script/cpython/gfitoff.py

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