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Fixes least_squares with migrad, tests extended

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Simon Kuberski 2022-02-02 09:05:13 +01:00
parent 9b63d8e2bd
commit d1e18b6673
2 changed files with 5 additions and 2 deletions
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5
pyerrors/fits.py
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@ -487,20 +487,21 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
chisq = anp.sum(((y_f - model) / dy_f) ** 2)
return chisq
if 'method' in kwargs:
if 'method' in kwargs and not (kwargs.get('method', 'Levenberg-Marquardt') == 'Levenberg-Marquardt'):
output.method = kwargs.get('method')
if not silent:
print('Method:', kwargs.get('method'))
if kwargs.get('method') == 'migrad':
fit_result = iminuit.minimize(chisqfunc, x0)
fit_result = iminuit.minimize(chisqfunc, fit_result.x)
output.iterations = fit_result.nfev
else:
fit_result = scipy.optimize.minimize(chisqfunc, x0, method=kwargs.get('method'))
fit_result = scipy.optimize.minimize(chisqfunc, fit_result.x, method=kwargs.get('method'), tol=1e-12)
output.iterations = fit_result.nit
chisquare = fit_result.fun
output.iterations = fit_result.nit
else:
output.method = 'Levenberg-Marquardt'
if not silent:

2
tests/fits_test.py
View file

@ -49,6 +49,8 @@ def test_least_squares():
y = a[0] * np.exp(-a[1] * x)
return y
out = pe.least_squares(x, oy, func, method='migrad')
out = pe.least_squares(x, oy, func, method='Powell')
out = pe.least_squares(x, oy, func, expected_chisquare=True, resplot=True, qqplot=True)
beta = out.fit_parameters