pycoal

Python toolkit for characterizing Coal and Open-pit surface mining impacts on American Lands

https://github.com/capstone-coal/pycoal

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Committers with academic emails
    6 of 15 committers (40.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (13.9%) to scientific vocabulary

Keywords

classification classification-algorithm coal hyperspectral-image-classification open-surface-mining python surface-mining-activities
Last synced: 6 months ago · JSON representation

Repository

Python toolkit for characterizing Coal and Open-pit surface mining impacts on American Lands

Basic Info
Statistics
  • Stars: 29
  • Watchers: 8
  • Forks: 13
  • Open Issues: 10
  • Releases: 0
Topics
classification classification-algorithm coal hyperspectral-image-classification open-surface-mining python surface-mining-activities
Created over 9 years ago · Last pushed over 4 years ago
Metadata Files
Readme License

README.rst

======
Pycoal
======

**Development**

|license| |PyPI| |Python3| |GoogleGroup| |documentation| |Travis| |Coveralls| |Requirements Status| |Anaconda-Server Version| |Anaconda-Server Downloads|

**Docker**

|Docker Pulls| |microbadger|

COAL is a Python library for processing hyperspectral imagery from remote sensing devices such as the
`Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) `__ and 
`AVIRIS-Next Generation `__ enabling scientific analysis of Coal and 
Open-pit surface mining impacts on American Lands.

Introduction and Context
------------------------
Mountain-top Mining (MTM) is a method of open surface mining with the primary aim of exploring and 
exploiting coal seams present within the land and solid earth (LSE) on mountaintops. Amongst other 
surface mining activities, MTM is known to be an extremely destructive mining procedure predominantly 
limited to the spatial boundaries of the Southern Appalachians (Eastern Kentucky, West Virginia 
and very small sections of Virginia and Tennessee). MTM is known to have caused irreparable damage 
to mountain landscapes and significant immediate and longer-term damage to key streams and watersheds. 
Larger afield, the rest of the U.S.A has some extensive surface mining in various places for 
exploitation of resources such as gravel/sand, various metals, other minerals and even radioactive 
materials, etc. Several studies have provided important scientific understanding related to the 
local, regional and state-level impacts of such environmentally destructive practices, however 
a similar understanding on the national and continental levels are very much lacking.

Project Motivation & Statement 
------------------------------
COAL provides a suite of algorithms (written in Python) to identify, classify, characterize,
and quantify (by reporting a number of key metrics) the direct and indirect impacts of 
MTM and related destructive surface mining activities across the continental U.S.A (and further afield). 

More information on COAL can be seen at the `Project Website `__ 
as well as the **docs** directory.

Installation
------------

pip
^^^
|PyPI|

The Python COAL package **pycoal** can be installed from the cheeseshop

::

	pip3 install pycoal
    
conda
^^^^^
|Anaconda-Server Version| |Anaconda-Server Downloads|

or from conda

::

	conda install -c conda-forge pycoal

Source
^^^^^^

or from source

::

	git clone https://github.com/capstone-coal/pycoal.git && cd pycoal
	python3 setup.py install

Docker
^^^^^^
|Docker Pulls| |microbadger|

`Docker `_ greatly simplifies installation of pycoal and the environment. 
The image can be installed from `Dockerhub `_ as follows

::

	docker pull capstonecoal/coal:latest

Additionally, if you are developing the image and wish to build it locally, you can run the following

**Installation**

1. Install `Docker `_.

2. Build from files in this directory:

::

	docker build -t capstonecoal/coal .

**Usage**

Start up an image and attach to it

::

	docker run -t -i -d --name coalcontainer capstonecoal/coal /bin/bash
	docker attach --sig-proxy=false coalcontainer

pycoal is located in /coal and is almost ready to run. You just need to grab some data.

Tests
-----

|Travis| |Coveralls|

COAL uses the popular `nose `__
testing suite for unit tests.

You can run the COAL tests simply by running

::

    nosetests

Additonally, click on the build sticker at the top of this readme to be
directed to the most recent build on `travis-ci `__.

Quickstart
----------

See the `quickstart documentation `_.

If you would like to run the examples yourself, head over to the **examples** module.

**WARNING** Running the examples requires `additional downloads `_. Ensure you have sufficient storage (~20 GB).

Documentation
-------------

|documentation|

COAL documentation can be found at `Readthedocs `__ however you can also build documentation manually.

::

	$ cd docs/source && make html

Documentation can then be located in **_build/html/index.html**

Community and Development
-------------------------

Slack
^^^^^^^^^^^^

|Slack|

Questions, concerns, and general communication is all encouraged in our `Slack organization `_.

Mailing list
^^^^^^^^^^^^

|GoogleGroup|

To become involved or if you require help using the project request to join our mailing list.

Issue Tracker
^^^^^^^^^^^^^

If you have issue using COAL, please log a ticket in our `Github issue tracker `__.

License
-------

COAL is licensed under the |license| a copy of which ships with this source code.

