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clustering-geodata-cubes-0.6.2
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مشاهده بیشترتوضیحات
A clustering tool for geospatial applications
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | clustering-geodata-cubes-0.6.2 |
| نام | clustering-geodata-cubes |
| نسخه کتابخانه | 0.6.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Netherlands eScience Center |
| ایمیل نویسنده | team-atlas@esciencecenter.nl |
| آدرس صفحه اصلی | https://github.com/phenology/cgc |
| آدرس اینترنتی | https://pypi.org/project/clustering-geodata-cubes/ |
| مجوز | Apache Software License 2.0 |
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CGC: Clustering Geo-Data Cubes
==============================
The Clustering Geo-Data Cubes (CGC) package focuses on the needs of geospatial data scientists who require tools to make sense of multi-dimensional data cubes. It provides the functionality to perform **co-cluster** and **tri-cluster** analyses on both local and distributed systems.
Installation
------------
To install CGC, do:
.. code-block:: console
pip install clustering-geodata-cubes
Alternatively, you can clone this repository and install it using `pip`:
.. code-block:: console
git clone https://github.com/phenology/cgc.git
cd cgc
pip install .
In order to run tests (including coverage) install the `dev` package version:
.. code-block:: console
git clone https://github.com/phenology/cgc.git
cd cgc
pip install .[dev]
pytest -v
Documentation
-------------
The project's full API documentation can be found `online <https://cgc.readthedocs.io/en/latest/>`_. Including:
- `Co-clustering <https://cgc.readthedocs.io/en/latest/coclustering.html>`_
- `Tri-clustering <https://cgc.readthedocs.io/en/latest/triclustering.html>`_
- `K-means refinement <https://cgc.readthedocs.io/en/latest/kmeans.html>`_
- `Utility Functions <https://cgc.readthedocs.io/en/latest/utils.html>`_
Examples of CGC applications on real geo-spatial data:
- `Co-clustering application <https://cgc-tutorial.readthedocs.io/en/latest/notebooks/coclustering.html>`_
- `Tri-clustering application <https://cgc-tutorial.readthedocs.io/en/latest/notebooks/triclustering.html>`_
Tutorial
--------
The tutorial of CGC can be found `here <https://cgc-tutorial.readthedocs.io/en/latest/index.html>`_.
Contributing
------------
If you want to contribute to the development of cgc, have a look at the `contribution guidelines`_.
.. _contribution guidelines: https://github.com/phenology/cgc/tree/master/CONTRIBUTING.rst
License
-------
Copyright (c) 2020-2022,
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Credits
-------
The code has been developed as a collaborative effort between the `ITC, University of Twente`_ and
`the Netherlands eScience Center`_ within the generalization of the project
`High spatial resolution phenological modelling at continental scales`_.
.. _ITC, University of Twente: https://www.itc.nl
.. _High spatial resolution phenological modelling at continental scales: https://research-software.nl/projects/1334
.. _the Netherlands eScience Center: https://www.esciencecenter.nl
This package was created with `Cookiecutter <https://github.com/audreyr/cookiecutter>`_ and the
`NLeSC/python-template <https://github.com/NLeSC/python-template>`_.
نیازمندی
| مقدار | نام |
|---|---|
| - | numpy |
| - | dask[complete] |
| - | scikit-learn |
| - | numba |
| - | matplotlib |
| - | pytest |
| - | pytest-cov |
| - | pycodestyle |
نحوه نصب
نصب پکیج whl clustering-geodata-cubes-0.6.2:
pip install clustering-geodata-cubes-0.6.2.whl
نصب پکیج tar.gz clustering-geodata-cubes-0.6.2:
pip install clustering-geodata-cubes-0.6.2.tar.gz