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fit results for all-fixed global parameter

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Dominik Demuth 2023-12-25 15:28:54 +01:00
parent 289de202bc
commit 7cca24950a
1 changed files with 20 additions and 15 deletions
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35
src/nmreval/fit/minimizer.py
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@ -237,29 +237,34 @@ class FitRoutine(object):
if p0_k is None:
self.make_results(data, data.para_keys, var_pars_k, data.para_keys, (len(data.para_keys), len(data.para_keys)),
err=None, corr=None, partial_corr=None)
return self.result
else:
if mode == 'lsq':
self._least_squares_single(data, p0_k, lb_k, ub_k, var_pars_k)
if mode == 'lsq':
self._least_squares_single(data, p0_k, lb_k, ub_k, var_pars_k)
elif mode == 'nm':
self._nm_single(data, p0_k, lb_k, ub_k, var_pars_k)
elif mode == 'nm':
self._nm_single(data, p0_k, lb_k, ub_k, var_pars_k)
elif mode == 'odr':
# ODR takes no bounds
self._odr_single(data, p0_k, var_pars_k)
elif mode == 'odr':
# ODR takes no bounds
self._odr_single(data, p0_k, var_pars_k)
else:
data_pars, p0, lb, ub, var_pars = self._prep_global(data_groups, linked_parameter)
if mode == 'lsq':
self._least_squares_global(data_groups, p0, lb, ub, var_pars, data_pars)
if not p0:
for data_k, p_k in zip(data_groups, data_pars):
self.make_results(data_k, p_k, [], p_k, (len(p_k), len(p_k)),
err=None, corr=None, partial_corr=None)
elif mode == 'nm':
self._nm_global(data_groups, p0, lb, ub, var_pars, data_pars)
else:
if mode == 'lsq':
self._least_squares_global(data_groups, p0, lb, ub, var_pars, data_pars)
elif mode == 'odr':
self._odr_global(data_groups, p0, var_pars, data_pars)
elif mode == 'nm':
self._nm_global(data_groups, p0, lb, ub, var_pars, data_pars)
elif mode == 'odr':
self._odr_global(data_groups, p0, var_pars, data_pars)
self.unprep_run()