  +
                  82  }
                  +
                  83  // for (LevelMap::const_iterator l = defaultLevels.begin(); l != defaultLevels.end(); ++l) {
                  +
                  84  //
                  +
                  85  // }
                  +
                  86 
                  +
                  87  // emplace returns pair<iterator,bool>
                  +
                  88  auto result = existingLogs.emplace(name, Log(name, level));
                  +
                  89  theLog = result.first;
                  +
                  90  }
                  +
                  91  return theLog->second;
                  +
                  92  }
                  +
                  93 
                  +
                  94 
                  +
                  95  string Log::getLevelName(int level) {
                  +
                  96  switch(level) {
                  +
                  97  case trace:
                  +
                  98  return "trace";
                  +
                  99  case debug:
                  +
                  100  return "debug";
                  +
                  101  case info:
                  +
                  102  return "info";
                  +
                  103  case warn:
                  +
                  104  return "warn";
                  +
                  105  case error:
                  +
                  106  return "error";
                  +
                  107  case critical:
                  +
                  108  return "critical";
                  +
                  109  default:
                  +
                  110  return "";
                  +
                  111  }
                  +
                  112  }
                  +
                  113 
                  +
                  114 
                  +
                  115  string Log::getColorCode(int level) {
                  +
                  116  // Skip codes if
                  +
                  117  if (!Log::useShellColors) return "";
                  +
                  118  const static bool IS_TTY = isatty(1);
                  +
                  119  if (!IS_TTY) return "";
                  +
                  120 
                  +
                  121  static const ColorCodes TTY_CODES = {
                  +
                  122  {trace, "\033[0;36m"},
                  +
                  123  {debug, "\033[0;34m"},
                  +
                  124  {info, "\033[0;32m"},
                  +
                  125  {warn, "\033[0;33m"},
                  +
                  126  {error, "\033[0;31m"},
                  +
                  127  {critical, "\033[0;31m"},
                  +
                  128  {end_color, "\033[0m"} // end-color code
                  +
                  129  };
                  +
                  130  try {
                  +
                  131  return TTY_CODES.at(level);
                  +
                  132  } catch (...) {
                  +
                  133  return "";
                  +
                  134  }
                  +
                  135  }
                  +
                  136 
                  +
                  137 
                  +
                  138  Log::Level Log::getLevelFromName(const string& level) {
                  +
                  139  if (level == "trace") return trace;
                  +
                  140  if (level == "debug") return debug;
                  +
                  141  if (level == "info") return info;
                  +
                  142  if (level == "warn") return warn;
                  +
                  143  if (level == "error") return error;
                  +
                  144  if (level == "critical") return critical;
                  +
                  145  SOPT_THROW("Couldn't create a log level from string '" + level + "'");
                  +
                  146  }
                  +
                  147 
                  +
                  148 
                  +
                  149  string Log::formatMessage(int level, const string& message) {
                  +
                  150  string out;
                  +
                  151  out += getColorCode(level);
                  +
                  152 
                  +
                  153  if (Log::showLoggerName) {
                  +
                  154  out += getName();
                  +
                  155  //out += ": ";
                  +
                  156  }
                  +
                  157 
                  +
                  158  if (Log::showLogLevel) {
                  +
                  159  out += Log::getLevelName(level);
                  +
                  160  out += " ";
                  +
                  161  }
                  +
                  162 
                  +
                  163  if (Log::showTimestamp) {
                  +
                  164  time_t rawtime;
                  +
                  165  time(&rawtime);
                  +
                  166  char* timestr = ctime(&rawtime);
                  +
                  167  timestr[24] = ' ';
                  +
                  168  out += timestr;
                  +
                  169  out += " ";
                  +
                  170  }
                  +
                  171 
                  +
                  172  out += getColorCode(end_color);
                  +
                  173  out += " ";
                  +
                  174  out += message;
                  +
                  175 
                  +
                  176  return out;
                  +
                  177  }
                  +
                  178 
                  +
                  179 
                  +
                  180  void Log::log(int level, const string& message) {
                  +
                  181  if (isActive(level)) {
                  +
                  182  if (level > warning)
                  +
                  183  cerr << formatMessage(level, message) << '\n';
                  +
                  184  else
                  +
                  185  cout << formatMessage(level, message) << '\n';
                  +
                  186  }
                  +
                  187  }
                  +
                  188 
                  +
                  189 
                  +
                  190  ostream& operator<<(Log& log, int level) {
                  +
                  191  if (log.isActive(level)) {
                  +
                  192  if (level > Log::warning) {
                  +
                  193  cerr << log.formatMessage(level, "");
                  +
                  194  return cerr;
                  +
                  195  } else {
                  +
                  196  cout << log.formatMessage(level, "");
                  +
                  197  return cout;
                  +
                  198  }
                  +
                  199  } else {
                  +
                  200  static ostream devNull(nullptr);
                  +
                  201  return devNull;
                  +
                  202  }
                  +
                  203  }
                  +
                  204 
                  +
                  205 }
                  +
                  206 
                  +
                  sopt::logging::Log
                  Logging system for controlled & formatted writing to stdout.
                  Definition: logging.h:14
                  +
                  sopt::logging::Log::LevelMap
                  std::map< std::string, int > LevelMap
                  Typedef for a collection of named log levels.
                  Definition: logging.h:33
                  +
                  sopt::logging::Log::isActive
                  bool isActive(int level) const
                  Will this log level produce output on this logger at the moment?
                  Definition: logging.h:118
                  +
                  sopt::logging::Log::LogMap
                  std::map< std::string, Log > LogMap
                  Typedef for a collection of named logs.
                  Definition: logging.h:30
                  +
                  sopt::logging::Log::getLevel
                  int getLevel() const
                  Get the priority level of this logger.
                  Definition: logging.h:90
                  +
                  sopt::logging::Log::Level
                  Level
                  Log priority levels.
                  Definition: logging.h:18
                  +
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  + + +
                  sopt::logging::getLog
                  Log & getLog()
                  Access method to default Log object.
                  Definition: logging.h:151
                  +
                  sopt::logging::operator<<
                  ostream & operator<<(Log &log, int level)
                  Streaming output to a logger must have a Log::Level/int as its first argument.
                  Definition: logging.cc:190
                  +
                  sopt::logging::_updateLevels
                  void _updateLevels(const Log::LevelMap &defaultLevels, Log::LogMap &existingLogs)
                  Definition: logging.cc:30
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                  -
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                  -#include <memory>
                  -#include <string>
                  -
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                  #define SOPT_LOG_(...)   ((void)0)
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                  std::shared_ptr< int > sopt::logging::initialize (std::string const &name="")
                   Initializes a logger. More...
                   
                  std::shared_ptr< int > sopt::logging::initialize ()
                   
                  std::shared_ptr< int > sopt::logging::get (std::string const &name="")
                   Returns shared pointer to logger or null if it does not exist. More...
                   
                  std::shared_ptr< int > sopt::logging::get ()
                   
                  void sopt::logging::set_level (std::string const &level, std::string const &name)
                   Sets loggin level. More...
                   
                  void sopt::logging::set_level (std::string const &)
                   
                  bool sopt::logging::has_level (std::string const &, std::string const &)
                   
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                  Definition at line 22 of file logging.disabled.h.

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                  SOPT -
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                  Sparse OPTimisation
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                  -
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                  -
                  -
                  -
                  logging.disabled.h
                  -
                  -
                  -Go to the documentation of this file.
                  1 #ifndef SOPT_LOGGING_DISABLED_H
                  -
                  2 #define SOPT_LOGGING_DISABLED_H
                  -
                  3 
                  -
                  4 #include "sopt/config.h"
                  -
                  5 #include <memory>
                  -
                  6 #include <string>
                  -
                  7 
                  -
                  8 namespace sopt::logging {
                  -
                  10 const std::string name_prefix = "sopt::";
                  -
                  11 
                  -
                  12 inline std::shared_ptr<int> initialize(std::string const &) { return nullptr; }
                  -
                  13 inline std::shared_ptr<int> initialize() { return nullptr; }
                  -
                  14 inline std::shared_ptr<int> get(std::string const &) { return nullptr; }
                  -
                  15 inline std::shared_ptr<int> get() { return nullptr; }
                  -
                  16 inline void set_level(std::string const &, std::string const &){}
                  -
                  17 inline void set_level(std::string const &){}
                  -
                  18 inline bool has_level(std::string const &, std::string const &) { return false; }
                  -
                  19 } // namespace sopt::logging
                  -
                  20 
                  -
                  22 #define SOPT_LOG_(...) ((void)0)
                  -
                  23 #endif
                  - -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::get
                  std::shared_ptr< int > get(std::string const &)
                  Returns shared pointer to logger or null if it does not exist.
                  Definition: logging.disabled.h:14
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  -
                  sopt::logging::name_prefix
                  const std::string name_prefix
                  Name of the sopt logger.
                  Definition: logging.disabled.h:10
                  -
                  sopt::logging::has_level
                  bool has_level(std::string const &, std::string const &)
                  Definition: logging.disabled.h:18
                  -
                  - -
                  -Generated by doxygen 1.9.1 -
                  - - diff --git a/logging_8enabled_8h.html b/logging_8enabled_8h.html deleted file mode 100644 index 274e02daa..000000000 --- a/logging_8enabled_8h.html +++ /dev/null @@ -1,255 +0,0 @@ - - - - - - - -SOPT: /home/runner/work/sopt/sopt/cpp/sopt/logging.enabled.h File Reference - - - - - - - - - - - - -
                  -
                  - - - - - - - -
                  -
                  SOPT -
                  -
                  Sparse OPTimisation
                  -
                  -
                  - - - - - - - - -
                  -
                  - - -
                  - -
                  - - -
                  -
                  -
                  -Namespaces | -Macros | -Typedefs | -Functions
                  -
                  -
                  logging.enabled.h File Reference
                  -
                  -
                  -
                  #include "sopt/config.h"
                  -#include <memory>
                  -#include <string>
                  -#include <Eigen/Core>
                  -#include <spdlog/fmt/ostr.h>
                  -#include <spdlog/spdlog.h>
                  -#include <spdlog/sinks/stdout_sinks.h>
                  -#include "sopt/exception.h"
                  -
                  - + Include dependency graph for logging.enabled.h:
                  -
                  -
                  - -
                  -

                  Go to the source code of this file.

                  - - - - - - -

                  -Namespaces

                   sopt
                   
                   sopt::logging
                   
                  - - - - - - - - -

                  -Macros

                  #define SOPT_MACRO(LEVEL)    if (level == #LEVEL) logger->set_level(spdlog::level::LEVEL)
                   
                  #define SOPT_MACRO(LEVEL)    if (level == #LEVEL) return logger->level() >= spdlog::level::LEVEL
                   
                  #define SOPT_LOG_(NAME, TYPE, ...)
                   \macro For internal use only More...
                   
                  - - - -

                  -Typedefs

                  using spdlogPtr = std::shared_ptr< spdlog::logger >
                   
                  - - - - - - - - - - - - -

                  -Functions

                  void sopt::logging::set_level (std::string const &level, std::string const &name)
                   Sets loggin level. More...
                   
                  std::shared_ptr< int > sopt::logging::initialize (std::string const &name="")
                   Initializes a logger. More...
                   
                  std::shared_ptr< int > sopt::logging::get (std::string const &name="")
                   Returns shared pointer to logger or null if it does not exist. More...
                   
                  bool sopt::logging::has_level (std::string const &, std::string const &)
                   
                  -

                  Macro Definition Documentation

                  - -

                  ◆ SOPT_LOG_

                  - -
                  -
                  - - - - - - - - - - - - - - - - - - - - - - - - -
                  #define SOPT_LOG_( NAME,
                   TYPE,
                   ... 
                  )
                  -
                  -Value:
                  if (auto sopt_logging_##__func__##_##__LINE__ = sopt::logging::get(NAME)) \
                  -
                  sopt_logging_##__func__##_##__LINE__->TYPE(__VA_ARGS__)
                  -
                  sopt::logging::get
                  std::shared_ptr< int > get(std::string const &)
                  Returns shared pointer to logger or null if it does not exist.
                  Definition: logging.disabled.h:14
                  -
                  -

                  \macro For internal use only

                  - -

                  Definition at line 86 of file logging.enabled.h.

                  - -
                  -
                  - -

                  ◆ SOPT_MACRO [1/2]

                  - -
                  -
                  - - - - - - - - -
                  #define SOPT_MACRO( LEVEL)    if (level == #LEVEL) logger->set_level(spdlog::level::LEVEL)
                  -
                  - -
                  -
                  - -

                  ◆ SOPT_MACRO [2/2]

                  - -
                  -
                  - - - - - - - - -
                  #define SOPT_MACRO( LEVEL)    if (level == #LEVEL) return logger->level() >= spdlog::level::LEVEL
                  -
                  - -
                  -
                  -

                  Typedef Documentation

                  - -

                  ◆ spdlogPtr

                  - -
                  -
                  - - - - -
                  using spdlogPtr = std::shared_ptr<spdlog::logger>
                  -
                  - -

                  Definition at line 13 of file logging.enabled.h.

                  - -
                  -
                  -
                  - -
                  -Generated by doxygen 1.9.1 -
                  - - diff --git a/logging_8enabled_8h__incl.map b/logging_8enabled_8h__incl.map deleted file mode 100644 index a0f7a2aa1..000000000 --- a/logging_8enabled_8h__incl.map +++ /dev/null @@ -1,13 +0,0 @@ - - - - - - - - - - - - - diff --git a/logging_8enabled_8h__incl.md5 b/logging_8enabled_8h__incl.md5 deleted file mode 100644 index a1aaaef35..000000000 --- a/logging_8enabled_8h__incl.md5 +++ /dev/null @@ -1 +0,0 @@ -25fe856fb051bbe8fd014e46ae465ba6 \ No newline at end of file diff --git a/logging_8enabled_8h__incl.png b/logging_8enabled_8h__incl.png deleted file mode 100644 index 9a2dc6c71..000000000 Binary files a/logging_8enabled_8h__incl.png and /dev/null differ diff --git a/logging_8enabled_8h_source.html b/logging_8enabled_8h_source.html deleted file mode 100644 index de0f5efb9..000000000 --- a/logging_8enabled_8h_source.html +++ /dev/null @@ -1,177 +0,0 @@ - - - - - - - -SOPT: /home/runner/work/sopt/sopt/cpp/sopt/logging.enabled.h Source File - - - - - - - - - - - - -
                  -
                  - - - - - - - -
                  -
                  SOPT -
                  -
                  Sparse OPTimisation
                  -
                  -
                  - - - - - - - - -
                  -
                  - - -
                  - -
                  - - -
                  -
                  -
                  -
                  logging.enabled.h
                  -
                  -
                  -Go to the documentation of this file.
                  1 #ifndef SOPT_LOGGING_ENABLED_H
                  -
                  2 #define SOPT_LOGGING_ENABLED_H
                  -
                  3 
                  -
                  4 #include "sopt/config.h"
                  -
                  5 #include <memory>
                  -
                  6 #include <string>
                  -
                  7 #include <Eigen/Core>
                  -
                  8 #include <spdlog/fmt/ostr.h>
                  -
                  9 #include <spdlog/spdlog.h>
                  -
                  10 #include <spdlog/sinks/stdout_sinks.h>
                  -
                  11 #include "sopt/exception.h"
                  -
                  12 
                  -
                  13 using spdlogPtr = std::shared_ptr<spdlog::logger>;
                  -
                  14 
                  -
                  15 #if FMT_VERSION >= 90000
                  -
                  16  template <typename... Args>
                  -
                  17  struct fmt::formatter< Eigen::Transpose<Args...> > : fmt::ostream_formatter {};
                  -
                  18 
                  -
                  19  template <typename T>
                  -
                  20  struct fmt::formatter<std::complex<T>> : fmt::ostream_formatter {};
                  -
                  21 #endif
                  -
                  22 
                  -
                  23 namespace sopt::logging {
                  -
                  24 
                  -
                  25  void set_level(std::string const &level, std::string const &name = "");
                  -
                  26 
                  -
                  29  inline spdlogPtr initialize(std::string const &name = "") {
                  -
                  30  const std::string loggerName = default_logger_name() + name;
                  -
                  31  const spdlogPtr result = spdlog::stdout_logger_mt(loggerName);
                  -
                  32  if (!spdlog::get(loggerName)) spdlog::register_logger(result);
                  -
                  33  set_level(default_logging_level(), name);
                  -
                  34  return result;
                  -
                  35  }
                  -
                  36 
                  -
                  38  inline spdlogPtr get(std::string const &name = "") {
                  -
                  39  return spdlog::get(default_logger_name() + name);
                  -
                  40  }
                  -
                  41 
                  -
                  51  inline void set_level(std::string const &level, std::string const &name) {
                  -
                  52  const spdlogPtr logger = get(name);
                  -
                  53  if (not logger) SOPT_THROW("No logger by the name of ") << name << ".\n";
                  -
                  54  #define SOPT_MACRO(LEVEL) \
                  -
                  55  if (level == #LEVEL) logger->set_level(spdlog::level::LEVEL)
                  -
                  56  SOPT_MACRO(trace);
                  -
                  57  else SOPT_MACRO(debug);
                  -
                  58  else SOPT_MACRO(info);
                  -
                  59  else SOPT_MACRO(warn);
                  -
                  60  else SOPT_MACRO(err);
                  -
                  61  else SOPT_MACRO(critical);
                  -
                  62  else SOPT_MACRO(off);
                  -
                  63  #undef SOPT_MACRO
                  -
                  64  else SOPT_THROW("Unknown logging level ") << level << "\n";
                  -
                  65  }
                  -
                  66 
                  -
                  67  inline bool has_level(std::string const &level, std::string const &name = "") {
                  -
                  68  const spdlogPtr logger = get(name);
                  -
                  69  if (not logger) return false;
                  -
                  70 
                  -
                  71  #define SOPT_MACRO(LEVEL) \
                  -
                  72  if (level == #LEVEL) return logger->level() >= spdlog::level::LEVEL
                  -
                  73  SOPT_MACRO(trace);
                  -
                  74  else SOPT_MACRO(debug);
                  -
                  75  else SOPT_MACRO(info);
                  -
                  76  else SOPT_MACRO(warn);
                  -
                  77  else SOPT_MACRO(err);
                  -
                  78  else SOPT_MACRO(critical);
                  -
                  79  else SOPT_MACRO(off);
                  -
                  80  #undef SOPT_MACRO
                  -
                  81  else SOPT_THROW("Unknown logging level ") << level << "\n";
                  -
                  82  }
                  -
                  83 } // namespace sopt::logging
                  -
                  84 
                  -
                  86 #define SOPT_LOG_(NAME, TYPE, ...) \
                  -
                  87  if (auto sopt_logging_##__func__##_##__LINE__ = sopt::logging::get(NAME)) \
                  -
                  88  sopt_logging_##__func__##_##__LINE__->TYPE(__VA_ARGS__)
                  -
                  89 
                  -
                  90 #endif
                  - -
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  -
                  SOPT_MACRO
                  #define SOPT_MACRO(LEVEL)
                  -
                  spdlogPtr
                  std::shared_ptr< spdlog::logger > spdlogPtr
                  Definition: logging.enabled.h:13
                  - - -
                  sopt::logging::set_level
                  void set_level(std::string const &, std::string const &)
                  Sets loggin level.
                  Definition: logging.disabled.h:16
                  -
                  sopt::logging::get
                  std::shared_ptr< int > get(std::string const &)
                  Returns shared pointer to logger or null if it does not exist.
                  Definition: logging.disabled.h:14
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  -
                  sopt::logging::has_level
                  bool has_level(std::string const &, std::string const &)
                  Definition: logging.disabled.h:18
                  -
                  sopt::default_logger_name
                  std::string default_logger_name()
                  Default logger name.
                  Definition: config.in.h:41
                  -
                  sopt::default_logging_level
                  std::string default_logging_level()
                  Default logging level.
                  Definition: config.in.h:39
                  -
                  - -
                  -Generated by doxygen 1.9.1 -
                  - - diff --git a/logging_8h.html b/logging_8h.html index 4f97a7d24..f46a4ad25 100644 --- a/logging_8h.html +++ b/logging_8h.html @@ -76,13 +76,19 @@
                  -Macros
                  +Classes | +Namespaces | +Macros | +Functions
                  logging.h File Reference
                  #include "sopt/config.h"
                  -#include "sopt/logging.disabled.h"
                  +#include "sopt/exception.h"
                  +#include <map>
                  +#include <memory>
                  +#include <cstring>
                  + Include dependency graph for logging.h:
                  @@ -90,11 +96,15 @@
                  @@ -104,89 +114,129 @@

                  Go to the source code of this file.

                  + + + + +

                  +Classes

                  class  sopt::logging::Log
                   Logging system for controlled & formatted writing to stdout. More...
                   
                  + + + + + +

                  +Namespaces

                   sopt
                   
                   sopt::logging
                   
                  - + + + + + + + - + - + - + - + - + - + - + - + +

                  Macros

                  #define SOPT_NOTICE(...)   SOPT_LOG_(, critical, __VA_ARGS__)
                  #define SOPT_MSG_LVL(lvl, ...)
                   Neat CPU-conserving logging macros. Use by preference! More...
                   
                  #define SOPT_LOG_(TYPE, ...)    SOPT_MSG_LVL(sopt::logging::Log::TYPE, __VA_ARGS__)
                   \macro For internal use only More...
                   
                  #define SOPT_NOTICE(...)   SOPT_LOG_(critical, __VA_ARGS__)
                   \macro Normal but significant condition or critical error More...
                   
                  #define SOPT_ERROR(...)   SOPT_LOG_(, error, __VA_ARGS__)
                  #define SOPT_ERROR(...)   SOPT_LOG_(error, __VA_ARGS__)
                   \macro Something is definitely wrong, algorithm exits More...
                   
                  #define SOPT_WARN(...)   SOPT_LOG_(, warn, __VA_ARGS__)
                  #define SOPT_WARN(...)   SOPT_LOG_(warn, __VA_ARGS__)
                   \macro Something might be going wrong More...
                   
                  #define SOPT_INFO(...)   SOPT_LOG_(, info, __VA_ARGS__)
                  #define SOPT_INFO(...)   SOPT_LOG_(info, __VA_ARGS__)
                   \macro Verbose informational message about normal condition More...
                   
                  #define SOPT_DEBUG(...)   SOPT_LOG_(, debug, __VA_ARGS__)
                  #define SOPT_DEBUG(...)   SOPT_LOG_(debug, __VA_ARGS__)
                   \macro Output some debugging More...
                   
                  #define SOPT_TRACE(...)   SOPT_LOG_(, trace, __VA_ARGS__)
                  #define SOPT_TRACE(...)   SOPT_LOG_(trace, __VA_ARGS__)
                   
                  #define SOPT_HIGH_LOG(...)   SOPT_LOG_(, critical, __VA_ARGS__)
                  #define SOPT_HIGH_LOG(...)   SOPT_LOG_(critical, __VA_ARGS__)
                   High priority message. More...
                   
                  #define SOPT_MEDIUM_LOG(...)   SOPT_LOG_(, info, __VA_ARGS__)
                  #define SOPT_MEDIUM_LOG(...)   SOPT_LOG_(info, __VA_ARGS__)
                   Medium priority message. More...
                   
                  #define SOPT_LOW_LOG(...)   SOPT_LOG_(, debug, __VA_ARGS__)
                  #define SOPT_LOW_LOG(...)   SOPT_LOG_(debug, __VA_ARGS__)
                   Low priority message. More...
                   
                  + + + + + + + + + + + + + + + + + + +

                  +Functions

                  ostream & sopt::logging::operator<< (Log &log, int level)
                   Streaming output to a logger must have a Log::Level/int as its first argument. More...
                   
                  Log & sopt::logging::getLog ()
                   Access method to default Log object. More...
                   
                  void sopt::logging::set_level (const std::string &level)
                   Method to set the logging level of the default Log object. More...
                   
                  template<typename Arg >
                  void sopt::logging::applyFormat (std::stringstream &ss, char *&pos, Arg &&arg)
                   
                  template<typename... Args>
                  std::string sopt::logging::mkFormattedString (const char *txt, Args &&... args)
                   Helper method to construct formatted string. More...
                   
                  const std::string & sopt::logging::mkFormattedString (const std::string &txt)
                   

                  Macro Definition Documentation

                  @@ -200,14 +250,14 @@

                    ...) -    SOPT_LOG_(, debug, __VA_ARGS__) +    SOPT_LOG_(debug, __VA_ARGS__)

                  \macro Output some debugging

                  -

                  Definition at line 21 of file logging.h.

                  +

                  Definition at line 217 of file logging.h.

