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MAINT: fixes prompted by the 'flake8' pre-commit hook
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‎asv_benchmarking/benchmarks/benchmarks.py

+19-24
Original file line numberDiff line numberDiff line change
@@ -1,15 +1,10 @@
11
# Benchmarking scripts for lmfit
22

3-
import cProfile
43
from copy import deepcopy
5-
import pstats
6-
from subprocess import PIPE, Popen
7-
import time
84

95
import numpy as np
106

11-
from lmfit import (Minimizer, Parameter, Parameters, __version__,
12-
conf_interval, minimize)
7+
from lmfit import Minimizer, Parameters, conf_interval, minimize
138

149

1510
def obj_func(params, x, data):
@@ -34,12 +29,12 @@ def time_minimize(self):
3429
x = np.linspace(0, 15, 601)
3530

3631
data = (5. * np.sin(2 * x - 0.1) * np.exp(-x*x*0.025) +
37-
np.random.normal(size=len(x), scale=0.3) )
32+
np.random.normal(size=len(x), scale=0.3))
3833
params = Parameters()
39-
params.add('amp', value= 1, min=0, max=100)
40-
params.add('decay', value= 0.0, min=0, max=10)
41-
params.add('shift', value= 0.0, min=-np.pi/2., max=np.pi/2)
42-
params.add('omega', value= 1.0, min=0, max=10)
34+
params.add('amp', value=1, min=0, max=100)
35+
params.add('decay', value=0.0, min=0, max=10)
36+
params.add('shift', value=0.0, min=-np.pi/2., max=np.pi/2)
37+
params.add('omega', value=1.0, min=0, max=10)
4338

4439
return minimize(obj_func, params, args=(x, data))
4540

@@ -49,32 +44,31 @@ def time_minimize_withnan(self):
4944
x[53] = np.nan
5045

5146
data = (5. * np.sin(2 * x - 0.1) * np.exp(-x*x*0.025) +
52-
np.random.normal(size=len(x), scale=0.3) )
47+
np.random.normal(size=len(x), scale=0.3))
5348
params = Parameters()
54-
params.add('amp', value= 1, min=0, max=100)
55-
params.add('decay', value= 0.0, min=0, max=10)
56-
params.add('shift', value= 0.0, min=-np.pi/2., max=np.pi/2)
57-
params.add('omega', value= 1.0, min=0, max=10)
49+
params.add('amp', value=1, min=0, max=100)
50+
params.add('decay', value=0.0, min=0, max=10)
51+
params.add('shift', value=0.0, min=-np.pi/2., max=np.pi/2)
52+
params.add('omega', value=1.0, min=0, max=10)
5853

5954
return minimize(obj_func, params, args=(x, data), nan_policy='omit')
6055

6156
def time_minimize_large(self):
6257
np.random.seed(201)
6358
x = np.linspace(0, 19, 70001)
64-
data = (5. * np.sin(0.6* x - 0.1) * np.exp(-x*x*0.0165) +
65-
np.random.normal(size=len(x), scale=0.3) )
59+
data = (5. * np.sin(0.6*x - 0.1) * np.exp(-x*x*0.0165) +
60+
np.random.normal(size=len(x), scale=0.3))
6661
params = Parameters()
67-
params.add('amp', value= 1, min=0, max=100)
68-
params.add('decay', value= 0.0, min=0, max=10)
69-
params.add('shift', value= 0.0, min=-np.pi/2., max=np.pi/2)
70-
params.add('omega', value= 0.40, min=0, max=10)
62+
params.add('amp', value=1, min=0, max=100)
63+
params.add('decay', value=0.0, min=0, max=10)
64+
params.add('shift', value=0.0, min=-np.pi/2., max=np.pi/2)
65+
params.add('omega', value=0.40, min=0, max=10)
7166

7267
return minimize(obj_func, params, args=(x, data))
7368

74-
7569
def time_confinterval(self):
7670
np.random.seed(0)
77-
x = np.linspace(0.3,10,100)
71+
x = np.linspace(0.3, 10, 100)
7872
y = 1/(0.1*x)+2+0.1*np.random.randn(x.size)
7973

8074
p = Parameters()
@@ -135,6 +129,7 @@ def Minimizer_Residual(p, x, y):
135129
+ v['a2'] * np.exp(-(x - 0.1) / v['t2'])
136130
- y)
137131

132+
138133
def Minimizer_lnprob(p, x, y):
139134
noise = p['noise'].value
140135
return -0.5 * np.sum((Minimizer_Residual(p, x, y) / noise)**2

‎examples/NISTModels.py

+31-31
Original file line numberDiff line numberDiff line change
@@ -138,33 +138,33 @@ def Thurber(b, x, y=0):
138138

