scikit-mps


Namescikit-mps JSON
Version 0.5.0 PyPI version JSON
download
home_pagehttps://github.com/ergosimulation/mpslib/tree/master/scikit-mps
SummaryMultiple point statistical (MPS) simulation
upload_time2023-01-10 09:09:53
maintainer
docs_urlNone
authorThomas Mejer Hansen
requires_python
licenseLGPL
keywords geostatistics simulation mps
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            scikit-mps: A python interface to MPSlib 
========================================================================================

.. image:: https://img.shields.io/pypi/v/scikit-mps.svg?style=flat-square
    :target: https://pypi.org/project/scikit-mps

.. image:: https://img.shields.io/pypi/pyversions/scikit-mps.svg?style=flat-square
    :target: https://pypi.org/project/scikit-mps

.. image:: https://img.shields.io/badge/license-MIT-blue.svg?style=flat-square
    :target: https://en.wikipedia.org/wiki/MIT_License

.. image:: https://colab.research.google.com/assets/colab-badge.svg
    :target: https://colab.research.google.com/github/ergosimulation/mpslib/blob/master/scikit-mps/examples/mpslib_in_google_colab.ipynb

`scikit-mps` is a Python interface to MPSlib, https://github.com/ergosimulation/mpslib/,
which is a C++ library for geostatistical multiple point simulation, with implementations
of 'SNESIM', 'ENESIM', and 'GENESIM'

It contains three modules:
  * mpslib: Interacts with MPSlib
  * eas: read and write EAS/GSLIB formatted files
  * trainingimages: Access to a number of trainingimages

.. code::

   import mpslib as mps
   O=mps.mpslib(method='mps_snesim_tree')
   O.run()
   O.plot_reals()
   O.plot_etype()

PyPI
~~~~~~~~~
`<http://pypi.python.org/pypi/scikit-mps>`

Requirements
~~~~~~~~~~~~
* Numpy >= 1.0.2
* Matplotlib >= 1.0.2
* MPSlib needs to be downloaded, installed, and in the system path (https://github.com/ergosimulation/mpslib/)
  [Any 11 C++11 compiler should work, such as gcc, MinGW, MSVC]



Installing
~~~~~~~~~~~~~~
* Via pip:: 

    pip install scikit-mps

optionally download and reinstall:: 

    import mpslib as mps
    O=mps.mpslib
    O.compile_mpslib()

* From source code 

.. code::

   cd ROOT_OF_MPSLIB/python   
   pip install .
   cd ROOT_OF_MPSLIB
   make clean
   make   

If you wish to develop the scikit-mps package, then install it in editable developer mode using

.. code::

    pip install -e .


            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/ergosimulation/mpslib/tree/master/scikit-mps",
    "name": "scikit-mps",
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "keywords": "geostatistics,simulation,MPS",
    "author": "Thomas Mejer Hansen",
    "author_email": "thomas.mejer.hansen@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/84/dd/96fe1ca2dc3773c070f187aa26828a8094fe3ec9b10eee72ce415d6136ff/scikit-mps-0.5.0.tar.gz",
    "platform": null,
    "description": "scikit-mps: A python interface to MPSlib \n========================================================================================\n\n.. image:: https://img.shields.io/pypi/v/scikit-mps.svg?style=flat-square\n    :target: https://pypi.org/project/scikit-mps\n\n.. image:: https://img.shields.io/pypi/pyversions/scikit-mps.svg?style=flat-square\n    :target: https://pypi.org/project/scikit-mps\n\n.. image:: https://img.shields.io/badge/license-MIT-blue.svg?style=flat-square\n    :target: https://en.wikipedia.org/wiki/MIT_License\n\n.. image:: https://colab.research.google.com/assets/colab-badge.svg\n    :target: https://colab.research.google.com/github/ergosimulation/mpslib/blob/master/scikit-mps/examples/mpslib_in_google_colab.ipynb\n\n`scikit-mps` is a Python interface to MPSlib, https://github.com/ergosimulation/mpslib/,\nwhich is a C++ library for geostatistical multiple point simulation, with implementations\nof 'SNESIM', 'ENESIM', and 'GENESIM'\n\nIt contains three modules:\n  * mpslib: Interacts with MPSlib\n  * eas: read and write EAS/GSLIB formatted files\n  * trainingimages: Access to a number of trainingimages\n\n.. code::\n\n   import mpslib as mps\n   O=mps.mpslib(method='mps_snesim_tree')\n   O.run()\n   O.plot_reals()\n   O.plot_etype()\n\nPyPI\n~~~~~~~~~\n`<http://pypi.python.org/pypi/scikit-mps>`\n\nRequirements\n~~~~~~~~~~~~\n* Numpy >= 1.0.2\n* Matplotlib >= 1.0.2\n* MPSlib needs to be downloaded, installed, and in the system path (https://github.com/ergosimulation/mpslib/)\n  [Any 11 C++11 compiler should work, such as gcc, MinGW, MSVC]\n\n\n\nInstalling\n~~~~~~~~~~~~~~\n* Via pip:: \n\n    pip install scikit-mps\n\noptionally download and reinstall:: \n\n    import mpslib as mps\n    O=mps.mpslib\n    O.compile_mpslib()\n\n* From source code \n\n.. code::\n\n   cd ROOT_OF_MPSLIB/python   \n   pip install .\n   cd ROOT_OF_MPSLIB\n   make clean\n   make   \n\nIf you wish to develop the scikit-mps package, then install it in editable developer mode using\n\n.. code::\n\n    pip install -e .\n\n",
    "bugtrack_url": null,
    "license": "LGPL",
    "summary": "Multiple point statistical (MPS) simulation",
    "version": "0.5.0",
    "split_keywords": [
        "geostatistics",
        "simulation",
        "mps"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "3392749357060fdda5f2997086f6876fa9c5f970ae8c9570679b48f139dd0758",
                "md5": "9fb4845c08ffc1fdb1ef277623256ae2",
                "sha256": "3d0c2446095ae4813a85ebde68b296a39699deaab910fb9e2c30b283e3444966"
            },
            "downloads": -1,
            "filename": "scikit_mps-0.5.0-py2.py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "9fb4845c08ffc1fdb1ef277623256ae2",
            "packagetype": "bdist_wheel",
            "python_version": "py2.py3",
            "requires_python": null,
            "size": 5147418,
            "upload_time": "2023-01-10T09:09:50",
            "upload_time_iso_8601": "2023-01-10T09:09:50.102008Z",
            "url": "https://files.pythonhosted.org/packages/33/92/749357060fdda5f2997086f6876fa9c5f970ae8c9570679b48f139dd0758/scikit_mps-0.5.0-py2.py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "84dd96fe1ca2dc3773c070f187aa26828a8094fe3ec9b10eee72ce415d6136ff",
                "md5": "9ba87b84ccbc964f8dc235bc365d7e66",
                "sha256": "d7155f37cc042ed011f190e9cd54e61c0026f1d089a4648c1b278f5434a471b1"
            },
            "downloads": -1,
            "filename": "scikit-mps-0.5.0.tar.gz",
            "has_sig": false,
            "md5_digest": "9ba87b84ccbc964f8dc235bc365d7e66",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 5111523,
            "upload_time": "2023-01-10T09:09:53",
            "upload_time_iso_8601": "2023-01-10T09:09:53.663335Z",
            "url": "https://files.pythonhosted.org/packages/84/dd/96fe1ca2dc3773c070f187aa26828a8094fe3ec9b10eee72ce415d6136ff/scikit-mps-0.5.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-01-10 09:09:53",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "lcname": "scikit-mps"
}
        
Elapsed time: 0.06874s