                  @@ -222,14 +272,14 @@

                    ...) -    SOPT_LOG_(, error, __VA_ARGS__) +    SOPT_LOG_(error, __VA_ARGS__)

                  \macro Something is definitely wrong, algorithm exits

                  -

                  Definition at line 15 of file logging.h.

                  +

                  Definition at line 211 of file logging.h.

                  @@ -244,14 +294,14 @@

                    ...) -    SOPT_LOG_(, critical, __VA_ARGS__) +    SOPT_LOG_(critical, __VA_ARGS__)

                  High priority message.

                  -

                  Definition at line 27 of file logging.h.

                  +

                  Definition at line 223 of file logging.h.

                  @@ -266,14 +316,14 @@

                    ...) -    SOPT_LOG_(, info, __VA_ARGS__) +    SOPT_LOG_(info, __VA_ARGS__)

                  \macro Verbose informational message about normal condition

                  -

                  Definition at line 19 of file logging.h.

                  +

                  Definition at line 215 of file logging.h.

                  @@ -288,14 +338,14 @@

                    ...) -    SOPT_LOG_(, debug, __VA_ARGS__) +    SOPT_LOG_(debug, __VA_ARGS__)

                  Low priority message.

                  -

                  Definition at line 31 of file logging.h.

                  +

                  Definition at line 227 of file logging.h.

                  @@ -310,14 +360,14 @@

                    ...) -    SOPT_LOG_(, info, __VA_ARGS__) +    SOPT_LOG_(info, __VA_ARGS__)

                  Medium priority message.

                  -

                  Definition at line 29 of file logging.h.

                  +

                  Definition at line 225 of file logging.h.

                  @@ -332,14 +382,14 @@

                    ...) -    SOPT_LOG_(, critical, __VA_ARGS__) +    SOPT_LOG_(critical, __VA_ARGS__)

                  \macro Normal but significant condition or critical error

                  -

                  Definition at line 13 of file logging.h.

                  +

                  Definition at line 209 of file logging.h.

                  @@ -354,14 +404,14 @@

                    ...) -    SOPT_LOG_(, trace, __VA_ARGS__) +    SOPT_LOG_(trace, __VA_ARGS__)

                  \macro Output internal values of no interest to anyone

                  Except maybe when debugging.

                  -

                  Definition at line 24 of file logging.h.

                  +

                  Definition at line 220 of file logging.h.

                  @@ -376,14 +426,14 @@

                    ...) -    SOPT_LOG_(, warn, __VA_ARGS__) +    SOPT_LOG_(warn, __VA_ARGS__)

                  \macro Something might be going wrong

                  -

                  Definition at line 17 of file logging.h.

                  +

                  Definition at line 213 of file logging.h.

                  diff --git a/logging_8h__dep__incl.map b/logging_8h__dep__incl.map index a729292b9..03cb64804 100644 --- a/logging_8h__dep__incl.map +++ b/logging_8h__dep__incl.map @@ -1,52 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/logging_8h__dep__incl.md5 b/logging_8h__dep__incl.md5 index 262df8613..79609d9f1 100644 --- a/logging_8h__dep__incl.md5 +++ b/logging_8h__dep__incl.md5 @@ -1 +1 @@ -0b8989e04d1380682f2eac69d9bfb761 \ No newline at end of file +2e158c97ef5803530710946091bfa1bd \ No newline at end of file diff --git a/logging_8h__dep__incl.png b/logging_8h__dep__incl.png index 491b0ef99..06c163727 100644 Binary files a/logging_8h__dep__incl.png and b/logging_8h__dep__incl.png differ diff --git a/logging_8h__incl.map b/logging_8h__incl.map index 0d8a4b013..133fdff00 100644 --- a/logging_8h__incl.map +++ b/logging_8h__incl.map @@ -1,7 +1,11 @@ - + - - - + + + + + + + diff --git a/logging_8h__incl.md5 b/logging_8h__incl.md5 index b986887c3..cfdcb6917 100644 --- a/logging_8h__incl.md5 +++ b/logging_8h__incl.md5 @@ -1 +1 @@ -2357a0831830f2e687a6fb85edd023b7 \ No newline at end of file +22183964a635c379efa165aa02e638b6 \ No newline at end of file diff --git a/logging_8h__incl.png b/logging_8h__incl.png index 8a82b3c9b..62c3713b0 100644 Binary files a/logging_8h__incl.png and b/logging_8h__incl.png differ diff --git a/logging_8h_source.html b/logging_8h_source.html index 3fa6be4ac..eeba94f64 100644 --- a/logging_8h_source.html +++ b/logging_8h_source.html @@ -83,26 +83,209 @@
                  2 #define SOPT_LOGGING_H
                  3 
                  4 #include "sopt/config.h"
                  -
                  5 
                  -
                  6 #ifdef SOPT_DO_LOGGING
                  -
                  7 #include "sopt/logging.enabled.h"
                  -
                  8 #else
                  -
                  9 #include "sopt/logging.disabled.h"
                  -
                  10 #endif
                  -
                  11 
                  -
                  13 #define SOPT_NOTICE(...) SOPT_LOG_(, critical, __VA_ARGS__)
                  -
                  15 #define SOPT_ERROR(...) SOPT_LOG_(, error, __VA_ARGS__)
                  -
                  17 #define SOPT_WARN(...) SOPT_LOG_(, warn, __VA_ARGS__)
                  -
                  19 #define SOPT_INFO(...) SOPT_LOG_(, info, __VA_ARGS__)
                  -
                  21 #define SOPT_DEBUG(...) SOPT_LOG_(, debug, __VA_ARGS__)
                  -
                  24 #define SOPT_TRACE(...) SOPT_LOG_(, trace, __VA_ARGS__)
                  -
                  25 
                  -
                  27 #define SOPT_HIGH_LOG(...) SOPT_LOG_(, critical, __VA_ARGS__)
                  -
                  29 #define SOPT_MEDIUM_LOG(...) SOPT_LOG_(, info, __VA_ARGS__)
                  -
                  31 #define SOPT_LOW_LOG(...) SOPT_LOG_(, debug, __VA_ARGS__)
                  -
                  32 #endif
                  - - +
                  5 #include "sopt/exception.h"
                  +
                  6 
                  +
                  7 #include <map>
                  +
                  8 #include <memory>
                  +
                  9 #include <cstring>
                  +
                  10 
                  +
                  11 namespace sopt::logging {
                  +
                  12 
                  +
                  14 class Log {
                  +
                  15 public:
                  +
                  16 
                  +
                  18  enum Level {
                  +
                  19  trace = 0,
                  +
                  20  debug = 10,
                  +
                  21  info = 20,
                  +
                  22  warn = 30, warning = 30,
                  +
                  23  error = 40,
                  +
                  24  critical = 50, always = 50
                  +
                  25  };
                  +
                  26  static const int end_color{-10};
                  +
                  27 
                  +
                  28 
                  +
                  30  using LogMap = std::map<std::string, Log>;
                  +
                  31 
                  +
                  33  using LevelMap = std::map<std::string, int>;
                  +
                  34 
                  +
                  36  using ColorCodes = std::map<int, std::string>;
                  +
                  37 
                  +
                  38 
                  +
                  39 private:
                  +
                  40 
                  +
                  42  thread_local static LogMap existingLogs;
                  +
                  43 
                  +
                  45  thread_local static LevelMap defaultLevels;
                  +
                  46 
                  +
                  48  static bool showTimestamp;
                  +
                  49 
                  +
                  51  static bool showLogLevel;
                  +
                  52 
                  +
                  54  static bool showLoggerName;
                  +
                  55 
                  +
                  57  static bool useShellColors;
                  +
                  58 
                  +
                  59 
                  +
                  60 public:
                  +
                  61 
                  +
                  63  static void setLevel(const std::string& name, int level);
                  +
                  64  static void setLevels(const LevelMap& logLevels);
                  +
                  65 
                  +
                  66 protected:
                  +
                  67 
                  +
                  70 
                  +
                  72  Log(const std::string& name);
                  +
                  73 
                  +
                  75  Log(const std::string& name, int level);
                  +
                  76 
                  +
                  78 
                  +
                  80  static std::string getColorCode(int level);
                  +
                  81 
                  +
                  82 
                  +
                  83 public:
                  +
                  84 
                  +
                  87  static Log& getLog(const std::string& name);
                  +
                  88 
                  +
                  90  int getLevel() const {
                  +
                  91  return _level;
                  +
                  92  }
                  +
                  93 
                  +
                  95  Log& setLevel(int level) {
                  +
                  96  _level = level;
                  +
                  97  return *this;
                  +
                  98  }
                  +
                  99 
                  +
                  101  static Level getLevelFromName(const std::string& level);
                  +
                  102 
                  +
                  104  static std::string getLevelName(int level);
                  +
                  105 
                  +
                  107  std::string getName() const {
                  +
                  108  return _name;
                  +
                  109  }
                  +
                  110 
                  +
                  112  Log& setName(const std::string& name) {
                  +
                  113  _name = name;
                  +
                  114  return *this;
                  +
                  115  }
                  +
                  116 
                  +
                  118  bool isActive(int level) const {
                  +
                  119  return (level >= _level);
                  +
                  120  }
                  +
                  121 
                  +
                  122 
                  +
                  123 private:
                  +
                  124 
                  +
                  126  std::string _name;
                  +
                  127 
                  +
                  129  int _level;
                  +
                  130 
                  +
                  131 protected:
                  +
                  132 
                  +
                  134  void log(int level, const std::string& message);
                  +
                  135 
                  +
                  137  std::string formatMessage(int level, const std::string& message);
                  +
                  138 
                  +
                  139 public:
                  +
                  140 
                  +
                  142  friend std::ostream& operator<<(Log& log, int level);
                  +
                  143 
                  +
                  144 };
                  +
                  145 
                  +
                  146 
                  +
                  148 std::ostream& operator<<(Log& log, int level);
                  +
                  149 
                  +
                  151 inline Log& getLog() { return Log::getLog("sopt::"); }
                  +
                  152 
                  +
                  154 inline void set_level(const std::string &level) {
                  +
                  155  getLog().setLevel(Log::getLevelFromName(level));
                  +
                  156 }
                  +
                  157 
                  +
                  158 
                  +
                  161 template <typename Arg>
                  +
                  162 void applyFormat(std::stringstream& ss, char*& pos, Arg&& arg) {
                  +
                  163  char* delim = strstr(pos, "{}");
                  +
                  164  if (delim != NULL) {
                  +
                  165  ss << std::string(pos, delim-pos) << std::forward<Arg>(arg);
                  +
                  166  pos = delim + 2;
                  +
                  167  }
                  +
                  168  else {
                  +
                  169  SOPT_THROW("Insufficient placeholders for number of arguments!");
                  +
                  170  }
                  +
                  171 }
                  +
                  172 
                  +
                  174 template <typename... Args>
                  +
                  175 inline std::string mkFormattedString(const char* txt, Args&& ... args) {
                  +
                  176  std::string mys = txt;
                  +
                  177  std::stringstream rtn;
                  +
                  178  char* pos = (char*)txt;
                  +
                  179  ((void)applyFormat(rtn, pos, std::forward<Args>(args)), ...);
                  +
                  180  rtn << std::string(pos);
                  +
                  181  return rtn.str();
                  +
                  182 }
                  +
                  183 
                  +
                  184 inline const std::string& mkFormattedString(const std::string& txt) { return txt; }
                  +
                  185 
                  +
                  188 
                  +
                  192 #define SOPT_MSG_LVL(lvl, ...) \
                  +
                  193  do { \
                  +
                  194  if (sopt::logging::getLog().isActive(lvl)) { \
                  +
                  195  sopt::logging::getLog() << lvl << sopt::logging::mkFormattedString(__VA_ARGS__) << '\n'; \
                  +
                  196  } \
                  +
                  197  } while (0)
                  +
                  198 
                  +
                  200 #define SOPT_LOG_(TYPE, ...) \
                  +
                  201  SOPT_MSG_LVL(sopt::logging::Log::TYPE, __VA_ARGS__)
                  +
                  202 
                  +
                  203 
                  +
                  205 
                  +
                  206 }
                  +
                  207 
                  +
                  209 #define SOPT_NOTICE(...) SOPT_LOG_(critical, __VA_ARGS__)
                  +
                  211 #define SOPT_ERROR(...) SOPT_LOG_(error, __VA_ARGS__)
                  +
                  213 #define SOPT_WARN(...) SOPT_LOG_(warn, __VA_ARGS__)
                  +
                  215 #define SOPT_INFO(...) SOPT_LOG_(info, __VA_ARGS__)
                  +
                  217 #define SOPT_DEBUG(...) SOPT_LOG_(debug, __VA_ARGS__)
                  +
                  220 #define SOPT_TRACE(...) SOPT_LOG_(trace, __VA_ARGS__)
                  +
                  221 
                  +
                  223 #define SOPT_HIGH_LOG(...) SOPT_LOG_(critical, __VA_ARGS__)
                  +
                  225 #define SOPT_MEDIUM_LOG(...) SOPT_LOG_(info, __VA_ARGS__)
                  +
                  227 #define SOPT_LOW_LOG(...) SOPT_LOG_(debug, __VA_ARGS__)
                  +
                  228 
                  +
                  229 #endif
                  +
                  sopt::logging::Log
                  Logging system for controlled & formatted writing to stdout.
                  Definition: logging.h:14
                  +
                  sopt::logging::Log::LevelMap
                  std::map< std::string, int > LevelMap
                  Typedef for a collection of named log levels.
                  Definition: logging.h:33
                  +
                  sopt::logging::Log::getLog
                  static Log & getLog(const std::string &name)
                  Definition: logging.cc:57
                  +
                  sopt::logging::Log::getLevelFromName
                  static Level getLevelFromName(const std::string &level)
                  Get a log level enum from a string.
                  Definition: logging.cc:138
                  +
                  sopt::logging::Log::getLevelName
                  static std::string getLevelName(int level)
                  Get the std::string representation of a log level.
                  Definition: logging.cc:95
                  +
                  sopt::logging::Log::end_color
                  static const int end_color
                  Special "level-like" code to end coloring.
                  Definition: logging.h:26
                  +
                  sopt::logging::Log::operator<<
                  friend std::ostream & operator<<(Log &log, int level)
                  The streaming operator can use Log's internals.
                  Definition: logging.cc:190
                  +
                  sopt::logging::Log::isActive
                  bool isActive(int level) const
                  Will this log level produce output on this logger at the moment?
                  Definition: logging.h:118
                  +
                  sopt::logging::Log::LogMap
                  std::map< std::string, Log > LogMap
                  Typedef for a collection of named logs.
                  Definition: logging.h:30
                  +
                  sopt::logging::Log::getLevel
                  int getLevel() const
                  Get the priority level of this logger.
                  Definition: logging.h:90
                  +
                  sopt::logging::Log::ColorCodes
                  std::map< int, std::string > ColorCodes
                  Typedef for a collection of shell color codes, accessed by log level.
                  Definition: logging.h:36
                  +
                  sopt::logging::Log::Level
                  Level
                  Log priority levels.
                  Definition: logging.h:18
                  + + + + + + + + +
                  sopt::logging::Log::setLevel
                  static void setLevel(const std::string &name, int level)
                  Set the log levels.
                  +
                  sopt::logging::Log::getName
                  std::string getName() const
                  Get the name of this logger.
                  Definition: logging.h:107
                  +
                  sopt::logging::Log::setLevel
                  Log & setLevel(int level)
                  Set the priority level of this logger.
                  Definition: logging.h:95
                  +
                  sopt::logging::Log::setName
                  Log & setName(const std::string &name)
                  Set the name of this logger.
                  Definition: logging.h:112
                  +
                  sopt::logging::Log::setLevels
                  static void setLevels(const LevelMap &logLevels)
                  Definition: logging.cc:49
                  + +
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  + +
                  sopt::logging::set_level
                  void set_level(const std::string &level)
                  Method to set the logging level of the default Log object.
                  Definition: logging.h:154
                  +
                  sopt::logging::getLog
                  Log & getLog()
                  Access method to default Log object.
                  Definition: logging.h:151
                  +
                  sopt::logging::mkFormattedString
                  std::string mkFormattedString(const char *txt, Args &&... args)
                  Helper method to construct formatted string.
                  Definition: logging.h:175
                  +
                  sopt::logging::operator<<
                  ostream & operator<<(Log &log, int level)
                  Streaming output to a logger must have a Log::Level/int as its first argument.
                  Definition: logging.cc:190
                  +
                  sopt::logging::applyFormat
                  void applyFormat(std::stringstream &ss, char *&pos, Arg &&arg)
                  Definition: logging.h:162
                  diff --git a/maths_8cc.html b/maths_8cc.html index 5df9d74b8..624bea7a6 100644 --- a/maths_8cc.html +++ b/maths_8cc.html @@ -96,34 +96,35 @@ diff --git a/maths_8cc__incl.map b/maths_8cc__incl.map index b7246f292..cc97cb0d8 100644 --- a/maths_8cc__incl.map +++ b/maths_8cc__incl.map @@ -1,30 +1,31 @@ - + - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/maths_8cc__incl.md5 b/maths_8cc__incl.md5 index 090551ee0..a883c13eb 100644 --- a/maths_8cc__incl.md5 +++ b/maths_8cc__incl.md5 @@ -1 +1 @@ -1a2b3110351e3167eb14555579f032ba \ No newline at end of file +2dab97c7f3eab4d25dfd4e39b4fbd65c \ No newline at end of file diff --git a/maths_8cc__incl.png b/maths_8cc__incl.png index 9c2f49623..6df72e1fc 100644 Binary files a/maths_8cc__incl.png and b/maths_8cc__incl.png differ diff --git a/menudata.js b/menudata.js index 3465d65b3..967d9e782 100644 --- a/menudata.js +++ b/menudata.js @@ -24,10 +24,12 @@ */ var menudata={children:[ {text:"Main Page",url:"index.html"}, +{text:"Modules",url:"modules.html"}, {text:"Namespaces",url:"namespaces.html",children:[ {text:"Namespace List",url:"namespaces.html"}, {text:"Namespace Members",url:"namespacemembers.html",children:[ {text:"All",url:"namespacemembers.html",children:[ +{text:"_",url:"namespacemembers.html#index__5F"}, {text:"a",url:"namespacemembers.html#index_a"}, {text:"b",url:"namespacemembers.html#index_b"}, {text:"c",url:"namespacemembers.html#index_c"}, @@ -35,7 +37,6 @@ var menudata={children:[ {text:"e",url:"namespacemembers.html#index_e"}, {text:"f",url:"namespacemembers.html#index_f"}, {text:"g",url:"namespacemembers.html#index_g"}, -{text:"h",url:"namespacemembers.html#index_h"}, {text:"i",url:"namespacemembers.html#index_i"}, {text:"l",url:"namespacemembers.html#index_l"}, {text:"m",url:"namespacemembers.html#index_m"}, @@ -49,6 +50,7 @@ var menudata={children:[ {text:"v",url:"namespacemembers.html#index_v"}, {text:"w",url:"namespacemembers.html#index_w"}]}, {text:"Functions",url:"namespacemembers_func.html",children:[ +{text:"_",url:"namespacemembers_func.html#index__5F"}, {text:"a",url:"namespacemembers_func.html#index_a"}, {text:"b",url:"namespacemembers_func.html#index_b"}, {text:"c",url:"namespacemembers_func.html#index_c"}, @@ -56,7 +58,6 @@ var menudata={children:[ {text:"e",url:"namespacemembers_func.html#index_e"}, {text:"f",url:"namespacemembers_func.html#index_f"}, {text:"g",url:"namespacemembers_func.html#index_g"}, -{text:"h",url:"namespacemembers_func.html#index_h"}, {text:"i",url:"namespacemembers_func.html#index_i"}, {text:"l",url:"namespacemembers_func.html#index_l"}, {text:"m",url:"namespacemembers_func.html#index_m"}, @@ -71,8 +72,7 @@ var menudata={children:[ {text:"w",url:"namespacemembers_func.html#index_w"}]}, {text:"Variables",url:"namespacemembers_vars.html",children:[ {text:"d",url:"namespacemembers_vars.html#index_d"}, -{text:"i",url:"namespacemembers_vars.html#index_i"}, -{text:"n",url:"namespacemembers_vars.html#index_n"}]}, +{text:"i",url:"namespacemembers_vars.html#index_i"}]}, {text:"Typedefs",url:"namespacemembers_type.html"}]}]}, {text:"Classes",url:"annotated.html",children:[ {text:"Class List",url:"annotated.html"}, @@ -145,10 +145,12 @@ var menudata={children:[ {text:"x",url:"functions_vars.html#index_x"}]}, {text:"Typedefs",url:"functions_type.html",children:[ {text:"a",url:"functions_type.html#index_a"}, +{text:"c",url:"functions_type.html#index_c"}, {text:"d",url:"functions_type.html#index_d"}, {text:"f",url:"functions_type.html#index_f"}, {text:"h",url:"functions_type.html#index_h"}, {text:"i",url:"functions_type.html#index_i"}, +{text:"l",url:"functions_type.html#index_l"}, {text:"p",url:"functions_type.html#index_p"}, {text:"r",url:"functions_type.html#index_r"}, {text:"s",url:"functions_type.html#index_s"}, @@ -156,6 +158,8 @@ var menudata={children:[ {text:"v",url:"functions_type.html#index_v"}, {text:"w",url:"functions_type.html#index_w"}, {text:"x",url:"functions_type.html#index_x"}]}, +{text:"Enumerations",url:"functions_enum.html"}, +{text:"Enumerator",url:"functions_eval.html"}, {text:"Related Functions",url:"functions_rela.html"}]}]}, {text:"Files",url:"files.html",children:[ {text:"File List",url:"files.html"}, diff --git a/modules.html b/modules.html new file mode 100644 index 000000000..0fdc8f75b --- /dev/null +++ b/modules.html @@ -0,0 +1,89 @@ + + + + + + + +SOPT: Modules + + + + + + + + + + + + +
                  +
                  + + + + + + + +
                  +
                  SOPT +
                  +
                  Sparse OPTimisation
                  +
                  +
                  + + + + + + + +
                  + +
                  +
                  + + +
                  + +
                  + +
                  +
                  +
                  Modules
                  +
                  +
                  +
                  Here is a list of all modules:
                  + + +
                   Logging macros
                  +
                  +
                  + +
                  +Generated by doxygen 1.9.1 +
                  + + diff --git a/mpi__session_8cc.html b/mpi__session_8cc.html index 5f4077de8..3bd65f4a8 100644 --- a/mpi__session_8cc.html +++ b/mpi__session_8cc.html @@ -101,12 +101,16 @@ - - - - - - + + + + + + + + + + @@ -193,16 +197,13 @@

                  38  if (returnCode != 0) // Indicates a command line error
                  39  return returnCode;
                  40 
                  -
                  41  sopt::logging::initialize();
                  -
                  42 
                  -
                  43  auto const result = session.run();
                  -
                  44  return result;
                  -
                  45 }
                  +
                  41  auto const result = session.run();
                  +
                  42  return result;
                  +
                  43 }
                  N
                  constexpr auto N
                  Definition: wavelets.cc:57
                  cargs
                  std::vector< char const * > cargs
                  Definition: mpi_session.cc:10
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  -

                  References cargs, sopt::logging::initialize(), and N.

