Product
Introducing License Enforcement in Socket
Ensure open-source compliance with Socket’s License Enforcement Beta. Set up your License Policy and secure your software!
This package contains functionality for indexed operations on numpy ndarrays, providing efficient vectorized functionality such as grouping and set operations.
|Travis| |PyPI| |Anaconda|
This package contains functionality for indexed operations on numpy ndarrays, providing efficient vectorized functionality such as grouping and set operations.
Rich and efficient grouping functionality:
Generalization of existing array set operation to nd-arrays, such as:
Some new functions:
Some brief examples to give an impression hereof:
.. code:: python
# three sets of graph edges (doublet of ints)
edges = np.random.randint(0, 9, (3, 100, 2))
# find graph edges exclusive to one of three sets
ex = exclusive(*edges)
print(ex)
# which edges are exclusive to the first set?
print(contains(edges[0], ex))
# where are the exclusive edges relative to the totality of them?
print(indices(union(*edges), ex))
# group and reduce values by identical keys
values = np.random.rand(100, 20)
# and so on...
print(group_by(edges[0]).median(values))
.. code:: python
> conda install numpy-indexed -c conda-forge
or
.. code:: python
> pip install numpy-indexed
See: https://pypi.python.org/pypi/numpy-indexed
This package builds upon a generalization of the design pattern as can be found in numpy.unique. That is, by argsorting an ndarray, many subsequent operations can be implemented efficiently and in a vectorized manner.
The sorting and related low level operations are encapsulated into a hierarchy of Index classes, which allows for efficient lookup of many properties for a variety of different key-types. The public API of this package is a quite thin wrapper around these Index objects.
The two complex key types currently supported, beyond standard sequences of sortable primitive types, are ndarray keys (i.e, finding unique rows/columns of an array) and composite keys (zipped sequences). For the exact casting rules describing valid sequences of key objects to index objects, see as_index().
.. |Travis| image:: https://travis-ci.org/EelcoHoogendoorn/Numpy_arraysetops_EP.svg?branch=master :target: https://travis-ci.org/EelcoHoogendoorn/Numpy_arraysetops_EP .. |PyPI| image:: https://badge.fury.io/py/numpy-indexed.svg :target: https://pypi.org/project/numpy-indexed/ .. |Anaconda| image:: https://anaconda.org/conda-forge/numpy-indexed/badges/version.svg :target: https://anaconda.org/conda-forge/numpy-indexed
FAQs
This package contains functionality for indexed operations on numpy ndarrays, providing efficient vectorized functionality such as grouping and set operations.
We found that numpy-indexed demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Product
Ensure open-source compliance with Socket’s License Enforcement Beta. Set up your License Policy and secure your software!
Product
We're launching a new set of license analysis and compliance features for analyzing, managing, and complying with licenses across a range of supported languages and ecosystems.
Product
We're excited to introduce Socket Optimize, a powerful CLI command to secure open source dependencies with tested, optimized package overrides.