Remove linear_chirp

src/deepc/__init__.py

@@ -1,6 +1,5 @@
-from .math import linear_chirp
 from .lti import DiscreteLTI, RandomNoiseDiscreteLTI
 from .deepc import deePC
 from .controller import Controller
 
-__all__ = ["linear_chirp", "DiscreteLTI", "RandomNoiseDiscreteLTI", "deePC", "Controller"]
+__all__ = ["DiscreteLTI", "RandomNoiseDiscreteLTI", "deePC", "Controller"]

src/deepc/math.py

@@ -54,21 +54,3 @@ def projected_gradient_method(
             return x_new
         x_old = x_new
     return x_old
-
-
-def linear_chirp(f0: float, f1: float, samples: int, phi: float = 0) -> list[float]:
-    """
-    Generate a linear chirp signal.
-    Args:
-        f0: Start frequency in Hz.
-        f1: End frequency in Hz.
-        samples: Number of samples.
-        phi: Phase offset in radians.
-    """
-    return [
-        math.sin(
-            phi
-            + 2 * math.pi * (f0 * (i / (samples - 1)) + 0.5 * (f1 - f0) * (i / (samples - 1)) ** 2)
-        )
-        for i in range(samples)
-    ]

src/deepcpp/algorithm.cpp

@@ -122,16 +122,3 @@ VectorXd projected_gradient_method(
     }
     return x_old;
 }
-
-std::vector<double> linear_chirp(double f0, double f1, int samples, int phi)
-{
-    double Pi = 3.14159265358979323846;
-    std::vector<double> res;
-    res.reserve(samples);
-    for (int i = 0; i < samples; ++i)
-    {
-        double t = i / (samples - 1.0);
-        res.push_back(std::sin(phi + 2 * Pi * (f0 * t + 0.5 * (f1 - f0) * t * t)));
-    }
-    return res;
-}

src/deepcpp/algorithm.h

@@ -32,6 +32,3 @@ VectorXd projected_gradient_method(
     std::function<VectorXd(const VectorXd&)> projection,
     int max_iterations = 300,
     double tolerance = 1e-6);
-
-
-std::vector<double> linear_chirp(double f0, double f1, int samples, int phi = 0);

tests/deepc/helpers/__init__.py

@@ -1,4 +1,5 @@
-from deepc import DiscreteLTI, linear_chirp
+import numpy as np
+from deepc import DiscreteLTI
 
 
 def create_1D_in_1D_out_LTI() -> DiscreteLTI:
@@ -36,10 +37,6 @@ def create_2D_in_3D_out_LTI() -> DiscreteLTI:
 
 
 def gather_offline_data(system: DiscreteLTI, samples: int) -> tuple:
-    if system.input_dim == 1:
-        u_d = linear_chirp(0, samples / 2, samples)
-    else:
-        chirps = [linear_chirp(0, samples / 2, samples, 0.1 * i) for i in range(system.input_dim)]
-        u_d = list(zip(*chirps))  # Transpose the list of chirp signals
+    u_d = np.random.uniform(-1, 1, (samples, system.input_dim))
     y_d = system.apply_multiple(u_d)
     return u_d, y_d

tests/deepc/test_math.py

@@ -1,6 +1,6 @@
 import unittest
 import numpy as np
-from deepc.math import linear_chirp, left_pseudoinverse, right_pseudoinverse, hankel_matrix
+from deepc.math import left_pseudoinverse, right_pseudoinverse, hankel_matrix
 
 
 class TestLeftPseudoinverse(unittest.TestCase):
@@ -77,24 +77,5 @@ def test_size_3_and_3_rows(self):
         np.testing.assert_array_equal(hankel_matrix(3, [(1, 2), (3, 4), (5, 6)]), [[1], [2], [3], [4], [5], [6]])
 
 
-class TestLinearChirp(unittest.TestCase):
-    def test_len(self):
-        chirp = linear_chirp(0, 100, 1000)
-        self.assertEqual(len(chirp), 1000)
-
-    def test_start(self):
-        chirp = linear_chirp(0, 100, 1000)
-        self.assertAlmostEqual(chirp[0], 0)
-
-    def test_end(self):
-        chirp = linear_chirp(0, 100, 1000)
-        self.assertAlmostEqual(chirp[-1], 0)
-
-    def test_symmetry(self):
-        chirp1 = linear_chirp(0, 100, 1_000)
-        chirp2 = [-x for x in reversed(linear_chirp(100, 0, 1_000))]
-        np.testing.assert_allclose(chirp1, chirp2, atol=1e-12)
-
-
 if __name__ == "__main__":
     unittest.main()

tests/deepcpp/test_algorithm.cpp

@@ -182,29 +182,3 @@ TEST(Algorithm, ProjectedGradientMethod)
 
 	EXPECT_EQ(res, Vector(0, 0));
 }
-
-TEST(LinearChirp, Size)
-{
-	auto chirp = linear_chirp(0, 100, 1'000);
-	EXPECT_EQ(chirp.size(), 1'000);
-}
-
-TEST(LinearChirp, Start)
-{
-	auto chirp = linear_chirp(0, 100, 1'000);
-	EXPECT_NEAR(chirp[0], 0, 1e-12);
-}
-
-TEST(LinearChirp, End)
-{
-	auto chirp = linear_chirp(0, 100, 1'000);
-	EXPECT_NEAR(chirp[999], 0, 1e-12);
-}
-
-TEST(LinearChirp, Symmetry)
-{
-	auto chirp1 = linear_chirp(0, 100, 1'000);
-	auto chirp2 = linear_chirp(100, 0, 1'000);
-	for (int i = 0; i < 1'000; ++i)
-		EXPECT_NEAR(chirp1[i], -chirp2[999 - i], 1e-12);
-}

tests/deepcpp/test_deepc.cpp

@@ -48,13 +48,9 @@ DiscreteLTI lti_2D_input_3D_output()
 std::tuple<std::vector<VectorXd>, std::vector<VectorXd>> gather_offline_data(DiscreteLTI &system)
 {
     const int samples = 1'000;
-    std::vector<VectorXd> u_d(samples, VectorXd::Zero(system.input_dim()));
-    for (int i = 0; i < system.input_dim(); ++i)
-    {
-        std::vector<double> chirp = linear_chirp(0, samples / 2, samples, 0.1 * i);
-        for (int j = 0; j < samples; ++j)
-            u_d[j](i) = chirp[j];
-    }
+    std::vector<VectorXd> u_d;
+    for (int i = 0; i < samples; ++i)
+        u_d.push_back(VectorXd::Random(system.input_dim()));
     std::vector<VectorXd> y_d = system.apply_multiple(u_d);
     return {u_d, y_d};
 }