CODEWITHSUNDEEP
pythonarraysnumpy
RParadox
RParadox

Reputation: 6851

Numpy: calculate edges of a matrix

I have the following to calculate the difference of a matrix, i.e. the i-th element - the (i-1) element.

How can I (easily) calculate the difference for each element horizontally and vertically? With a transpose?

inputarr = np.arange(12)
inputarr.shape = (3,4)
inputarr+=1

#shift one position
newarr = list()
for x in inputarr:
    newarr.append(np.hstack((np.array([0]),x[:-1])))

z = np.array(newarr)    
print inputarr
print 'first differences'
print inputarr-z

Output

[[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]]

first differences
[[1 1 1 1]
 [5 1 1 1]
 [9 1 1 1]]

Upvotes: 2

Views: 1279

Answers (1)

John Vinyard
John Vinyard

Reputation: 13485

Check out numpy.diff.

From the documentation:

Calculate the n-th order discrete difference along given axis.

The first order difference is given by out[n] = a[n+1] - a[n] along the given axis, higher order differences are calculated by using diff recursively.

An example:

>>> import numpy as np
>>> a = np.arange(12).reshape((3,4))
>>> a
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
>>> np.diff(a,axis = 1) # row-wise
array([[1, 1, 1],
       [1, 1, 1],
       [1, 1, 1]])
>>> np.diff(a, axis = 0) # column-wise
array([[4, 4, 4, 4],
       [4, 4, 4, 4]])

Upvotes: 3

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