如何在python中检查（numpy数组）的真实相等性？

Question

I have some function in python returning a numpy.array:

matrix = np.array([0.,0.,0.,0.,0.,0.,1.,1.,1.,0.],
             [0.,0.,0.,1.,1.,0.,0.,1.,0.,0.])

def some_function:
    rows1, cols1 = numpy.nonzero(matrix)
    cols2 = numpy.array([6,7,8,3,4,7])
    rows2 = numpy.array([0,0,0,1,1,1])
    print numpy.array_equal(rows1, rows2) # returns True
    print numpy.array_equal(cols1, cols2) # returns True
    return (rows1, cols1)                   # or (rows2, cols2)

It should normally extract the indices of nonzero entries of a matrix (rows1, cols1). However, I can also extract the indices manually (rows2, cols2). The problem is that the program returns different results depending on whether the function returns (rows1, cols1) or (rows2, cols2) , although the arrays should be equal.

I should probably add that this code is used in the context of pyipopt , which calls a c++ software package IPOPT . The problem then occurs within this package.

Can it be that the arrays are not "completely" equal? I would say that they somehow must be because I am not modifying anything but returning one instead of the other.

Any idea on how to debug this problem?

Answer 1

You could check where the arrays are not equal:

print(where(rows1 != rows2))

But what you are doing is unclear, first there is no nonzeros function in numpy, only a nonzero which returns a tuple of coordinates. Are you only using the one corresponding to the rows?