Numpy: views vs copy by slicing

The accepted answer by John Zwinck is actually false (I just figured this out the hard way!).The problem in the question is a combination of doing "lvalue indexing" with numpy's fancy indexing.The following doc explains exactly this case

https://scipy-cookbook.readthedocs.io/items/ViewsVsCopies.html

in the section "But fancy indexing does seem to return views sometimes, doesn't it?"

All that matters is whether you slice by rows or by columns. Slicing by rows can return a view because it is a contiguous segment of the original array. Slicing by column must return a copy because it is not a contiguous segment. For example:

A1 A2 A3B1 B2 B3C1 C2 C3

By default, it is stored in memory this way:

A1 A2 A3 B1 B2 B3 C1 C2 C3

So if you want to choose every second row, it is:

[A1 A2 A3] B1 B2 B3 [C1 C2 C3]

That can be described as {start: 0, size: 3, stride: 6}.

But if you want to choose every second column:

[A1] A2 [A3 B1] B2 [B3 C1] C2 [C3]

And there is no way to describe that using a single start, size, and stride. So there is no way to construct such a view.

If you want to be able to view every second column instead of every second row, you can construct your array in column-major aka Fortran order instead:

np.array(a, order='F')

Then it will be stored as such:

A1 B1 C1 A2 B2 C2 A3 B3 C3

This is my understanding, for your reference

a[0:3:2, :]                     # basic indexing, a view... = a[0:3:2, :][:, [0, 2]]    # getitme version, a copy,                                # because you use advanced                                # indexing [:,[0,2]]a[0:3:2, :][:, [0, 2]] = ...    # howver setitem version is                                # like a view, setitem version                                # is different from getitem version,                                # this is not c++a[:, [0, 2]]                    # getitem version, a copy,                                # because you use advanced indexinga[:, [0, 2]][0:3:2, :] = 0      # the copy is modied,                                # but a keeps unchanged.

If I have any misunderstanding, please point it out.