                  +

                  References cargs, and N.

                  diff --git a/mpi__session_8cc__incl.map b/mpi__session_8cc__incl.map index 519498423..05d6fdf7b 100644 --- a/mpi__session_8cc__incl.map +++ b/mpi__session_8cc__incl.map @@ -4,10 +4,14 @@ - - - - - - + + + + + + + + + + diff --git a/mpi__session_8cc__incl.md5 b/mpi__session_8cc__incl.md5 index 57731dc14..1da336f18 100644 --- a/mpi__session_8cc__incl.md5 +++ b/mpi__session_8cc__incl.md5 @@ -1 +1 @@ -e0934cc79ad12bdcfdc53f3f026c50fd \ No newline at end of file +c42cbb502e53a9f2131987ec96ca7c2d \ No newline at end of file diff --git a/mpi__session_8cc__incl.png b/mpi__session_8cc__incl.png index a2b602bc4..5c2537ffd 100644 Binary files a/mpi__session_8cc__incl.png and b/mpi__session_8cc__incl.png differ diff --git a/mpi__session_8cc_source.html b/mpi__session_8cc_source.html index 62f4310cd..7c8658819 100644 --- a/mpi__session_8cc_source.html +++ b/mpi__session_8cc_source.html @@ -119,17 +119,14 @@
                  38  if (returnCode != 0) // Indicates a command line error
                  39  return returnCode;
                  40 
                  -
                  41  sopt::logging::initialize();
                  -
                  42 
                  -
                  43  auto const result = session.run();
                  -
                  44  return result;
                  -
                  45 }
                  +
                  41  auto const result = session.run();
                  +
                  42  return result;
                  +
                  43 }
                  N
                  constexpr auto N
                  Definition: wavelets.cc:57
                  main
                  int main(int argc, const char **argv)
                  Definition: mpi_session.cc:22
                  cargs
                  std::vector< char const * > cargs
                  Definition: mpi_session.cc:10
                  TEST_CASE
                  TEST_CASE("Create/delete session")
                  Definition: mpi_session.cc:11
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  sopt::mpi::finalized
                  bool finalized()
                  Definition: session.cc:71
                  sopt::mpi::init
                  std::shared_ptr< details::initializer > init(int argc, const char **argv)
                  Definition: session.cc:27
                  sopt::mpi::initialized
                  bool initialized()
                  Definition: session.cc:61
                  diff --git a/mpi__wavelets_8cc.html b/mpi__wavelets_8cc.html index 2bd335513..81ad0c553 100644 --- a/mpi__wavelets_8cc.html +++ b/mpi__wavelets_8cc.html @@ -93,41 +93,42 @@ diff --git a/mpi__wavelets_8cc__incl.map b/mpi__wavelets_8cc__incl.map index 03aea6137..e515aa27b 100644 --- a/mpi__wavelets_8cc__incl.map +++ b/mpi__wavelets_8cc__incl.map @@ -1,37 +1,38 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/mpi__wavelets_8cc__incl.md5 b/mpi__wavelets_8cc__incl.md5 index 48cf573eb..3898653ea 100644 --- a/mpi__wavelets_8cc__incl.md5 +++ b/mpi__wavelets_8cc__incl.md5 @@ -1 +1 @@ -a5b52b70f32b0a01c3172093a3586d31 \ No newline at end of file +4541145814afbd2b043ae03292036c36 \ No newline at end of file diff --git a/mpi__wavelets_8cc__incl.png b/mpi__wavelets_8cc__incl.png index c74755e31..4826cabab 100644 Binary files a/mpi__wavelets_8cc__incl.png and b/mpi__wavelets_8cc__incl.png differ diff --git a/namespacemembers.html b/namespacemembers.html index 93afdbfd3..2fde0fbac 100644 --- a/namespacemembers.html +++ b/namespacemembers.html @@ -73,10 +73,20 @@
                  Here is a list of all namespace members with links to the namespace documentation for each member:
                  +

                  - _ -

                  + +

                  - a -

                  diff --git a/namespacesopt.html b/namespacesopt.html index 29e17d2f9..6f247dcc2 100644 --- a/namespacesopt.html +++ b/namespacesopt.html @@ -210,9 +210,6 @@ std::string default_logger_name ()  Default logger name. More...
                    -constexpr bool color_logger () - Wether to add color to the logger. More...
                  -  constexpr std::size_t number_of_threads_in_tests ()  Number of threads used during testing. More...
                    @@ -731,9 +728,9 @@

                  a
                  constexpr Scalar a
                  Definition: bisection_method.cc:13
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  t_real
                  sopt::t_real t_real
                  Definition: forward_backward.cc:27
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  -

                  References a, b, SOPT_LOW_LOG, and SOPT_THROW.

                  +

                  References a, b, SOPT_LOW_LOG, and SOPT_THROW.

                  Referenced by sopt::credible_region::find_credible_interval(), and TEST_CASE().

                  @@ -796,36 +793,6 @@

                  Referenced by TEST_CASE().

                  - - - -

                  ◆ color_logger()

                  - -
                  -
                  - - - - - -
                  - - - - - - - -
                  constexpr bool sopt::color_logger ()
                  -                   		-inlineconstexpr
                  -
                  - -

                  Wether to add color to the logger.

                  - -

                  Definition at line 43 of file config.in.h.

                  -
                  43 { return @SOPT_COLOR_LOGGING@; }
                  -
                  @@ -853,8 +820,8 @@

                  Definition at line 41 of file config.in.h.

                  -
                  41 { return "@SOPT_LOGGER_NAME@"; }
                  +

                  Definition at line 46 of file config.in.h.

                  +
                  46 { return "@SOPT_LOGGER_NAME@"; }
                  @@ -883,8 +850,8 @@

                  Definition at line 39 of file config.in.h.

                  -
                  39 { return "@SOPT_TEST_LOG_LEVEL@"; }
                  +

                  Definition at line 43 of file config.in.h.

                  +
                  43 { return "@SOPT_TEST_LOG_LEVEL@"; }
                  @@ -1058,8 +1025,8 @@

                  Definition at line 37 of file config.in.h.

                  -
                  37 { return "@SOPT_GITREF@"; }
                  +

                  Definition at line 40 of file config.in.h.

                  +
                  40 { return "@SOPT_GITREF@"; }
                  @@ -1793,8 +1760,8 @@

                  Definition at line 46 of file config.in.h.

                  -
                  46 { return @SOPT_DEFAULT_OPENMP_THREADS@; }
                  +

                  Definition at line 50 of file config.in.h.

                  +
                  50 { return @SOPT_DEFAULT_OPENMP_THREADS@; }
                  @@ -2315,8 +2282,8 @@

                  Definition at line 30 of file config.in.h.

                  -
                  30 { return "@SOPT_VERSION@"; }
                  +

                  Definition at line 31 of file config.in.h.

                  +
                  31 { return "@SOPT_VERSION@"; }
                  @@ -2345,11 +2312,11 @@

                  Definition at line 32 of file config.in.h.

                  -
                  32  {
                  -
                  33  return std::tuple<uint8_t, uint8_t, uint8_t>(
                  -
                  34  @SOPT_VERSION_MAJOR@, @SOPT_VERSION_MINOR@, @SOPT_VERSION_PATCH@);
                  -
                  35 }
                  +

                  Definition at line 34 of file config.in.h.

                  +
                  34  {
                  +
                  35  return std::tuple<uint8_t, uint8_t, uint8_t>(
                  +
                  36  @SOPT_VERSION_MAJOR@, @SOPT_VERSION_MINOR@, @SOPT_VERSION_PATCH@);
                  +
                  37 }
                  diff --git a/namespacesopt_1_1algorithm.html b/namespacesopt_1_1algorithm.html index c8e370a69..35cd506ab 100644 --- a/namespacesopt_1_1algorithm.html +++ b/namespacesopt_1_1algorithm.html @@ -393,10 +393,10 @@

                  55  return std::make_tuple(std::sqrt(old_value), estimate_eigen_vector);
                  56 }
                  sopt::LinearTransform::adjoint
                  LinearTransform< VECTOR > adjoint() const
                  Indirect transform.
                  Definition: linear_transform.h:79
                  -
                  SOPT_DEBUG
                  #define SOPT_DEBUG(...)
                  \macro Output some debugging
                  Definition: logging.h:21
                  +
                  SOPT_DEBUG
                  #define SOPT_DEBUG(...)
                  \macro Output some debugging
                  Definition: logging.h:217
                  sopt::t_int
                  int t_int
                  Root of the type hierarchy for signed integers.
                  Definition: types.h:13
                  -

                  References sopt::LinearTransform< VECTOR >::adjoint(), and SOPT_DEBUG.

                  +

                  References sopt::LinearTransform< VECTOR >::adjoint(), and SOPT_DEBUG.

                  Referenced by normalise_operator().

                  diff --git a/namespacesopt_1_1credible__region.html b/namespacesopt_1_1credible__region.html index 8d3e34df9..904b6bc11 100644 --- a/namespacesopt_1_1credible__region.html +++ b/namespacesopt_1_1credible__region.html @@ -152,9 +152,9 @@

                  N
                  constexpr auto N
                  Definition: wavelets.cc:57
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  t_real
                  sopt::t_real t_real
                  Definition: forward_backward.cc:27
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  -

                  References N, SOPT_MEDIUM_LOG, and SOPT_THROW.

                  +

                  References N, SOPT_MEDIUM_LOG, and SOPT_THROW.

                  Referenced by credible_interval(), and TEST_CASE().

                  @@ -385,12 +385,12 @@

                  173  return std::make_tuple(credible_grid_lower_bound, credible_grid_mean, credible_grid_upper_bound);
                  174 }
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  sopt::credible_region::find_credible_interval
                  std::tuple< t_real, t_real, t_real > find_credible_interval(const Eigen::MatrixBase< T > &solution, const t_uint &rows, const t_uint &cols, const std::tuple< t_uint, t_uint, t_uint, t_uint > &region, const std::function< t_real(typename T::PlainObject)> &objective_function, const t_real &energy_upperbound)
                  Definition: credible_region.h:75
                  sopt::t_int
                  int t_int
                  Root of the type hierarchy for signed integers.
                  Definition: types.h:13
                  sopt::t_uint
                  size_t t_uint
                  Root of the type hierarchy for unsigned integers.
                  Definition: types.h:15
                  -

                  References cols, find_credible_interval(), rows, SOPT_LOW_LOG, and SOPT_THROW.

                  +

                  References cols, find_credible_interval(), rows, SOPT_LOW_LOG, and SOPT_THROW.

                  diff --git a/namespacesopt_1_1logging.html b/namespacesopt_1_1logging.html index b163e72e4..2d1a75edc 100644 --- a/namespacesopt_1_1logging.html +++ b/namespacesopt_1_1logging.html @@ -76,119 +76,111 @@
                  -Functions | -Variables
                  +Classes | +Functions
                  sopt::logging Namespace Reference
                  + + + + +

                  +Classes

                  class  Log
                   Logging system for controlled & formatted writing to stdout. More...
                   
                  - - - - - - - - - - - - - - - - - -

                  Functions

                  std::shared_ptr< int > initialize (std::string const &name="")
                   Initializes a logger. More...
                   
                  std::shared_ptr< int > initialize ()
                   
                  std::shared_ptr< int > get (std::string const &name="")
                   Returns shared pointer to logger or null if it does not exist. More...
                   
                  std::shared_ptr< int > get ()
                   
                  void set_level (std::string const &level, std::string const &name)
                   Sets loggin level. More...
                   
                  void set_level (std::string const &)
                   
                  bool has_level (std::string const &, std::string const &)
                   
                  - - - - + + + + + + + + + + + + + + + + + + + +

                  -Variables

                  const std::string name_prefix = "sopt::"
                   Name of the sopt logger. More...
                   
                  void _updateLevels (const Log::LevelMap &defaultLevels, Log::LogMap &existingLogs)
                   
                  ostream & operator<< (Log &log, int level)
                   Streaming output to a logger must have a Log::Level/int as its first argument. More...
                   
                  Log & getLog ()
                   Access method to default Log object. More...
                   
                  void set_level (const std::string &level)
                   Method to set the logging level of the default Log object. More...
                   
                  template<typename Arg >
                  void applyFormat (std::stringstream &ss, char *&pos, Arg &&arg)
                   
                  template<typename... Args>
                  std::string mkFormattedString (const char *txt, Args &&... args)
                   Helper method to construct formatted string. More...
                   
                  const std::string & mkFormattedString (const std::string &txt)
                   

                  Function Documentation

                  - -

                  ◆ get() [1/2]

                  + +

                  ◆ _updateLevels()

                  - - - - - -
                  - + - + + + + + + + -
                  std::shared_ptr<int> sopt::logging::get void sopt::logging::_updateLevels ()const Log::LevelMap & defaultLevels,
                  Log::LogMap & existingLogs 
                  -                   		-inline
                  -
                  - -

                  Definition at line 15 of file logging.disabled.h.

                  -
                  15 { return nullptr; }
                  -
                  -
                  -
                  - -

                  ◆ get() [2/2]

                  - -
                  -
                  - - - - - -
                  - - - - - + +
                  spdlogPtr sopt::logging::get (std::string const & name = "") )
                  -                   		-inline
                  +
                  Todo:
                  Add single static setLevel
                  +
                  Todo:
                  Check ordering - "Foo" should come before "Foo.Bar"
                  -

                  Returns shared pointer to logger or null if it does not exist.

                  - -

                  Definition at line 14 of file logging.disabled.h.

                  -
                  14 { return nullptr; }
                  +

                  Definition at line 30 of file logging.cc.

                  +
                  30  {
                  +
                  32  for (Log::LevelMap::const_iterator lev = defaultLevels.begin(); lev != defaultLevels.end(); ++lev) {
                  +
                  33  for (Log::LogMap::iterator log = existingLogs.begin(); log != existingLogs.end(); ++log) {
                  +
                  34  if (log->first.find(lev->first) == 0) {
                  +
                  35  log->second.setLevel(lev->second);
                  +
                  36  }
                  +
                  37  }
                  +
                  38  }
                  +
                  39  }
                  +

                  Referenced by sopt::logging::Log::setLevels().

                  +
                  - -

                  ◆ has_level()

                  + +

                  ◆ applyFormat()

                  - - -
                  +
                  +template<typename Arg >
                  - + - - + + - - + + + + + + + + @@ -196,20 +188,30 @@

                  -inline -

                  -
                  bool sopt::logging::has_level void sopt::logging::applyFormat (std::string const & level, std::stringstream & ss,
                  std::string const & name = "" char *& pos,
                  Arg && arg 
                  +

                  Helper method to ireplace a set of curly braces with the template argument arg in a string stream

                  -

                  Definition at line 18 of file logging.disabled.h.

                  -
                  18 { return false; }
                  +

                  Definition at line 162 of file logging.h.

                  +
                  162  {
                  +
                  163  char* delim = strstr(pos, "{}");
                  +
                  164  if (delim != NULL) {
                  +
                  165  ss << std::string(pos, delim-pos) << std::forward<Arg>(arg);
                  +
                  166  pos = delim + 2;
                  +
                  167  }
                  +
                  168  else {
                  +
                  169  SOPT_THROW("Insufficient placeholders for number of arguments!");
                  +
                  170  }
                  +
                  171 }
                  +
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  +

                  References SOPT_THROW.

                  + +

                  Referenced by mkFormattedString().

                  +
                  - -

                  ◆ initialize() [1/2]

                  + +

                  ◆ getLog()

                  @@ -218,7 +220,7 @@

                  - + @@ -231,26 +233,45 @@

                  -

                  Definition at line 13 of file logging.disabled.h.

                  -
                  13 { return nullptr; }
                  +

                  Access method to default Log object.

                  + +

                  Definition at line 151 of file logging.h.

                  +
                  151 { return Log::getLog("sopt::"); }
                  +
                  sopt::logging::getLog
                  Log & getLog()
                  Access method to default Log object.
                  Definition: logging.h:151
                  +

                  References sopt::logging::Log::getLog().

                  + +

                  Referenced by set_level().

                  +
                  - -

                  ◆ initialize() [2/2]

                  + +

                  ◆ mkFormattedString() [1/2]

                  +
                  +template<typename... Args>

                  std::shared_ptr<int> sopt::logging::initialize Log& sopt::logging::getLog ( )
                  @@ -260,18 +281,25 @@

                  -

                  Initializes a logger.

                  -

                  Logger only exists as long as return is kept alive.

                  +

                  Helper method to construct formatted string.

                  -

                  Definition at line 12 of file logging.disabled.h.

                  -
                  12 { return nullptr; }
                  +

                  Definition at line 175 of file logging.h.

                  +
                  175  {
                  +
                  176  std::string mys = txt;
                  +
                  177  std::stringstream rtn;
                  +
                  178  char* pos = (char*)txt;
                  +
                  179  ((void)applyFormat(rtn, pos, std::forward<Args>(args)), ...);
                  +
                  180  rtn << std::string(pos);
                  +
                  181  return rtn.str();
                  +
                  182 }
                  +
                  sopt::logging::applyFormat
                  void applyFormat(std::stringstream &ss, char *&pos, Arg &&arg)
                  Definition: logging.h:162
                  -

                  Referenced by main().

                  +

                  References applyFormat().

                  - -

                  ◆ set_level() [1/2]

                  + +

                  ◆ mkFormattedString() [2/2]

                  @@ -280,10 +308,10 @@

                  - + - - + + + + + + + + + + + +
                  spdlogPtr sopt::logging::initialize std::string sopt::logging::mkFormattedString (std::string const & name = "")const char * txt,
                  Args &&... args 
                  )
                  - + - - + +
                  void sopt::logging::set_level const std::string& sopt::logging::mkFormattedString (std::string const & )const std::string & txt)
                  @@ -294,31 +322,28 @@

                  -

                  Definition at line 17 of file logging.disabled.h.

                  -
                  17 {}
                  +

                  Definition at line 184 of file logging.h.

                  +
                  184 { return txt; }

                  - -

                  ◆ set_level() [2/2]

                  + +

                  ◆ operator<<()

                  - - -
                  - + - - + + - - + + @@ -326,47 +351,64 @@

                  -inline -

                  -
                  void sopt::logging::set_level std::ostream & sopt::logging::operator<< (std::string const & level, Log & log,
                  std::string const & name = "" int level 
                  -

                  Sets loggin level.

                  -

                  Levels can be one of

                    -
                  • "trace"
                    • -
                  • "debug"
                    • -
                  • "info"
                    • -
                  • "warn"
                    • -
                  • "err"
                    • -
                  • "critical"
                    • -
                  • "off"
                    • -
                  +

                  Streaming output to a logger must have a Log::Level/int as its first argument.

                  +

                  The streaming operator can use Log's internals.

                  -

                  Definition at line 16 of file logging.disabled.h.

                  -
                  16 {}
                  +

                  Definition at line 190 of file logging.cc.

                  +
                  190  {
                  +
                  191  if (log.isActive(level)) {
                  +
                  192  if (level > Log::warning) {
                  +
                  193  cerr << log.formatMessage(level, "");
                  +
                  194  return cerr;
                  +
                  195  } else {
                  +
                  196  cout << log.formatMessage(level, "");
                  +
                  197  return cout;
                  +
                  198  }
                  +
                  199  } else {
                  +
                  200  static ostream devNull(nullptr);
                  +
                  201  return devNull;
                  +
                  202  }
                  +
                  203  }
                  -

                  Referenced by main(), and TEST_CASE().

                  -
                  -

                  Variable Documentation

                  - -

                  ◆ name_prefix

                  + +

                  ◆ set_level()

                  + + + + + +
                  - + + + + +
                  const std::string sopt::logging::name_prefix = "sopt::"void sopt::logging::set_level (const std::string & level)
                  +                   		+inline
                  -

                  Name of the sopt logger.

                  +

                  Method to set the logging level of the default Log object.

                  -

                  Definition at line 10 of file logging.disabled.h.

                  +

                  Definition at line 154 of file logging.h.

                  +
                  154  {
                  +
                  155  getLog().setLevel(Log::getLevelFromName(level));
                  +
                  156 }
                  +
                  sopt::logging::Log::setLevel
                  static void setLevel(const std::string &name, int level)
                  Set the log levels.
                  +
                  +

                  References sopt::logging::Log::getLevelFromName(), getLog(), and sopt::logging::Log::setLevel().

                  + +

                  Referenced by main(), and TEST_CASE().

                  diff --git a/namespacesopt_1_1mpi.html b/namespacesopt_1_1mpi.html index b83be081c..1915179fd 100644 --- a/namespacesopt_1_1mpi.html +++ b/namespacesopt_1_1mpi.html @@ -254,9 +254,9 @@

                  67  }
                  68  return static_cast<bool>(flag);
                  69 }
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  +
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:211
                  -

                  References SOPT_ERROR.

                  +

                  References SOPT_ERROR.

                  Referenced by finalize(), init(), session_singleton(), and TEST_CASE().

                  diff --git a/namespacesopt_1_1utilities.html b/namespacesopt_1_1utilities.html index 34ed0914d..3efaf2b89 100644 --- a/namespacesopt_1_1utilities.html +++ b/namespacesopt_1_1utilities.html @@ -647,10 +647,10 @@

                  66 }
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  -

                  References SOPT_LOW_LOG, SOPT_MEDIUM_LOG, and SOPT_THROW.

                  +

                  References SOPT_LOW_LOG, SOPT_MEDIUM_LOG, and SOPT_THROW.

                  Referenced by main(), and sopt::notinstalled::read_standard_tiff().

                  @@ -781,9 +781,9 @@

                  100  TIFFClose(tif);
                  101  SOPT_TRACE("Freeing raster");
                  102 }
                  -
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:24
                  +
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
                  -

                  References SOPT_LOW_LOG, SOPT_MEDIUM_LOG, SOPT_THROW, and SOPT_TRACE.

                  +

                  References SOPT_LOW_LOG, SOPT_MEDIUM_LOG, SOPT_THROW, and SOPT_TRACE.

                  Referenced by main().

                  diff --git a/namespacesopt_1_1wavelets.html b/namespacesopt_1_1wavelets.html index 5b742ef56..84d4a11ba 100644 --- a/namespacesopt_1_1wavelets.html +++ b/namespacesopt_1_1wavelets.html @@ -633,7 +633,7 @@

                  21  // Unknown input wavelet
                  22  throw std::exception();
                  23 }
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::wavelets::daubechies_data
                  WaveletData const & daubechies_data(t_uint n)
                  Factory function returning specific daubechie wavelet data.
                  Definition: wavelet_data.cc:1597

                  Referenced by direct_matrix(), direct_vector(), sopt::wavelets::SARA::emplace_back(), indirect_matrix(), indirect_vector(), main(), and TEST_CASE().

                  diff --git a/objective__functions_8h.html b/objective__functions_8h.html index bd2cb0420..5901f7546 100644 --- a/objective__functions_8h.html +++ b/objective__functions_8h.html @@ -97,27 +97,28 @@
                  diff --git a/objective__functions_8h__incl.map b/objective__functions_8h__incl.map index d4863f5e2..3503e867b 100644 --- a/objective__functions_8h__incl.map +++ b/objective__functions_8h__incl.map @@ -1,23 +1,24 @@ - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/objective__functions_8h__incl.md5 b/objective__functions_8h__incl.md5 index 652db063e..42ba6466c 100644 --- a/objective__functions_8h__incl.md5 +++ b/objective__functions_8h__incl.md5 @@ -1 +1 @@ -b6fc7c1ca2f40ca5df30def81740b034 \ No newline at end of file +b76c8efaff5dc0ca485c0e1d89093abb \ No newline at end of file diff --git a/objective__functions_8h__incl.png b/objective__functions_8h__incl.png index 40ef12a50..ce54ed6e5 100644 Binary files a/objective__functions_8h__incl.png and b/objective__functions_8h__incl.png differ diff --git a/ort__model_8cc.html b/ort__model_8cc.html index ecacfcde5..b9db534ec 100644 --- a/ort__model_8cc.html +++ b/ort__model_8cc.html @@ -93,26 +93,29 @@
                  diff --git a/ort__model_8cc__incl.map b/ort__model_8cc__incl.map index e716e99d5..db5c4e025 100644 --- a/ort__model_8cc__incl.map +++ b/ort__model_8cc__incl.map @@ -1,22 +1,25 @@ - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + diff --git a/ort__model_8cc__incl.md5 b/ort__model_8cc__incl.md5 index 7b9d9a550..94f1ac0f5 100644 --- a/ort__model_8cc__incl.md5 +++ b/ort__model_8cc__incl.md5 @@ -1 +1 @@ -147db2f9b14db5cd5648b67515124b72 \ No newline at end of file +f15c494722bf38c0e84cf42e84feb901 \ No newline at end of file diff --git a/ort__model_8cc__incl.png b/ort__model_8cc__incl.png index 783ad472f..8262e71da 100644 Binary files a/ort__model_8cc__incl.png and b/ort__model_8cc__incl.png differ diff --git a/ort__session_8h.html b/ort__session_8h.html index d418bad9d..90d309e84 100644 --- a/ort__session_8h.html +++ b/ort__session_8h.html @@ -98,18 +98,21 @@ diff --git a/padmm_8cc__incl.map b/padmm_8cc__incl.map index 580764452..0bb55a3ba 100644 --- a/padmm_8cc__incl.map +++ b/padmm_8cc__incl.map @@ -1,35 +1,36 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/padmm_8cc__incl.md5 b/padmm_8cc__incl.md5 index eba480238..a612be183 100644 --- a/padmm_8cc__incl.md5 +++ b/padmm_8cc__incl.md5 @@ -1 +1 @@ -6f863770d2696ff5e6dc3ba70514ae11 \ No newline at end of file +2187dbbb6736d9f76e94d585afc2d012 \ No newline at end of file diff --git a/padmm_8cc__incl.png b/padmm_8cc__incl.png index af0bc496a..db0d7e224 100644 Binary files a/padmm_8cc__incl.png and b/padmm_8cc__incl.png differ diff --git a/padmm_8h.html b/padmm_8h.html index 6147bfffe..5c7ac7012 100644 --- a/padmm_8h.html +++ b/padmm_8h.html @@ -99,29 +99,30 @@
                  diff --git a/padmm_8h__incl.map b/padmm_8h__incl.map index 5847ad084..5d7cf3fb8 100644 --- a/padmm_8h__incl.map +++ b/padmm_8h__incl.map @@ -1,25 +1,26 @@ - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/padmm_8h__incl.md5 b/padmm_8h__incl.md5 index 7688c0fad..3bf6dc6d1 100644 --- a/padmm_8h__incl.md5 +++ b/padmm_8h__incl.md5 @@ -1 +1 @@ -e53176885e03e02770d47d183c2f5057 \ No newline at end of file +3d7448acf73100ae65c0ea3a1206c5e2 \ No newline at end of file diff --git a/padmm_8h__incl.png b/padmm_8h__incl.png index a41099091..167c1ca67 100644 Binary files a/padmm_8h__incl.png and b/padmm_8h__incl.png differ diff --git a/padmm_8h_source.html b/padmm_8h_source.html index 048ee6a39..6e62ae0f1 100644 --- a/padmm_8h_source.html +++ b/padmm_8h_source.html @@ -323,11 +323,11 @@
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  -
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:17
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  +
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:211
                  +
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:213
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::linear_transform
                  LinearTransform< VECTOR > linear_transform(OperatorFunction< VECTOR > const &direct, OperatorFunction< VECTOR > const &indirect, std::array< t_int, 3 > const &sizes={{1, 1, 0}})
                  Definition: linear_transform.h:101
                  sopt::t_uint
                  size_t t_uint
                  Root of the type hierarchy for unsigned integers.
                  Definition: types.h:15
                  diff --git a/padmm__warm__start_8cc.html b/padmm__warm__start_8cc.html index ed91efafb..8b763cf3c 100644 --- a/padmm__warm__start_8cc.html +++ b/padmm__warm__start_8cc.html @@ -96,35 +96,36 @@
                  @@ -277,13 +278,13 @@

                  sopt::algorithm::ProximalADMM::is_converged
                  ProximalADMM< Scalar > & is_converged(std::function< bool(t_Vector const &x)> const &func)
                  Convergence function that takes only the output as argument.
                  Definition: padmm.h:115

                  sopt::algorithm::ProximalADMM::Phi
                  ProximalADMM &::type Phi(ARGS &&... args)
                  Definition: padmm.h:177
                  sopt::proximal::EuclidianNorm
                  Proximal of euclidian norm.
                  Definition: proximal.h:18
                  -
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:24
                  +
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
                  sopt::proximal::translate
                  Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
                  Translates given proximal by given vector.
                  Definition: proximal.h:362
                  sopt::t_real
                  double t_real
                  Root of the type hierarchy for real numbers.
                  Definition: types.h:17
                  N
                  constexpr auto N
                  Definition: padmm_warm_start.cc:14
                  -

                  References sopt::algorithm::ProximalADMM< SCALAR >::is_converged(), N, sopt::algorithm::ProximalADMM< SCALAR >::Phi(), SOPT_TRACE, and sopt::proximal::translate().

