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fix: Combined fit can now handle list and array inputs for y-values, test added.
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2 changed files with 12 additions and 15 deletions
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@ -703,12 +703,8 @@ def _combined_fit(x, y, func, silent=False, **kwargs):
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jacobian = auto_jacobian
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hessian = auto_hessian
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x_all = []
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y_all = []
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for key in x.keys():
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y_all += y[key]
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x_all = np.concatenate([np.array(o) for o in x.values()])
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y_all = np.concatenate([np.array(o) for o in y.values()])
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if len(x_all.shape) > 2:
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raise Exception('Unknown format for x values')
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@ -610,18 +610,19 @@ def test_ks_test():
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def test_combined_fit_list_v_array():
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res = []
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y_test = {'a': [pe.Obs([np.random.normal(i, 0.5, 1000)], ['ensemble1']) for i in range(1, 7)]}
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for x_test in [{'a': [0, 1, 2, 3, 4, 5]}, {'a': np.arange(6)}]:
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for key in y_test.keys():
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[item.gamma_method() for item in y_test[key]]
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def func_a(a, x):
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return a[1] * x + a[0]
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for y_test in [{'a': [pe.Obs([np.random.normal(i, 0.5, 1000)], ['ensemble1']) for i in range(1, 7)]},
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{'a': np.array([pe.Obs([np.random.normal(i, 0.5, 1000)], ['ensemble1']) for i in range(1, 7)])}]:
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for x_test in [{'a': [0, 1, 2, 3, 4, 5]}, {'a': np.arange(6)}]:
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for key in y_test.keys():
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[item.gamma_method() for item in y_test[key]]
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def func_a(a, x):
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return a[1] * x + a[0]
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funcs_test = {"a": func_a}
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res.append(pe.fits.least_squares(x_test, y_test, funcs_test))
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funcs_test = {"a": func_a}
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res.append(pe.fits.least_squares(x_test, y_test, funcs_test))
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assert (res[0][0] - res[1][0]).is_zero(atol=1e-8)
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assert (res[0][1] - res[1][1]).is_zero(atol=1e-8)
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assert (res[0][0] - res[1][0]).is_zero(atol=1e-8)
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assert (res[0][1] - res[1][1]).is_zero(atol=1e-8)
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def fit_general(x, y, func, silent=False, **kwargs):
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