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Merge branch 'develop' into documentation

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fjosw 2023-03-08 16:53:18 +00:00
commit f6b14f006e
1 changed files with 4 additions and 6 deletions
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10
pyerrors/fits.py
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@ -204,10 +204,10 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
dy_f = [o.dvalue for o in y_all] dy_f = [o.dvalue for o in y_all]
if len(x_all.shape) > 2: if len(x_all.shape) > 2:
raise Exception('Unknown format for x values') raise ValueError("Unknown format for x values")
if np.any(np.asarray(dy_f) <= 0.0): if np.any(np.asarray(dy_f) <= 0.0):
raise Exception('No y errors available, run the gamma method first.') raise Exception("No y errors available, run the gamma method first.")
# number of fit parameters # number of fit parameters
n_parms_ls = [] n_parms_ls = []
@ -276,7 +276,7 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
p_f = [o.value for o in loc_priors] p_f = [o.value for o in loc_priors]
dp_f = [o.dvalue for o in loc_priors] dp_f = [o.dvalue for o in loc_priors]
if np.any(np.asarray(dp_f) <= 0.0): if np.any(np.asarray(dp_f) <= 0.0):
raise Exception('No prior errors available, run the gamma method first.') raise Exception("No prior errors available, run the gamma method first.")
else: else:
p_f = dp_f = np.array([]) p_f = dp_f = np.array([])
prior_mask = [] prior_mask = []
@ -285,7 +285,7 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
if 'initial_guess' in kwargs: if 'initial_guess' in kwargs:
x0 = kwargs.get('initial_guess') x0 = kwargs.get('initial_guess')
if len(x0) != n_parms: if len(x0) != n_parms:
raise Exception('Initial guess does not have the correct length: %d vs. %d' % (len(x0), n_parms)) raise ValueError('Initial guess does not have the correct length: %d vs. %d' % (len(x0), n_parms))
else: else:
x0 = [0.1] * n_parms x0 = [0.1] * n_parms
@ -404,8 +404,6 @@ def least_squares(x, y, func, priors=None, silent=False, **kwargs):
print('chisquare/expected_chisquare:', output.chisquare_by_expected_chisquare) print('chisquare/expected_chisquare:', output.chisquare_by_expected_chisquare)
fitp = fit_result.x fitp = fit_result.x
if np.any(np.asarray(dy_f) <= 0.0):
raise Exception('No y errors available, run the gamma method first.')
try: try:
hess = hessian(chisqfunc)(fitp) hess = hessian(chisqfunc)(fitp)