                  +

                  References sopt::algorithm::ProximalADMM< SCALAR >::is_converged(), N, sopt::algorithm::ProximalADMM< SCALAR >::Phi(), SOPT_TRACE, and sopt::proximal::translate().

                  diff --git a/padmm__warm__start_8cc__incl.map b/padmm__warm__start_8cc__incl.map index 0c7b83897..7e991b855 100644 --- a/padmm__warm__start_8cc__incl.map +++ b/padmm__warm__start_8cc__incl.map @@ -1,31 +1,32 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/padmm__warm__start_8cc__incl.md5 b/padmm__warm__start_8cc__incl.md5 index e083c7e4c..c364e9191 100644 --- a/padmm__warm__start_8cc__incl.md5 +++ b/padmm__warm__start_8cc__incl.md5 @@ -1 +1 @@ -618b0c5170aa9438769a1b0c8de54672 \ No newline at end of file +29db245b45952fe25283c18da4e48198 \ No newline at end of file diff --git a/padmm__warm__start_8cc__incl.png b/padmm__warm__start_8cc__incl.png index de5e4e30a..7aef7e482 100644 Binary files a/padmm__warm__start_8cc__incl.png and b/padmm__warm__start_8cc__incl.png differ diff --git a/padmm__warm__start_8cc_source.html b/padmm__warm__start_8cc_source.html index c6a6779d9..28f204029 100644 --- a/padmm__warm__start_8cc_source.html +++ b/padmm__warm__start_8cc_source.html @@ -145,7 +145,7 @@
                  sopt::algorithm::ProximalADMM::is_converged
                  ProximalADMM< Scalar > & is_converged(std::function< bool(t_Vector const &x)> const &func)
                  Convergence function that takes only the output as argument.
                  Definition: padmm.h:115
                  sopt::algorithm::ProximalADMM::Phi
                  ProximalADMM &::type Phi(ARGS &&... args)
                  Definition: padmm.h:177
                  sopt::proximal::EuclidianNorm
                  Proximal of euclidian norm.
                  Definition: proximal.h:18
                  -
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:24
                  +
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
                  sopt::proximal::translate
                  Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
                  Translates given proximal by given vector.
                  Definition: proximal.h:362
                  sopt::t_real
                  double t_real
                  Root of the type hierarchy for real numbers.
                  Definition: types.h:17
                  diff --git a/positive__quadrant_8h.html b/positive__quadrant_8h.html index e4b5e720c..ed4238d29 100644 --- a/positive__quadrant_8h.html +++ b/positive__quadrant_8h.html @@ -93,27 +93,28 @@
                  diff --git a/positive__quadrant_8h__incl.map b/positive__quadrant_8h__incl.map index 1676f94b2..976784cb6 100644 --- a/positive__quadrant_8h__incl.map +++ b/positive__quadrant_8h__incl.map @@ -1,23 +1,24 @@ - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/positive__quadrant_8h__incl.md5 b/positive__quadrant_8h__incl.md5 index 75f4d8f1b..7afa26fa4 100644 --- a/positive__quadrant_8h__incl.md5 +++ b/positive__quadrant_8h__incl.md5 @@ -1 +1 @@ -fbb600af92fbdd2457b5e7c8f489d3b3 \ No newline at end of file +c78fbb6b89829562d299bae207aa1388 \ No newline at end of file diff --git a/positive__quadrant_8h__incl.png b/positive__quadrant_8h__incl.png index f479abf40..3260801f1 100644 Binary files a/positive__quadrant_8h__incl.png and b/positive__quadrant_8h__incl.png differ diff --git a/power__method_8h.html b/power__method_8h.html index 8800af3c7..bb32c6833 100644 --- a/power__method_8h.html +++ b/power__method_8h.html @@ -102,30 +102,31 @@
                  diff --git a/power__method_8h__incl.map b/power__method_8h__incl.map index 1d9238d69..9ad218a28 100644 --- a/power__method_8h__incl.map +++ b/power__method_8h__incl.map @@ -1,26 +1,27 @@ - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/power__method_8h__incl.md5 b/power__method_8h__incl.md5 index 264689b62..8236f9570 100644 --- a/power__method_8h__incl.md5 +++ b/power__method_8h__incl.md5 @@ -1 +1 @@ -4c1e1262308cc3fad0c18b96fcbccc75 \ No newline at end of file +b536c7c099d78d0561573f42cb316112 \ No newline at end of file diff --git a/power__method_8h__incl.png b/power__method_8h__incl.png index 7d8e5d654..d05684a6c 100644 Binary files a/power__method_8h__incl.png and b/power__method_8h__incl.png differ diff --git a/power__method_8h_source.html b/power__method_8h_source.html index 45872f1d1..a4637e25a 100644 --- a/power__method_8h_source.html +++ b/power__method_8h_source.html @@ -328,9 +328,9 @@
                  t_real
                  sopt::t_real t_real
                  Definition: forward_backward.cc:27
                  linear_transform.h
                  -
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:17
                  -
                  SOPT_INFO
                  #define SOPT_INFO(...)
                  \macro Verbose informational message about normal condition
                  Definition: logging.h:19
                  -
                  SOPT_DEBUG
                  #define SOPT_DEBUG(...)
                  \macro Output some debugging
                  Definition: logging.h:21
                  +
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:213
                  +
                  SOPT_INFO
                  #define SOPT_INFO(...)
                  \macro Verbose informational message about normal condition
                  Definition: logging.h:215
                  +
                  SOPT_DEBUG
                  #define SOPT_DEBUG(...)
                  \macro Output some debugging
                  Definition: logging.h:217
                  sopt::algorithm::normalise_operator
                  std::tuple< t_real, T, std::shared_ptr< sopt::LinearTransform< T > > > normalise_operator(const std::shared_ptr< sopt::LinearTransform< T > const > &op, const t_uint &niters, const t_real &relative_difference, const T &initial_vector)
                  Definition: power_method.h:59
                  sopt::algorithm::power_method
                  std::tuple< t_real, T > power_method(const sopt::LinearTransform< T > &op, const t_uint niters, const t_real relative_difference, const T &initial_vector)
                  Returns the eigenvalue and eigenvector for eigenvalue of the Linear Transform with largest magnitude.
                  Definition: power_method.h:23
                  diff --git a/primal__dual_8cc.html b/primal__dual_8cc.html index 1b194c019..469931f1b 100644 --- a/primal__dual_8cc.html +++ b/primal__dual_8cc.html @@ -104,35 +104,36 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
                  diff --git a/primal__dual_8cc__incl.map b/primal__dual_8cc__incl.map index c919e5219..863deb742 100644 --- a/primal__dual_8cc__incl.map +++ b/primal__dual_8cc__incl.map @@ -4,33 +4,34 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/primal__dual_8cc__incl.md5 b/primal__dual_8cc__incl.md5 index badc36e5d..47a87e242 100644 --- a/primal__dual_8cc__incl.md5 +++ b/primal__dual_8cc__incl.md5 @@ -1 +1 @@ -08313dd77bcced9cbf83797419394521 \ No newline at end of file +2fb09178e215979eefb5388fe7d4eb59 \ No newline at end of file diff --git a/primal__dual_8cc__incl.png b/primal__dual_8cc__incl.png index 58ad1168e..650f1722e 100644 Binary files a/primal__dual_8cc__incl.png and b/primal__dual_8cc__incl.png differ diff --git a/primal__dual_8h.html b/primal__dual_8h.html index 7e41a3f0b..f073f2b58 100644 --- a/primal__dual_8h.html +++ b/primal__dual_8h.html @@ -99,29 +99,30 @@
                  diff --git a/primal__dual_8h__incl.map b/primal__dual_8h__incl.map index 1dbcff9f9..3fa552edf 100644 --- a/primal__dual_8h__incl.map +++ b/primal__dual_8h__incl.map @@ -1,25 +1,26 @@ - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/primal__dual_8h__incl.md5 b/primal__dual_8h__incl.md5 index 1876b1f68..def9b9959 100644 --- a/primal__dual_8h__incl.md5 +++ b/primal__dual_8h__incl.md5 @@ -1 +1 @@ -580e599ae24680248a46848c4039c39d \ No newline at end of file +18df7978c4c5f13bd5d4c817dfef110e \ No newline at end of file diff --git a/primal__dual_8h__incl.png b/primal__dual_8h__incl.png index bcc9c46d7..2686d8d17 100644 Binary files a/primal__dual_8h__incl.png and b/primal__dual_8h__incl.png differ diff --git a/primal__dual_8h_source.html b/primal__dual_8h_source.html index 588445972..4d88c378a 100644 --- a/primal__dual_8h_source.html +++ b/primal__dual_8h_source.html @@ -418,11 +418,11 @@
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  -
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:17
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  +
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:211
                  +
                  SOPT_WARN
                  #define SOPT_WARN(...)
                  \macro Something might be going wrong
                  Definition: logging.h:213
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::linear_transform
                  LinearTransform< VECTOR > linear_transform(OperatorFunction< VECTOR > const &direct, OperatorFunction< VECTOR > const &indirect, std::array< t_int, 3 > const &sizes={{1, 1, 0}})
                  Definition: linear_transform.h:101
                  diff --git a/proximal_8cc.html b/proximal_8cc.html index 9843c50e1..a17a1a9ab 100644 --- a/proximal_8cc.html +++ b/proximal_8cc.html @@ -95,33 +95,34 @@
                  diff --git a/proximal_8cc__incl.map b/proximal_8cc__incl.map index 968f08551..41af51b08 100644 --- a/proximal_8cc__incl.map +++ b/proximal_8cc__incl.map @@ -1,29 +1,30 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/proximal_8cc__incl.md5 b/proximal_8cc__incl.md5 index 1a4bfc54b..06660a519 100644 --- a/proximal_8cc__incl.md5 +++ b/proximal_8cc__incl.md5 @@ -1 +1 @@ -a52e019a5c212b117b76e71db87ab7ec \ No newline at end of file +de2cec40a574abc4b048b889153973fb \ No newline at end of file diff --git a/proximal_8cc__incl.png b/proximal_8cc__incl.png index d0923dcbf..f5ac495e7 100644 Binary files a/proximal_8cc__incl.png and b/proximal_8cc__incl.png differ diff --git a/proximal__admm_2euclidian__norm_8cc.html b/proximal__admm_2euclidian__norm_8cc.html index 3911d7101..c2e0eb798 100644 --- a/proximal__admm_2euclidian__norm_8cc.html +++ b/proximal__admm_2euclidian__norm_8cc.html @@ -93,33 +93,34 @@
                  @@ -159,55 +160,52 @@

                  Definition at line 8 of file euclidian_norm.cc.

                  8  {
                  -
                  9  // Initializes and sets logger (if compiled with logging)
                  -
                  10  // See set_level function for levels.
                  -
                  11  sopt::logging::initialize();
                  -
                  12 
                  -
                  13  // Some type aliases for simplicity
                  -
                  14  using t_Scalar = sopt::t_real;
                  -
                  15  using t_Vector = sopt::Vector<t_Scalar>;
                  -
                  16  using t_Matrix = sopt::Matrix<t_Scalar>;
                  -
                  17 
                  -
                  18  // Creates the target vectors
                  -
                  19  auto constexpr N = 5;
                  -
                  20  t_Vector const target0 = t_Vector::Random(N);
                  -
                  21  t_Vector const target1 = t_Vector::Random(N) * 4;
                  -
                  22 
                  -
                  23  // Creates the resulting proximal
                  -
                  24  // In practice g_0 and g_1 are any functions with the signature
                  -
                  25  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  -
                  26  // They are the proximal of ||x - x_0|| and ||x - x_1||
                  -
                  27  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  -
                  28  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  -
                  29 
                  -
                  30  auto padmm = sopt::algorithm::ProximalADMM<t_Scalar>(prox_g0, prox_g1, t_Vector::Zero(N))
                  -
                  31  .itermax(5000)
                  -
                  32  .is_converged(sopt::RelativeVariation<t_Scalar>(1e-12))
                  -
                  33  .gamma(0.01)
                  -
                  34  // Phi == -1, so that we can minimize f(x) + g(x), as per problem definition in
                  -
                  35  // padmm.
                  -
                  36  .Phi(-t_Matrix::Identity(N, N));
                  -
                  37 
                  -
                  38  // Alternatively, padmm can be called with a tuple (x, residual) as argument
                  -
                  39  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  -
                  40  auto const diagnostic = padmm();
                  -
                  41 
                  -
                  42  // diagnostic should tell us the function converged
                  -
                  43  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  44  // diagnostic from the last call to the conjugate gradient.
                  -
                  45  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  -
                  46 
                  -
                  47  // x should be any point on the segment linking x_0 and x_1
                  -
                  48  t_Vector const segment = (target1 - target0).normalized();
                  -
                  49  t_Scalar const alpha = (diagnostic.x - target0).transpose() * segment;
                  -
                  50  if ((target1 - target0).transpose() * segment < alpha)
                  -
                  51  throw std::runtime_error("Point beyond x_1 plane");
                  -
                  52  if (alpha < 0e0) throw std::runtime_error("Point before x_0 plane");
                  -
                  53  if ((diagnostic.x - target0 - alpha * segment).stableNorm() > 1e-8)
                  -
                  54  throw std::runtime_error("Point not on (x_0, x_1) line");
                  -
                  55 
                  -
                  56  return 0;
                  -
                  57 }
                  +
                  9 
                  +
                  10  // Some type aliases for simplicity
                  +
                  11  using t_Scalar = sopt::t_real;
                  +
                  12  using t_Vector = sopt::Vector<t_Scalar>;
                  +
                  13  using t_Matrix = sopt::Matrix<t_Scalar>;
                  +
                  14 
                  +
                  15  // Creates the target vectors
                  +
                  16  auto constexpr N = 5;
                  +
                  17  t_Vector const target0 = t_Vector::Random(N);
                  +
                  18  t_Vector const target1 = t_Vector::Random(N) * 4;
                  +
                  19 
                  +
                  20  // Creates the resulting proximal
                  +
                  21  // In practice g_0 and g_1 are any functions with the signature
                  +
                  22  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  +
                  23  // They are the proximal of ||x - x_0|| and ||x - x_1||
                  +
                  24  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  +
                  25  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  +
                  26 
                  +
                  27  auto padmm = sopt::algorithm::ProximalADMM<t_Scalar>(prox_g0, prox_g1, t_Vector::Zero(N))
                  +
                  28  .itermax(5000)
                  +
                  29  .is_converged(sopt::RelativeVariation<t_Scalar>(1e-12))
                  +
                  30  .gamma(0.01)
                  +
                  31  // Phi == -1, so that we can minimize f(x) + g(x), as per problem definition in
                  +
                  32  // padmm.
                  +
                  33  .Phi(-t_Matrix::Identity(N, N));
                  +
                  34 
                  +
                  35  // Alternatively, padmm can be called with a tuple (x, residual) as argument
                  +
                  36  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  +
                  37  auto const diagnostic = padmm();
                  +
                  38 
                  +
                  39  // diagnostic should tell us the function converged
                  +
                  40  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  41  // diagnostic from the last call to the conjugate gradient.
                  +
                  42  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  43 
                  +
                  44  // x should be any point on the segment linking x_0 and x_1
                  +
                  45  t_Vector const segment = (target1 - target0).normalized();
                  +
                  46  t_Scalar const alpha = (diagnostic.x - target0).transpose() * segment;
                  +
                  47  if ((target1 - target0).transpose() * segment < alpha)
                  +
                  48  throw std::runtime_error("Point beyond x_1 plane");
                  +
                  49  if (alpha < 0e0) throw std::runtime_error("Point before x_0 plane");
                  +
                  50  if ((diagnostic.x - target0 - alpha * segment).stableNorm() > 1e-8)
                  +
                  51  throw std::runtime_error("Point not on (x_0, x_1) line");
                  +
                  52 
                  +
                  53  return 0;
                  +
                  54 }
                  N
                  constexpr auto N
                  Definition: wavelets.cc:57
                  t_Vector
                  sopt::Vector< Scalar > t_Vector
                  Definition: bisection_method.cc:10
                  t_Matrix
                  sopt::Matrix< Scalar > t_Matrix
                  Definition: bisection_method.cc:11
                  @@ -215,13 +213,12 @@

                  sopt::algorithm::ProximalADMM
                  Proximal Alternate Direction method of mutltipliers.
                  Definition: padmm.h:19

                  sopt::algorithm::ProximalADMM::is_converged
                  ProximalADMM< Scalar > & is_converged(std::function< bool(t_Vector const &x)> const &func)
                  Convergence function that takes only the output as argument.
                  Definition: padmm.h:115
                  sopt::proximal::EuclidianNorm
                  Proximal of euclidian norm.
                  Definition: proximal.h:18
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  sopt::proximal::translate
                  Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
                  Translates given proximal by given vector.
                  Definition: proximal.h:362
                  sopt::t_real
                  double t_real
                  Root of the type hierarchy for real numbers.
                  Definition: types.h:17
                  sopt::Vector
                  Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
                  A vector of a given type.
                  Definition: types.h:24
                  sopt::Matrix
                  Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
                  A matrix of a given type.
                  Definition: types.h:29
                  -

                  References sopt::logging::initialize(), sopt::algorithm::ProximalADMM< SCALAR >::is_converged(), N, and sopt::proximal::translate().

                  +

                  References sopt::algorithm::ProximalADMM< SCALAR >::is_converged(), N, and sopt::proximal::translate().

