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feat: Hotelling t-squared p-value for correlated fits added.

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Fabian Joswig 2022-12-06 17:17:03 +00:00
parent d7628b69d1
commit 19bf558c78
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1 changed files with 13 additions and 0 deletions
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pyerrors/fits.py
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@ -25,6 +25,12 @@ class Fit_result(Sequence):
fit_parameters : list
results for the individual fit parameters,
also accessible via indices.
chisquare_by_dof : float
reduced chisquare.
p_value : float
p-value of the fit
t2_p_value : float
Hotelling t-squared p-value for correlated fits.
"""
def __init__(self):
@ -50,6 +56,8 @@ class Fit_result(Sequence):
my_str += '\u03C7\u00b2/\u03C7\u00b2exp = ' + f'{self.chisquare_by_expected_chisquare:2.6f}' + '\n'
if hasattr(self, 'p_value'):
my_str += 'p-value = ' + f'{self.p_value:2.4f}' + '\n'
if hasattr(self, 't2_p_value'):
my_str += 't\u00B2p-value = ' + f'{self.t2_p_value:2.4f}' + '\n'
my_str += 'Fit parameters:\n'
for i_par, par in enumerate(self.fit_parameters):
my_str += str(i_par) + '\t' + ' ' * int(par >= 0) + str(par).rjust(int(par < 0.0)) + '\n'
@ -633,6 +641,11 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
output.chisquare = chisquare
output.dof = x.shape[-1] - n_parms
output.p_value = 1 - scipy.stats.chi2.cdf(output.chisquare, output.dof)
# Hotelling t-squared p-value for correlated fits.
if kwargs.get('correlated_fit') is True:
n_cov = np.min(np.vectorize(lambda x: x.N)(y))
output.t2_p_value = 1 - scipy.stats.f.cdf((n_cov - output.dof) / (output.dof * (n_cov - 1)) * output.chisquare,
output.dof, n_cov - output.dof)
if kwargs.get('resplot') is True:
residual_plot(x, y, func, result)