{ "info": { "author": "['Aaron Bradley', 'Timothy Sweetser']", "author_email": "abradley@stitchfix.com", "bugtrack_url": null, "classifiers": [], "description": "Diamond\n=======\n\nO Diamond, Diamond, thou little knowest the mischief thou hast done.\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\n.. figure:: diamond_fire.jpg?raw=true\n :alt: Damn You Diamond!\n\n Damn You Diamond\n\n`(Diamond was Newton's mischievous\ndog) `__\n\nWhat is Diamond?\n----------------\n\nDiamond utilizes iterative, quasi-Newton 2nd-order solvers for certain\nkinds of generalized linear models (GLMs) with arbitrary but known\nL2-regularization. A common use is fitting mixed-effects models, with\ntheir covariance already being known by another means (e.g. lme4). These\n2nd-order iterative solvers are considerably faster than a full-blown\nsolution.\n\nLimitations\n-----------\n\n- The random-effects covariances must be input a-priori. Unlike `R's\n lme4 `__ or\n `Julia's MixedModels `__,\n Diamond does not estimate the covariance of random effects terms.\n- Diamond only supports the following models\n\n - logistic regression\n - ordinal logistic regression using proportional odds, as defined in\n Section 7.2.1 of Categorical Data Analysis, 2nd Ed., by Alan\n Agresti\n\n- Currently, only formulae with crossed, independent random effects are\n supported. Using the mtcars dataset as an example, these look like\n ``mpg ~ 1 + hp + (1 + hp | cyl) + (1 | gear)``. I.e. no hierarchical\n terms\n\nInstallation\n------------\n\nYou must have `docker `__\ninstalled. Then, run\n``docker run -ti --rm -p 8888:8888 tsweetser/diamond``\n\nCopy-paste the URL, including the token, into your browser. Then, check\nout the Jupyter notebook examples!\n\nTroubleshooting installation\n----------------------------\n\n- You may need to restart docker if you've been running jupyter\n notebooks locally on port 8888.\n\nDocumentation\n-------------\n\nSee `documentation `__ for more\ndetails on the details of Diamond and how to use it\n\nContributing to Diamond\n-----------------------\n\nWe always welcome contributions. See\n`CONTRIBUTING.md `__\n\nRunning Tests\n-------------\n\nYou will need R to run the integration tests. From the root directory,\nrun ``pip install nose`` then ``nosetests``.\n\nDevelopment Status\n------------------\n\nDiamond is an evolving project. Please file issues if you would like to\nuse Diamond in new ways.\n\nLicense\n-------\n\nSee `LICENSE.txt `__\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://github.com/stitchfix/diamond", "keywords": "", "license": "LICENSE.txt", "maintainer": "", "maintainer_email": "", "name": "sf-diamond", "package_url": "https://pypi.org/project/sf-diamond/", "platform": "", "project_url": "https://pypi.org/project/sf-diamond/", "project_urls": { "Homepage": "http://github.com/stitchfix/diamond" }, "release_url": "https://pypi.org/project/sf-diamond/0.2.2/", "requires_dist": null, "requires_python": "", "summary": "GLMMs with known variances in python with Newton-like solver", "version": "0.2.2" }, "last_serial": 3446590, "releases": { "0.2.2": [ { "comment_text": "", "digests": { "md5": "4069f962460ac7f3845113a85a98ad2c", "sha256": "e205b5d74d59c36ab1294a6b4edc01cd80278bbf65027b878606d962451e4ed9" }, "downloads": -1, "filename": "sf-diamond-0.2.2.tar.gz", "has_sig": false, "md5_digest": "4069f962460ac7f3845113a85a98ad2c", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 62047, "upload_time": "2017-12-28T04:34:18", "url": "https://files.pythonhosted.org/packages/3b/ff/db0d7080e9dceb6c426911e861a7a060ad3bd8821578d6932a9763bdf234/sf-diamond-0.2.2.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "4069f962460ac7f3845113a85a98ad2c", "sha256": "e205b5d74d59c36ab1294a6b4edc01cd80278bbf65027b878606d962451e4ed9" }, "downloads": -1, "filename": "sf-diamond-0.2.2.tar.gz", "has_sig": false, "md5_digest": "4069f962460ac7f3845113a85a98ad2c", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 62047, "upload_time": "2017-12-28T04:34:18", "url": "https://files.pythonhosted.org/packages/3b/ff/db0d7080e9dceb6c426911e861a7a060ad3bd8821578d6932a9763bdf234/sf-diamond-0.2.2.tar.gz" } ] }