Skip to main content

A python version of IDL tplot libraries

Project description

build DOI

Full Documentation here: https://pytplot.readthedocs.io/en/latest/

Pytplot is a python package which aims to mimic the functionality of the IDL "tplot" libraries.

These plots have several user interaction tools built in, such as zooming and panning. The can be exported as standalone HTML files (to retain their interactivity) or as static PNG files.

Pytplot can be used in python scripts, or interactively through IPython and the Jupyter notebook.

Quick Start

Install Python

You will need the Anaconda distribution of Python 3 in order to run pytplot.

Anaconda <https://www.continuum.io/downloads/>_ comes with a suite of packages that are useful for data science.

Install pytplot

Open up a terminal, and type::

pip install pytplot

This will install pytplot and all of it's dependencies.

You will also need to install nodejs. This can be done through Anaconda with the following command::

conda install -c bokeh nodejs

Running Pytplot

To start using pytplot in a similar manner to IDL tplot, start up an interactive environment through the terminal command::

ipython 

or, if you prefer the jupyter interactive notebook::

jupyter notebook

then, just import the package by typing the command::

import pytplot

A demo/tutorial can be found here: docs/pytplot_tutorial.html <http://htmlpreview.github.com/?https://github.com/MAVENSDC/PyTplot/blob/master/docs/pytplot_tutorial.html>_.

A full description of each function can be found in docs/build/index.html <http://htmlpreview.github.com/?https://github.com/MAVENSDC/PyTplot/blob/master/docs/build/index.html>_.

Alternatively, the PDF version is located in docs/build/PyTplot.pdf <https://github.com/MAVENSDC/PyTplot/blob/master/docs/build/PyTplot.pdf>_.

Contact

If you have any suggestions or notice any problems, don't hesitate to contact Bryan Harter: harter@lasp.colorado.edu

Copyright 2019 Regents of the University of Colorado. All Rights Reserved. Released under the MIT license. This software was developed at the University of Colorado's Laboratory for Atmospheric and Space Physics. Verify current version before use at: https://github.com/MAVENSDC/PyTplot

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytplot-mpl-temp-2.1.29.tar.gz (1.7 MB view details)

Uploaded Source

Built Distribution

pytplot_mpl_temp-2.1.29-py3-none-any.whl (1.8 MB view details)

Uploaded Python 3

File details

Details for the file pytplot-mpl-temp-2.1.29.tar.gz.

File metadata

  • Download URL: pytplot-mpl-temp-2.1.29.tar.gz
  • Upload date:
  • Size: 1.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.10.1

File hashes

Hashes for pytplot-mpl-temp-2.1.29.tar.gz
Algorithm Hash digest
SHA256 1b7a60c51a97e4a83b40338c8e7d8be251cce7cb133ed3bf5ee3217d990c9b9d
MD5 155615dea2c1ae41fe4d8ba8a6bed28b
BLAKE2b-256 fd4bcef954cecffaac60ffcc3602c537e25615410be9b9634d9f7860d6808a29

See more details on using hashes here.

File details

Details for the file pytplot_mpl_temp-2.1.29-py3-none-any.whl.

File metadata

File hashes

Hashes for pytplot_mpl_temp-2.1.29-py3-none-any.whl
Algorithm Hash digest
SHA256 757559e6d42c50d7888f1313d2f4c19a07d164179adb2548aabef63d8ab5aa28
MD5 186a361a6ca7db83f2898fa361e2767f
BLAKE2b-256 7d330bd85419deec476962e4a54b39433af25bd0012a36d84760ed3aec2265a3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page