{ "info": { "author": "Robert T. McGibbon", "author_email": "robert.mcgibbon@deshawresearch.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 4 - Beta", "Environment :: Console", "Operating System :: OS Independent", "Programming Language :: Python" ], "description": "Spin-network-scaled MP2 (SNS-MP2)\n=================================\n\nThis module implements the SNS-MP2 method for computing dimer interaction\nenergies described by McGibbon et al. [1]. It is implemented as a plugin\nfor the Psi4 electronic structure method, and requires Psi4 version 1.1\nor greater.\n\nInstallation\n------------\n- First, you need to install a working copy of Psi4 1.1 or greater. Head to\n [their website](http://www.psicode.org/psi4manual/master/build_obtaining.html)\n for installation instructions.\n- Next, install this plugin using the following commands\n```\n# Grab the path to the Python interpreter used by your copy of Psi4\n$ PSI4_PYTHON=$(head $(which psi4) -n 1 | sed -r 's/^.{2}//')\n\n# Install the SNS-MP2 package with this copy of Python.\n$ PSI4_PYTHON -m pip install .\n```\n\nRunning calculations\n--------------------\n\nHere's probably the simplest possible input file. It computes the\ninteraction energy between two helium atoms separated by two angstroms.\n\n```\nmolecule {\nHe 0 0 0\n--\nHe 2 0 0\n\n}\n\nimport snsmp2\nenergy('sns-mp2')\n```\n\n\nCopy the contents to a file called `first-cak.dat.`. To run the calculation,\nexecute\n\n```\n$ psi4 first-calc.dat\n```\n\nAfter it finishes, you can find the results in `first-calc.out`.\n\n\n\n\nReferences\n----------\n[1] R. T. McGibbon, A. G. Taube, A. G. Donchev, K. Siva, F. Fernandez, C. Hargus,\n K.-H. Law, J.L. Klepeis, and D. E. Shaw. \"Improving the accuracy of\n Moller-Plesset perturbation theory with neural networks\"\n\nLicense\n-------\n\n```\n SNS-MP2 LICENSE AGREEMENT\n\nCopyright 2017, D. E. Shaw Research. All rights reserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions\nare met:\n\n * Redistributions of source code must retain the above copyright notice,\n this list of conditions, and the following disclaimer.\n\n * Redistributions in binary form must reproduce the above copyright\n notice, this list of conditions, and the following disclaimer in the\n documentation and/or other materials provided with the distribution.\n\nNeither the name of D. E. Shaw Research nor the names of its contributors\nmay be used to endorse or promote products derived from this software\nwithout specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS\n\"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT\nLIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR\nA PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT\nOWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,\nSPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED\nTO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF\nLIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING\nNEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n```\n\nThe file `snsmp2/contextdecorator.py` is copyright Michael Foord and is\nredistributed under the 3-clause BSD license (see `nsmp2/contextdecorator.py`\nfor details).\n\n\n\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "", "keywords": "", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "snsmp2", "package_url": "https://pypi.org/project/snsmp2/", "platform": "", "project_url": "https://pypi.org/project/snsmp2/", "project_urls": null, "release_url": "https://pypi.org/project/snsmp2/1.0.0/", "requires_dist": null, "requires_python": "", "summary": "Spin-network-scaled MP2", "version": "1.0.0" }, "last_serial": 3161061, "releases": { "1.0.0": [ { "comment_text": "", "digests": { "md5": "5d581c56839b49233d0bcc50d8b0a7cb", "sha256": "acfc95f8eb40e18d9d0c737b42fc8dfa786c381a5510a3094772b82538d211ed" }, "downloads": -1, "filename": "snsmp2-1.0.0-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "5d581c56839b49233d0bcc50d8b0a7cb", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 124545, "upload_time": "2017-09-09T03:33:19", "url": "https://files.pythonhosted.org/packages/13/6e/00b46e89e15b07ca3b82b34161823fe8af09a994d2517f21a9b18a494bcf/snsmp2-1.0.0-py2.py3-none-any.whl" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "5d581c56839b49233d0bcc50d8b0a7cb", "sha256": "acfc95f8eb40e18d9d0c737b42fc8dfa786c381a5510a3094772b82538d211ed" }, "downloads": -1, "filename": "snsmp2-1.0.0-py2.py3-none-any.whl", "has_sig": false, "md5_digest": "5d581c56839b49233d0bcc50d8b0a7cb", "packagetype": "bdist_wheel", "python_version": "py2.py3", "requires_python": null, "size": 124545, "upload_time": "2017-09-09T03:33:19", "url": "https://files.pythonhosted.org/packages/13/6e/00b46e89e15b07ca3b82b34161823fe8af09a994d2517f21a9b18a494bcf/snsmp2-1.0.0-py2.py3-none-any.whl" } ] }