Compare Columns Of Numpy Matrix With Array

I have a numpy matrix and want to compare every columns to a given array, like: M = np.array([1,2,3,3,2,1,1,3,2]).reshape((3,3)).T v = np.array([1,2,3]) Now I want to compare ever

Solution 1:

Use broadcasted comparison:

>>> M == v[:, None]
array([[ True, False,  True],
       [ True,  True, False],
       [ True, False, False]])

Solution 2:

You might consider using np.equal column-wise:

np.array([np.equal(col, v) for col in M.T]).T

it compares the elements of two numpy arrays element-wise. The M.T makes for loop to pop your original M columns as one-dimensional arrays and the final transpose is needed to reverse it. Here the equal/not_equal functions are described.

Solution 3:

Alternatively, you could match each row in the matrix with the given vector using np.apply_along_axis

>>> M
array([[1, 3, 1],
       [2, 2, 3],
       [3, 1, 2]])
>>> v
array([1, 2, 3])
>>> np.apply_along_axis(lambda x: x==v, 1, M)
array([[ True, False, False],
       [False,  True,  True],
       [False, False, False]], dtype=bool)