I would do something like:
diff_is_large = (array1 - array2) > threshold
index_at_large_diff = numpy.nonzero(diff_is_large)
array1[index_at_large_diff].tolist()
On Wed, May 17, 2017 at 9:50 AM, Nissim Derdiger <niss...@elspec-ltd.com>
wrote:
> Hi,
> In my script, I need to compare big NumPy arrays (2D or 3D), and return a
> list of all cells with difference bigger than a defined threshold.
> The compare itself can be done easily done with "allclose" function, like
> that:
> Threshold = 0.1
> if (np.allclose(Arr1, Arr2, Threshold, equal_nan=True)):
> Print('Same')
> But this compare does not return *which* cells are not the same.
>
> The easiest (yet naive) way to know which cells are not the same is to use
> a simple for loops code like this one:
> def CheckWhichCellsAreNotEqualInArrays(Arr1,Arr2,Threshold):
> if not Arr1.shape == Arr2.shape:
> return ['Arrays size not the same']
> Dimensions = Arr1.shape
> Diff = []
> for i in range(Dimensions [0]):
> for j in range(Dimensions [1]):
> if not np.allclose(Arr1[i][j], Arr2[i][j], Threshold,
> equal_nan=True):
> Diff.append(',' + str(i) + ',' + str(j) + ',' +
> str(Arr1[i,j]) + ','
> + str(Arr2[i,j]) + ',' + str(Threshold) + ',Fail\n')
> return Diff
> (and same for 3D arrays - with 1 more for loop)
> This way is very slow when the Arrays are big and full of none-equal cells.
>
> Is there a fast straight forward way in case they are not the same - to
> get a list of the uneven cells? maybe some built-in function in the NumPy
> itself?
> Thanks!
> Nissim
>
>
>
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