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Update fit2.py

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While function to find different indexes if the peak is very thin and sigma is much smaller than step, added the find_nearest which was missing for some reason.
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JakHolzer 2020-09-14 14:34:26 +02:00 committed by Ivan Usov
parent b157c2a3ae
commit aa9b0c99ae
1 changed files with 19 additions and 3 deletions
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18
pyzebra/fit2.py
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@ -4,6 +4,12 @@ from scipy import integrate
from scipy.integrate import simps from scipy.integrate import simps
def find_nearest(array, value):
array = np.asarray(array)
idx = (np.abs(array - value)).argmin()
return idx
def fitccl( def fitccl(
data, keys, guess, vary, constraints_min, constraints_max, numfit_min=None, numfit_max=None data, keys, guess, vary, constraints_min, constraints_max, numfit_min=None, numfit_max=None
): ):
@ -100,7 +106,17 @@ def fitccl(
) )
numfit_min = gauss_3sigmamin if numfit_min is None else find_nearest(x, numfit_min) numfit_min = gauss_3sigmamin if numfit_min is None else find_nearest(x, numfit_min)
numfit_max = gauss_3sigmamax if numfit_max is None else find_nearest(x, numfit_max) numfit_max = gauss_3sigmamax if numfit_max is None else find_nearest(x, numfit_max)
print(numfit_max, numfit_min) it = -1
while numfit_max == numfit_min:
it = it + 1
numfit_min = find_nearest(
x, result.params["g_cen"].value - 3 * (1 + it / 10) * result.params["g_width"].value
)
numfit_max = find_nearest(
x, result.params["g_cen"].value + 3 * (1 + it / 10) * result.params["g_width"].value
)
if x[numfit_min] < np.min(x): if x[numfit_min] < np.min(x):
numfit_min = gauss_3sigmamin numfit_min = gauss_3sigmamin
print("Minimal integration value outside of x range") print("Minimal integration value outside of x range")