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Matplotlib Jupyter Integration
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matplotlib/ipympl
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Leveraging the Jupyter interactive widgets framework,ipympl
enables the interactive features of matplotlib in the Jupyter notebook and in JupyterLab.
Besides, the figurecanvas
element is a proper Jupyter interactive widget which can be positioned in interactive widget layouts.
To enable theipympl
backend, simply use thematplotlib
Jupytermagic:
%matplotlib ipympl
See the documentation at:https://matplotlib.org/ipympl/
See theexample notebook for more!
conda install -c conda-forge ipympl
pip install ipympl
If you want to use ipympl in JupyterLab, we recommend using JupyterLab >= 3.
If you use JupyterLab 2, you still need to install the labextension manually:
conda install -c conda-forge nodejsjupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib
If you are using JupyterLab 1 or 2, you will need to install the rightjupyter-matplotlib
version, according to theipympl
andjupyterlab
versions you installed.For example, if you installed ipympl0.5.1
, you need to install jupyter-matplotlib0.7.0
, and this version is only compatible with JupyterLab1
.
conda install -c conda-forge ipympl==0.5.1jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib@0.7.0
Versions lookup table:
ipympl | jupyter-matplotlib | JupyterLab | Matplotlib |
---|---|---|---|
0.9.5-7 | 0.11.5-7 | >=2,<5 | >=3.5.0 |
0.9.3-4 | 0.11.3-4 | >=2,<5 | 3.4.0>= |
0.9.0-2 | 0.11.0-2 | >=2,<5 | 3.4.0>= <3.7 |
0.8.8 | 0.10.x | >=2,<5 | 3.3.1>= <3.7 |
0.8.0-7 | 0.10.x | >=2,<5 | 3.3.1>=, <3.6 |
0.7.0 | 0.9.0 | >=2,<5 | 3.3.1>= |
0.6.x | 0.8.x | >=2,<5 | 3.3.1>=, <3.4 |
0.5.8 | 0.7.4 | >=1,<3 | 3.3.1>=, <3.4 |
0.5.7 | 0.7.3 | >=1,<3 | 3.2.* |
... | ... | ... | |
0.5.3 | 0.7.2 | >=1,<3 | |
0.5.2 | 0.7.1 | >=1,<2 | |
0.5.1 | 0.7.0 | >=1,<2 | |
0.5.0 | 0.6.0 | >=1,<2 | |
0.4.0 | 0.5.0 | >=1,<2 | |
0.3.3 | 0.4.2 | >=1,<2 | |
0.3.2 | 0.4.1 | >=1,<2 | |
0.3.1 | 0.4.0 | >=0<2 |
Create a dev environment that has nodejs installed. The instructions here usemamba but youcan also use conda.
mamba env create --file dev-environment.ymlconda activate ipympl-dev
Install the Python Packge
pip install -e.
When developing your extensions, you need to manually enable your extensions with thenotebook / lab frontend. For lab, this is done by the command:
jupyter labextension develop --overwrite.jlpm build
For classic notebook, you need to run:
jupyter nbextension install --py --symlink --sys-prefix --overwrite ipympljupyter nbextensionenable --py --sys-prefix ipympl
Typescript:
If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the widget.
# Watch the source directory in one terminal, automatically rebuilding when neededjlpm watch# Run JupyterLab in another terminaljupyter lab
After a change wait for the build to finish and then refresh your browser and the changes should take effect.
Python:
If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
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