MAINT: clean up views/strides/dtypes utilities in cluster.hierarcy
#18858
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Spell some conversions uniformly as: ``` np.asarray(Z, order='C', dtype=np.float64) ``` rather than use harder to read helper functions like `_convert_to_double`. The semantics are unchanged: use a C-contiguous float64 array, copy only if needed. Also removes some unused code (`_randdm`, `_convert_to_bool`).
This internal utility function was quite odd and effectively broken. Its stated purpose in code comments was about strides, but instead it would: 1. copy if the input array was a view, 2. convert float32 arrays to float64, but only if they were not a copy. this conversion would also fail to correctly convert float16 or other input types. In addition to the above removals, document in the Cython code that was being called which input arguments modify their input array in-place. There were no bugs here; all input arrays which were being modified were allocated inside the public functions with `np.zeros` or a similar array creation function.
rgommers
added
scipy.cluster
maintenance
|
The one failure is a network connection issue; this PR is pure Python so I won't bother restarting it. This should be good to merge. |
tupui
approved these changes
Jul 11, 2023
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The utility functions cleaned up here (
_copy_arrays_if_base_present,_convert_to_bool,_convert_to_double) were the cause of a couple of open review comments in gh-18668, where it wasn't clear whether or not changing them was preserving the existing semantics. In the process of looking into that, I also discovered some spurious double checks, weird conversion logic (float32arrays were converted tofloat64, but only if they weren't views;float16input remained unconverted) and some other code oddities.The key thing for removal of
_copy_arrays_if_base_presentwas checking which input arrays for_hierarchy.pyxfunctions were being modified in-place, so I added some docs for that.