{ "info": { "author": "Rohan Kumar", "author_email": "seirdy@pm.ch", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Developers", "Intended Audience :: Education", "License :: OSI Approved :: GNU Affero General Public License v3 or later (AGPLv3+)", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: Implementation :: CPython", "Topic :: Scientific/Engineering :: Mathematics" ], "description": "# Function Analysis\n\n[![pipeline status]](https://gitlab.com/Seirdy/func-analysis/commits/master)\n[![coverage report]](https://gitlab.com/Seirdy/func-analysis/commits/master)\n[![Code Climate]](https://codeclimate.com/github/Seirdy/func-analysis)\n[![License]](https://gitlab.com/Seirdy/func-analysis/blob/master/LICENSE)\n[![PYPI latest release]](https://pypi.org/project/func-analysis/)\n[![Python version]](https://pypi.org/project/func-analysis/)\n[![Code style: black]](https://github.com/ambv/black)\n\n[pipeline status]:\nhttps://gitlab.com/Seirdy/func-analysis/badges/master/pipeline.svg\n[coverage report]:\nhttps://gitlab.com/Seirdy/func-analysis/badges/master/coverage.svg\n[Code Climate]:\nhttps://codeclimate.com/github/Seirdy/func-analysis/badges/gpa.svg\n[License]:\nhttps://img.shields.io/pypi/l/func-analysis.svg\n[PYPI Latest Release]:\nhttps://img.shields.io/pypi/v/func-analysis.svg\n[Python version]:\nhttps://img.shields.io/pypi/pyversions/func-analysis.svg\n[Code style: black]:\nhttps://img.shields.io/badge/code%20style-black-000000.svg\n\nThis library uses concepts typically taught in an introductory Calculus\nclass to describe properties of continuous, differentiable, single-variable\nfunctions.\n\n## Using this library\n\nThe `func_analysis` module defines the class `AnalyzedFunc`. An instance\nof this class has several attributes describing the behavior of this\nfunction.\n\nRequired data include:\n\n- A range\n- The function to be analyzed\n\nSpecial points include zeros, critical numbers, extrema, and points of\ninflection. Calculating these is possible when given the number of points\nwanted.\n\nOptional data can be provided to improve precision and performance. Such\ndata include:\n\n- Any derivatives of the function\n- Any known zeros, critical numbers, extrema, points of inflection\n- Intervals of concavity, convexity, increase, decrease\n- Any vertical axis of symmetry\n\nAny of the above data can be calculated by an instance of `AnalyzedFunc`.\n\n## License\n\nThis program is licensed under the GNU Affero General Public License v3 or\nlater.\n\n\n", "description_content_type": "text/markdown", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://gitlab.com/Seirdy/func_memoized-analysis", "keywords": "func_memoized-analysis,calculus,math", "license": "AGPLv3+", "maintainer": "", "maintainer_email": "", "name": "func-memoized-analysis", "package_url": "https://pypi.org/project/func-memoized-analysis/", "platform": "", "project_url": "https://pypi.org/project/func-memoized-analysis/", "project_urls": { "Homepage": "https://gitlab.com/Seirdy/func_memoized-analysis" }, "release_url": "https://pypi.org/project/func-memoized-analysis/0.1.2/", "requires_dist": [ "mpmath", "numpy", "scipy" ], "requires_python": "", "summary": "Analyze function behavior using introductory calculus.", "version": "0.1.2" }, "last_serial": 4639729, "releases": { "0.1.2": [ { "comment_text": "", "digests": { "md5": "d6d4ca3a6c30ea5b31c5762b8fa099f4", "sha256": "ec5dbf5485e2e9061354b6c77a8ded4a64a2b35b89572644490baf93711ba0db" }, "downloads": -1, "filename": "func_memoized_analysis-0.1.2-py3-none-any.whl", "has_sig": false, "md5_digest": "d6d4ca3a6c30ea5b31c5762b8fa099f4", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 28905, "upload_time": "2018-12-28T03:52:41", "url": "https://files.pythonhosted.org/packages/c0/46/c138919b7d87c1b5e5624a241e1559cc648c3641876db1a25fc980069ebf/func_memoized_analysis-0.1.2-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "b8755d5411e3a5030a0133c3b1a4c157", "sha256": "4ee19888618157711a9aed8af2295f79f37e7b49b9870df2bd20d26155cba586" }, "downloads": -1, "filename": "func_memoized-analysis-0.1.2.tar.gz", "has_sig": false, "md5_digest": "b8755d5411e3a5030a0133c3b1a4c157", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10706, "upload_time": "2018-12-28T03:52:44", "url": "https://files.pythonhosted.org/packages/cb/a7/6f1e868970a196a2e8bef5ebfda87bdc67bd268b4f6079859dd3423a0960/func_memoized-analysis-0.1.2.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "d6d4ca3a6c30ea5b31c5762b8fa099f4", "sha256": "ec5dbf5485e2e9061354b6c77a8ded4a64a2b35b89572644490baf93711ba0db" }, "downloads": -1, "filename": "func_memoized_analysis-0.1.2-py3-none-any.whl", "has_sig": false, "md5_digest": "d6d4ca3a6c30ea5b31c5762b8fa099f4", "packagetype": "bdist_wheel", "python_version": "py3", "requires_python": null, "size": 28905, "upload_time": "2018-12-28T03:52:41", "url": "https://files.pythonhosted.org/packages/c0/46/c138919b7d87c1b5e5624a241e1559cc648c3641876db1a25fc980069ebf/func_memoized_analysis-0.1.2-py3-none-any.whl" }, { "comment_text": "", "digests": { "md5": "b8755d5411e3a5030a0133c3b1a4c157", "sha256": "4ee19888618157711a9aed8af2295f79f37e7b49b9870df2bd20d26155cba586" }, "downloads": -1, "filename": "func_memoized-analysis-0.1.2.tar.gz", "has_sig": false, "md5_digest": "b8755d5411e3a5030a0133c3b1a4c157", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 10706, "upload_time": "2018-12-28T03:52:44", "url": "https://files.pythonhosted.org/packages/cb/a7/6f1e868970a196a2e8bef5ebfda87bdc67bd268b4f6079859dd3423a0960/func_memoized-analysis-0.1.2.tar.gz" } ] }