                  diff --git a/proximal__admm_2euclidian__norm_8cc__incl.map b/proximal__admm_2euclidian__norm_8cc__incl.map index a01b86c79..839422e65 100644 --- a/proximal__admm_2euclidian__norm_8cc__incl.map +++ b/proximal__admm_2euclidian__norm_8cc__incl.map @@ -1,29 +1,30 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/proximal__admm_2euclidian__norm_8cc__incl.md5 b/proximal__admm_2euclidian__norm_8cc__incl.md5 index 47b781416..a5a89d273 100644 --- a/proximal__admm_2euclidian__norm_8cc__incl.md5 +++ b/proximal__admm_2euclidian__norm_8cc__incl.md5 @@ -1 +1 @@ -987ec0e82d29e0638bfdb0d89013b014 \ No newline at end of file +4f99728f53b62f42801e2e15f9a9dd2b \ No newline at end of file diff --git a/proximal__admm_2euclidian__norm_8cc__incl.png b/proximal__admm_2euclidian__norm_8cc__incl.png index cd7095761..e9bb3fddd 100644 Binary files a/proximal__admm_2euclidian__norm_8cc__incl.png and b/proximal__admm_2euclidian__norm_8cc__incl.png differ diff --git a/proximal__admm_2euclidian__norm_8cc_source.html b/proximal__admm_2euclidian__norm_8cc_source.html index 036661608..7a434f2e0 100644 --- a/proximal__admm_2euclidian__norm_8cc_source.html +++ b/proximal__admm_2euclidian__norm_8cc_source.html @@ -87,55 +87,52 @@
                  6 
                  7 // We will minimize ||x - x_0|| + ||x - x_1||, ||.|| the euclidian norm
                  8 int main(int, char const **) {
                  -
                  9  // Initializes and sets logger (if compiled with logging)
                  -
                  10  // See set_level function for levels.
                  -
                  11  sopt::logging::initialize();
                  -
                  12 
                  -
                  13  // Some type aliases for simplicity
                  -
                  14  using t_Scalar = sopt::t_real;
                  -
                  15  using t_Vector = sopt::Vector<t_Scalar>;
                  -
                  16  using t_Matrix = sopt::Matrix<t_Scalar>;
                  -
                  17 
                  -
                  18  // Creates the target vectors
                  -
                  19  auto constexpr N = 5;
                  -
                  20  t_Vector const target0 = t_Vector::Random(N);
                  -
                  21  t_Vector const target1 = t_Vector::Random(N) * 4;
                  -
                  22 
                  -
                  23  // Creates the resulting proximal
                  -
                  24  // In practice g_0 and g_1 are any functions with the signature
                  -
                  25  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  -
                  26  // They are the proximal of ||x - x_0|| and ||x - x_1||
                  -
                  27  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  -
                  28  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  -
                  29 
                  -
                  30  auto padmm = sopt::algorithm::ProximalADMM<t_Scalar>(prox_g0, prox_g1, t_Vector::Zero(N))
                  -
                  31  .itermax(5000)
                  -
                  32  .is_converged(sopt::RelativeVariation<t_Scalar>(1e-12))
                  -
                  33  .gamma(0.01)
                  -
                  34  // Phi == -1, so that we can minimize f(x) + g(x), as per problem definition in
                  -
                  35  // padmm.
                  -
                  36  .Phi(-t_Matrix::Identity(N, N));
                  -
                  37 
                  -
                  38  // Alternatively, padmm can be called with a tuple (x, residual) as argument
                  -
                  39  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  -
                  40  auto const diagnostic = padmm();
                  -
                  41 
                  -
                  42  // diagnostic should tell us the function converged
                  -
                  43  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  44  // diagnostic from the last call to the conjugate gradient.
                  -
                  45  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  -
                  46 
                  -
                  47  // x should be any point on the segment linking x_0 and x_1
                  -
                  48  t_Vector const segment = (target1 - target0).normalized();
                  -
                  49  t_Scalar const alpha = (diagnostic.x - target0).transpose() * segment;
                  -
                  50  if ((target1 - target0).transpose() * segment < alpha)
                  -
                  51  throw std::runtime_error("Point beyond x_1 plane");
                  -
                  52  if (alpha < 0e0) throw std::runtime_error("Point before x_0 plane");
                  -
                  53  if ((diagnostic.x - target0 - alpha * segment).stableNorm() > 1e-8)
                  -
                  54  throw std::runtime_error("Point not on (x_0, x_1) line");
                  -
                  55 
                  -
                  56  return 0;
                  -
                  57 }
                  +
                  9 
                  +
                  10  // Some type aliases for simplicity
                  +
                  11  using t_Scalar = sopt::t_real;
                  +
                  12  using t_Vector = sopt::Vector<t_Scalar>;
                  +
                  13  using t_Matrix = sopt::Matrix<t_Scalar>;
                  +
                  14 
                  +
                  15  // Creates the target vectors
                  +
                  16  auto constexpr N = 5;
                  +
                  17  t_Vector const target0 = t_Vector::Random(N);
                  +
                  18  t_Vector const target1 = t_Vector::Random(N) * 4;
                  +
                  19 
                  +
                  20  // Creates the resulting proximal
                  +
                  21  // In practice g_0 and g_1 are any functions with the signature
                  +
                  22  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  +
                  23  // They are the proximal of ||x - x_0|| and ||x - x_1||
                  +
                  24  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  +
                  25  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  +
                  26 
                  +
                  27  auto padmm = sopt::algorithm::ProximalADMM<t_Scalar>(prox_g0, prox_g1, t_Vector::Zero(N))
                  +
                  28  .itermax(5000)
                  +
                  29  .is_converged(sopt::RelativeVariation<t_Scalar>(1e-12))
                  +
                  30  .gamma(0.01)
                  +
                  31  // Phi == -1, so that we can minimize f(x) + g(x), as per problem definition in
                  +
                  32  // padmm.
                  +
                  33  .Phi(-t_Matrix::Identity(N, N));
                  +
                  34 
                  +
                  35  // Alternatively, padmm can be called with a tuple (x, residual) as argument
                  +
                  36  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  +
                  37  auto const diagnostic = padmm();
                  +
                  38 
                  +
                  39  // diagnostic should tell us the function converged
                  +
                  40  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  41  // diagnostic from the last call to the conjugate gradient.
                  +
                  42  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  43 
                  +
                  44  // x should be any point on the segment linking x_0 and x_1
                  +
                  45  t_Vector const segment = (target1 - target0).normalized();
                  +
                  46  t_Scalar const alpha = (diagnostic.x - target0).transpose() * segment;
                  +
                  47  if ((target1 - target0).transpose() * segment < alpha)
                  +
                  48  throw std::runtime_error("Point beyond x_1 plane");
                  +
                  49  if (alpha < 0e0) throw std::runtime_error("Point before x_0 plane");
                  +
                  50  if ((diagnostic.x - target0 - alpha * segment).stableNorm() > 1e-8)
                  +
                  51  throw std::runtime_error("Point not on (x_0, x_1) line");
                  +
                  52 
                  +
                  53  return 0;
                  +
                  54 }
                  N
                  constexpr auto N
                  Definition: wavelets.cc:57
                  t_Vector
                  sopt::Vector< Scalar > t_Vector
                  Definition: bisection_method.cc:10
                  t_Matrix
                  sopt::Matrix< Scalar > t_Matrix
                  Definition: bisection_method.cc:11
                  @@ -143,7 +140,6 @@
                  sopt::algorithm::ProximalADMM
                  Proximal Alternate Direction method of mutltipliers.
                  Definition: padmm.h:19
                  sopt::algorithm::ProximalADMM::is_converged
                  ProximalADMM< Scalar > & is_converged(std::function< bool(t_Vector const &x)> const &func)
                  Convergence function that takes only the output as argument.
                  Definition: padmm.h:115
                  sopt::proximal::EuclidianNorm
                  Proximal of euclidian norm.
                  Definition: proximal.h:18
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  sopt::proximal::translate
                  Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
                  Translates given proximal by given vector.
                  Definition: proximal.h:362
                  sopt::t_real
                  double t_real
                  Root of the type hierarchy for real numbers.
                  Definition: types.h:17
                  sopt::Vector
                  Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
                  A vector of a given type.
                  Definition: types.h:24
                  diff --git a/relative__variation_8h.html b/relative__variation_8h.html index 5aab66f03..e949890a5 100644 --- a/relative__variation_8h.html +++ b/relative__variation_8h.html @@ -94,23 +94,24 @@
                  diff --git a/relative__variation_8h__incl.map b/relative__variation_8h__incl.map index 8463cf070..3fc6ea0ff 100644 --- a/relative__variation_8h__incl.map +++ b/relative__variation_8h__incl.map @@ -1,19 +1,20 @@ - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + diff --git a/relative__variation_8h__incl.md5 b/relative__variation_8h__incl.md5 index d6cf1540f..be6407d64 100644 --- a/relative__variation_8h__incl.md5 +++ b/relative__variation_8h__incl.md5 @@ -1 +1 @@ -f542442f18616b20f5119fdb8f5c6af0 \ No newline at end of file +488e4a4827432150683c9f865c365fb6 \ No newline at end of file diff --git a/relative__variation_8h__incl.png b/relative__variation_8h__incl.png index 5da5bb32d..b30cb6f33 100644 Binary files a/relative__variation_8h__incl.png and b/relative__variation_8h__incl.png differ diff --git a/relative__variation_8h_source.html b/relative__variation_8h_source.html index 535ec1882..9a2eb5b8a 100644 --- a/relative__variation_8h_source.html +++ b/relative__variation_8h_source.html @@ -227,7 +227,7 @@
                  sopt::ScalarRelativeVariation::name
                  std::string const & name() const
                  Name that gets interpolated into the log's output.
                  Definition: relative_variation.h:94
                  sopt::details::underlying_value_type
                  Computes inner-most element type.
                  Definition: real_type.h:42
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  sopt::gradient_operator::diff
                  Vector< T > diff(const Vector< T > &x)
                  Numerical derivative of 1d vector.
                  Definition: gradient_operator.h:11
                  diff --git a/reweighted_8h.html b/reweighted_8h.html index 12770ae5b..a4b3c5b8f 100644 --- a/reweighted_8h.html +++ b/reweighted_8h.html @@ -95,28 +95,29 @@
                  diff --git a/reweighted_8h__incl.map b/reweighted_8h__incl.map index da75ad3fd..652a57998 100644 --- a/reweighted_8h__incl.map +++ b/reweighted_8h__incl.map @@ -1,24 +1,25 @@ - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + diff --git a/reweighted_8h__incl.md5 b/reweighted_8h__incl.md5 index 0de227e9b..e28e819f5 100644 --- a/reweighted_8h__incl.md5 +++ b/reweighted_8h__incl.md5 @@ -1 +1 @@ -f2e8a579b75165000db051700a3f89e8 \ No newline at end of file +8c54606f91d6512bdf2bfab788872303 \ No newline at end of file diff --git a/reweighted_8h__incl.png b/reweighted_8h__incl.png index 8a28df84b..792a46715 100644 Binary files a/reweighted_8h__incl.png and b/reweighted_8h__incl.png differ diff --git a/reweighted_8h_source.html b/reweighted_8h_source.html index 7087329d9..12854acd0 100644 --- a/reweighted_8h_source.html +++ b/reweighted_8h_source.html @@ -349,10 +349,10 @@
                  sopt::algorithm::Reweighted::t_IsConverged
                  ConvergenceFunction< Scalar > t_IsConverged
                  Type of the convergence function.
                  Definition: reweighted.h:47
                  sopt::details::underlying_value_type
                  Computes inner-most element type.
                  Definition: real_type.h:42
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  +
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:211
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::algorithm::positive_quadrant
                  PositiveQuadrant< ALGORITHM > positive_quadrant(ALGORITHM const &algo)
                  Extended algorithm where the solution is projected on the positive quadrant.
                  Definition: positive_quadrant.h:59
                  sopt::algorithm::reweighted
                  Reweighted< ALGORITHM > reweighted(ALGORITHM const &algo, typename Reweighted< ALGORITHM >::t_SetWeights const &set_weights, typename Reweighted< ALGORITHM >::t_Reweightee const &reweightee)
                  Factory function to create an l0-approximation by reweighting an l1 norm.
                  Definition: reweighted.h:238
                  diff --git a/sampling_8cc.html b/sampling_8cc.html index de4a121d0..1ed8fc62a 100644 --- a/sampling_8cc.html +++ b/sampling_8cc.html @@ -89,31 +89,32 @@
                  diff --git a/sampling_8cc__incl.map b/sampling_8cc__incl.map index c78b3b7a9..d3b39de71 100644 --- a/sampling_8cc__incl.map +++ b/sampling_8cc__incl.map @@ -1,27 +1,28 @@ - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/sampling_8cc__incl.md5 b/sampling_8cc__incl.md5 index 58c6f941f..8a8d3835f 100644 --- a/sampling_8cc__incl.md5 +++ b/sampling_8cc__incl.md5 @@ -1 +1 @@ -e3bff0da0ecdaf8ff0f21c5d488b5032 \ No newline at end of file +9d6b37c552739f44d13b542edc30ad66 \ No newline at end of file diff --git a/sampling_8cc__incl.png b/sampling_8cc__incl.png index b9ae39f90..ea5750de8 100644 Binary files a/sampling_8cc__incl.png and b/sampling_8cc__incl.png differ diff --git a/sampling_8h.html b/sampling_8h.html index d768538a5..2ec74a9e2 100644 --- a/sampling_8h.html +++ b/sampling_8h.html @@ -98,30 +98,31 @@
                  diff --git a/sampling_8h__incl.map b/sampling_8h__incl.map index e53a981f8..35c1b4aae 100644 --- a/sampling_8h__incl.map +++ b/sampling_8h__incl.map @@ -1,26 +1,27 @@ - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/sampling_8h__incl.md5 b/sampling_8h__incl.md5 index 9bd5d1417..5e621980d 100644 --- a/sampling_8h__incl.md5 +++ b/sampling_8h__incl.md5 @@ -1 +1 @@ -da864c892d11a7c4f12e8ca7175f9ad2 \ No newline at end of file +f975f2ddaf78f3d981064d3d3717e3c2 \ No newline at end of file diff --git a/sampling_8h__incl.png b/sampling_8h__incl.png index d8c7156cc..70f5268be 100644 Binary files a/sampling_8h__incl.png and b/sampling_8h__incl.png differ diff --git a/sara_8h.html b/sara_8h.html index fc6c7f13f..6a630c9c3 100644 --- a/sara_8h.html +++ b/sara_8h.html @@ -99,28 +99,32 @@
                  diff --git a/sara_8h__incl.map b/sara_8h__incl.map index 9cd99f359..ea0b71845 100644 --- a/sara_8h__incl.map +++ b/sara_8h__incl.map @@ -1,24 +1,28 @@ - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/sara_8h__incl.md5 b/sara_8h__incl.md5 index fb89f10ce..96e42843b 100644 --- a/sara_8h__incl.md5 +++ b/sara_8h__incl.md5 @@ -1 +1 @@ -57fdb4d5a49306b7ad63b3fa53089b46 \ No newline at end of file +b3b469da9809f65e413b33a58a82c4d2 \ No newline at end of file diff --git a/sara_8h__incl.png b/sara_8h__incl.png index a7d10a3e9..b7c89fbba 100644 Binary files a/sara_8h__incl.png and b/sara_8h__incl.png differ diff --git a/sara_8h_source.html b/sara_8h_source.html index 9a4b927eb..fc9716886 100644 --- a/sara_8h_source.html +++ b/sara_8h_source.html @@ -258,7 +258,7 @@
                  sopt::wavelets::Wavelet
                  Performs direct and indirect wavelet transforms.
                  Definition: wavelets.h:21
                  -
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:24
                  +
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
                  sopt::mpi::init
                  std::shared_ptr< details::initializer > init(int argc, const char **argv)
                  Definition: session.cc:27
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  diff --git a/sdmm_2euclidian__norm_8cc.html b/sdmm_2euclidian__norm_8cc.html index ad01ceced..b13e7befb 100644 --- a/sdmm_2euclidian__norm_8cc.html +++ b/sdmm_2euclidian__norm_8cc.html @@ -91,34 +91,35 @@
                  @@ -158,103 +159,99 @@

                  Definition at line 6 of file euclidian_norm.cc.

                  6  {
                  -
                  7  // Initializes and sets logger (if compiled with logging)
                  -
                  8  // See set_level function for levels.
                  -
                  9  sopt::logging::initialize();
                  -
                  10 
                  -
                  11  // Some type aliases for simplicity
                  -
                  12  using t_Scalar = sopt::t_complex;
                  -
                  13  using t_Vector = sopt::Vector<t_Scalar>;
                  -
                  14  using t_Matrix = sopt::Matrix<t_Scalar>;
                  -
                  15 
                  -
                  16  // Creates the transformation matrices
                  -
                  17  auto constexpr N = 10;
                  -
                  18  t_Matrix const L0 = t_Matrix::Random(N, N) * 2;
                  -
                  19  t_Matrix const L1 = t_Matrix::Random(N, N) * 4;
                  -
                  20  // L1_direct and L1_adjoint are used to demonstrate that we can define L_i in SDMM both directly
                  -
                  21  // as matrices, or as a pair of functions that apply a linear operator and its transpose.
                  -
                  22  auto L1_direct = [&L1](t_Vector &out, t_Vector const &input) { out = L1 * input; };
                  -
                  23  auto L1_adjoint = [&L1](t_Vector &out, t_Vector const &input) { out = L1.adjoint() * input; };
                  -
                  24  // Creates the target vectors
                  -
                  25  t_Vector const target0 = t_Vector::Random(N);
                  -
                  26  t_Vector const target1 = t_Vector::Random(N);
                  -
                  27 
                  -
                  28  // Creates the resulting proximal
                  -
                  29  // In practice g_0 and g_1 are any functions with the signature
                  -
                  30  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  -
                  31  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  -
                  32  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  -
                  33 
                  -
                  34  // This function is called at every iteration. It should return true when convergence is achieved.
                  -
                  35  // Otherwise the convex optimizer will trudge on until the requisite number of iterations have
                  -
                  36  // been achieved.
                  -
                  37  // It takes the convex minimizer and the current candidate output vector as arguments.
                  -
                  38  // The example below assumes convergence when the candidate vector does not change anymore.
                  -
                  39  std::shared_ptr<t_Vector> previous;
                  -
                  40  auto relative = [&previous](t_Vector const &candidate) {
                  -
                  41  if (not previous) {
                  -
                  42  previous = std::make_shared<t_Vector>(candidate);
                  -
                  43  return false;
                  -
                  44  }
                  -
                  45  auto const norm = (*previous - candidate).stableNorm();
                  -
                  46  SOPT_TRACE(" - Checking convergence {}", norm);
                  -
                  47  auto const result = norm < 1e-8 * candidate.size();
                  -
                  48  *previous = candidate;
                  -
                  49  return result;
                  -
                  50  };
                  -
                  51 
                  -
                  52  // Now we can create the sdmm convex minimizer
                  -
                  53  // Its parameters are set by calling member functions with appropriate names.
                  -
                  54  auto sdmm = sopt::algorithm::SDMM<t_Scalar>()
                  -
                  55  .itermax(500) // maximum number of iterations
                  -
                  56  .gamma(1)
                  -
                  57  .conjugate_gradient(std::numeric_limits<sopt::t_uint>::max(), 1e-12)
                  -
                  58  .is_converged(relative)
                  -
                  59  // Any number of (proximal g_i, L_i) pairs can be added
                  -
                  60  // L_i can be a matrix
                  -
                  61  .append(prox_g0, L0)
                  -
                  62  // L_i can be a pair of functions applying a linear transform and its adjoint
                  -
                  63  .append(prox_g1, L1_direct, L1_adjoint);
                  -
                  64 
                  -
                  65  t_Vector result;
                  -
                  66  t_Vector const input = t_Vector::Random(N);
                  -
                  67  auto const diagnostic = sdmm(result, input);
                  -
                  68 
                  -
                  69  // diagnostic should tell us the function converged
                  -
                  70  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  71  // diagnostic from the last call to the conjugate gradient.
                  -
                  72  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  -
                  73 
                  -
                  74  // Lets test we are at a minimum by recreating the objective function
                  -
                  75  // and checking that stepping in any direction raises its value
                  -
                  76  auto const objective = [&target0, &target1, &L0, &L1](t_Vector const &x) {
                  -
                  77  return (L0 * x - target0).norm() + (L1 * x - target1).norm();
                  -
                  78  };
                  -
                  79  auto const minimum = objective(result);
                  -
                  80  for (int i(0); i < N; ++i) {
                  -
                  81  t_Vector epsilon = t_Vector::Zero(N);
                  -
                  82  epsilon(i) = 1e-4;
                  -
                  83  auto const at_x_plus_epsilon = objective(input + epsilon);
                  -
                  84  if (minimum >= at_x_plus_epsilon) throw std::runtime_error("That's no minimum!");
                  -
                  85  }
                  -
                  86 
                  -
                  87  return 0;
                  -
                  88 }
                  +
                  7 
                  +
                  8  // Some type aliases for simplicity
                  +
                  9  using t_Scalar = sopt::t_complex;
                  +
                  10  using t_Vector = sopt::Vector<t_Scalar>;
                  +
                  11  using t_Matrix = sopt::Matrix<t_Scalar>;
                  +
                  12 
                  +
                  13  // Creates the transformation matrices
                  +
                  14  auto constexpr N = 10;
                  +
                  15  t_Matrix const L0 = t_Matrix::Random(N, N) * 2;
                  +
                  16  t_Matrix const L1 = t_Matrix::Random(N, N) * 4;
                  +
                  17  // L1_direct and L1_adjoint are used to demonstrate that we can define L_i in SDMM both directly
                  +
                  18  // as matrices, or as a pair of functions that apply a linear operator and its transpose.
                  +
                  19  auto L1_direct = [&L1](t_Vector &out, t_Vector const &input) { out = L1 * input; };
                  +
                  20  auto L1_adjoint = [&L1](t_Vector &out, t_Vector const &input) { out = L1.adjoint() * input; };
                  +
                  21  // Creates the target vectors
                  +
                  22  t_Vector const target0 = t_Vector::Random(N);
                  +
                  23  t_Vector const target1 = t_Vector::Random(N);
                  +
                  24 
                  +
                  25  // Creates the resulting proximal
                  +
                  26  // In practice g_0 and g_1 are any functions with the signature
                  +
                  27  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  +
                  28  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  +
                  29  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  +
                  30 
                  +
                  31  // This function is called at every iteration. It should return true when convergence is achieved.
                  +
                  32  // Otherwise the convex optimizer will trudge on until the requisite number of iterations have
                  +
                  33  // been achieved.
                  +
                  34  // It takes the convex minimizer and the current candidate output vector as arguments.
                  +
                  35  // The example below assumes convergence when the candidate vector does not change anymore.
                  +
                  36  std::shared_ptr<t_Vector> previous;
                  +
                  37  auto relative = [&previous](t_Vector const &candidate) {
                  +
                  38  if (not previous) {
                  +
                  39  previous = std::make_shared<t_Vector>(candidate);
                  +
                  40  return false;
                  +
                  41  }
                  +
                  42  auto const norm = (*previous - candidate).stableNorm();
                  +
                  43  SOPT_TRACE(" - Checking convergence {}", norm);
                  +
                  44  auto const result = norm < 1e-8 * candidate.size();
                  +
                  45  *previous = candidate;
                  +
                  46  return result;
                  +
                  47  };
                  +
                  48 
                  +
                  49  // Now we can create the sdmm convex minimizer
                  +
                  50  // Its parameters are set by calling member functions with appropriate names.
                  +
                  51  auto sdmm = sopt::algorithm::SDMM<t_Scalar>()
                  +
                  52  .itermax(500) // maximum number of iterations
                  +
                  53  .gamma(1)
                  +
                  54  .conjugate_gradient(std::numeric_limits<sopt::t_uint>::max(), 1e-12)
                  +
                  55  .is_converged(relative)
                  +
                  56  // Any number of (proximal g_i, L_i) pairs can be added
                  +
                  57  // L_i can be a matrix
                  +
                  58  .append(prox_g0, L0)
                  +
                  59  // L_i can be a pair of functions applying a linear transform and its adjoint
                  +
                  60  .append(prox_g1, L1_direct, L1_adjoint);
                  +
                  61 
                  +
                  62  t_Vector result;
                  +
                  63  t_Vector const input = t_Vector::Random(N);
                  +
                  64  auto const diagnostic = sdmm(result, input);
                  +
                  65 
                  +
                  66  // diagnostic should tell us the function converged
                  +
                  67  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  68  // diagnostic from the last call to the conjugate gradient.
                  +
                  69  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  70 
                  +
                  71  // Lets test we are at a minimum by recreating the objective function
                  +
                  72  // and checking that stepping in any direction raises its value
                  +
                  73  auto const objective = [&target0, &target1, &L0, &L1](t_Vector const &x) {
                  +
                  74  return (L0 * x - target0).norm() + (L1 * x - target1).norm();
                  +
                  75  };
                  +
                  76  auto const minimum = objective(result);
                  +
                  77  for (int i(0); i < N; ++i) {
                  +
                  78  t_Vector epsilon = t_Vector::Zero(N);
                  +
                  79  epsilon(i) = 1e-4;
                  +
                  80  auto const at_x_plus_epsilon = objective(input + epsilon);
                  +
                  81  if (minimum >= at_x_plus_epsilon) throw std::runtime_error("That's no minimum!");
                  +
                  82  }
                  +
                  83 
                  +
                  84  return 0;
                  +
                  85 }
                  N
                  constexpr auto N
                  Definition: wavelets.cc:57
                  t_Vector
                  sopt::Vector< Scalar > t_Vector
                  Definition: bisection_method.cc:10
                  t_Matrix
                  sopt::Matrix< Scalar > t_Matrix
                  Definition: bisection_method.cc:11
                  sopt::algorithm::SDMM
                  Simultaneous-direction method of the multipliers.
                  Definition: sdmm.h:23
                  sopt::algorithm::SDMM::conjugate_gradient
                  SDMM< SCALAR > & conjugate_gradient(t_uint itermax, t_real tolerance)
                  Helps setup conjugate gradient.
                  Definition: sdmm.h:83
                  sopt::proximal::EuclidianNorm
                  Proximal of euclidian norm.
                  Definition: proximal.h:18
                  -
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:24
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
                  sopt::proximal::translate
                  Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
                  Translates given proximal by given vector.
                  Definition: proximal.h:362
                  sopt::epsilon
                  real_type< T >::type epsilon(sopt::LinearTransform< Vector< T >> const &sampling, sopt::Image< T > const &image)
                  Definition: inpainting.h:38
                  sopt::Vector
                  Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
                  A vector of a given type.
                  Definition: types.h:24
                  sopt::t_complex
                  std::complex< t_real > t_complex
                  Root of the type hierarchy for (real) complex numbers.
                  Definition: types.h:19
                  sopt::Matrix
                  Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
                  A matrix of a given type.
                  Definition: types.h:29
                  -

                  References sopt::algorithm::SDMM< SCALAR >::conjugate_gradient(), sopt::epsilon(), sopt::logging::initialize(), N, SOPT_TRACE, and sopt::proximal::translate().

