[Numpy-discussion] Learn about numpy

Folkert Boonstra F.Boonstra@inter.nl....
Sun May 4 04:52:44 CDT 2008

With a python background but new to numpy, I have the following.

Suppose I have a 2-D array and I want to apply a function to each element.
The function needs to access the direct neighbouring elements in order
to set a new value for the element. How would I do that in the most
efficient way with numpy?

Currently I have a uint8 array (self.bufbw) filled with 0 and 1 elements:

    def applyRule(self, rule):
       for xy in self.xydims:

    def rule(self, xy):
        x = xy[0]; y = xy[1]
        sum = self.bufbw[x-1:x+2, y-1:y+2].sum() \
            - self.bufbw[x-1,y-1] - self.bufbw[x+1,y-1] \
            - self.bufbw[x-1,y+1] - self.bufbw[x+1,y+1]
        if sum == 1:
            self.bufbw[x,y] = 1
            self.bufbw[x,y] = 0

I have looked at the documentation online but couldn't find another faster solution yet. 
Does anyone want to share some ideas on a faster solution with numpy?


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