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fix: bug in estimation of chisquare for correlated fit fixed, tests

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added.
This commit is contained in:
Fabian Joswig 2022-05-26 13:52:05 +01:00
parent ff5540d667
commit e7f5961cd6
2 changed files with 9 additions and 1 deletions
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6
pyerrors/fits.py
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@ -525,6 +525,10 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
fit_result = scipy.optimize.least_squares(chisqfunc_residuals_corr, fit_result.x, method='lm', ftol=1e-15, gtol=1e-15, xtol=1e-15) fit_result = scipy.optimize.least_squares(chisqfunc_residuals_corr, fit_result.x, method='lm', ftol=1e-15, gtol=1e-15, xtol=1e-15)
chisquare = np.sum(fit_result.fun ** 2) chisquare = np.sum(fit_result.fun ** 2)
if kwargs.get('correlated_fit') is True:
assert np.isclose(chisquare, chisqfunc_corr(fit_result.x), atol=1e-14)
else:
assert np.isclose(chisquare, chisqfunc(fit_result.x), atol=1e-14)
output.iterations = fit_result.nfev output.iterations = fit_result.nfev
@ -585,7 +589,7 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
output.fit_parameters = result output.fit_parameters = result
output.chisquare = chisqfunc(fit_result.x) output.chisquare = chisquare
output.dof = x.shape[-1] - n_parms output.dof = x.shape[-1] - n_parms
output.p_value = 1 - chi2.cdf(output.chisquare, output.dof) output.p_value = 1 - chi2.cdf(output.chisquare, output.dof)

4
tests/fits_test.py
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@ -149,8 +149,10 @@ def test_correlated_fit():
return p[1] * anp.exp(-p[0] * x) return p[1] * anp.exp(-p[0] * x)
fitp = pe.least_squares(x, data, fitf, expected_chisquare=True) fitp = pe.least_squares(x, data, fitf, expected_chisquare=True)
assert np.isclose(fitp.chisquare / fitp.dof, fitp.chisquare_by_dof, atol=1e-14)
fitpc = pe.least_squares(x, data, fitf, correlated_fit=True) fitpc = pe.least_squares(x, data, fitf, correlated_fit=True)
assert np.isclose(fitpc.chisquare / fitpc.dof, fitpc.chisquare_by_dof, atol=1e-14)
for i in range(2): for i in range(2):
diff = fitp[i] - fitpc[i] diff = fitp[i] - fitpc[i]
diff.gamma_method() diff.gamma_method()
@ -176,6 +178,8 @@ def test_fit_corr_independent():
out_corr = pe.least_squares(x, oy, func, correlated_fit=True, method=method) out_corr = pe.least_squares(x, oy, func, correlated_fit=True, method=method)
assert np.isclose(out.chisquare, out_corr.chisquare) assert np.isclose(out.chisquare, out_corr.chisquare)
assert np.isclose(out.dof, out_corr.dof)
assert np.isclose(out.chisquare_by_dof, out_corr.chisquare_by_dof)
assert (out[0] - out_corr[0]).is_zero(atol=1e-5) assert (out[0] - out_corr[0]).is_zero(atol=1e-5)
assert (out[1] - out_corr[1]).is_zero(atol=1e-5) assert (out[1] - out_corr[1]).is_zero(atol=1e-5)