When visualizing data, one always has to choose:
Either create the plot with an intuitive graphical user interface (GUI) (e.g. panoply) but less options for customization and difficult to script
or create the plot from the command line, e.g. via NCL, R or python with more possibilities for customization and scripting but also less intuitive
psyplot wants to combine these two worlds: create a well-documented and
easy accessible framework to visualize data from a GUI and the command line
(and of course through a script).
There exists nothing like that. Of course you can also work with software like Paraview via the built-in python shell. But, if you really want to explore your data it is totally not straightforward to access and explore it from within such a software using numeric functions from numpy, scipy, etc.
Therefore I developed this modular framework that can create and customize plots efficiently with short and comprehensive commands, that can be accessed through a GUI (see Subprojects) and where you have always a comprehensive API to access your data.
Different from the usual use with matplotlib, which in the end results most of the time in copy-pasting parts of your code, this software is build on the don’t repeat yourself principle. Each of the small parts that make up a visualization, whether it is part of the data evaluation or of the appearance of the plot, psyplot puts it into a formatoption can be reused when it is needed.
Nevertheless, it’s again a new piece of software. Therefore, if you want to use it, for sure you need a bit of time to get comfortable with the framework. I promise to you, it’s worth it. So get started and please let me know if you have a different opinion.
What it is, and what it is not
First of all, it’s open source! So please, if you don’t agree with the points below, edit this document and click on Propose File Change and Create pull request. We can then discuss your changes.
There are tons of software tools around for visualization, so what is special about psyplot? The following list should hopefully provide you some guidance.
What it is
It is fast. Not necessarily when it comes down to being the fastest interactive visualization software, but for sure when it comes down to development time, as it is very user-friendly from the command line. There are no other software packages that provide a simple and intuitive visualization such as
while still providing a very high range of flexible options to adjust the visualization. No GUI, independent of it’s intuitiveness, can ever beat the speed of a scientist that knows a bit of coding and how to use the different formatoptions in psyplot.
it automatically decodes CF-conventions
it intuitively integrates the structure of netCDF files. So if you often work with netCDF files, psyplot might be a good option
it is pythonic. If you are using python anyway, psyplot is worth a try and we are always keen to help new users getting started.
it is very flexible (I think we made this point already), from command-line and GUI.
We can implement tons of new visualization and data analysis techniques and you can implement your own.
they are automatically implemented in the GUI
the user can do his statistical and numerical computations with software like xarray, numpy, scipy, etc. and then use the psyplot visualization methods in the same script
its modular framework allows to tackle new scientific questions and handle them in separate psyplot plugins with it’s own formatoptions and plotting methods
it will always be free and open-source under the LGPL License.
What it is not
No software can do everything, neither can psyplot. Our main focus on flexibility, easy command-line usage and the GUI integration inevitably comes with a few downsides.
it is not the fastest, because we use matplotlib to be flexible in our visualization, and this runs on the CPU, rather than the GPU. But if matplotlib or the standard visualization utilities from R, NCL, etc. are sufficient for you, you can go with psyplot.
it is not the best for interactive web-applications. Although it would be pretty simple to set up a backend server with psyplot and tornado or Flask, for instance, it’s limited to sending rastered image data around, due to the options provided by matplotlib.
it is not as fast as ncview. psyplot (and psy-view in particular) are written in the dynamically interpreted python language (which allows the combination of GUI and command-line, and the high flexibility). But we will never beat the speed of the (compiled but less flexible) ncview software.
our GUI is not the most interactive one. psyplot is a command-line-first software, i.e. we put the most effort in making the usage from command-line and scripts as easy as possible. The GUI is something on top and is limited by the speed and functionalities of matplotlib (which is, nevertheless, pretty rich). But we are constantly improving the GUI, see psy-view for instance.
it is not made for statistical visualizations. We will never beat the possibilities by packages like seaborn or R. The only advantage of psy-reg over these other software tools, is the possibility to adapt everything using the full power of matplotlib artists within and outside of the psyplot framework
it is not the best software for manipulating shapefiles, although some support of this might come in the future.
Copyright © 2021 Helmholtz-Zentrum Hereon, 2020-2021 Helmholtz-Zentrum Geesthacht, 2016-2021 University of Lausanne
psyplot is released under the GNU LGPL-3.O license. See COPYING and COPYING.LESSER in the root of the repository for full licensing details.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Lesser General Public License version 3.0 as published by the Free Software Foundation.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU LGPL-3.0 license for more details.
You should have received a copy of the GNU LGPL-3.0 license along with this program. If not, see https://www.gnu.org/licenses/.