Sympy Plotting Backends

Coverage

This module contains a few plotting backends that can be used with SymPy and Numpy. A backend represents the plotting library: it provides the necessary functionalities to quickly and easily plot the most common types of symbolic expressions (line plots, surface plots, parametric plots, vector plots, complex plots).

The following plotting libraries are supported: Matplolib, Plotly, Bokeh, K3D-Jupyter, Mayavi.

What's new in comparison to SymPy

On top of the usual plotting functions exposed by SymPy (plot, plot_parametric, plot3d, etc.), this module offers the capabily to:

use a different backend.
visualize discontinuities on 2D line plots.
plot_piecewise to visualize 2D line plots of piecewise functions with their discontinuities.
plot_vector to quickly visualize 2D/3D vector fields with quivers or streamlines.
plot_real_imag, plot_complex, plot_complex_list, plot_complex_vector to visualize complex functions.
plot_polar function.
plot_geometry to quickly visualize entities from the sympy.geometry module.
iplot function to create parametric-interactive plots using widgets (sliders, buttons, etc.).
plotgrid function, which replaces the PlotGrid class: it allows to combine multiple plots into a grid-like layout. It works with Matplotlib, Bokeh and Plotly.

Please, read the following documentation page to understand the differences between this module and sympy.plotting.

If you feel like some feature could be implemented, open an issue or create a PR.

Explore the Capabilities

To explore the capabilities before the installation, you can:

Read the documentation, download this repository and follow the tutorials inside the tutorials folder.
Click the following button to run the tutorials with Binder (note that Binder is slow to load the module and execute the commands).

Installation

SymPy Plotting Backends can be installed with pip or conda. By default, only basic plotting with Matplotlib will be installed:

pip install sympy_plot_backends

conda install -c davide_sd sympy_plot_backends

To install the complete requirements in order to get interactive plots, bokeh, plotly, k3d, vtk, execute the following command:

pip install sympy_plot_backends[all]

Or:

conda install -c anaconda scipy notebook
conda install -c conda-forge ipympl panel k3d msgpack-python
conda install -c bokeh ipywidgets_bokeh colorcet
conda install -c plotly plotly
conda install -c conda-forge vtk

Finally, if you are using zshell, the above pip command is going to fail. Use the following instead:

pip install "sympy_plot_backends[all]"

Warnings

Some backend comes with a memory cost. Since they require external libraries and/or open a server-process in order to visualize the data, memory usage can quickly rise if we are showing many plots. Keep an eye on you system monitor and act accordingly (close the kernels, restart the browser, etc.).

Metadata

Release files for sympy-plot-backends 1.6.7

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sympy-plot-backends 1.6.7
File	Size	Uploaded
sympy_plot_backends-1.6.7.tar.gz	225.8 kB	Feb 27, 2023	Details

Built distribution (wheel)

Table of built distributions (wheels) for sympy-plot-backends 1.6.7
File	Interpreter	ABI	Platform	Reset
sympy_plot_backends-1.6.7-py3-none-any.whl 166.4 kB Feb 27, 2023	Python 3	none	any	Details

Total release size: 392.2 kB

Release files / sympy_plot_backends-1.6.7.tar.gz

Download URL	sympy_plot_backends-1.6.7.tar.gz
Size	225.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`b72fde0b328cb725202590ed6eb05e8159ce823b4eefee444b375d0c35c43192`
BLAKE2b-256 checksum How to use checksums	`94fe23ba001e441744b35451ecb0ff5fc96c55a46f00f6364448d910005ecf0c`
Upload date	Feb 27, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.9.16`

Release files / sympy_plot_backends-1.6.7-py3-none-any.whl

Download URL	sympy_plot_backends-1.6.7-py3-none-any.whl
Size	166.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`a0a129dde9432b82d0e06a0a2b3a2017b6e888ff5c86933028da94d172a34fdb`
BLAKE2b-256 checksum How to use checksums	`6536eb90770e45e22b4a2a48ce97a2c0ea4e00139a489b1bef821c6f29ccbb35`
Upload date	Feb 27, 2023
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.2 CPython/3.9.16`