.. |license| image:: https://anaconda.org/conda-forge/pycoal/badges/license.svg
   :target: https://www.gnu.org/licenses/gpl-2.0.html
.. |Python3| image:: https://img.shields.io/badge/python-3-blue.svg
   :target: https://www.python.org/downloads/
.. |PyPI| image:: https://img.shields.io/pypi/v/pycoal.svg?maxAge=2592000?style=plastic
   :target: https://pypi.python.org/pypi/pycoal
.. |Slack| image:: https://assets.brandfolder.com/pl546j-7le8zk-6gwiyo/element.png?v=1547165361
    :target: https://capstone-coal.slack.com
.. |GoogleGroup| image:: https://img.shields.io/badge/-Google%20Group-lightgrey.svg
   :target: https://groups.google.com/forum/#!forum/coal-capstone
.. |documentation| image:: https://readthedocs.org/projects/pycoal/badge/?version=latest
   :target: http://pycoal.readthedocs.org/en/latest/
.. |Travis| image:: https://img.shields.io/travis/capstone-coal/pycoal.svg?maxAge=2592000?style=plastic
   :target: https://travis-ci.org/capstone-coal/pycoal
.. |Coveralls| image:: https://coveralls.io/repos/github/capstone-coal/pycoal/badge.svg?branch=master
   :target: https://coveralls.io/github/capstone-coal/pycoal?branch=master
.. |Requirements Status| image:: https://requires.io/github/capstone-coal/pycoal/requirements.svg?branch=master
   :target: https://requires.io/github/capstone-coal/pycoal/requirements/?branch=master
.. |Anaconda-Server Version| image:: https://anaconda.org/conda-forge/pycoal/badges/version.svg
   :target: https://anaconda.org/conda-forge/pycoal
.. |Anaconda-Server Downloads| image:: https://anaconda.org/conda-forge/pycoal/badges/downloads.svg
   :target: https://anaconda.org/conda-forge/pycoal
.. |Docker Pulls| image:: https://img.shields.io/docker/pulls/capstonecoal/coal.svg?maxAge=2592000?style=plastic
   :target: https://cloud.docker.com/swarm/capstonecoal/repository/docker/capstonecoal/coal/general
.. |microbadger| image:: https://images.microbadger.com/badges/image/capstonecoal/coal.svg
   :target: https://microbadger.com/images/capstonecoal/coal

Owner

  • Name: COAL Capstone
  • Login: capstone-coal
  • Kind: organization
  • Email: coal-capstone@googlegroups.com

Coal and Open-pit surface mining impacts on American Lands (COAL) Capstone Project

GitHub Events

Total
  • Issues event: 1
  • Watch event: 1
  • Issue comment event: 1
Last Year
  • Issues event: 1
  • Watch event: 1
  • Issue comment event: 1

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 399
  • Total Committers: 15
  • Avg Commits per committer: 26.6
  • Development Distribution Score (DDS): 0.684
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Taylor Alexander Brown b****l@o****u 126
Lewis John McGibbney l****y@g****m 105
bdegley4789 e****b@o****u 62
Heidi h****n@y****m 37
mjn0898 m****n@u****u 30
Lactem l****m@o****m 13
Xiaomei x****7@g****m 6
Luner j****r@u****u 5
Evandro C. Taquary e****y@g****m 5
Heidi H****n 3
Andrew Heermann h****n@u****u 2
Theo t****e@u****u 2
Bryce Egley b****y@c****o 1
Taylor Alexander Brown r****t@t****t 1
Ibrahim Jarif j****m@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 111
  • Total pull requests: 104
  • Average time to close issues: 2 months
  • Average time to close pull requests: 9 days
  • Total issue authors: 11
  • Total pull request authors: 14
  • Average comments per issue: 5.23
  • Average comments per pull request: 5.13
  • Merged pull requests: 82
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 1
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 1
  • Pull request authors: 0
  • Average comments per issue: 1.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • ghost (44)
  • lewismc (36)
  • Luner (9)
  • theoilie (6)
  • aheermann (5)
  • heidiaclayton (4)
  • EvandroCT (2)
  • mjn0898 (2)
  • TinyBugBigProblem (1)
  • dbsi-pinkman (1)
  • BlcaKHat (1)
Pull Request Authors
  • ghost (36)
  • lewismc (15)
  • bdegley4789 (14)
  • heidiaclayton (9)
  • theoilie (6)
  • EvandroCT (5)
  • Luner (5)
  • mjn0898 (4)
  • thomkenn (2)
  • TinyBugBigProblem (2)
  • aheermann (2)
  • xiaomei7 (2)
  • jarifibrahim (1)
  • someshdhurve (1)
Top Labels
Issue Labels
enhancement (56) help wanted (25) mineral (24) documentation (22) classification (20) build (12) testing (10) environment (6) bug (5) examples (5) question (4) Docker (4) mining (2) wontfix (1) inputoutput (1) rest api (1)
Pull Request Labels
enhancement (24) documentation (12) mineral (11) classification (8) examples (6) help wanted (6) testing (6) build (5) Docker (4) environment (3) bug (2) mining (1)

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 18 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 6
  • Total maintainers: 1
pypi.org: pycoal

COAL mining library for AVIRIS data.

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 18 Last month
Rankings
Dependent packages count: 7.4%
Forks count: 9.9%
Stargazers count: 12.5%
Dependent repos count: 22.2%
Average: 26.4%
Downloads: 80.2%
Maintainers (1)
Last synced: 6 months ago
conda-forge.org: pycoal

pycoal is a Python library for processing hyperspectral imagery from remote sensing devices such as the Airborne Visible/InfraRed Imaging Spectrometer (AVIRIS) and AVIRIS-Next Generation enabling scientific analysis of Coal and Open-pit surface mining impacts on American Lands (COAL).

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 34.0%
Forks count: 39.0%
Average: 42.3%
Stargazers count: 44.9%
Dependent packages count: 51.2%
Last synced: 6 months ago

Dependencies

docs/source/requirements.txt pypi
  • guzzle_sphinx_theme *