30 lines
891 B
Python
30 lines
891 B
Python
import numpy as np
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import scipy.optimize
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def gfitoff(x, y, off=None, amp=None, com=None, sigma=None):
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if off is None:
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off = y.min() # good enough starting point for offset
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if com is None:
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com = x[y.argmax()]
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if amp is None:
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amp = y.max() - off
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# For normalised gauss curve sigma=1/(amp*sqrt(2*pi))
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if sigma is None:
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surface = np.trapz((y-off), x=x)
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sigma = surface / (amp * np.sqrt(2 * np.pi))
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try:
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popt, pcov = scipy.optimize.curve_fit(gauss_fn, x, y, p0=[off, amp, com, sigma], method='lm')
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popt[3] = abs(popt[3]) # sigma should be returned as positive
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except Exception as e:
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print("Gauss fitting not successful.\n" + str(e))
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popt = [off, amp, com, abs(sigma)]
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return popt
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def gauss_fn(x, a, b, c, d):
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return a + b * np.exp(-(np.power((x - c), 2) / (2 * np.power(d, 2)))) |