Welcome to kwarray’s documentation!¶
The kwarray module implements a small set of pure-python extensions to
numpy and torch along with a few select algorithms. Each module contains
module level docstring that gives a rough idea of the utilities in each module,
and each function or class itself contains a docstring with more details and
examples.
KWarray is part of Kitware’s computer vision Python suite:
Function Usefulness¶
Function name |
Usefulness |
|---|---|
475 |
|
202 |
|
98 |
|
77 |
|
72 |
|
60 |
|
59 |
|
53 |
|
48 |
|
33 |
|
31 |
|
30 |
|
29 |
|
27 |
|
25 |
|
20 |
|
19 |
|
15 |
|
14 |
|
14 |
|
10 |
|
10 |
|
10 |
|
10 |
|
9 |
|
9 |
|
7 |
|
6 |
|
6 |
|
5 |
|
5 |
|
3 |
|
3 |
|
1 |
|
1 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
|
0 |
- kwarray package
- Submodules
- kwarray.algo_assignment module
- kwarray.algo_setcover module
- kwarray.arrayapi module
- kwarray.dataframe_light module
- kwarray.distributions module
- kwarray.fast_rand module
- kwarray.util_averages module
- kwarray.util_groups module
- kwarray.util_misc module
- kwarray.util_numpy module
- kwarray.util_random module
- kwarray.util_robust module
- kwarray.util_slices module
- kwarray.util_slider module
- kwarray.util_torch module
- Module contents
ArrayAPIDataFrameArrayDataFrameLightFlatIndexerLocLightNoSupportErrorRunningStatsSlidingWindowStitcherapply_embedded_slice()apply_grouping()arglexmax()argmaxima()argminima()atleast_nd()boolmask()dtype_info()embed_slice()ensure_rng()equal_with_nan()find_robust_normalizers()generalized_logistic()group_consecutive()group_consecutive_indices()group_indices()group_items()isect_flags()iter_reduce_ufunc()maxvalue_assignment()mincost_assignment()mindist_assignment()normalize()one_hot_embedding()one_hot_lookup()padded_slice()random_combinations()random_product()robust_normalize()seed_global()setcover()shuffle()standard_normal()standard_normal32()standard_normal64()stats_dict()uniform()uniform32()unique_rows()
- Submodules