                  +

                  References sopt::algorithm::SDMM< SCALAR >::conjugate_gradient(), sopt::epsilon(), N, SOPT_TRACE, and sopt::proximal::translate().

                  diff --git a/sdmm_2euclidian__norm_8cc__incl.map b/sdmm_2euclidian__norm_8cc__incl.map index 4b4131367..85d2d890e 100644 --- a/sdmm_2euclidian__norm_8cc__incl.map +++ b/sdmm_2euclidian__norm_8cc__incl.map @@ -1,30 +1,31 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/sdmm_2euclidian__norm_8cc__incl.md5 b/sdmm_2euclidian__norm_8cc__incl.md5 index 988cd98bb..eea9890a2 100644 --- a/sdmm_2euclidian__norm_8cc__incl.md5 +++ b/sdmm_2euclidian__norm_8cc__incl.md5 @@ -1 +1 @@ -732e02046f25ea851fa757b02a4fbd46 \ No newline at end of file +88ed3f13de894fd817ac963d644f4442 \ No newline at end of file diff --git a/sdmm_2euclidian__norm_8cc__incl.png b/sdmm_2euclidian__norm_8cc__incl.png index 85d8c7447..9cb9dcfab 100644 Binary files a/sdmm_2euclidian__norm_8cc__incl.png and b/sdmm_2euclidian__norm_8cc__incl.png differ diff --git a/sdmm_2euclidian__norm_8cc_source.html b/sdmm_2euclidian__norm_8cc_source.html index 75b1a3515..7e9a7012c 100644 --- a/sdmm_2euclidian__norm_8cc_source.html +++ b/sdmm_2euclidian__norm_8cc_source.html @@ -85,96 +85,92 @@
                  4 
                  5 // We will minimize ||L_0 x - x_0|| + ||L_1 x - x_1||, ||.|| the euclidian norm
                  6 int main(int, char const **) {
                  -
                  7  // Initializes and sets logger (if compiled with logging)
                  -
                  8  // See set_level function for levels.
                  -
                  9  sopt::logging::initialize();
                  -
                  10 
                  -
                  11  // Some type aliases for simplicity
                  -
                  12  using t_Scalar = sopt::t_complex;
                  -
                  13  using t_Vector = sopt::Vector<t_Scalar>;
                  -
                  14  using t_Matrix = sopt::Matrix<t_Scalar>;
                  -
                  15 
                  -
                  16  // Creates the transformation matrices
                  -
                  17  auto constexpr N = 10;
                  -
                  18  t_Matrix const L0 = t_Matrix::Random(N, N) * 2;
                  -
                  19  t_Matrix const L1 = t_Matrix::Random(N, N) * 4;
                  -
                  20  // L1_direct and L1_adjoint are used to demonstrate that we can define L_i in SDMM both directly
                  -
                  21  // as matrices, or as a pair of functions that apply a linear operator and its transpose.
                  -
                  22  auto L1_direct = [&L1](t_Vector &out, t_Vector const &input) { out = L1 * input; };
                  -
                  23  auto L1_adjoint = [&L1](t_Vector &out, t_Vector const &input) { out = L1.adjoint() * input; };
                  -
                  24  // Creates the target vectors
                  -
                  25  t_Vector const target0 = t_Vector::Random(N);
                  -
                  26  t_Vector const target1 = t_Vector::Random(N);
                  -
                  27 
                  -
                  28  // Creates the resulting proximal
                  -
                  29  // In practice g_0 and g_1 are any functions with the signature
                  -
                  30  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  -
                  31  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  -
                  32  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  -
                  33 
                  -
                  34  // This function is called at every iteration. It should return true when convergence is achieved.
                  -
                  35  // Otherwise the convex optimizer will trudge on until the requisite number of iterations have
                  -
                  36  // been achieved.
                  -
                  37  // It takes the convex minimizer and the current candidate output vector as arguments.
                  -
                  38  // The example below assumes convergence when the candidate vector does not change anymore.
                  -
                  39  std::shared_ptr<t_Vector> previous;
                  -
                  40  auto relative = [&previous](t_Vector const &candidate) {
                  -
                  41  if (not previous) {
                  -
                  42  previous = std::make_shared<t_Vector>(candidate);
                  -
                  43  return false;
                  -
                  44  }
                  -
                  45  auto const norm = (*previous - candidate).stableNorm();
                  -
                  46  SOPT_TRACE(" - Checking convergence {}", norm);
                  -
                  47  auto const result = norm < 1e-8 * candidate.size();
                  -
                  48  *previous = candidate;
                  -
                  49  return result;
                  -
                  50  };
                  -
                  51 
                  -
                  52  // Now we can create the sdmm convex minimizer
                  -
                  53  // Its parameters are set by calling member functions with appropriate names.
                  -
                  54  auto sdmm = sopt::algorithm::SDMM<t_Scalar>()
                  -
                  55  .itermax(500) // maximum number of iterations
                  -
                  56  .gamma(1)
                  -
                  57  .conjugate_gradient(std::numeric_limits<sopt::t_uint>::max(), 1e-12)
                  -
                  58  .is_converged(relative)
                  -
                  59  // Any number of (proximal g_i, L_i) pairs can be added
                  -
                  60  // L_i can be a matrix
                  -
                  61  .append(prox_g0, L0)
                  -
                  62  // L_i can be a pair of functions applying a linear transform and its adjoint
                  -
                  63  .append(prox_g1, L1_direct, L1_adjoint);
                  -
                  64 
                  -
                  65  t_Vector result;
                  -
                  66  t_Vector const input = t_Vector::Random(N);
                  -
                  67  auto const diagnostic = sdmm(result, input);
                  -
                  68 
                  -
                  69  // diagnostic should tell us the function converged
                  -
                  70  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  71  // diagnostic from the last call to the conjugate gradient.
                  -
                  72  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  -
                  73 
                  -
                  74  // Lets test we are at a minimum by recreating the objective function
                  -
                  75  // and checking that stepping in any direction raises its value
                  -
                  76  auto const objective = [&target0, &target1, &L0, &L1](t_Vector const &x) {
                  -
                  77  return (L0 * x - target0).norm() + (L1 * x - target1).norm();
                  -
                  78  };
                  -
                  79  auto const minimum = objective(result);
                  -
                  80  for (int i(0); i < N; ++i) {
                  -
                  81  t_Vector epsilon = t_Vector::Zero(N);
                  -
                  82  epsilon(i) = 1e-4;
                  -
                  83  auto const at_x_plus_epsilon = objective(input + epsilon);
                  -
                  84  if (minimum >= at_x_plus_epsilon) throw std::runtime_error("That's no minimum!");
                  -
                  85  }
                  -
                  86 
                  -
                  87  return 0;
                  -
                  88 }
                  +
                  7 
                  +
                  8  // Some type aliases for simplicity
                  +
                  9  using t_Scalar = sopt::t_complex;
                  +
                  10  using t_Vector = sopt::Vector<t_Scalar>;
                  +
                  11  using t_Matrix = sopt::Matrix<t_Scalar>;
                  +
                  12 
                  +
                  13  // Creates the transformation matrices
                  +
                  14  auto constexpr N = 10;
                  +
                  15  t_Matrix const L0 = t_Matrix::Random(N, N) * 2;
                  +
                  16  t_Matrix const L1 = t_Matrix::Random(N, N) * 4;
                  +
                  17  // L1_direct and L1_adjoint are used to demonstrate that we can define L_i in SDMM both directly
                  +
                  18  // as matrices, or as a pair of functions that apply a linear operator and its transpose.
                  +
                  19  auto L1_direct = [&L1](t_Vector &out, t_Vector const &input) { out = L1 * input; };
                  +
                  20  auto L1_adjoint = [&L1](t_Vector &out, t_Vector const &input) { out = L1.adjoint() * input; };
                  +
                  21  // Creates the target vectors
                  +
                  22  t_Vector const target0 = t_Vector::Random(N);
                  +
                  23  t_Vector const target1 = t_Vector::Random(N);
                  +
                  24 
                  +
                  25  // Creates the resulting proximal
                  +
                  26  // In practice g_0 and g_1 are any functions with the signature
                  +
                  27  // void(t_Vector &output, t_Vector::Scalar gamma, t_Vector const &input)
                  +
                  28  auto prox_g0 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target0);
                  +
                  29  auto prox_g1 = sopt::proximal::translate(sopt::proximal::EuclidianNorm(), -target1);
                  +
                  30 
                  +
                  31  // This function is called at every iteration. It should return true when convergence is achieved.
                  +
                  32  // Otherwise the convex optimizer will trudge on until the requisite number of iterations have
                  +
                  33  // been achieved.
                  +
                  34  // It takes the convex minimizer and the current candidate output vector as arguments.
                  +
                  35  // The example below assumes convergence when the candidate vector does not change anymore.
                  +
                  36  std::shared_ptr<t_Vector> previous;
                  +
                  37  auto relative = [&previous](t_Vector const &candidate) {
                  +
                  38  if (not previous) {
                  +
                  39  previous = std::make_shared<t_Vector>(candidate);
                  +
                  40  return false;
                  +
                  41  }
                  +
                  42  auto const norm = (*previous - candidate).stableNorm();
                  +
                  43  SOPT_TRACE(" - Checking convergence {}", norm);
                  +
                  44  auto const result = norm < 1e-8 * candidate.size();
                  +
                  45  *previous = candidate;
                  +
                  46  return result;
                  +
                  47  };
                  +
                  48 
                  +
                  49  // Now we can create the sdmm convex minimizer
                  +
                  50  // Its parameters are set by calling member functions with appropriate names.
                  +
                  51  auto sdmm = sopt::algorithm::SDMM<t_Scalar>()
                  +
                  52  .itermax(500) // maximum number of iterations
                  +
                  53  .gamma(1)
                  +
                  54  .conjugate_gradient(std::numeric_limits<sopt::t_uint>::max(), 1e-12)
                  +
                  55  .is_converged(relative)
                  +
                  56  // Any number of (proximal g_i, L_i) pairs can be added
                  +
                  57  // L_i can be a matrix
                  +
                  58  .append(prox_g0, L0)
                  +
                  59  // L_i can be a pair of functions applying a linear transform and its adjoint
                  +
                  60  .append(prox_g1, L1_direct, L1_adjoint);
                  +
                  61 
                  +
                  62  t_Vector result;
                  +
                  63  t_Vector const input = t_Vector::Random(N);
                  +
                  64  auto const diagnostic = sdmm(result, input);
                  +
                  65 
                  +
                  66  // diagnostic should tell us the function converged
                  +
                  67  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  68  // diagnostic from the last call to the conjugate gradient.
                  +
                  69  if (not diagnostic.good) throw std::runtime_error("Did not converge!");
                  +
                  70 
                  +
                  71  // Lets test we are at a minimum by recreating the objective function
                  +
                  72  // and checking that stepping in any direction raises its value
                  +
                  73  auto const objective = [&target0, &target1, &L0, &L1](t_Vector const &x) {
                  +
                  74  return (L0 * x - target0).norm() + (L1 * x - target1).norm();
                  +
                  75  };
                  +
                  76  auto const minimum = objective(result);
                  +
                  77  for (int i(0); i < N; ++i) {
                  +
                  78  t_Vector epsilon = t_Vector::Zero(N);
                  +
                  79  epsilon(i) = 1e-4;
                  +
                  80  auto const at_x_plus_epsilon = objective(input + epsilon);
                  +
                  81  if (minimum >= at_x_plus_epsilon) throw std::runtime_error("That's no minimum!");
                  +
                  82  }
                  +
                  83 
                  +
                  84  return 0;
                  +
                  85 }
                  N
                  constexpr auto N
                  Definition: wavelets.cc:57
                  t_Vector
                  sopt::Vector< Scalar > t_Vector
                  Definition: bisection_method.cc:10
                  t_Matrix
                  sopt::Matrix< Scalar > t_Matrix
                  Definition: bisection_method.cc:11
                  sopt::algorithm::SDMM
                  Simultaneous-direction method of the multipliers.
                  Definition: sdmm.h:23
                  sopt::algorithm::SDMM::conjugate_gradient
                  SDMM< SCALAR > & conjugate_gradient(t_uint itermax, t_real tolerance)
                  Helps setup conjugate gradient.
                  Definition: sdmm.h:83
                  sopt::proximal::EuclidianNorm
                  Proximal of euclidian norm.
                  Definition: proximal.h:18
                  -
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:24
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
                  sopt::proximal::translate
                  Translation< FUNCTION, VECTOR > translate(FUNCTION const &func, VECTOR const &translation)
                  Translates given proximal by given vector.
                  Definition: proximal.h:362
                  sopt::epsilon
                  real_type< T >::type epsilon(sopt::LinearTransform< Vector< T >> const &sampling, sopt::Image< T > const &image)
                  Definition: inpainting.h:38
                  sopt::Vector
                  Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
                  A vector of a given type.
                  Definition: types.h:24
                  diff --git a/sdmm_8cc.html b/sdmm_8cc.html index cb9dd52c0..614ee9ae4 100644 --- a/sdmm_8cc.html +++ b/sdmm_8cc.html @@ -97,37 +97,38 @@
                  diff --git a/sdmm_8cc__incl.map b/sdmm_8cc__incl.map index 06a0d1f16..e6a3743f1 100644 --- a/sdmm_8cc__incl.map +++ b/sdmm_8cc__incl.map @@ -1,33 +1,34 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/sdmm_8cc__incl.md5 b/sdmm_8cc__incl.md5 index 63c67f8f4..5ce79d0e7 100644 --- a/sdmm_8cc__incl.md5 +++ b/sdmm_8cc__incl.md5 @@ -1 +1 @@ -5a62b07a2ba325f064e8912b17324243 \ No newline at end of file +7e91be619a9aaa0401e37ebb22d06f85 \ No newline at end of file diff --git a/sdmm_8cc__incl.png b/sdmm_8cc__incl.png index d4f7e7e3b..0657bf7d0 100644 Binary files a/sdmm_8cc__incl.png and b/sdmm_8cc__incl.png differ diff --git a/sdmm_8h.html b/sdmm_8h.html index a4f290424..33a17f6f0 100644 --- a/sdmm_8h.html +++ b/sdmm_8h.html @@ -103,33 +103,34 @@
                  diff --git a/sdmm_8h__incl.map b/sdmm_8h__incl.map index 6a03a1426..73486400b 100644 --- a/sdmm_8h__incl.map +++ b/sdmm_8h__incl.map @@ -1,29 +1,30 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/sdmm_8h__incl.md5 b/sdmm_8h__incl.md5 index ed35fd6c7..8d9843498 100644 --- a/sdmm_8h__incl.md5 +++ b/sdmm_8h__incl.md5 @@ -1 +1 @@ -52a2b948750c715097d49061f3940ded \ No newline at end of file +55f2fb7a839c904e8c1832c565e9ebf5 \ No newline at end of file diff --git a/sdmm_8h__incl.png b/sdmm_8h__incl.png index 9f70f0d3a..9c9d9391c 100644 Binary files a/sdmm_8h__incl.png and b/sdmm_8h__incl.png differ diff --git a/sdmm_8h_source.html b/sdmm_8h_source.html index 7c8cf4ba7..c978f1ad7 100644 --- a/sdmm_8h_source.html +++ b/sdmm_8h_source.html @@ -384,11 +384,11 @@
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  -
                  SOPT_TRACE
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                  Definition: logging.h:24
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                  \macro Something might be going wrong
                  Definition: logging.h:17
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                  Low priority message.
                  Definition: logging.h:227
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                  High priority message.
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                  Definition: logging.h:211
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                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
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                  Definition: logging.h:213
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                  Definition: linear_transform.h:101
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                  sopt::algorithm::ImagingProximalADMM::l2ball_proximal
                  proximal::WeightedL2Ball< Scalar > & l2ball_proximal()
                  Proximal of the L2 ball.
                  Definition: imaging_padmm.h:190
                  mersenne
                  std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  @@ -319,7 +319,7 @@

                  sopt::l1_norm
                  real_type< typename T0::Scalar >::type l1_norm(Eigen::ArrayBase< T0 > const &input, Eigen::ArrayBase< T1 > const &weights)
                  Computes weighted L1 norm.
                  Definition: maths.h:116
                  sopt::l2_norm
                  real_type< typename T0::Scalar >::type l2_norm(Eigen::ArrayBase< T0 > const &input, Eigen::ArrayBase< T1 > const &weights)
                  Computes weighted L2 norm.
                  Definition: maths.h:140
                  -

                  References sopt::epsilon(), sopt::wavelets::factory(), sopt::Sampling::indices(), sopt::l1_norm(), sopt::l2_norm(), sopt::algorithm::ImagingProximalADMM< SCALAR >::l2ball_proximal(), mersenne(), N, sopt::notinstalled::read_standard_tiff(), sopt::sigma(), and SOPT_LOW_LOG.

                  +

                  References sopt::epsilon(), sopt::wavelets::factory(), sopt::Sampling::indices(), sopt::l1_norm(), sopt::l2_norm(), sopt::algorithm::ImagingProximalADMM< SCALAR >::l2ball_proximal(), mersenne(), N, sopt::notinstalled::read_standard_tiff(), sopt::sigma(), and SOPT_LOW_LOG.

