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backedarray-0.0.1

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مشاهده بیشتر
0.0.1
0.0.1

توضیحات

Sparse and dense arrays backed by on-disk storage in Zarr or HDF5
ویژگی مقدار
سیستم عامل -
نام فایل backedarray-0.0.1
نام backedarray
نسخه کتابخانه 0.0.1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Joshua Gould
ایمیل نویسنده -
آدرس صفحه اصلی -
آدرس اینترنتی https://pypi.org/project/backedarray/
مجوز BSD 3-Clause License Copyright (c) 2022, lilab-bcb All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
============== backedarray ============== Sparse (csc and csr) and dense arrays backed by on-disk storage in Zarr_ or HDF5_. Allows accessing slices of larger than memory arrays. Inspired by h5sparse_. Examples -------- .. code:: ipython3 import backedarray as ba import scipy.sparse import numpy as np import h5py import zarr Create Dataset ============== .. code:: ipython3 csr_matrix = scipy.sparse.random(100, 50, format="csr", density=0.2) dense_array = csr_matrix.toarray() HDF5 Backend ------------ .. code:: ipython3 # Write sparse matrix in csc or csr format to hdf5 file h5_csr_path = 'csr.h5' with h5py.File(h5_csr_path, "w") as f: ba.write_sparse(f.create_group("X"), csr_matrix) .. code:: ipython3 # Write 2-d numpy array to hdf5 h5_dense_path = 'dense.h5' with h5py.File(h5_dense_path, "w") as f: f["X"] = dense_array Zarr Backend ------------ .. code:: ipython3 # Write sparse matrix in csc or csr format to zarr file zarr_csr_path = 'csr.zarr' with zarr.open(zarr_csr_path, mode="w") as f: ba.write_sparse(f.create_group("X"), csr_matrix) .. code:: ipython3 # Write 2-d numpy array to zarr format zarr_dense_path = 'dense.zarr' with zarr.open(zarr_dense_path, mode="w") as f: f["X"] = dense_array Read Dataset ============ HDF5 Backend ------------ .. code:: ipython3 h5_csr_file = h5py.File(h5_csr_path, "r") h5_csr_disk = ba.open(h5_csr_file["X"]) h5_dense_file = h5py.File(h5_dense_path, "r") h5_dense_disk = ba.open(h5_dense_file["X"]) Zarr Backend ------------ .. code:: ipython3 zarr_csr_disk = ba.open(zarr.open(zarr_csr_path)["X"]) zarr_dense_disk = ba.open(zarr.open(zarr_dense_path)["X"]) Numpy Style Indexing ==================== .. code:: ipython3 zarr_csr_disk[1:3].toarray() .. parsed-literal:: array([[0. , 0.25620103, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.57643237, 0.7628611 , 0. , 0. , 0. , 0.99872378, 0. , 0. , 0. , 0. , 0. , 0. , 0.82040632, 0. , 0.09788999, 0. , 0. , 0.67186548, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.24171919, 0. , 0. , 0. , 0. , 0.5893689 , 0. , 0. ], [0. , 0. , 0. , 0. , 0.1650544 , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.98852861, 0. , 0.01475572, 0. , 0.82875194, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.28405987, 0. , 0. , 0.72342298, 0. , 0. , 0. , 0.12985154, 0. ]]) .. code:: ipython3 zarr_dense_disk[-2:] .. parsed-literal:: array([[0.51141143, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.87214978, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.95867897, 0. , 0.00825137, 0. , 0. , 0. , 0. , 0. , 0. , 0.29541905, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.68913921, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.87239577, 0. , 0.93164802, 0. , 0. ], [0. , 0. , 0. , 0.04102313, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.81888661, 0. , 0. , 0. , 0. , 0. , 0. , 0.18858683, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.83726992, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.60594181, 0.61483901, 0. , 0. , 0.37080615, 0.62691013]]) .. code:: ipython3 h5_csr_disk[2:].toarray() .. parsed-literal:: array([[0. , 0. , 0. , ..., 0. , 0.12985154, 0. ], [0. , 0. , 0.56872386, ..., 0. , 0. , 0.36926708], [0. , 0. , 0.75702799, ..., 0.97589322, 0. , 0.34865313], ..., [0. , 0.14634835, 0. , ..., 0. , 0. , 0. ], [0.51141143, 0. , 0. , ..., 0.93164802, 0. , 0. ], [0. , 0. , 0. , ..., 0. , 0.37080615, 0.62691013]]) .. code:: ipython3 h5_csr_disk[...].toarray() .. parsed-literal:: array([[0. , 0. , 0. , ..., 0. , 0. , 0. ], [0. , 0.25620103, 0. , ..., 0.5893689 , 0. , 0. ], [0. , 0. , 0. , ..., 0. , 0.12985154, 0. ], ..., [0. , 0.14634835, 0. , ..., 0. , 0. , 0. ], [0.51141143, 0. , 0. , ..., 0.93164802, 0. , 0. ], [0. , 0. , 0. , ..., 0. , 0.37080615, 0.62691013]]) .. code:: ipython3 h5_dense_disk[:2] .. parsed-literal:: array([[0. , 0. , 0. , 0. , 0. , 0.71493443, 0.20460768, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.68284516, 0. , 0. , 0. , 0. , 0. , 0.93012152, 0. , 0. , 0.2165738 , 0. , 0. , 0. , 0.93954512, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.1808206 , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. ], [0. , 0.25620103, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.57643237, 0.7628611 , 0. , 0. , 0. , 0.99872378, 0. , 0. , 0. , 0. , 0. , 0. , 0.82040632, 0. , 0.09788999, 0. , 0. , 0.67186548, 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0. , 0.24171919, 0. , 0. , 0. , 0. , 0.5893689 , 0. , 0. ]]) .. code:: ipython3 h5_csr_file.close() h5_dense_file.close() Append ====== .. code:: ipython3 zarr_csr_disk.append(csr_matrix) np.testing.assert_array_equal(zarr_csr_disk[...].toarray(), scipy.sparse.vstack((csr_matrix, csr_matrix)).toarray()) Read h5ad files created using `anndata <https://anndata.readthedocs.io/>`__ =========================================================================== .. code:: bash %%bash if [ ! -f "pbmc3k.h5ad" ]; then wget https://raw.githubusercontent.com/chanzuckerberg/cellxgene/main/example-dataset/pbmc3k.h5ad fi .. code:: ipython3 import anndata.experimental with h5py.File('pbmc3k.h5ad', 'r') as f: obs = anndata.experimental.read_elem(f['obs']) var = anndata.experimental.read_elem(f['var']) X = ba.open(f['X']) .. _Zarr: https://zarr.readthedocs.io/ .. _HDF5: https://www.hdfgroup.org/solutions/hdf5 .. _h5sparse: https://github.com/appier/h5sparse


نیازمندی

مقدار نام
- h5py
- numpy
- scipy
- zarr
xtr pytest;


زبان مورد نیاز

مقدار نام
>=3.7 Python


نحوه نصب


نصب پکیج whl backedarray-0.0.1:

    pip install backedarray-0.0.1.whl


نصب پکیج tar.gz backedarray-0.0.1:

    pip install backedarray-0.0.1.tar.gz