Update fit2.py
moved the check up so it catches it right after fitting. I think this should solve the problem.
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@ -131,14 +131,16 @@ def fitccl(
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result = mod.fit(
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result = mod.fit(
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y, params, weights=[np.abs(1 / y_err[i]) for i in range(len(y_err))], x=x, calc_covar=True
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y, params, weights=[np.abs(1 / y_err[i]) for i in range(len(y_err))], x=x, calc_covar=True
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)
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)
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# u.ufloat to work with uncertanities
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fit_area = u.ufloat(result.params["g_amp"].value, result.params["g_amp"].stderr)
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comps = result.eval_components()
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if result.params["g_amp"].stderr is None:
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if result.params["g_amp"].stderr is None:
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result.params["g_amp"].stderr = result.params["g_amp"].value
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result.params["g_amp"].stderr = result.params["g_amp"].value
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elif result.params["g_amp"].stderr > result.params["g_amp"].value:
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elif result.params["g_amp"].stderr > result.params["g_amp"].value:
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result.params["g_amp"].stderr = result.params["g_amp"].value
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result.params["g_amp"].stderr = result.params["g_amp"].value
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# u.ufloat to work with uncertanities
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fit_area = u.ufloat(result.params["g_amp"].value, result.params["g_amp"].stderr)
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comps = result.eval_components()
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if len(meas["peak_indexes"]) == 0:
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if len(meas["peak_indexes"]) == 0:
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# for case of no peak, there is no reason to integrate, therefore fit and int are equal
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# for case of no peak, there is no reason to integrate, therefore fit and int are equal
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