Coder Social home page Coder Social logo

pyglow's Introduction

Semaphore CI: Build Status

Travis CI: Build Status

(airglow viewed aboard the ISS)

Overview

pyglow is a Python module that wraps several upper atmosphere climatological models written in FORTRAN, such as the Horizontal Wind Model (HWM), the International Geomagnetic Reference Field (IGRF), the International Reference Ionosphere (IRI), and the Mass Spectrometer and Incoherent Scatter Radar (MSIS).

It includes the following upper atmospheric models:

  • HWM 1993
  • HWM 2007
  • HWM 2014
  • IGRF 11
  • IGRF 12
  • IRI 2012
  • IRI 2016
  • MSIS 2000

pyglow also provides access to the the following geophysical indices:

  • AP
  • Kp
  • F10.7
  • DST
  • AE

pyglow offers access to these models & indices in a convenient, high-level object-oriented interface within Python.

Prerequisites

pyglow requires the following packages for installation:

  1. gfortran ($ sudo apt-get install gfortran)
  2. f2py ($ pip install numpy --upgrade)
  3. Python packages listed in requirements.txt ($ pip install -r requirements.txt)

Installation

I'm Feeling Lucky:

First, checkout the repository:

$ git clone git://github.com/timduly4/pyglow.git pyglow

Change directories into the repository folder, compile the f2py bindings, then install the Python package:

$ cd pyglow/
$ make -C src/pyglow/models source
$ python3 setup.py install --user

Trouble in downloading model files:

If you have problems downloading files from the official websites, follow the next steps:

(1) Create the local http server:

$ cd static/
$ python3 -m http.server 8080

(2) Edit the file src/pyglow/models/Makefile, replace the appropriate line with the following code:

download:
  python get_models_offline.py

(3) Compile the f2py bindings, then install the Python package:

$ cd pyglow/
$ make -C src/pyglow/models source
$ python3 setup.py install --user

Note: The model files may not be latest.

Individual installation steps:

If you have troubles, follow the individual installation steps:

(1) Download the package:

$ git clone git://github.com/timduly4/pyglow.git
$ cd pyglow/

(2) Download the climatological models and wrap them with f2py:

$ cd ./src/pyglow/models/
$ make all
  • If successful, there should be a *.so file in each of the ./models/dl_models/<model>/ directories:

    $ find . -name "*.so"
    ./dl_models/hwm07/hwm07py.so
    ./dl_models/hwm93/hwm93py.so
    ./dl_models/hwm14/hwm14py.so
    ./dl_models/igrf11/igrf11py.so
    ./dl_models/igrf12/igrf12py.so
    ./dl_models/iri12/iri12py.so
    ./dl_models/iri16/iri16py.so
    ./dl_models/msis/msis00py.so
    

(3) Install the Python package

$ cd ../../../   # get back to root directory
$ python3 setup.py install --user
  • On a mac, the folder pyglow and *.so files from ./models/dl_models/<model>/ should be in /Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages
  • The --user flag installs the package locally (i.e., you do not need sudo access)

Unit tests

See unit tests in ./test. For example, run the unittest suite with:

$ python3 -m unittest test.test_suite_pyglow

(Be sure that the f2py modules have been compiled via $ make -C src/pyglow/models source, first.)

Examples

See example scripts located in ./examples for example calls to pyglow.

Docker

We've included a Dockerfile for pyglow. To build the image:

$ docker build -t pyglow .

This will compile and install pyglow within the Docker container.

Run the unit tests within the container via:

$ docker run pyglow

Hints

General

  1. Use tab completion in ipython to view the full set of member data and variables available in the Point class.
  • For example, in the test code, run pt.<TAB><TAB> and class information will be listed.

Updating geophysical indices with pyglow.update_indices()

You'll need to download the geophysical indices as they become available. The update_indices() function is available in pyglow that enables you do this:

# Grabs indices between 2016 and 2018:
$ python3 -c "import pyglow; pyglow.update_indices(2016, 2018)"

Note: you only need to run this function when you would like to update the indices.

You can check if you have geophysical indices between dates with:

$ python3 -c "import pyglow;  pyglow.check_stored_indices('2015-01-01', '2019-01-01')"

Checking: input date range:
  2015-01-01
  to
  2019-01-01
>> We have all of the geophysical indices files between these dates.

Uninstallation

The install directory for pyglow can be outputted via python3 -c "import pyglow; print(pyglow.__file__)". For example:

~ $ python3 -c "import pyglow; print(pyglow.__file__)"
/Users/duly/Library/Python/3.7/lib/python/site-packages/pyglow/__init__.pyc

This tells you the installation location, and then you can remove the package with:

~ $ rm -rf /Users/duly/Library/Python/3.7/lib/python/site-packages/pyglow

pyglow's People

Contributors

bharding512 avatar butala avatar fishnchips1624 avatar jklenzing avatar pmreyes2 avatar romanvaleryevich avatar timduly4 avatar ukamaci avatar zfb132 avatar

Stargazers

 avatar

Watchers

 avatar  avatar  avatar

Forkers

macicco

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.