Skip to main content

A python version of IDL tplot libraries

Project description

image image

########## pytplot ##########

Pytplot is a python package which aims to mimic the functionality of the IDL "tplot" libraries. The primary routine (tplot) generates HTML files for the specified plots, and automatically opens the files in a Qt interface.

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.

How It Works

Data is read into pytplot by using the "store_data" command. Each dataset is assigned a unique name by the user.

The data is stored in a "tplot variable" class. The tplot variables contain all the information required to create a plot of the dataset. The details of the plot, such as axis titles, types, line colors, etc, can be changed through other functions in pytplot.

When you are ready to create a graph of your dataset(s), supply the dataset names you wish to plot to the "tplot" function, and a graph will be generated.

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 2018 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-1.3.4.tar.gz (1.7 MB view details)

Uploaded Source

File details

Details for the file pytplot-1.3.4.tar.gz.

File metadata

  • Download URL: pytplot-1.3.4.tar.gz
  • Upload date:
  • Size: 1.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.19.1 setuptools/40.2.0 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.7.0

File hashes

Hashes for pytplot-1.3.4.tar.gz
Algorithm Hash digest
SHA256 03837aaf193e6bef194befceeb7548bfb3917c3a79ddf5143dc2c802182f5bd9
MD5 4bd3f111190faac4cb9133c9182234a1
BLAKE2b-256 8b37b29fb2c7a5a21515c950bfbcb265eeb98f472e2c3daf8a6acb1a50dc622f

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