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 every columns of M with v, i.e. I want a matrix with the first column consisting of True, True, True. A second saying False, True, False. A third True, False, False.
How do I achieve this? Thanks!
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.
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)