139139

140140
# Model name fcn, #fitting params, dim of x
141-
Models = {'Bennett5': (Bennet5, 3, 1),
142-
'BoxBOD': (BoxBOD, 2, 1),
143-
'Chwirut1': (Chwirut, 3, 1),
144-
'Chwirut2': (Chwirut, 3, 1),
145-
'DanWood': (DanWood, 2, 1),
146-
'ENSO': (ENSO, 9, 1),
147-
'Eckerle4': (Eckerle4, 3, 1),
148-
'Gauss1': (Gauss, 8, 1),
149-
'Gauss2': (Gauss, 8, 1),
150-
'Gauss3': (Gauss, 8, 1),
151-
'Hahn1': (Hahn1, 7, 1),
152-
'Kirby2': (Kirby, 5, 1),
153-
'Lanczos1': (Lanczos, 6, 1),
154-
'Lanczos2': (Lanczos, 6, 1),
155-
'Lanczos3': (Lanczos, 6, 1),
156-
'MGH09': (MGH09, 4, 1),
157-
'MGH10': (MGH10, 3, 1),
158-
'MGH17': (MGH17, 5, 1),
159-
'Misra1a': (Misra1a, 2, 1),
160-
'Misra1b': (Misra1b, 2, 1),
161-
'Misra1c': (Misra1c, 2, 1),
162-
'Misra1d': (Misra1d, 2, 1),
163-
'Nelson': (Nelson, 3, 2),
164-
'Rat42': (Rat42, 3, 1),
165-
'Rat43': (Rat43, 4, 1),
166-
'Roszman1': (Roszman1, 4, 1),
167-
'Thurber': (Thurber, 7, 1)}
141+
Models = {'Bennett5': (Bennet5, 3, 1),
142+
'BoxBOD': (BoxBOD, 2, 1),
143+
'Chwirut1': (Chwirut, 3, 1),
144+
'Chwirut2': (Chwirut, 3, 1),
145+
'DanWood': (DanWood, 2, 1),
146+
'ENSO': (ENSO, 9, 1),
147+
'Eckerle4': (Eckerle4, 3, 1),
148+
'Gauss1': (Gauss, 8, 1),
149+
'Gauss2': (Gauss, 8, 1),
150+
'Gauss3': (Gauss, 8, 1),
151+
'Hahn1': (Hahn1, 7, 1),
152+
'Kirby2': (Kirby, 5, 1),
153+
'Lanczos1': (Lanczos, 6, 1),
154+
'Lanczos2': (Lanczos, 6, 1),
155+
'Lanczos3': (Lanczos, 6, 1),
156+
'MGH09': (MGH09, 4, 1),
157+
'MGH10': (MGH10, 3, 1),
158+
'MGH17': (MGH17, 5, 1),
159+
'Misra1a': (Misra1a, 2, 1),
160+
'Misra1b': (Misra1b, 2, 1),
161+
'Misra1c': (Misra1c, 2, 1),
162+
'Misra1d': (Misra1d, 2, 1),
163+
'Nelson': (Nelson, 3, 2),
164+
'Rat42': (Rat42, 3, 1),
165+
'Rat43': (Rat43, 4, 1),
166+
'Roszman1': (Roszman1, 4, 1),
167+
'Thurber': (Thurber, 7, 1)}
168168

169169

170170
def ReadNistData(dataset):
@@ -217,8 +217,8 @@ def ReadNistData(dataset):
217217

218218
y = array(y)
219219
x = array(x)
220-
out = {'y': y, 'x': x, 'nparams': nparams, 'ndata': ndata,
221-
'nfree': nfree, 'start1': start1, 'start2': start2,
222-
'sum_squares': sum_squares, 'std_dev': std_dev,
223-
'cert': certval, 'cert_values': certval, 'cert_stderr': certerr}
220+
out = {'y': y, 'x': x, 'nparams': nparams, 'ndata': ndata, 'nfree': nfree,
221+
'start1': start1, 'start2': start2, 'sum_squares': sum_squares,
222+
'std_dev': std_dev, 'cert': certval, 'cert_values': certval,
223+
'cert_stderr': certerr}
224224
return out

‎examples/benchmark_fit.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -55,7 +55,7 @@ def profile_command(command, filename=None):
5555
gitversion = get_git_version()
5656
if filename is None:
5757
filename = '%s.prof' % gitversion
58-
prof = cProfile.run(command, filename=filename)
58+
cProfile.run(command, filename=filename)
5959
show_profile(filename)
6060

6161

‎examples/example_covar.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -36,7 +36,7 @@ def residual(pars, x, sigma=None, data=None):
3636
p_true.add('line_slope', value=0.62)
3737

