Subtracting 3D numpy arrays in Python Vs Matlab
matlab, numpy, python, python-3.x
Solution
You are using Unsigned 32 bit ints. So you're getting an overflow
>>> numpy.uint32(0) - numpy.uint32(1)
4294967295
Try changing your array's to type int…
>>> A = numpy.array([0,1,2],'uint32')
>>> B = numpy.array([1,2,3],'uint32')
>>> A-B
array([4294967295, 4294967295, 4294967295], dtype=uint32)
>>> A = A.astype(int)
>>> B = B.astype(int)
>>> A-B
array([-1, -1, -1])
Problem
I have two 3D numpy arrays and I would like to find out the difference between them. ``` >>>A.dtype dtype('uint32') >>>B.dtype dtype('uint32') >>>A.shape (86, 50, 108) >>>B.shape (86, 50, 108) >>>A.min() 0 >>>B.min() 0 >>>A.max() 89478487 >>>B.max() 89115767 ``` Now, if we do `A - B` ``` >>> diff = abs( A-B ); >>> diff.min() 0 >>> diff.max() 4294967292 ``` Considering the `min` and `max` values of both matrices we cannot have `4294967292` as maximum value of the difference matrix. I have also done similar operations in Matlab and the difference `diff` and maximum value `diff.max()` are consistent. What is exactly `A-B` operation doing? My understanding is that the default behaviour for add, subtract, multiply and divide arrays with each other was element-wise operations however there is something funny happening here.