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fix: r_values in fits are now properly propagated

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Fabian Joswig 2021-12-04 11:55:11 +00:00
parent 37e93f754c
commit 06dc6cd808
1 changed files with 3 additions and 6 deletions
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9
pyerrors/fits.py
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@ -301,8 +301,7 @@ def total_least_squares(x, y, func, silent=False, **kwargs):
result = []
for i in range(n_parms):
result.append(derived_observable(lambda x, **kwargs: x[0], list(x.ravel()) + list(y), man_grad=list(deriv_x[i]) + list(deriv_y[i])))
result[-1]._value = out.beta[i]
result.append(derived_observable(lambda my_var, **kwargs: my_var[0] / x.ravel()[0].value * out.beta[i], list(x.ravel()) + list(y), man_grad=list(deriv_x[i]) + list(deriv_y[i])))
output.fit_parameters = result + const_par
@ -419,8 +418,7 @@ def _prior_fit(x, y, func, priors, silent=False, **kwargs):
result = []
for i in range(n_parms):
result.append(derived_observable(lambda x, **kwargs: x[0], list(y) + list(loc_priors), man_grad=list(deriv[i])))
result[-1]._value = params[i]
result.append(derived_observable(lambda x, **kwargs: x[0] / y[0].value * params[i], list(y) + list(loc_priors), man_grad=list(deriv[i])))
output.fit_parameters = result
output.chisquare = chisqfunc(np.asarray(params))
@ -614,8 +612,7 @@ def _standard_fit(x, y, func, silent=False, **kwargs):
result = []
for i in range(n_parms):
result.append(derived_observable(lambda x, **kwargs: x[0], list(y), man_grad=list(deriv[i])))
result[-1]._value = fit_result.x[i]
result.append(derived_observable(lambda x, **kwargs: x[0] / y[0].value * fit_result.x[i], list(y), man_grad=list(deriv[i])))
output.fit_parameters = result + const_par