semvec/pypi-packages huggingface dataset:
fast-array-utils 1.3.1
Fast array utilities with minimal dependencies.
Requires Python: >=3.11



usage
-----

``fast-array-utils`` supports the following array types:

- ``numpy.ndarray``
- ``scipy.sparse.cs{rc}_{array,matrix}``
- ``cupy.ndarray`` and ``cupyx.scipy.sparse.cs{rc}_matrix``
- ``dask.array.Array``
- ``h5py.Dataset`` and ``zarr.Array``
- ``anndata.abc.CS{CR}Dataset`` (only supported by ``.conv.to_dense`` at the moment)

Use ``fast_array_utils.conv.to_dense`` to densify arrays and optionally move them to CPU memory:

.. code:: python

   from fast_array_utils.conv import to_dense

   numpy_arr = to_dense(sparse_arr_or_mat)
   numpy_arr = to_dense(dask_or_cuda_arr, to_cpu_memory=True)
   dense_dask_arr = to_dense(dask_arr)
   dense_cupy_arr = to_dense(sparse_cupy_mat)

Use ``fast_array_utils.conv.*`` to calculate statistics across one or both axes of a 2D array.
All of them support an `axis` and `dtype` parameter:

.. code:: python

   from fast_array_utils import stats

   all_equal = stats.is_constant(arr_2d)
   col_sums = stats.sum(arr_2d, axis=0)
   mean = stats.mean(arr_2d)
   row_means, row_vars = stats.mean_var(arr_2d, axis=1)

installation
------------

To use ``fast_array_utils.stats`` or ``fast_array_utils.conv``:

.. code:: bash

   (uv) pip install 'fast-array-utils[accel]'

To use ``testing.fast_array_utils``:

.. code:: bash

   (uv) pip install 'fast-array-utils[testing]'