207-noncomplex-fits #244
| @@ -469,7 +469,6 @@ class FitRoutine(object): | |||||||
|             corr: np.ndarray = None, |             corr: np.ndarray = None, | ||||||
|             partial_corr: np.ndarray = None, |             partial_corr: np.ndarray = None, | ||||||
|     ): |     ): | ||||||
|         print(data.complex_type) |  | ||||||
|         if err is None: |         if err is None: | ||||||
|             err = [0] * len(p) |             err = [0] * len(p) | ||||||
|  |  | ||||||
| @@ -523,6 +522,7 @@ class FitRoutine(object): | |||||||
|  |  | ||||||
|         return self.result |         return self.result | ||||||
|  |  | ||||||
|  |  | ||||||
| def _calc_error(jac, chi, nobs, nvars): | def _calc_error(jac, chi, nobs, nvars): | ||||||
|     # copy of scipy.curve_fit to calculate covariance |     # copy of scipy.curve_fit to calculate covariance | ||||||
|     # noinspection PyTupleAssignmentBalance |     # noinspection PyTupleAssignmentBalance | ||||||
|   | |||||||
| @@ -99,7 +99,6 @@ class FitResultCreator: | |||||||
|             fun_kwargs['complex_mode'] = 0 |             fun_kwargs['complex_mode'] = 0 | ||||||
|  |  | ||||||
|         _y = check_complex(model.func(p_final, _x, **fun_kwargs), actual_mode, data_mode) |         _y = check_complex(model.func(p_final, _x, **fun_kwargs), actual_mode, data_mode) | ||||||
|         print(_y) |  | ||||||
|  |  | ||||||
|         fun_kwargs['complex_mode'] = actual_mode |         fun_kwargs['complex_mode'] = actual_mode | ||||||
|  |  | ||||||
|   | |||||||
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