[SciPy-User] Fitting to a combination of gaussian functions
Fri Oct 5 14:03:28 CDT 2012
I wanted to fit some data to a function that contains the combination of
2 gaussian functions of different widths (the same height and position
of the peak). For that I created the following function:
def gaussian_func(x, a, b, c1, c2):
a is the height of curve peak
b is the position of the center of the peak
c1 is the width for negative values of x
c2 is the width for positive values of x
val = a*exp( -( (x-b)**2/(2*c2**2) ) )
val = a*exp( -( (x-b)**2/(2*c1**2) ) )
But when I try to fit the data with scipy.optimize.curve_fit i get the
"The truth value of an array with more than one element is ambiguous.
Use a.any() or a.all()"
xdata = np.array([21, 36, 53, 67,60,66, 30,36, 19])
ydata = np.array([-100. -50. -20. -10. 0. 10. 20. 50. 100.])
curve_fit(gaussian_func, xdata, ydata)
I guess this is because the function is vectorized. Is there any way to
avoid this behaviour or any other way to fit these data ?
Thanks in advance
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