Keep the last value when setitem gets repeated indices - #4601

When an index array repeats a position, oindex, vindex and __setitem__ could store any of the values given for it. The issue's example, arr.oindex[np.array([-1, -1, 0, 0])] = [0, 1, 2, 3] on a chunked array, gives [2, 0, 0, 0] on Linux with numpy 2 and [3, 0, 0, 1] on macOS, while NumPy itself gives [3, 0, 0, 1] everywhere. The reason is that the in-chunk scatter receives the repeated positions in whatever order the (unstable) argsort by chunk put them, so the "last" write is platform dependent, and for a single-chunk array the order is different again.

This follows the suggestion in the thread: before any chunk is touched, the selection is reduced so that it names each element once, keeping the last occurrence, and the value array is reduced to match. The stored value is then the last one given for the element, which is what sequential NumPy assignment produces, on every platform and for every chunking. For orthogonal selections the reduction is per dimension (that matches a[np.ix_(i, j)] = v, where the last row wins for a repeated i and the last column for a repeated j); for coordinate selections the points are reduced on their linear index. Negative and positive spellings of the same index count as the same position. Selections with no repeats take the existing path unchanged: the check is a linear pass for sorted index arrays and one np.unique or np.lexsort otherwise. Masks never repeat a point and are skipped.

A value that cannot be broadcast to the selection now raises ValueError: shape mismatch ... (NumPy's wording) on this path instead of silently writing a prefix of it.

Tests: the previously skipped test_setitem_repeated_index runs again, parametrised over chunkings and over oindex, vindex and __setitem__; new tests cover repeats along both dimensions of an orthogonal selection (with integer, slice and Boolean selectors on the other dimension, and scalar values), repeated points across chunk boundaries with 1-D and 2-D coordinate arrays and the sorted single-array path, the shape-mismatch error, and the last_occurrences helper. The hypothesis tests test_oindex and test_vindex no longer assume away repeated indices, so they now compare repeated-index writes against NumPy as well; before the change test_oindex fails within a few examples.

Fixes #2855