Filtering a ndarray in numpy-CodePudding

I have a ndarray and I want to filter out a particular value of it. My array is:

arr = np.array([
   [1., 6., 1.],
   [1., 7., 0.],
   [1., 8., 0.],
   [3., 5., 1.],
   [5., 1., 1.],
   [5., 2., 2.],
   [6., 1., 1.],
   [6., 2., 2.],
   [6., 7., 3.],
   [6., 8., 0.]
])

I want to filter out [6., 1., 1.]. So I have tried:

arr[arr != [6., 1., 1.]]

and I got:

array([1., 6., 1., 7., 0., 1., 8., 0., 3., 5., 5., 5., 2., 2., 2., 2., 7.,
   3., 8., 0.])

which is not what I want (and also destroyed the previous structure of the array). I have also tried:

arr[arr[:] != [6., 1., 1.]]

but I got the same output as before.

P.S.: I know I can delete an element by its index, but I don't want to do that. I want to check for the particular element.

P.P.S.: For 1-d arrays my method works.

CodePudding user response：

You're very close. The boolean array you get tells you how many elements match in each row. You need to make sure that all the elements in a row match to delete it, or that any of the elements don't match to keep it:

arr[(arr != [6, 1, 1]).any(axis=1)]

You can also write it as

arr[~(arr == [6, 1, 1]).all(axis=1)]