For example: I have
a = np.array([123, 412, 444])
b = np.array([123, 321])
You can use set difference to determine what you are looking for. Numpy has a built-in function called numpy.setdiff1d(ar1, ar2):
Return the sorted, unique values in ar1 that are not in ar2.
Example for your case:
>>> a = np.array([123, 412, 444]) >>> b = np.array([123, 321]) >>> diff = np.setdiff1d(b, a) >>> print diff array() >>> if diff.size: >>> print "Not passed"
So for your case, you would do a set difference you would subtract a from b and obtain an array with elements in b which are not in a. Then you can check if that was empty or not. As you can see, the output is
312, which is an entry present in
a but not in
b; the length of it is now larger then zero, therefore there were elements in
b which were not present in