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                  imaging_padmm.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  diff --git a/session_8cc.html b/session_8cc.html index 2dea82368..0ee8b31bc 100644 --- a/session_8cc.html +++ b/session_8cc.html @@ -95,23 +95,24 @@ diff --git a/session_8cc__incl.map b/session_8cc__incl.map index 3187e81e9..af400e65b 100644 --- a/session_8cc__incl.map +++ b/session_8cc__incl.map @@ -1,19 +1,20 @@ - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + diff --git a/session_8cc__incl.md5 b/session_8cc__incl.md5 index 0aef0eeb9..cea01ddba 100644 --- a/session_8cc__incl.md5 +++ b/session_8cc__incl.md5 @@ -1 +1 @@ -88c69c8154d5ea8a46e35ed44cb24c0b \ No newline at end of file +b65e8ee21b73f5d81d9f8976bda14d64 \ No newline at end of file diff --git a/session_8cc__incl.png b/session_8cc__incl.png index 53600a176..45ee890b8 100644 Binary files a/session_8cc__incl.png and b/session_8cc__incl.png differ diff --git a/session_8cc_source.html b/session_8cc_source.html index 05e5d3d53..d80654c42 100644 --- a/session_8cc_source.html +++ b/session_8cc_source.html @@ -164,7 +164,7 @@
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  -
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:15
                  +
                  SOPT_ERROR
                  #define SOPT_ERROR(...)
                  \macro Something is definitely wrong, algorithm exits
                  Definition: logging.h:211
                  sopt::mpi::finalized
                  bool finalized()
                  Definition: session.cc:71
                  sopt::mpi::session_singleton
                  std::shared_ptr< details::initializer > session_singleton()
                  Definition: session.cc:50
                  diff --git a/sopt.tag b/sopt.tag index cb947520d..416eee901 100644 --- a/sopt.tag +++ b/sopt.tag @@ -987,13 +987,6 @@ a7d4a92230a7a1fea0033bf12c848c2b8 () - - constexpr bool - color_logger - http://astro-informatics.github.io/sopt/namespacesopt.html - a8665e2e558cf502796c385e0b350d54d - () - constexpr std::size_t number_of_threads_in_tests @@ -1525,144 +1518,49 @@ - logging.disabled.h + logging.cc /home/runner/work/sopt/sopt/cpp/sopt/ - http://astro-informatics.github.io/sopt/logging_8disabled_8h.html + http://astro-informatics.github.io/sopt/logging_8cc.html + sopt/logging.h sopt sopt::logging - - #define - SOPT_LOG_ - logging_8disabled_8h.html - aa64f240f46ed8708082955c6d66ff13f - (...) - - - std::shared_ptr< int > - initialize - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a4b0ad6b43587c4601283b52da3c47800 - (std::string const &name="") - - - std::shared_ptr< int > - initialize - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - aa7efdb8dfaa270a5ee5915c08a64ebaa - () - - - std::shared_ptr< int > - get - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a44a1302dbe6c3a0a187838fc246e1ee5 - (std::string const &name="") - - - std::shared_ptr< int > - get - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a5109e37f29d40ef6695c4291fcbb063d - () - void - set_level + _updateLevels http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a1a3ff36211cc8e01a397f484fb967f41 - (std::string const &level, std::string const &name) + adcf103419e3ac1c9fea0403e7d87d8cf + (const Log::LevelMap &defaultLevels, Log::LogMap &existingLogs) - void - set_level - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a7f2d11c952cce70b2a92c7402c14d2f6 - (std::string const &) - - - bool - has_level - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - adfbe0795d12d3119704baf0f64dc9d3c - (std::string const &, std::string const &) - - - const std::string - name_prefix + ostream & + operator<< http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a6c538b24670a61401f0fabf038e07931 - + a7cb336aaec82dbb82888b3139926505a + (Log &log, int level) - logging.enabled.h + logging.h /home/runner/work/sopt/sopt/cpp/sopt/ - http://astro-informatics.github.io/sopt/logging_8enabled_8h.html + http://astro-informatics.github.io/sopt/logging_8h.html sopt/exception.h + sopt::logging::Log sopt sopt::logging #define - SOPT_MACRO - logging_8enabled_8h.html - a1ed0e99f6e0e5337f165d2590412052b - (LEVEL) - - - #define - SOPT_MACRO - logging_8enabled_8h.html - a1ed0e99f6e0e5337f165d2590412052b - (LEVEL) + SOPT_MSG_LVL + group__logmacros.html + gad278b21b198636a7aab4a64d32774f3e + (lvl,...) #define SOPT_LOG_ - logging_8enabled_8h.html - aa3140c50e21c9f1b55df324632c73a77 - (NAME, TYPE,...) + group__logmacros.html + ga029e05e5481737c5960823c4fff3b81f + (TYPE,...) - - std::shared_ptr< spdlog::logger > - spdlogPtr - logging_8enabled_8h.html - aa9892412af755840eb432b2132a55122 - - - - void - set_level - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a1a3ff36211cc8e01a397f484fb967f41 - (std::string const &level, std::string const &name) - - - std::shared_ptr< int > - initialize - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a4b0ad6b43587c4601283b52da3c47800 - (std::string const &name="") - - - std::shared_ptr< int > - get - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a44a1302dbe6c3a0a187838fc246e1ee5 - (std::string const &name="") - - - bool - has_level - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - adfbe0795d12d3119704baf0f64dc9d3c - (std::string const &, std::string const &) - - - - logging.h - /home/runner/work/sopt/sopt/cpp/sopt/ - http://astro-informatics.github.io/sopt/logging_8h.html - sopt/logging.disabled.h #define SOPT_NOTICE @@ -1726,6 +1624,48 @@ a4a497e6b273bf510772846ac52cef095 (...) + + ostream & + operator<< + http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html + a7cb336aaec82dbb82888b3139926505a + (Log &log, int level) + + + Log & + getLog + http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html + a42b7b103eba3224902e75a145a87c866 + () + + + void + set_level + http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html + a3849ca5dbfcb69aa22066146b8ee781d + (const std::string &level) + + + void + applyFormat + http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html + ae20c08f799e58e2983a6ec139cf3dcc4 + (std::stringstream &ss, char *&pos, Arg &&arg) + + + std::string + mkFormattedString + http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html + a60307772406264e603590704d663be39 + (const char *txt, Args &&... args) + + + const std::string & + mkFormattedString + http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html + a45b4577bcf8a8042cf10881b9b824bb6 + (const std::string &txt) + maths.h @@ -8370,6 +8310,218 @@ () const + + sopt::logging::Log + http://astro-informatics.github.io/sopt/classsopt_1_1logging_1_1Log.html + + + Level + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5c + + + + trace + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca779e3f268322303fef9fcf8034aca5b0 + + + + debug + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5caf39f93723bcbe469657dba3ba3dcc5ea + + + + info + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca528453dc18158f612a2cc32e0c63a952 + + + + warn + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca4e06ce88b88673f1df0216a6afa3f267 + + + + warning + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca439a24d07673e25dad5e155d046d77ce + + + + error + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5caf4d6fe772a790054f4dcdc69286a3ff7 + + + + critical + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca49f7fcea9294a6525bdc8180d79d8351 + + + + always + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca9b93792f9b4e17c24fd89962127e91ec + + + + std::map< std::string, Log > + LogMap + classsopt_1_1logging_1_1Log.html + a4297e552320dfbeb93fa6327440a52b1 + + + + std::map< std::string, int > + LevelMap + classsopt_1_1logging_1_1Log.html + a06f646b84fe3196be226c35ed83e4e85 + + + + std::map< int, std::string > + ColorCodes + classsopt_1_1logging_1_1Log.html + a829091a647340d761b1b363b8c4bf8a7 + + + + trace + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca779e3f268322303fef9fcf8034aca5b0 + + + + debug + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5caf39f93723bcbe469657dba3ba3dcc5ea + + + + info + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca528453dc18158f612a2cc32e0c63a952 + + + + warn + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca4e06ce88b88673f1df0216a6afa3f267 + + + + warning + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca439a24d07673e25dad5e155d046d77ce + + + + error + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5caf4d6fe772a790054f4dcdc69286a3ff7 + + + + critical + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca49f7fcea9294a6525bdc8180d79d8351 + + + + always + classsopt_1_1logging_1_1Log.html + ab99691d0c2f5fb7edbca87b38409dc5ca9b93792f9b4e17c24fd89962127e91ec + + + + int + getLevel + classsopt_1_1logging_1_1Log.html + a5ca22451a5a48935565b02225f6594e2 + () const + + + Log & + setLevel + classsopt_1_1logging_1_1Log.html + ae8f8e492392d320cdc107f0090b23ae9 + (int level) + + + std::string + getName + classsopt_1_1logging_1_1Log.html + ae67d78e7d41a85c839e23f88b2db5791 + () const + + + Log & + setName + classsopt_1_1logging_1_1Log.html + aeb8f1a81ff808b403ef642d27f776535 + (const std::string &name) + + + bool + isActive + classsopt_1_1logging_1_1Log.html + a4003230356460180e2136e155f476bcc + (int level) const + + + static void + setLevel + classsopt_1_1logging_1_1Log.html + adf3dc665ee8c3628d08bb8941644be92 + (const std::string &name, int level) + + + static void + setLevels + classsopt_1_1logging_1_1Log.html + afcfc14315f7696eccd1d6acab9602f3f + (const LevelMap &logLevels) + + + static Log & + getLog + classsopt_1_1logging_1_1Log.html + a0ddb98645dcbd641b283839958d811c8 + (const std::string &name) + + + static Level + getLevelFromName + classsopt_1_1logging_1_1Log.html + a0f5d05e235de8856c0ff65bb81548ec5 + (const std::string &level) + + + static std::string + getLevelName + classsopt_1_1logging_1_1Log.html + a1628728a88da08d57db2998efd21de89 + (int level) + + + static const int + end_color + classsopt_1_1logging_1_1Log.html + a1c34fa06b82e3461e7a2773121568e13 + + + + friend std::ostream & + operator<< + classsopt_1_1logging_1_1Log.html + a249e58e04cd0cac940c864288681fcfc + (Log &log, int level) + + sopt::details::MatrixAdjointToLinearTransform http://astro-informatics.github.io/sopt/classsopt_1_1details_1_1MatrixAdjointToLinearTransform.html @@ -11462,13 +11614,6 @@ a7d4a92230a7a1fea0033bf12c848c2b8 () - - constexpr bool - color_logger - http://astro-informatics.github.io/sopt/namespacesopt.html - a8665e2e558cf502796c385e0b350d54d - () - constexpr std::size_t number_of_threads_in_tests @@ -11977,61 +12122,55 @@ sopt::logging http://astro-informatics.github.io/sopt/http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html + sopt::logging::Log - std::shared_ptr< int > - initialize - http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a4b0ad6b43587c4601283b52da3c47800 - (std::string const &name="") - - - std::shared_ptr< int > - initialize + void + _updateLevels http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - aa7efdb8dfaa270a5ee5915c08a64ebaa - () + adcf103419e3ac1c9fea0403e7d87d8cf + (const Log::LevelMap &defaultLevels, Log::LogMap &existingLogs) - std::shared_ptr< int > - get + ostream & + operator<< http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a44a1302dbe6c3a0a187838fc246e1ee5 - (std::string const &name="") + a7cb336aaec82dbb82888b3139926505a + (Log &log, int level) - std::shared_ptr< int > - get + Log & + getLog http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a5109e37f29d40ef6695c4291fcbb063d + a42b7b103eba3224902e75a145a87c866 () void set_level http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a1a3ff36211cc8e01a397f484fb967f41 - (std::string const &level, std::string const &name) + a3849ca5dbfcb69aa22066146b8ee781d + (const std::string &level) void - set_level + applyFormat http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a7f2d11c952cce70b2a92c7402c14d2f6 - (std::string const &) + ae20c08f799e58e2983a6ec139cf3dcc4 + (std::stringstream &ss, char *&pos, Arg &&arg) - bool - has_level + std::string + mkFormattedString http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - adfbe0795d12d3119704baf0f64dc9d3c - (std::string const &, std::string const &) + a60307772406264e603590704d663be39 + (const char *txt, Args &&... args) - - const std::string - name_prefix + + const std::string & + mkFormattedString http://astro-informatics.github.io/sopt/namespacesopt_1_1logging.html - a6c538b24670a61401f0fabf038e07931 - + a45b4577bcf8a8042cf10881b9b824bb6 + (const std::string &txt) @@ -12683,6 +12822,25 @@ ({1.425776641674131672055420247567865803211784397464191115245081e-06, 3.576251994264023012742569014888876217958307227940126418281357e-05, 4.211702664727116432247014444906469155300573201130549739553848e-04, 3.083088119253751774288740090262741910177322520624582862578292e-03, 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-1.470188206539868213708986402816605045648481224662435114088245e-02, -4.131306656031089274123231103326745723188134548520938157995702e-03, 9.214785032197180512031534870181734003522861645903894504302286e-03, 5.625715748403532005741565594881148757066703437214522101740941e-04, -5.071314509218348093935061417505663002006821323958752649640329e-03, 7.169821821064019257784165364894915621888541496773370435889585e-04, 2.400697781890973183892306914082592143984140550210130139535193e-03, -8.448626665537775009068937851465856973251363010924003314643612e-04, -9.424614077227377964015942271780098283910230639908018778588910e-04, 5.810759750532863662020321063678196633409555706981476723988312e-04, 2.817639250380670746018048967535608190123523180612961062603672e-04, -3.031020460726611993600629020329784682496477106470427787747855e-04, -4.555682696668420274688683005987764360677217149927938344795290e-05, 1.262043350166170705382346537131817701361522387904917335958705e-04, -1.155409103833717192628479047983460953381959342642374175822863e-05, -4.175141648540397797296325065775711309197411926289412468280801e-05, 1.334176149921350382547503457286060922218070031330137601427324e-05, 1.037359184045599795632258335010065103524959844966094870217687e-05, -6.456730428469619160379910439617575420986972394137121953806236e-06, -1.550844350118602575853380148525912999401292473185534395740371e-06, 2.149960269939665207789548199790770596890252405076394885606038e-06, -8.487087586072593071869805266089426629606479876982221840833098e-08, -5.187733738874144426008474683378542368066310000602823096009187e-07, 1.396377545508355481227961581059961184519872502493462010264633e-07, 8.400351046895965526933587176781279507953080669259318722910523e-08, -4.884757937459286762082185411608763964041010392101914854918157e-08, -5.424274800287298511126684174854414928447521710664476410973981e-09, 1.034704539274858480924046490952803937328239537222908159451039e-08, -1.436329487795135706854539856979275911183628476521636251660849e-09, -1.349197753983448821850381770889786301246741304307934955997111e-09, 5.261132557357598494535766638772624572100332209198979659077082e-10, 6.732336490189308685740626964182623159759767536724844030164551e-11, -8.278256522538134727330692938158991115335384611795874767521731e-11, 1.101692934599454551150832622160224231280195362919498540913658e-11, 6.291537317039508581580913620859140835852886308989584198166174e-12, -2.484789237563642857043361214502760723611468591833262675852242e-12, 2.626496504065252070488282876470525379851429538389481576454618e-14, 1.808661236274530582267084846343959377085922019067808145635263e-13, -4.249817819571463006966616371554206572863122562744916796556474e-14, -4.563397162127373109101691643047923747796563449194075621854491e-16, 2.045099676788988907802272564402310095398641092819367167252952e-15, -4.405307042483461342449027139838301611006835285455050155842865e-16, 4.304596839558790016251867477122791508849697688058169053134463e-17, -1.716152451088744188732404281737964277713026087224248235541071e-18}) + + logmacros + Logging macros + http://astro-informatics.github.io/sopt/group__logmacros.html + + #define + SOPT_MSG_LVL + group__logmacros.html + gad278b21b198636a7aab4a64d32774f3e + (lvl,...) + + + #define + SOPT_LOG_ + group__logmacros.html + ga029e05e5481737c5960823c4fff3b81f + (TYPE,...) + + sopt_contributors Contributors diff --git a/sopt_2wavelets_2wavelets_8cc.html b/sopt_2wavelets_2wavelets_8cc.html index 60f3852f3..25ca46d68 100644 --- a/sopt_2wavelets_2wavelets_8cc.html +++ b/sopt_2wavelets_2wavelets_8cc.html @@ -93,25 +93,28 @@ diff --git a/sopt_2wavelets_2wavelets_8cc__incl.map b/sopt_2wavelets_2wavelets_8cc__incl.map index 0dab75532..59973fae9 100644 --- a/sopt_2wavelets_2wavelets_8cc__incl.map +++ b/sopt_2wavelets_2wavelets_8cc__incl.map @@ -1,21 +1,24 @@ - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + diff --git a/sopt_2wavelets_2wavelets_8cc__incl.md5 b/sopt_2wavelets_2wavelets_8cc__incl.md5 index a4932e9ec..283a79223 100644 --- a/sopt_2wavelets_2wavelets_8cc__incl.md5 +++ b/sopt_2wavelets_2wavelets_8cc__incl.md5 @@ -1 +1 @@ -665886160b4e349aa94ba3e7d1cf579e \ No newline at end of file +db1b523be7626a24d74795a3f1a7c7d9 \ No newline at end of file diff --git a/sopt_2wavelets_2wavelets_8cc__incl.png b/sopt_2wavelets_2wavelets_8cc__incl.png index 4b3f21cd9..073a22a67 100644 Binary files a/sopt_2wavelets_2wavelets_8cc__incl.png and b/sopt_2wavelets_2wavelets_8cc__incl.png differ diff --git a/sopt_2wavelets_2wavelets_8cc_source.html b/sopt_2wavelets_2wavelets_8cc_source.html index d5f454d1c..92fd3b11c 100644 --- a/sopt_2wavelets_2wavelets_8cc_source.html +++ b/sopt_2wavelets_2wavelets_8cc_source.html @@ -105,7 +105,7 @@
                  24 } // namespace sopt::wavelets
                  sopt::wavelets::Wavelet
                  Performs direct and indirect wavelet transforms.
                  Definition: wavelets.h:21
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::wavelets::factory
                  Wavelet factory(const std::string &name, t_uint nlevels)
                  Creates a wavelet transform object.
                  Definition: wavelets.cc:8
                  sopt::wavelets::daubechies_data
                  WaveletData const & daubechies_data(t_uint n)
                  Factory function returning specific daubechie wavelet data.
                  Definition: wavelet_data.cc:1597
                  diff --git a/tests_2conjugate__gradient_8cc.html b/tests_2conjugate__gradient_8cc.html index b42b1903e..977193531 100644 --- a/tests_2conjugate__gradient_8cc.html +++ b/tests_2conjugate__gradient_8cc.html @@ -91,30 +91,31 @@ diff --git a/tests_2conjugate__gradient_8cc__incl.map b/tests_2conjugate__gradient_8cc__incl.map index 14f7719c6..8fd8030e5 100644 --- a/tests_2conjugate__gradient_8cc__incl.map +++ b/tests_2conjugate__gradient_8cc__incl.map @@ -1,26 +1,27 @@ - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests_2conjugate__gradient_8cc__incl.md5 b/tests_2conjugate__gradient_8cc__incl.md5 index 265902176..9a271f3e1 100644 --- a/tests_2conjugate__gradient_8cc__incl.md5 +++ b/tests_2conjugate__gradient_8cc__incl.md5 @@ -1 +1 @@ -e87a8201b4e002beddf12c74e21c2776 \ No newline at end of file +39379546afd7ff7040223c5fa11af4fa \ No newline at end of file diff --git a/tests_2conjugate__gradient_8cc__incl.png b/tests_2conjugate__gradient_8cc__incl.png index c1d69c348..5479f7dcd 100644 Binary files a/tests_2conjugate__gradient_8cc__incl.png and b/tests_2conjugate__gradient_8cc__incl.png differ diff --git a/tests_2inpainting_8cc.html b/tests_2inpainting_8cc.html index a7c748910..31704f9c1 100644 --- a/tests_2inpainting_8cc.html +++ b/tests_2inpainting_8cc.html @@ -108,56 +108,56 @@ diff --git a/tests_2inpainting_8cc__incl.map b/tests_2inpainting_8cc__incl.map index 7f6f1b822..843c5dd03 100644 --- a/tests_2inpainting_8cc__incl.map +++ b/tests_2inpainting_8cc__incl.map @@ -1,52 +1,52 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests_2inpainting_8cc__incl.md5 b/tests_2inpainting_8cc__incl.md5 index 9b514da86..4533f9ead 100644 --- a/tests_2inpainting_8cc__incl.md5 +++ b/tests_2inpainting_8cc__incl.md5 @@ -1 +1 @@ -bf72054b20e6daffc60ca7e2491f2df9 \ No newline at end of file +3162baa2b90a9e11835a8abccb9035b6 \ No newline at end of file diff --git a/tests_2inpainting_8cc__incl.png b/tests_2inpainting_8cc__incl.png index ae74c8fa5..be94c4b95 100644 Binary files a/tests_2inpainting_8cc__incl.png and b/tests_2inpainting_8cc__incl.png differ diff --git a/tests_2power__method_8cc.html b/tests_2power__method_8cc.html index fd1a76a12..0bae4f658 100644 --- a/tests_2power__method_8cc.html +++ b/tests_2power__method_8cc.html @@ -93,35 +93,36 @@ diff --git a/tests_2power__method_8cc__incl.map b/tests_2power__method_8cc__incl.map index cfc5b0c35..1948f53bf 100644 --- a/tests_2power__method_8cc__incl.map +++ b/tests_2power__method_8cc__incl.map @@ -1,31 +1,32 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests_2power__method_8cc__incl.md5 b/tests_2power__method_8cc__incl.md5 index bc0b391c6..e9eed5171 100644 --- a/tests_2power__method_8cc__incl.md5 +++ b/tests_2power__method_8cc__incl.md5 @@ -1 +1 @@ -03c9c57d681999a495367307672346f5 \ No newline at end of file +9c37280259b692fcabc7f238d9074f6b \ No newline at end of file diff --git a/tests_2power__method_8cc__incl.png b/tests_2power__method_8cc__incl.png index 59d09ca03..653c0b22e 100644 Binary files a/tests_2power__method_8cc__incl.png and b/tests_2power__method_8cc__incl.png differ diff --git a/tests_2reweighted_8cc.html b/tests_2reweighted_8cc.html index 0ac931f23..6f3d6a0c2 100644 --- a/tests_2reweighted_8cc.html +++ b/tests_2reweighted_8cc.html @@ -94,40 +94,41 @@ diff --git a/tests_2reweighted_8cc__incl.map b/tests_2reweighted_8cc__incl.map index c4b709ed3..1059324d3 100644 --- a/tests_2reweighted_8cc__incl.map +++ b/tests_2reweighted_8cc__incl.map @@ -1,36 +1,37 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests_2reweighted_8cc__incl.md5 b/tests_2reweighted_8cc__incl.md5 index 1de1cfcc5..e3fb5b6fb 100644 --- a/tests_2reweighted_8cc__incl.md5 +++ b/tests_2reweighted_8cc__incl.md5 @@ -1 +1 @@ -f1ee357f1eb017b9a4645ead16a28861 \ No newline at end of file +ae8296b96c6ec11a48a9b097d042f1c5 \ No newline at end of file diff --git a/tests_2reweighted_8cc__incl.png b/tests_2reweighted_8cc__incl.png index 18a7f8567..9bb950f75 100644 Binary files a/tests_2reweighted_8cc__incl.png and b/tests_2reweighted_8cc__incl.png differ diff --git a/tests_2sara_8cc.html b/tests_2sara_8cc.html index 4a700cd98..d51447b85 100644 --- a/tests_2sara_8cc.html +++ b/tests_2sara_8cc.html @@ -94,41 +94,42 @@ diff --git a/tests_2sara_8cc__incl.map b/tests_2sara_8cc__incl.map index 8a03ce55f..e38770b6d 100644 --- a/tests_2sara_8cc__incl.map +++ b/tests_2sara_8cc__incl.map @@ -1,37 +1,38 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tests_2sara_8cc__incl.md5 b/tests_2sara_8cc__incl.md5 index c1d70aeb2..a087778fe 100644 --- a/tests_2sara_8cc__incl.md5 +++ b/tests_2sara_8cc__incl.md5 @@ -1 +1 @@ -c376baf131f1f96c19b86f4a85e24619 \ No newline at end of file +0961efd3cc18ef96ebfba8601292c39d \ No newline at end of file diff --git a/tests_2sara_8cc__incl.png b/tests_2sara_8cc__incl.png index 26becfbfd..d89dc0ce0 100644 Binary files a/tests_2sara_8cc__incl.png and b/tests_2sara_8cc__incl.png differ diff --git a/tf__g__proximal_8h.html b/tf__g__proximal_8h.html index 6e6f5ae4a..3210d06e3 100644 --- a/tf__g__proximal_8h.html +++ b/tf__g__proximal_8h.html @@ -106,40 +106,41 @@
                  diff --git a/tf__g__proximal_8h__incl.map b/tf__g__proximal_8h__incl.map index c57802e27..7e1b5f6c5 100644 --- a/tf__g__proximal_8h__incl.map +++ b/tf__g__proximal_8h__incl.map @@ -1,36 +1,37 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tf__g__proximal_8h__incl.md5 b/tf__g__proximal_8h__incl.md5 index 84b04ae20..12772471e 100644 --- a/tf__g__proximal_8h__incl.md5 +++ b/tf__g__proximal_8h__incl.md5 @@ -1 +1 @@ -2582a1481e560da8498bbe69e49f1310 \ No newline at end of file +5639c2bf79af5aced7efe8674dcf658e \ No newline at end of file diff --git a/tf__g__proximal_8h__incl.png b/tf__g__proximal_8h__incl.png index f6844e344..89d4c21bc 100644 Binary files a/tf__g__proximal_8h__incl.png and b/tf__g__proximal_8h__incl.png differ diff --git a/tf__g__proximal_8h_source.html b/tf__g__proximal_8h_source.html index ed8a5d503..bd1c94ee1 100644 --- a/tf__g__proximal_8h_source.html +++ b/tf__g__proximal_8h_source.html @@ -221,7 +221,7 @@
                  g_proximal.h
                  linear_transform.h
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  sopt::cppflowutils::convert_image_to_tensor
                  cppflow::tensor convert_image_to_tensor(Image< double > const &image, int image_rows, int image_cols)
                  Converts a sopt::Image to a cppflow::tensor.
                  Definition: cppflow_utils.cc:14
                  sopt::linear_transform_identity
                  LinearTransform< Vector< SCALAR > > linear_transform_identity()
                  Helper function to create a linear transform that's just the identity.
                  Definition: linear_transform.h:226
                  diff --git a/tf__inpainting_8cc.html b/tf__inpainting_8cc.html index 94929055a..0ecc76ab6 100644 --- a/tf__inpainting_8cc.html +++ b/tf__inpainting_8cc.html @@ -107,51 +107,52 @@
                  diff --git a/tf__inpainting_8cc__incl.map b/tf__inpainting_8cc__incl.map index bbf4f096f..e94588d44 100644 --- a/tf__inpainting_8cc__incl.map +++ b/tf__inpainting_8cc__incl.map @@ -1,47 +1,48 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tf__inpainting_8cc__incl.md5 b/tf__inpainting_8cc__incl.md5 index a73453d00..de73e486b 100644 --- a/tf__inpainting_8cc__incl.md5 +++ b/tf__inpainting_8cc__incl.md5 @@ -1 +1 @@ -107b33655c72ff5bd52c60bf5382c821 \ No newline at end of file +79da29cca9d57a05a32f4d3520f8131f \ No newline at end of file diff --git a/tf__inpainting_8cc__incl.png b/tf__inpainting_8cc__incl.png index c96bfa077..ad8964ce3 100644 Binary files a/tf__inpainting_8cc__incl.png and b/tf__inpainting_8cc__incl.png differ diff --git a/todo.html b/todo.html new file mode 100644 index 000000000..5f29c1855 --- /dev/null +++ b/todo.html @@ -0,0 +1,91 @@ + + + + + + + +SOPT: Todo List + + + + + + + + + + + + +
                  +
                  + + + + + + + +
                  +
                  SOPT +
                  +
                  Sparse OPTimisation
                  +
                  +
                  + + + + + + + + +
                  +
                  + + +
                  + +
                  + +
                  +
                  +
                  +
                  Todo List
                  +
                  +
                  +
                  +
                  Member sopt::logging::_updateLevels (const Log::LevelMap &defaultLevels, Log::LogMap &existingLogs)
                  +

                  Add single static setLevel

                  +

                  Check ordering - "Foo" should come before "Foo.Bar"

                  +
                  +
                  +
                  +
                  + +
                  +Generated by doxygen 1.9.1 +
                  + + diff --git a/tv__inpainting_8cc.html b/tv__inpainting_8cc.html index 54078da5d..f15acce7e 100644 --- a/tv__inpainting_8cc.html +++ b/tv__inpainting_8cc.html @@ -89,6 +89,7 @@ #include <iostream>
                  #include <random>
                  #include <vector>
                  +#include <ctime>
                  #include <Eigen/Eigenvalues>
                  #include "sopt/types.h"
                  #include "sopt/gradient_operator.h"
                  @@ -107,46 +108,48 @@
                  @@ -184,110 +187,106 @@

                  -

                  Definition at line 28 of file tv_inpainting.cc.

                  -
                  28  {
                  -
                  29  // Some type aliases for simplicity
                  -
                  30  using Scalar = double;
                  -
                  31  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  -
                  32  // type expected by PrimalDual
                  -
                  33  using Vector = sopt::Vector<Scalar>;
                  -
                  34 
                  -
                  35  // using Complex = sopt::Vector<sopt::t_complex>;
                  -
                  36  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  -
                  37  // type expected by PrimalDual
                  -
                  38  using Matrix = sopt::Matrix<Scalar>;
                  -
                  39  // Image - 2D array - A * x is a coefficient-wise multiplication
                  -
                  40  // Type expected by wavelets and image write/read functions
                  -
                  41  using Image = sopt::Image<Scalar>;
                  -
                  42 
                  -
                  43  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  -
                  44  std::string const output = argc == 3 ? argv[2] : "none";
                  -
                  45  if (argc > 3) {
                  -
                  46  std::cout << "Usage:\n"
                  -
                  47  "$ "
                  -
                  48  << argv[0]
                  -
                  49  << " [input [output]]\n\n"
                  -
                  50  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  -
                  51  "- output: filename pattern for output image\n";
                  -
                  52  exit(0);
                  -
                  53  }
                  -
                  54  // Set up random numbers for C and C++
                  -
                  55  auto const seed = std::time(nullptr);
                  -
                  56  std::srand(static_cast<unsigned int>(seed));
                  -
                  57  std::mt19937 mersenne(std::time(nullptr));
                  -
                  58 
                  -
                  59  // Initializes and sets logger (if compiled with logging)
                  -
                  60  // See set_level function for levels.
                  -
                  61  sopt::logging::initialize();
                  +

                  Definition at line 29 of file tv_inpainting.cc.