3838
data = (gaussian(x, p_true['amp_g'], p_true['cen_g'], p_true['wid_g']) +
39-
random.normal(scale=0.23, size=n) +
39+
random.normal(scale=0.23, size=n) +
4040
x*p_true['line_slope'] + p_true['line_off'])
4141

4242
if HASPYLAB:

‎examples/example_derivfunc.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -20,7 +20,7 @@ def func(pars, x, data=None):
2020

2121

2222
def dfunc(pars, x, data=None):
23-
a, b, c = pars['a'], pars['b'], pars['c']
23+
a, b = pars['a'], pars['b']
2424
v = np.exp(-b*x)
2525
return np.array([v, -a*x*v, np.ones(len(x))])
2626

‎examples/example_lbfgsb.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -38,7 +38,7 @@ def residual(pars, x, data=None):
3838
fit_params = Parameters()
3939
fit_params.add('amp', value=11.0, min=5, max=20)
4040
fit_params.add('period', value=5., min=1., max=7)
41-
fit_params.add('shift', value=.10, min=0.0, max=0.2)
41+
fit_params.add('shift', value=.10, min=0.0, max=0.2)
4242
fit_params.add('decay', value=6.e-3, min=0, max=0.1)
4343

4444
init = residual(fit_params, x)

‎examples/fit_NIST_lmfit.py

+1-3
Original file line numberDiff line numberDiff line change
@@ -49,7 +49,7 @@ def Compare_NIST_Results(DataSet, myfit, NISTdata):
4949
chi2 = myfit.chisqr
5050
print(' | Sum of Squares | %.7e | %.7e | %2i |' % (chi2, sumsq,
5151
ndig(chi2, sumsq)))
52-
except:
52+
except Exception:
5353
pass
5454
print(' |----------------+----------------+------------------+-------------------|')
5555
if not myfit.errorbars:
@@ -72,8 +72,6 @@ def NIST_Test(DataSet, method='leastsq', start='start2', plot=True):
7272
params = Parameters()
7373
for i in range(npar):
7474
pname = 'b%i' % (i+1)
75-
cval = NISTdata['cert_values'][i]
76-
cerr = NISTdata['cert_stderr'][i]
7775
pval1 = NISTdata[start][i]
7876
params.add(pname, value=pval1)
7977

‎examples/fit_NIST_scipy_lmdif.py

-4
Original file line numberDiff line numberDiff line change
@@ -32,7 +32,6 @@ def Compare_NIST_Results(DataSet, vals, NISTdata):
3232
print(' |----------------+----------------+------------------+-------------------|')
3333

3434
val_dig_min = 1000
35-
err_dig_min = 1000
3635
for i in range(NISTdata['nparams']):
3736
parname = 'b%i' % (i+1)
3837
thisval = vals[i]
@@ -58,9 +57,6 @@ def NIST_Test(DataSet, start='start2', plot=True):
5857

5958
vals = []
6059
for i in range(npar):
61-
pname = 'b%i' % (i+1)
62-
cval = NISTdata['cert_values'][i]
63-
cerr = NISTdata['cert_stderr'][i]
6460
pval1 = NISTdata[start][i]
6561
vals.append(pval1)
6662

‎examples/fit_with_analytic_jacobian.py

+2-1
Original file line numberDiff line numberDiff line change
@@ -43,7 +43,8 @@ def dfunc_lorentzian(params, *ys, **xs):
4343
mod = GaussianModel()
4444
pars = mod.guess(yn, xs)
4545
out = mod.fit(yn, pars, x=xs)
46-
out2 = mod.fit(yn, pars, x=xs, fit_kws={'Dfun': dfunc_gaussian, 'col_deriv': 1})
46+
out2 = mod.fit(yn, pars, x=xs, fit_kws={'Dfun': dfunc_gaussian,
47+
'col_deriv': 1})
4748
print('lmfit without dfunc **************')
4849
print('number of function calls: ', out.nfev)
4950
print('params', out.best_values)

‎examples/lmfit_and_emcee.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -67,7 +67,7 @@ def create_all(mini, sigma=None):
6767
sigma will be assumed the same for all residuals and
6868
is added to the sampled parameters.
6969
"""
70-
sigma_given = not sigma is None
70+
sigma_given = sigma is not None
7171
lnprior = create_prior(mini.params)
7272
lnprob = create_lnliklihood(mini, sigma=sigma)
7373
guess = starting_guess(mini, not sigma_given)

‎lmfit/jsonutils.py

+2-1
Original file line numberDiff line numberDiff line change
@@ -27,7 +27,8 @@ def bindecode(val):
2727
if six.PY3:
2828
def binencode(val):
2929
"""b64encode wrapper, Python 3 version."""
30-
return str(b64encode(val), 'utf-8') # b64encode results is /always/ UTF-8
30+
# b64encode result is /always/ UTF-8
31+
return str(b64encode(val), 'utf-8')
3132
else:
3233
def binencode(val):
3334
"""b64encode wrapper, Python 2 version."""

