{"id":13574878,"url":"https://github.com/haasad/PyPardiso","last_synced_at":"2025-04-04T18:32:42.223Z","repository":{"id":11040656,"uuid":"68109129","full_name":"haasad/PyPardiso","owner":"haasad","description":"Python interface to the Intel MKL Pardiso library to solve large sparse linear systems of equations","archived":false,"fork":false,"pushed_at":"2024-04-06T09:40:32.000Z","size":806,"stargazers_count":125,"open_issues_count":3,"forks_count":19,"subscribers_count":8,"default_branch":"master","last_synced_at":"2024-05-21T21:14:25.670Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/haasad.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2016-09-13T13:06:59.000Z","updated_at":"2024-06-08T10:54:30.659Z","dependencies_parsed_at":"2024-04-06T10:37:59.324Z","dependency_job_id":null,"html_url":"https://github.com/haasad/PyPardiso","commit_stats":{"total_commits":194,"total_committers":4,"mean_commits":48.5,"dds":0.4587628865979382,"last_synced_commit":"7f53e2156c0adbeab0045351a7241e8588fcf375"},"previous_names":["haasad/pypardiso","haasad/pypardisoproject"],"tags_count":15,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haasad%2FPyPardiso","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haasad%2FPyPardiso/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haasad%2FPyPardiso/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haasad%2FPyPardiso/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/haasad","download_url":"https://codeload.github.com/haasad/PyPardiso/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":223153674,"owners_count":17096583,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-08-01T15:00:55.494Z","updated_at":"2025-04-04T18:32:42.217Z","avatar_url":"https://github.com/haasad.png","language":"Python","funding_links":[],"categories":["Table of Contents"],"sub_categories":["Mathematics and Science"],"readme":"[![pypardiso-tests](https://github.com/haasad/PyPardisoProject/actions/workflows/tests.yaml/badge.svg?branch=master)](https://github.com/haasad/PyPardisoProject/actions/workflows/tests.yaml)\n# PyPardiso\n\nPyPardiso is a python package to solve large sparse linear systems of equations with the [Intel oneAPI Math Kernel Library PARDISO solver](https://www.intel.com/content/www/us/en/develop/documentation/onemkl-developer-reference-fortran/top/sparse-solver-routines/onemkl-pardiso-parallel-direct-sparse-solver-iface.html), a shared-memory multiprocessing parallel direct sparse solver.\n\nPyPardiso provides the same functionality as SciPy's [scipy.sparse.linalg.spsolve](https://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.linalg.spsolve.html#scipy.sparse.linalg.spsolve) for solving the sparse linear system `Ax=b`. However in many cases it is significantly faster than SciPy's built-in single-threaded SuperLU solver.\n\nPyPardiso is not a python interface to the PARDISO Solver from the [PARDISO 7.2 Solver Project](https://www.pardiso-project.org/) and it also doesn't currently support complex numbers. Check out [JuliaSparse/Pardiso.jl](https://github.com/JuliaSparse/Pardiso.jl/) for these more advanced use cases.\n\n## Installation\n\nPyPardiso runs on Linux, Windows and MacOS. It can be installed with __conda__ or __pip__. It is recommended to install PyPardiso using a virtual environment.\n\nconda-forge | PyPI\n:---:|:---:\n[![conda-forge version](https://anaconda.org/conda-forge/pypardiso/badges/version.svg)](https://anaconda.org/conda-forge/pypardiso) | [![PyPI version](https://badge.fury.io/py/pypardiso.svg)](https://pypi.org/project/pypardiso/)\n`conda install -c conda-forge pypardiso` | `pip install pypardiso`\n\n\n## Basic usage\n\nHow to solve the sparse linear system `Ax=b` for `x`, where `A` is a square, sparse matrix in CSR (or CSC) format and `b` is a vector (or matrix):\n```python\nIn [1]: import pypardiso\n\nIn [2]: import numpy as np\n\nIn [3]: import scipy.sparse as sp\n\nIn [4]: A = sp.rand(10, 10, density=0.5, format='csr')\n\nIn [5]: A\nOut[5]:\n\u003c10x10 sparse matrix of type '\u003cclass 'numpy.float64'\u003e'\n\twith 50 stored elements in Compressed Sparse Row format\u003e\n\nIn [6]: b = np.random.rand(10)\n\nIn [7]: x = pypardiso.spsolve(A, b)\n\nIn [8]: x\nOut[8]:\narray([ 0.02918389,  0.59629935,  0.33407289, -0.48788966,  3.44508841,\n        0.52565687, -0.48420646,  0.22136413, -0.95464127,  0.58297397])\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhaasad%2FPyPardiso","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhaasad%2FPyPardiso","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhaasad%2FPyPardiso/lists"}