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simple numpy based 2d gaussian function
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import numpy as np | |
def makeGaussian(size, fwhm = 3, center=None): | |
""" Make a square gaussian kernel. | |
size is the length of a side of the square | |
fwhm is full-width-half-maximum, which | |
can be thought of as an effective radius. | |
""" | |
x = np.arange(0, size, 1, float) | |
y = x[:,np.newaxis] | |
if center is None: | |
x0 = y0 = size // 2 | |
else: | |
x0 = center[0] | |
y0 = center[1] | |
return np.exp(-4*np.log(2) * ((x-x0)**2 + (y-y0)**2) / fwhm**2) |
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