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)):
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:
if not Arr1.shape == Arr2.shape:
return ['Arrays size not the same']
Dimensions = Arr1.shape
Diff = 
for i in range(Dimensions ):
for j in range(Dimensions ):
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')
(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?