{ "info": { "author": "Luke Granlund", "author_email": "luke.r.granlund@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Operating System :: MacOS", "Operating System :: Microsoft :: Windows", "Operating System :: POSIX", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Topic :: Scientific/Engineering :: Chemistry", "Topic :: Scientific/Engineering :: Physics", "Topic :: Software Development :: Libraries" ], "description": "#########################\nSrMise\n#########################\n\n`DiffPy project `_ tool for unbiased peak extraction from\natomic pair distribution functions.\n\nSrMise is an implementation of the `ParSCAPE algorithm \n`_ for peak extraction from \natomic pair distribution functions (PDFs). It is designed to function even \nwhen *a priori* knowledge of the physical sample is limited, utilizing the \nAkaike Information Criterion (AIC) to estimate whether peaks are \nstatistically justified relative to alternate models. Three basic use cases \nare anticipated for SrMise. The first is peak fitting a user-supplied \ncollections of peaks. The second is peak extraction from a PDF with no (or \nonly partial) user-supplied peaks. The third is an AIC-driven multimodeling \nanalysis where the output of multiple SrMise trials are ranked. \n\nThe framework for peak extraction defines peak-like clusters within the data, \nextracts a single peak within each cluster, and iteratively combines nearby \nclusters while performing a recursive search on the residual to identify \noccluded peaks. Eventually this results in a single global cluster \ncontaining many peaks fit over all the data. Over- and underfitting are \ndiscouraged by use of the AIC when adding or, during a pruning step, removing\npeaks. Termination effects, which can lead to physically spurious peaks in \nthe PDF, are incorporated in the mathematical peak model and the pruning step \nattempts to remove peaks which are fit better as termination ripples due to \nanother peak. \n\nWhere possible, SrMise provides physically reasonable default values \nfor extraction parameters. However, the PDF baseline should be estimated by \nthe user before extraction, or by performing provisional peak extraction with \nvarying baseline parameters. The package defines a linear (crystalline) \nbaseline, arbitrary polynomial baseline, a spherical nanoparticle baseline, \nand an arbitrary baseline interpolated from a list of user-supplied values. \nIn addition, PDFs with accurate experimentally-determined uncertainties are \nnecessary to provide the most reliable results, but historically such PDFs \nare rare. In the absence of accurate uncertainties an *ad hoc* uncertainty \nmust be specified. \n\nFor more information about SrMise, see the users manual at\nhttp://diffpy.github.io/diffpy.srmise.\n\nGetting Started\n=================\n\nThe diffpy.srmise package requires Python 2.6 or 2.7 and the following software:\n\n* ``setuptools`` - software distribution tools for Python\n* ``NumPy`` - numerical mathematics and fast array operations for Python\n* ``SciPy`` - scientific libraries for Python\n* ``matplotlib`` - python plotting library\n\nSee the `SrMise license `__ for terms and conditions of use.\nDetailed installation instructions for the `Windows`_, `Mac OS X`_, and\n`Linux`_ platforms follow.\n\nWindows\n-------\n\nSeveral prebuilt Python distributions for Windows include all the\nprerequisite software required to run SrMise, and installing one of these is the\nsimplest way to get started. These distributions are usually free for\nindividual and/or academic use, but some also have commercial version. Links to\nexecutables, installation instructions, and licensing information\nfor some popular options are listed below.\n\n* `Anaconda `_\n* `Enthought Canopy `_\n* `Python(x,y) `_\n* `WinPython `_\n\nAlternately, individual Windows executables for Python and the required\ncomponents can be downloaded and installed. The official Windows releases of\nNumpy and SciPy do not currently support 64-bit Python installations, so be\nsure to download the 32-bit versions of these packages.\n\n* `Python 2.6/2.7 `_\n* `NumPy `_\n* `SciPy `_\n* `matplotlib `_\n\nAfter installing Python and the required packages, the simplest way to obtain\nSrMise is using ``pip`` to download and install the latest release from the\n`Python Package Index `_ (PyPI). Open a command window\nby running ``cmd`` from the Start Menu's application search box (Windows 7/8/10)\nor Run command (Windows Vista and earlier). Verify that the\n``pip`` program is installed by running ::\n\n pip --version\n\nIf this command is not found, download and run\n`get-pip.py `_, which will install both it\nand setuptools. For example, if the file were downloaded to the desktop, a\nWindows user named ``MyName`` should run the following from the command\nline: ::\n\n cd C:\\Users\\MyName\\Desktop\n python get-pip.py\n\nFinally, install the latest version of SrMise by running ::\n\n pip install diffpy.srmise\n\n\nMac OS X\n--------\n\nFor Mac OS X systems with the MacPorts package manager, the required\nsoftware can be installed with ::\n\n sudo port install \\\n python27 py27-setuptools py27-numpy py27-scipy py27-matplotlib\n\nWhen installing for MacPorts, make sure the MacPorts bin directory is the first\nin the system PATH and that python27 is selected as the default Python version\nin MacPorts::\n\n sudo port select --set python python27\n\nThe simplest way to obtain diffpy.srmise on Mac OS X systems\nis using ``pip`` to download and install the latest release from\n`PyPI `_. :: \n\n sudo pip install diffpy.srmise\n\nThose who prefer to install from sources may download them from the\n`GitHub `__ or\n`PyPI `__ pages for SrMise.