{ "info": { "author": "Thread Tech", "author_email": "tech@thread.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Operating System :: POSIX", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Information Analysis", "Topic :: Scientific/Engineering :: Mathematics", "Topic :: Software Development :: Libraries" ], "description": "wide-product\n============\n\n`wide-product` implements a partial, column-wise Khatri-Rao product. It is fast,\nand works on sparse matrices.\n\nIt can be useful for engineering of cross-features for machine learning.\n\nDefinition\n----------\n\nFor a pair of scalars (~ one by one matrices), the wide product is\nmultiplication:\n\n.. code:: python\n\n wide_product ( [[a]], [[b]] ) == [[a * b]]\n\nWhere matrices are constructed by *vertical stacking*, the product is row-wise:\n\n.. code:: python\n\n wide_product ( vstack((A, B)), vstack((C, D)) ) ==\n vstack((wide_product(A, C),\n wide_product(B, D)))\n\nWhere matrices are constructed by *horizontal stacking*, the product contains\nall the products of the subcomponents up to permutation of columns:\n\n.. code:: python\n\n wide_product ( hstack((A, B)), hstack((C, D)) ) ==\n hstack((wide_product(A, C),\n wide_product(A, D),\n wide_product(B, C),\n wide_product(B, D)))\n\nInstallation\n------------\n\n.. code:: bash\n\n pip install wide-product\n\nDevelopment\n-----------\n\nTo build the module:\n\n.. code:: bash\n\n python setup.py build\n\nTo test:\n\n.. code:: bash\n\n PYTHONPATH=$(echo build/lib*):. py.test\n\nTo install:\n\n.. code:: bash\n\n pip install .", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/thread/wide-product", "keywords": "numpy,scipy,matrix,sparse,khatri-rao,product,science,feature,courgette", "license": "MIT", "maintainer": null, "maintainer_email": null, "name": "wide-product", "package_url": "https://pypi.org/project/wide-product/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/wide-product/", "project_urls": { "Download": "UNKNOWN", "Homepage": "https://github.com/thread/wide-product" }, "release_url": "https://pypi.org/project/wide-product/0.0.1/", "requires_dist": null, "requires_python": null, "summary": "Wide (partial Khatri-Rao) sparse matrix product", "version": "0.0.1" }, "last_serial": 2819987, "releases": { "0.0.1": [ { 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