def moving_average_2d(self, data, window):
"""Moving average on two-dimensional data.
"""
# Makes sure that the window function is normalized.
window /= window.sum()
# Makes sure data array is a numpy array or masked array.
if type(data).__name__ not in ['ndarray', 'MaskedArray']:
data = numpy.asarray(data)
# The output array has the same dimensions as the input data
# (mode='same') and symmetrical boundary conditions are assumed
# (boundary='symm').
return convolve2d(data, window, mode='same', boundary='symm')
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