I'm trying to use scipy.ndimage.filters.generic_filter to calculate a weighted sum from a neighborhood. The neighborhood will be variable at some point but for now 3x3 is what I'm working towards. So far this is where I am:
def Func(a):
a = np.reshape((3,3))
weights = np.array([[0.5,.05,0.5],[0.5,1,0.5],[0.5,0.5,0.5]])
a = np.multiply(a,weights)
a = np.sum(a)
return a
ndimage.filters.generic_filter(Array,Func,
footprint=np.ones((3,3)),mode='constant',cval=0.0,origin=0.0)
I get an error from ndimage saying 'TypeError: a float is required' but I don't know what argument it's referring to and it looks basically the same as other examples I've seen.
This worked for me. There were a couple little problems with the code:
import scipy.ndimage.filters
import numpy as np
Array = rand( 100,100 )
def Func(a):
a = a.reshape((3,3))
weights = np.array([[0.5,.05,0.5],[0.5,1,0.5],[0.5,0.5,0.5]])
a = np.multiply(a,weights)
a = np.sum(a)
return a
out = scipy.ndimage.filters.generic_filter(Array,Func,footprint=np.ones((3,3)),mode='constant',cval=0.0,origin=0.0)
You had a = np.reshape( (3,3) )
which isn't correct. Is that what you want?
[update]
To clean this up a little based on our discussion:
import scipy.ndimage.filters
import numpy as np
Array = rand( 100,100 )
def Func(a):
return np.sum( a * r_[0.5,.05,0.5, 0.5,1,0.5, 0.5,0.5,0.5] )
out = scipy.ndimage.filters.generic_filter(Array,Func,footprint=np.ones((3,3)),mode='constant',cval=0.0,origin=0.0)