\nUncompress them to a directory, and from that directory run ::\n\n sudo python setup.py install\n\nThis installs diffpy.srmise for all users in the default system location. If \nadministrator (root) access is not available, see the usage info from \n``python setup.py install --help`` for options to install to user-writable \ndirectories.\n\n\nLinux\n-----\n\nOn Ubuntu and Debian Linux, the required software can easily be installed using\nthe system package manager::\n\n sudo apt-get install \\\n python-setuptools python-numpy python-scipy python-matplotlib\n\nSimilarly, on Fedora::\n\n sudo yum install python-setuptools numpy scipy python-matplotlib\n\nFor other Linux distributions consult the appropriate package manager.\n\nThe simplest way to obtain diffpy.srmise on Linux systems\nis using ``pip`` to download and install the latest release from the\n`PyPI `_. :: \n\n sudo pip install diffpy.srmise\n\nThose who prefer to install from sources may download them from the\n`GitHub `__ or\n`PyPI `__ pages for SrMise.\nUncompress them to a directory, and from that directory run ::\n\n sudo python setup.py install\n\nThis installs diffpy.srmise for all users in the default system location. If \nadministrator (root) access is not available, see the usage info from \n``python setup.py install --help`` for options to install to user-writable \ndirectories. \n\n\nDEVELOPMENT\n===========\n\ndiffpy.srmise is open-source software developed with support of the Center of \nResearch Excellence in Complex Materials at Michigan State University, in \ncooperation with the DiffPy-CMI complex modeling initiative at the Brookhaven \nNational Laboratory. The diffpy.srmise sources are hosted at \nhttps://github.com/diffpy/diffpy.srmise. \n\nFeel free to fork the project and contribute. To install diffpy.srmise in a \ndevelopment mode, with its sources being directly used by Python rather than \ncopied to a package directory, use :: \n\n python setup.py develop --user\n\n\nACKNOWLEDGEMENT\n===============\n\nThe source code of *pdfdataset.py* was derived from diffpy.pdfgui.\n\n\nCONTACTS\n========\n\nFor more information on SrMise please visit the DiffPy project web-page\n\nhttp://www.diffpy.org/\n\nor email Prof. Simon Billinge at sb2896@columbia.edu.\n", "description_content_type": null, "docs_url": null, "download_url": null, "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/diffpy/diffpy.srmise/", "keywords": "peak extraction fitting PDF AIC multimodeling", "license": "BSD-style license", "maintainer": null, "maintainer_email": null, "name": "diffpy.srmise", "package_url": "https://pypi.org/project/diffpy.srmise/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/diffpy.srmise/", "project_urls": { "Homepage": "https://github.com/diffpy/diffpy.srmise/" }, "release_url": "https://pypi.org/project/diffpy.srmise/0.5.2/", "requires_dist": null, "requires_python": null, "summary": "Peak extraction and peak fitting tool for atomic pair distribution functions.", "version": "0.5.2" }, "last_serial": 1615038, "releases": { "0.5": [ { "comment_text": "", "digests": { "md5": "6b7f27884bbfc8e3fec632673a3eed3b", "sha256": "0f98aacd8094b13f0e9011368dc14d1693200e7304b2f2237d25168c89ec6d9b" }, "downloads": -1, "filename": "diffpy.srmise-0.5.tar.gz", "has_sig": false, "md5_digest": "6b7f27884bbfc8e3fec632673a3eed3b", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 304798, "upload_time": "2015-05-29T05:31:14", "url": "https://files.pythonhosted.org/packages/19/61/8c925ab03039598e8f2a623c4f1f615d21cf82fb3bcec6e20211aee4d0bc/diffpy.srmise-0.5.tar.gz" } ], "0.5.1": [ { "comment_text": "", "digests": { "md5": "aef0fd1113b521d8869393d1bd27418e", "sha256": "dcb883e0f5907ee087ce146e681233e787b98f82667ba66b5051769401d88009" }, "downloads": -1, "filename": "diffpy.srmise-0.5.1.tar.gz", "has_sig": false, "md5_digest": "aef0fd1113b521d8869393d1bd27418e", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 304819, "upload_time": "2015-05-30T16:33:29", "url": "https://files.pythonhosted.org/packages/e2/41/f8e6614c8c857be1d20d7c775c0ed49b661a7c05b66fb71844e5f2567998/diffpy.srmise-0.5.1.tar.gz" } ], "0.5.2": [ { "comment_text": "", "digests": { "md5": "0f872c8c4c4414cd560fb19061c8f68b", "sha256": "02d80a182ea19e300dda5d199c0a5a5345b14a3089a7d51b1a7a9d21ee370523" }, "downloads": -1, "filename": "diffpy.srmise-0.5.2.tar.gz", "has_sig": false, "md5_digest": "0f872c8c4c4414cd560fb19061c8f68b", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 326441, "upload_time": "2015-07-01T15:33:19", "url": "https://files.pythonhosted.org/packages/fa/1e/474ce885cde15ea217539a161d911d713c36e95ab7c3d4296e3ba40fdc17/diffpy.srmise-0.5.2.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "0f872c8c4c4414cd560fb19061c8f68b", "sha256": "02d80a182ea19e300dda5d199c0a5a5345b14a3089a7d51b1a7a9d21ee370523" }, "downloads": -1, "filename": "diffpy.srmise-0.5.2.tar.gz", "has_sig": false, "md5_digest": "0f872c8c4c4414cd560fb19061c8f68b", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 326441, "upload_time": "2015-07-01T15:33:19", "url": "https://files.pythonhosted.org/packages/fa/1e/474ce885cde15ea217539a161d911d713c36e95ab7c3d4296e3ba40fdc17/diffpy.srmise-0.5.2.tar.gz" } ] }