mpl_plotter VS pytransform3d

Compare mpl_plotter vs pytransform3d and see what are their differences.

mpl_plotter

Publication-quality data representation library based on Matplotlib. (by alopezrivera)
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mpl_plotter pytransform3d
3 2
167 580
- 1.7%
0.0 8.7
over 1 year ago 3 months ago
Python Python
GNU General Public License v3.0 only GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

mpl_plotter

Posts with mentions or reviews of mpl_plotter. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-14.

pytransform3d

Posts with mentions or reviews of pytransform3d. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing mpl_plotter and pytransform3d you can also consider the following projects:

VisPy - Main repository for Vispy

meshio - :spider_web: input/output for many mesh formats

TinyBaker - Composable, first-order file-to-file transformations in Python

itermplot - An awesome iTerm2 backend for Matplotlib, so you can plot directly in your terminal.

primify - Embed any image into a prime number.

ndim - :books: Compute multidimensional volumes and monomial integrals.

netgraph - Publication-quality network visualisations in python

Nashpy - A python library for 2 player games.

difw - Expressive diffeomorphic transformations based on the closed-form integration of continuous piecewise affine velocity functions.

yellowbrick - Visual analysis and diagnostic tools to facilitate machine learning model selection.