‎lmfit/minimizer.py

+1-2
Original file line numberDiff line numberDiff line change
@@ -102,8 +102,7 @@ def eval_stderr(obj, uvars, _names, _pars):
102102
uval = wrap_ueval(*uvars, _obj=obj, _names=_names, _pars=_pars)
103103
try:
104104
obj.stderr = uval.std_dev
105-
# TODO: do not use bare except
106-
except:
105+
except Exception:
107106
obj.stderr = 0
108107

109108

‎lmfit/model.py

+1-1
Original file line numberDiff line numberDiff line change
@@ -36,7 +36,7 @@ def _align(var, mask, data):
3636

3737

3838
try:
39-
import matplotlib
39+
import matplotlib # noqa: F401
4040
_HAS_MATPLOTLIB = True
4141
except Exception:
4242
_HAS_MATPLOTLIB = False

‎lmfit/parameter.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -190,8 +190,8 @@ def __setstate__(self, state):
190190
def update_constraints(self):
191191
"""Update all constrained parameters, checking that dependencies are
192192
evaluated as needed."""
193-
requires_update = {name for name, par in self.items()
194-
if par._expr is not None}
193+
requires_update = {name for name, par in self.items() if par._expr is
194+
not None}
195195
updated_tracker = set(requires_update)
196196

197197
def _update_param(name):

‎lmfit/ui/basefitter.py

+12-10
Original file line numberDiff line numberDiff line change
@@ -1,10 +1,10 @@
1-
import warnings
1+
import warnings # noqa: F401
22

33
from asteval import Interpreter
44
from asteval.astutils import NameFinder
5-
import numpy as np
5+
import numpy as np # noqa: F401
66

7-
from ..model import Model
7+
from ..model import Model # noqa: F401
88
from ..models import ExponentialModel # arbitrary default
99
from ..parameter import check_ast_errors
1010

@@ -55,6 +55,7 @@ class BaseFitter(object):
5555
model : lmfit.Model
5656
optional initial Model to use, maybe be set or changed later
5757
""" + _COMMON_EXAMPLES_DOC
58+
5859
def __init__(self, data, model=None, **kwargs):
5960
self._data = data
6061
self.kwargs = kwargs
@@ -165,8 +166,8 @@ def __assign_deps(self, params):
165166
self.namefinder.names = []
166167
self.namefinder.generic_visit(par.ast)
167168
for symname in self.namefinder.names:
168-
if (symname in self.current_params and
169-
symname not in par.deps):
169+
if (symname in self.current_params and symname not in
170+
par.deps):
170171
par.deps.append(symname)
171172
self.asteval.symtable[name] = par.value
172173
if par.name is None:
@@ -223,8 +224,9 @@ class MPLFitter(BaseFitter):
223224
line
224225
**kwargs : independent variables or extra arguments, passed like `x=x`
225226
""" + _COMMON_EXAMPLES_DOC
226-
def __init__(self, data, model=None, axes_style={},
227-
data_style={}, init_style={}, best_style={}, **kwargs):
227+
228+
def __init__(self, data, model=None, axes_style={}, data_style={},
229+
init_style={}, best_style={}, **kwargs):
228230
self.axes_style = axes_style
229231
self.data_style = data_style
230232
self.init_style = init_style
@@ -266,16 +268,16 @@ def plot(self, axes_style={}, data_style={}, init_style={}, best_style={},
266268
"that does not depend on matplotlib.")
267269

268270
# Configure style
269-
_axes_style= {} # none, but this is here for possible future use
271+
_axes_style = {} # none, but this is here for possible future use
270272
_axes_style.update(self.axes_style)
271273
_axes_style.update(axes_style)
272-
_data_style= dict(color='blue', marker='o', linestyle='none')
274+
_data_style = dict(color='blue', marker='o', linestyle='none')
273275
_data_style.update(**_normalize_kwargs(self.data_style, 'line2d'))
274276
_data_style.update(**_normalize_kwargs(data_style, 'line2d'))
275277
_init_style = dict(color='gray')
276278
_init_style.update(**_normalize_kwargs(self.init_style, 'line2d'))
277279
_init_style.update(**_normalize_kwargs(init_style, 'line2d'))
278-
_best_style= dict(color='red')
280+
_best_style = dict(color='red')
279281
_best_style.update(**_normalize_kwargs(self.best_style, 'line2d'))
280282
_best_style.update(**_normalize_kwargs(best_style, 'line2d'))
281283

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