                  +
                  29  {
                  +
                  30  // Some type aliases for simplicity
                  +
                  31  using Scalar = double;
                  +
                  32  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  +
                  33  // type expected by PrimalDual
                  +
                  34  using Vector = sopt::Vector<Scalar>;
                  +
                  35 
                  +
                  36  // using Complex = sopt::Vector<sopt::t_complex>;
                  +
                  37  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  +
                  38  // type expected by PrimalDual
                  +
                  39  using Matrix = sopt::Matrix<Scalar>;
                  +
                  40  // Image - 2D array - A * x is a coefficient-wise multiplication
                  +
                  41  // Type expected by wavelets and image write/read functions
                  +
                  42  using Image = sopt::Image<Scalar>;
                  +
                  43 
                  +
                  44  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  +
                  45  std::string const output = argc == 3 ? argv[2] : "none";
                  +
                  46  if (argc > 3) {
                  +
                  47  std::cout << "Usage:\n"
                  +
                  48  "$ "
                  +
                  49  << argv[0]
                  +
                  50  << " [input [output]]\n\n"
                  +
                  51  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  +
                  52  "- output: filename pattern for output image\n";
                  +
                  53  exit(0);
                  +
                  54  }
                  +
                  55  // Set up random numbers for C and C++
                  +
                  56  auto const seed = std::time(nullptr);
                  +
                  57  std::srand(static_cast<unsigned int>(seed));
                  +
                  58  std::mt19937 mersenne(std::time(nullptr));
                  +
                  59 
                  +
                  60  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  61  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  62 
                  -
                  63  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  64  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  -
                  65 
                  -
                  66  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  67  sopt::t_uint const nmeasure = 0.33 * image.size();
                  -
                  68  auto const sampling =
                  -
                  69  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  70 
                  -
                  71  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  72 
                  -
                  73  auto const psi = sopt::gradient_operator::gradient_operator<Scalar>(image.rows(), image.cols());
                  +
                  63  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  64  sopt::t_uint const nmeasure = 0.33 * image.size();
                  +
                  65  auto const sampling =
                  +
                  66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  67 
                  +
                  68  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  69 
                  +
                  70  auto const psi = sopt::gradient_operator::gradient_operator<Scalar>(image.rows(), image.cols());
                  +
                  71 
                  +
                  72  SOPT_HIGH_LOG("Computing primal-dual parameters");
                  +
                  73  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  74 
                  -
                  75  SOPT_HIGH_LOG("Computing primal-dual parameters");
                  -
                  76  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  77 
                  -
                  78  auto constexpr snr = 30.0;
                  -
                  79  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  80  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  -
                  81 
                  -
                  82  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  83  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  84  Vector y(y0.size());
                  -
                  85  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  86  // Write dirty image to file
                  -
                  87  if (output != "none") {
                  -
                  88  Vector const dirty = sampling.adjoint() * y;
                  -
                  89  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  90  "dirty_" + output + ".tiff");
                  -
                  91  }
                  -
                  92  const Vector grad = psi.adjoint() * (sampling.adjoint() * y);
                  -
                  93  const sopt::t_real gamma = (grad.segment(0, image.size()).array().square() +
                  -
                  94  grad.segment(image.size(), image.size()).array().square())
                  -
                  95  .sqrt()
                  -
                  96  .real()
                  -
                  97  .maxCoeff() *
                  -
                  98  2e-2;
                  -
                  99 
                  -
                  100  SOPT_HIGH_LOG("Creating primal-dual Functor");
                  -
                  101  auto const pd = sopt::algorithm::TVPrimalDual<Scalar>(y)
                  -
                  102  .itermax(2000)
                  -
                  103  .gamma(gamma)
                  -
                  104  .tau(0.5 / (1. + 1.))
                  -
                  105  .l2ball_proximal_epsilon(epsilon)
                  -
                  106  .Psi(psi)
                  -
                  107  .Phi(sampling)
                  -
                  108  .relative_variation(1e-4)
                  -
                  109  .residual_convergence(epsilon)
                  -
                  110  .positivity_constraint(true);
                  -
                  111 
                  -
                  112  SOPT_HIGH_LOG("Starting primal dual");
                  -
                  113  // Alternatively, pd can be called with a tuple (x, residual) as argument
                  -
                  114  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  -
                  115  auto const diagnostic = pd();
                  -
                  116  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
                  -
                  117 
                  -
                  118  // diagnostic should tell us the function converged
                  -
                  119  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  120  // diagnostic from the last call to the conjugate gradient.
                  -
                  121  if (not diagnostic.good) {
                  -
                  122  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
                  -
                  123  // throw std::runtime_error("Did not converge!");
                  -
                  124  }
                  -
                  125  if (output != "none")
                  -
                  126  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  127  output + ".tiff");
                  -
                  128 
                  -
                  129  return 0;
                  -
                  130 }
                  +
                  75  auto constexpr snr = 30.0;
                  +
                  76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  +
                  78 
                  +
                  79  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  80  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  81  Vector y(y0.size());
                  +
                  82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  83  // Write dirty image to file
                  +
                  84  if (output != "none") {
                  +
                  85  Vector const dirty = sampling.adjoint() * y;
                  +
                  86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  87  "dirty_" + output + ".tiff");
                  +
                  88  }
                  +
                  89  const Vector grad = psi.adjoint() * (sampling.adjoint() * y);
                  +
                  90  const sopt::t_real gamma = (grad.segment(0, image.size()).array().square() +
                  +
                  91  grad.segment(image.size(), image.size()).array().square())
                  +
                  92  .sqrt()
                  +
                  93  .real()
                  +
                  94  .maxCoeff() *
                  +
                  95  2e-2;
                  +
                  96 
                  +
                  97  SOPT_HIGH_LOG("Creating primal-dual Functor");
                  +
                  98  auto const pd = sopt::algorithm::TVPrimalDual<Scalar>(y)
                  +
                  99  .itermax(2000)
                  +
                  100  .gamma(gamma)
                  +
                  101  .tau(0.5 / (1. + 1.))
                  +
                  102  .l2ball_proximal_epsilon(epsilon)
                  +
                  103  .Psi(psi)
                  +
                  104  .Phi(sampling)
                  +
                  105  .relative_variation(1e-4)
                  +
                  106  .residual_convergence(epsilon)
                  +
                  107  .positivity_constraint(true);
                  +
                  108 
                  +
                  109  SOPT_HIGH_LOG("Starting primal dual");
                  +
                  110  // Alternatively, pd can be called with a tuple (x, residual) as argument
                  +
                  111  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  +
                  112  auto const diagnostic = pd();
                  +
                  113  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
                  +
                  114 
                  +
                  115  // diagnostic should tell us the function converged
                  +
                  116  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  117  // diagnostic from the last call to the conjugate gradient.
                  +
                  118  if (not diagnostic.good) {
                  +
                  119  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
                  +
                  120  // throw std::runtime_error("Did not converge!");
                  +
                  121  }
                  +
                  122  if (output != "none")
                  +
                  123  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  124  output + ".tiff");
                  +
                  125 
                  +
                  126  return 0;
                  +
                  127 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::Sampling
                  An operator that samples a set of measurements.
                  Definition: sampling.h:17
                  @@ -296,8 +295,7 @@

                  sopt::algorithm::TVPrimalDual::Psi
                  TVPrimalDual &::type Psi(ARGS &&... args)
                  Definition: tv_primal_dual.h:228

                  mersenne
                  std::unique_ptr< std::mt19937_64 > mersenne(new std::mt19937_64(0))
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::t_int
                  int t_int
                  Root of the type hierarchy for signed integers.
                  Definition: types.h:13
                  @@ -312,7 +310,7 @@

                  Vector
                  sopt::Vector< Scalar > Vector
                  Definition: inpainting.cc:28

                  Matrix
                  sopt::Matrix< Scalar > Matrix
                  Definition: inpainting.cc:29
                  -

                  References sopt::dirty(), sopt::epsilon(), sopt::logging::initialize(), mersenne(), sopt::algorithm::TVPrimalDual< SCALAR >::Phi(), sopt::algorithm::TVPrimalDual< SCALAR >::Psi(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::TVPrimalDual< SCALAR >::residual_convergence(), sopt::sigma(), SOPT_HIGH_LOG, and sopt::utilities::write_tiff().

                  +

                  References sopt::dirty(), sopt::epsilon(), mersenne(), sopt::algorithm::TVPrimalDual< SCALAR >::Phi(), sopt::algorithm::TVPrimalDual< SCALAR >::Psi(), sopt::notinstalled::read_standard_tiff(), sopt::algorithm::TVPrimalDual< SCALAR >::residual_convergence(), sopt::sigma(), SOPT_HIGH_LOG, and sopt::utilities::write_tiff().

                  diff --git a/tv__inpainting_8cc__incl.map b/tv__inpainting_8cc__incl.map index 5ea4907a2..f05c5cd0f 100644 --- a/tv__inpainting_8cc__incl.map +++ b/tv__inpainting_8cc__incl.map @@ -1,42 +1,44 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tv__inpainting_8cc__incl.md5 b/tv__inpainting_8cc__incl.md5 index 336c9ebfb..dff5004bc 100644 --- a/tv__inpainting_8cc__incl.md5 +++ b/tv__inpainting_8cc__incl.md5 @@ -1 +1 @@ -22f33f503b680d277e6af83b858af87e \ No newline at end of file +984340d721c1baab4daf96b620183940 \ No newline at end of file diff --git a/tv__inpainting_8cc__incl.png b/tv__inpainting_8cc__incl.png index e4f2baeed..3a852afe6 100644 Binary files a/tv__inpainting_8cc__incl.png and b/tv__inpainting_8cc__incl.png differ diff --git a/tv__inpainting_8cc_source.html b/tv__inpainting_8cc_source.html index 75b0172f7..b9010d41c 100644 --- a/tv__inpainting_8cc_source.html +++ b/tv__inpainting_8cc_source.html @@ -88,127 +88,124 @@
                  7 #include <iostream>
                  8 #include <random>
                  9 #include <vector>
                  -
                  10 #include <Eigen/Eigenvalues>
                  -
                  11 
                  -
                  12 #include "sopt/types.h"
                  -
                  13 
                  -
                  14 #include "sopt/gradient_operator.h"
                  -
                  15 #include "sopt/maths.h"
                  -
                  16 #include "sopt/power_method.h"
                  -
                  17 #include "sopt/relative_variation.h"
                  -
                  18 #include "sopt/sampling.h"
                  -
                  19 #include "sopt/tv_primal_dual.h"
                  -
                  20 #include "sopt/utilities.h"
                  -
                  21 
                  -
                  22 // This header is not part of the installed sopt interface
                  -
                  23 // It is only present in tests
                  -
                  24 #include "tools_for_tests/directories.h"
                  -
                  25 #include "tools_for_tests/tiffwrappers.h"
                  -
                  26 
                  -
                  27 // \min_{x} ||\Psi^Tx||_1 \quad \mbox{s.t.} \quad ||y - Ax||_2 < \epsilon and x \geq 0
                  -
                  28 int main(int argc, char const **argv) {
                  -
                  29  // Some type aliases for simplicity
                  -
                  30  using Scalar = double;
                  -
                  31  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  -
                  32  // type expected by PrimalDual
                  -
                  33  using Vector = sopt::Vector<Scalar>;
                  -
                  34 
                  -
                  35  // using Complex = sopt::Vector<sopt::t_complex>;
                  -
                  36  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  -
                  37  // type expected by PrimalDual
                  -
                  38  using Matrix = sopt::Matrix<Scalar>;
                  -
                  39  // Image - 2D array - A * x is a coefficient-wise multiplication
                  -
                  40  // Type expected by wavelets and image write/read functions
                  -
                  41  using Image = sopt::Image<Scalar>;
                  -
                  42 
                  -
                  43  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  -
                  44  std::string const output = argc == 3 ? argv[2] : "none";
                  -
                  45  if (argc > 3) {
                  -
                  46  std::cout << "Usage:\n"
                  -
                  47  "$ "
                  -
                  48  << argv[0]
                  -
                  49  << " [input [output]]\n\n"
                  -
                  50  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  -
                  51  "- output: filename pattern for output image\n";
                  -
                  52  exit(0);
                  -
                  53  }
                  -
                  54  // Set up random numbers for C and C++
                  -
                  55  auto const seed = std::time(nullptr);
                  -
                  56  std::srand(static_cast<unsigned int>(seed));
                  -
                  57  std::mt19937 mersenne(std::time(nullptr));
                  -
                  58 
                  -
                  59  // Initializes and sets logger (if compiled with logging)
                  -
                  60  // See set_level function for levels.
                  -
                  61  sopt::logging::initialize();
                  +
                  10 #include <ctime>
                  +
                  11 #include <Eigen/Eigenvalues>
                  +
                  12 
                  +
                  13 #include "sopt/types.h"
                  +
                  14 
                  +
                  15 #include "sopt/gradient_operator.h"
                  +
                  16 #include "sopt/maths.h"
                  +
                  17 #include "sopt/power_method.h"
                  +
                  18 #include "sopt/relative_variation.h"
                  +
                  19 #include "sopt/sampling.h"
                  +
                  20 #include "sopt/tv_primal_dual.h"
                  +
                  21 #include "sopt/utilities.h"
                  +
                  22 
                  +
                  23 // This header is not part of the installed sopt interface
                  +
                  24 // It is only present in tests
                  +
                  25 #include "tools_for_tests/directories.h"
                  +
                  26 #include "tools_for_tests/tiffwrappers.h"
                  +
                  27 
                  +
                  28 // \min_{x} ||\Psi^Tx||_1 \quad \mbox{s.t.} \quad ||y - Ax||_2 < \epsilon and x \geq 0
                  +
                  29 int main(int argc, char const **argv) {
                  +
                  30  // Some type aliases for simplicity
                  +
                  31  using Scalar = double;
                  +
                  32  // Column vector - linear algebra - A * x is a matrix-vector multiplication
                  +
                  33  // type expected by PrimalDual
                  +
                  34  using Vector = sopt::Vector<Scalar>;
                  +
                  35 
                  +
                  36  // using Complex = sopt::Vector<sopt::t_complex>;
                  +
                  37  // Matrix - linear algebra - A * x is a matrix-vector multiplication
                  +
                  38  // type expected by PrimalDual
                  +
                  39  using Matrix = sopt::Matrix<Scalar>;
                  +
                  40  // Image - 2D array - A * x is a coefficient-wise multiplication
                  +
                  41  // Type expected by wavelets and image write/read functions
                  +
                  42  using Image = sopt::Image<Scalar>;
                  +
                  43 
                  +
                  44  std::string const input = argc >= 2 ? argv[1] : "cameraman256";
                  +
                  45  std::string const output = argc == 3 ? argv[2] : "none";
                  +
                  46  if (argc > 3) {
                  +
                  47  std::cout << "Usage:\n"
                  +
                  48  "$ "
                  +
                  49  << argv[0]
                  +
                  50  << " [input [output]]\n\n"
                  +
                  51  "- input: path to the image to clean (or name of standard SOPT image)\n"
                  +
                  52  "- output: filename pattern for output image\n";
                  +
                  53  exit(0);
                  +
                  54  }
                  +
                  55  // Set up random numbers for C and C++
                  +
                  56  auto const seed = std::time(nullptr);
                  +
                  57  std::srand(static_cast<unsigned int>(seed));
                  +
                  58  std::mt19937 mersenne(std::time(nullptr));
                  +
                  59 
                  +
                  60  SOPT_HIGH_LOG("Read input file {}", input);
                  +
                  61  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  62 
                  -
                  63  SOPT_HIGH_LOG("Read input file {}", input);
                  -
                  64  Image const image = sopt::notinstalled::read_standard_tiff(input);
                  -
                  65 
                  -
                  66  SOPT_HIGH_LOG("Initializing sensing operator");
                  -
                  67  sopt::t_uint const nmeasure = 0.33 * image.size();
                  -
                  68  auto const sampling =
                  -
                  69  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  -
                  70 
                  -
                  71  SOPT_HIGH_LOG("Initializing wavelets");
                  -
                  72 
                  -
                  73  auto const psi = sopt::gradient_operator::gradient_operator<Scalar>(image.rows(), image.cols());
                  +
                  63  SOPT_HIGH_LOG("Initializing sensing operator");
                  +
                  64  sopt::t_uint const nmeasure = 0.33 * image.size();
                  +
                  65  auto const sampling =
                  +
                  66  sopt::linear_transform<Scalar>(sopt::Sampling(image.size(), nmeasure, mersenne));
                  +
                  67 
                  +
                  68  SOPT_HIGH_LOG("Initializing wavelets");
                  +
                  69 
                  +
                  70  auto const psi = sopt::gradient_operator::gradient_operator<Scalar>(image.rows(), image.cols());
                  +
                  71 
                  +
                  72  SOPT_HIGH_LOG("Computing primal-dual parameters");
                  +
                  73  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  74 
                  -
                  75  SOPT_HIGH_LOG("Computing primal-dual parameters");
                  -
                  76  Vector const y0 = sampling * Vector::Map(image.data(), image.size());
                  -
                  77 
                  -
                  78  auto constexpr snr = 30.0;
                  -
                  79  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  -
                  80  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  -
                  81 
                  -
                  82  SOPT_HIGH_LOG("Create dirty vector");
                  -
                  83  std::normal_distribution<> gaussian_dist(0, sigma);
                  -
                  84  Vector y(y0.size());
                  -
                  85  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  -
                  86  // Write dirty image to file
                  -
                  87  if (output != "none") {
                  -
                  88  Vector const dirty = sampling.adjoint() * y;
                  -
                  89  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  -
                  90  "dirty_" + output + ".tiff");
                  -
                  91  }
                  -
                  92  const Vector grad = psi.adjoint() * (sampling.adjoint() * y);
                  -
                  93  const sopt::t_real gamma = (grad.segment(0, image.size()).array().square() +
                  -
                  94  grad.segment(image.size(), image.size()).array().square())
                  -
                  95  .sqrt()
                  -
                  96  .real()
                  -
                  97  .maxCoeff() *
                  -
                  98  2e-2;
                  -
                  99 
                  -
                  100  SOPT_HIGH_LOG("Creating primal-dual Functor");
                  -
                  101  auto const pd = sopt::algorithm::TVPrimalDual<Scalar>(y)
                  -
                  102  .itermax(2000)
                  -
                  103  .gamma(gamma)
                  -
                  104  .tau(0.5 / (1. + 1.))
                  -
                  105  .l2ball_proximal_epsilon(epsilon)
                  -
                  106  .Psi(psi)
                  -
                  107  .Phi(sampling)
                  -
                  108  .relative_variation(1e-4)
                  -
                  109  .residual_convergence(epsilon)
                  -
                  110  .positivity_constraint(true);
                  -
                  111 
                  -
                  112  SOPT_HIGH_LOG("Starting primal dual");
                  -
                  113  // Alternatively, pd can be called with a tuple (x, residual) as argument
                  -
                  114  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  -
                  115  auto const diagnostic = pd();
                  -
                  116  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
                  -
                  117 
                  -
                  118  // diagnostic should tell us the function converged
                  -
                  119  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  -
                  120  // diagnostic from the last call to the conjugate gradient.
                  -
                  121  if (not diagnostic.good) {
                  -
                  122  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
                  -
                  123  // throw std::runtime_error("Did not converge!");
                  -
                  124  }
                  -
                  125  if (output != "none")
                  -
                  126  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  -
                  127  output + ".tiff");
                  -
                  128 
                  -
                  129  return 0;
                  -
                  130 }
                  +
                  75  auto constexpr snr = 30.0;
                  +
                  76  auto const sigma = y0.stableNorm() / std::sqrt(y0.size()) * std::pow(10.0, -(snr / 20.0));
                  +
                  77  auto const epsilon = std::sqrt(nmeasure + 2 * std::sqrt(y0.size())) * sigma;
                  +
                  78 
                  +
                  79  SOPT_HIGH_LOG("Create dirty vector");
                  +
                  80  std::normal_distribution<> gaussian_dist(0, sigma);
                  +
                  81  Vector y(y0.size());
                  +
                  82  for (sopt::t_int i = 0; i < y0.size(); i++) y(i) = y0(i) + gaussian_dist(mersenne);
                  +
                  83  // Write dirty image to file
                  +
                  84  if (output != "none") {
                  +
                  85  Vector const dirty = sampling.adjoint() * y;
                  +
                  86  sopt::utilities::write_tiff(Matrix::Map(dirty.data(), image.rows(), image.cols()),
                  +
                  87  "dirty_" + output + ".tiff");
                  +
                  88  }
                  +
                  89  const Vector grad = psi.adjoint() * (sampling.adjoint() * y);
                  +
                  90  const sopt::t_real gamma = (grad.segment(0, image.size()).array().square() +
                  +
                  91  grad.segment(image.size(), image.size()).array().square())
                  +
                  92  .sqrt()
                  +
                  93  .real()
                  +
                  94  .maxCoeff() *
                  +
                  95  2e-2;
                  +
                  96 
                  +
                  97  SOPT_HIGH_LOG("Creating primal-dual Functor");
                  +
                  98  auto const pd = sopt::algorithm::TVPrimalDual<Scalar>(y)
                  +
                  99  .itermax(2000)
                  +
                  100  .gamma(gamma)
                  +
                  101  .tau(0.5 / (1. + 1.))
                  +
                  102  .l2ball_proximal_epsilon(epsilon)
                  +
                  103  .Psi(psi)
                  +
                  104  .Phi(sampling)
                  +
                  105  .relative_variation(1e-4)
                  +
                  106  .residual_convergence(epsilon)
                  +
                  107  .positivity_constraint(true);
                  +
                  108 
                  +
                  109  SOPT_HIGH_LOG("Starting primal dual");
                  +
                  110  // Alternatively, pd can be called with a tuple (x, residual) as argument
                  +
                  111  // Here, we default to (Φ^Ty/ν, ΦΦ^Ty/ν - y)
                  +
                  112  auto const diagnostic = pd();
                  +
                  113  SOPT_HIGH_LOG("primal dual returned {}", diagnostic.good);
                  +
                  114 
                  +
                  115  // diagnostic should tell us the function converged
                  +
                  116  // it also contains diagnostic.niters - the number of iterations, and cg_diagnostic - the
                  +
                  117  // diagnostic from the last call to the conjugate gradient.
                  +
                  118  if (not diagnostic.good) {
                  +
                  119  SOPT_HIGH_LOG("SOPT-primal-dual converged in {} iterations", diagnostic.niters);
                  +
                  120  // throw std::runtime_error("Did not converge!");
                  +
                  121  }
                  +
                  122  if (output != "none")
                  +
                  123  sopt::utilities::write_tiff(Matrix::Map(diagnostic.x.data(), image.rows(), image.cols()),
                  +
                  124  output + ".tiff");
                  +
                  125 
                  +
                  126  return 0;
                  +
                  127 }
                  Scalar
                  sopt::t_real Scalar
                  Definition: bisection_method.cc:9
                  sopt::Sampling
                  An operator that samples a set of measurements.
                  Definition: sampling.h:17
                  @@ -219,9 +216,8 @@
                  Image
                  sopt::Image< Scalar > Image
                  Definition: cppflow_model.cc:20
                  gradient_operator.h
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  -
                  sopt::logging::initialize
                  std::shared_ptr< int > initialize(std::string const &)
                  Initializes a logger.
                  Definition: logging.disabled.h:12
                  sopt::notinstalled::read_standard_tiff
                  Image read_standard_tiff(std::string const &name)
                  Reads tiff image from sopt data directory if it exists.
                  Definition: tiffwrappers.cc:9
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::t_int
                  int t_int
                  Root of the type hierarchy for signed integers.
                  Definition: types.h:13
                  @@ -239,7 +235,7 @@
                  Vector
                  sopt::Vector< Scalar > Vector
                  Definition: inpainting.cc:28
                  Matrix
                  sopt::Matrix< Scalar > Matrix
                  Definition: inpainting.cc:29
                  -
                  main
                  int main(int argc, char const **argv)
                  Definition: tv_inpainting.cc:28
                  +
                  main
                  int main(int argc, char const **argv)
                  Definition: tv_inpainting.cc:29
                  tv_primal_dual.h
                  diff --git a/tv__primal__dual_8h.html b/tv__primal__dual_8h.html index a94f39dc7..00881d374 100644 --- a/tv__primal__dual_8h.html +++ b/tv__primal__dual_8h.html @@ -102,34 +102,35 @@
                  diff --git a/tv__primal__dual_8h__incl.map b/tv__primal__dual_8h__incl.map index 8eb2bd4bd..4bcc50005 100644 --- a/tv__primal__dual_8h__incl.map +++ b/tv__primal__dual_8h__incl.map @@ -1,30 +1,31 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/tv__primal__dual_8h__incl.md5 b/tv__primal__dual_8h__incl.md5 index 21d0a4984..6d1adc57d 100644 --- a/tv__primal__dual_8h__incl.md5 +++ b/tv__primal__dual_8h__incl.md5 @@ -1 +1 @@ -fab8b121cc6c928ed7722803be952928 \ No newline at end of file +7772e1d1246782dc5a03bb7eb7beb34d \ No newline at end of file diff --git a/tv__primal__dual_8h__incl.png b/tv__primal__dual_8h__incl.png index 894448380..801011127 100644 Binary files a/tv__primal__dual_8h__incl.png and b/tv__primal__dual_8h__incl.png differ diff --git a/tv__primal__dual_8h_source.html b/tv__primal__dual_8h_source.html index 19425fd80..32cea77d0 100644 --- a/tv__primal__dual_8h_source.html +++ b/tv__primal__dual_8h_source.html @@ -474,8 +474,8 @@
                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  linear_transform.h
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:27
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_HIGH_LOG
                  #define SOPT_HIGH_LOG(...)
                  High priority message.
                  Definition: logging.h:223
                  sopt::tv_norm
                  real_type< typename T0::Scalar >::type tv_norm(Eigen::ArrayBase< T0 > const &input, Eigen::ArrayBase< T1 > const &weights)
                  Computes weighted TV norm.
                  Definition: maths.h:168
                  sopt::linear_transform
                  LinearTransform< VECTOR > linear_transform(OperatorFunction< VECTOR > const &direct, OperatorFunction< VECTOR > const &indirect, std::array< t_int, 3 > const &sizes={{1, 1, 0}})
                  Definition: linear_transform.h:101
                  diff --git a/utilities_8cc.html b/utilities_8cc.html index d71b981ed..7290e612a 100644 --- a/utilities_8cc.html +++ b/utilities_8cc.html @@ -98,26 +98,27 @@
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                  SOPT_THROW
                  #define SOPT_THROW(MSG)
                  Definition: exception.h:46
                  -
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:31
                  -
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:24
                  -
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:29
                  +
                  SOPT_LOW_LOG
                  #define SOPT_LOW_LOG(...)
                  Low priority message.
                  Definition: logging.h:227
                  +
                  SOPT_TRACE
                  #define SOPT_TRACE(...)
                  Definition: logging.h:220
                  +
                  SOPT_MEDIUM_LOG
                  #define SOPT_MEDIUM_LOG(...)
                  Medium priority message.
                  Definition: logging.h:225
                  sopt::utilities::write_tiff
                  void write_tiff(Image<> const &image, std::string const &filename)
                  Writes a tiff greyscale file.
                  Definition: utilities.cc:68
                  sopt::utilities::read_tiff
                  Image read_tiff(std::string const &filename)
                  Reads tiff image.
                  Definition: utilities.cc:38
                  diff --git a/wavelets_8h.html b/wavelets_8h.html index 2f3b1f5c2..e0ff013d1 100644 --- a/wavelets_8h.html +++ b/wavelets_8h.html @@ -95,38 +95,39 @@
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