From 938e9ba72f26fef4d06e7609f7855078b25f1743 Mon Sep 17 00:00:00 2001 From: Ian Hunt-Isaak Date: Thu, 24 Feb 2022 23:53:21 -0500 Subject: [PATCH 1/4] create docs page --- .gitignore | 3 + dev-environment.yml | 9 ++ docs/Makefile | 23 +++++ docs/_static/basic.apng | Bin 0 -> 172641 bytes docs/_static/custom.css | 12 +++ docs/conf.py | 185 ++++++++++++++++++++++++++++++++++++++++ docs/contributing.md | 92 ++++++++++++++++++++ docs/index.ipynb | 118 +++++++++++++++++++++++++ docs/installing.md | 66 ++++++++++++++ docs/make.bat | 35 ++++++++ setup.py | 11 +++ 11 files changed, 554 insertions(+) create mode 100644 docs/Makefile create mode 100644 docs/_static/basic.apng create mode 100644 docs/_static/custom.css create mode 100644 docs/conf.py create mode 100644 docs/contributing.md create mode 100644 docs/index.ipynb create mode 100644 docs/installing.md create mode 100644 docs/make.bat diff --git a/.gitignore b/.gitignore index 7e9a87e9..70907701 100644 --- a/.gitignore +++ b/.gitignore @@ -32,3 +32,6 @@ ipympl/labextension # OS specific items .DS_Store + +# sphinx build dir +docs/_build diff --git a/dev-environment.yml b/dev-environment.yml index df8e89e6..92b5725a 100644 --- a/dev-environment.yml +++ b/dev-environment.yml @@ -13,5 +13,14 @@ dependencies: - flake8 - pytest - nbval + - pre-commit - pip: - build + - myst-nb + - Sphinx >= 1.5 + - sphinx-copybutton + - sphinx-panels + - sphinx-thebe + - sphinx-togglebutton + - sphinx-book-theme + - sphinx-autobuild diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 00000000..6ff62d75 --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,23 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line, and also +# from the environment for the first two. +SPHINXOPTS ?= -T --color +SPHINXBUILD ?= sphinx-build +SOURCEDIR = . +BUILDDIR = _build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" 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" # doctest + +# Settings for linkcheck +linkcheck_anchors = False +linkcheck_ignore = [] # type: ignore + +execution_timeout = -1 +jupyter_execute_notebooks = "off" +if "EXECUTE_NB" in os.environ: + print("\033[93;1mWill run Jupyter notebooks!\033[0m") + jupyter_execute_notebooks = "force" + +# Settings for myst-parser +myst_enable_extensions = [ + "amsmath", + "colon_fence", + "dollarmath", + "smartquotes", + "substitution", +] +suppress_warnings = [ + "myst.header", +] + +# Add any paths that contain templates here, relative to this directory. +templates_path = ["_templates"] + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = [ + "**ipynb_checkpoints", + ".DS_Store", + "Thumbs.db", + "_build", +] + + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_copy_source = True # needed for download notebook button +html_css_files = [ + "custom.css", +] +html_sourcelink_suffix = "" +html_static_path = ["_static"] +html_theme = "sphinx_book_theme" +html_theme_options = { + "launch_buttons": { + "binderhub_url": "https://mybinder.org", + "colab_url": "https://colab.research.google.com", + "notebook_interface": "jupyterlab", + "thebe": True, + "thebelab": True, + }, + "path_to_docs": "docs", + "repository_branch": "main", + "repository_url": "https://github.com/matplotlib/ipympl", + "use_download_button": True, + "use_edit_page_button": True, + "use_issues_button": True, + "use_repository_button": True, +} +html_title = "ipympl" + +master_doc = "index" +thebe_config = { + "repository_url": html_theme_options["repository_url"], + "repository_branch": html_theme_options["repository_branch"], +} + + +# based on pandas/doc/source/conf.py +def linkcode_resolve(domain, info): + """ + Determine the URL corresponding to Python object + """ + if domain != "py": + return None + + modname = info["module"] + fullname = info["fullname"] + + submod = sys.modules.get(modname) + if submod is None: + return None + + obj = submod + for part in fullname.split("."): + try: + obj = getattr(obj, part) + except AttributeError: + return None + + try: + fn = inspect.getsourcefile(inspect.unwrap(obj)) + except TypeError: + fn = None + if not fn: + return None + + try: + source, lineno = inspect.getsourcelines(obj) + except OSError: + lineno = None + + if lineno: + linespec = f"#L{lineno}-L{lineno + len(source) - 1}" + else: + linespec = "" + + fn = os.path.relpath(fn, start=os.path.dirname("../ipympl")) + + return ( + f"https://github.com/matplotlib/ipympl/blob/main/ipympl/{fn}{linespec}" # noqa + ) diff --git a/docs/contributing.md b/docs/contributing.md new file mode 100644 index 00000000..c8be4e35 --- /dev/null +++ b/docs/contributing.md @@ -0,0 +1,92 @@ +# Contributing + +Thanks for thinking of a way to help improve this library! Remember that contributions come in all shapes and sizes beyond writing bug fixes. Contributing to [documentation](#documentation), opening new [issues](https://github.com/matplotlib/ipympl/issues) for bugs, asking for clarification on things you find unclear, and requesting new features, are all super valuable contributions. + +## Code Improvements + +All development for this library happens on GitHub [here](https://github.com/matplotlib/ipympl). We recommend you work with a [Conda](https://www.anaconda.com/products/individual) environment (or an alternative virtual environment like [`venv`](https://docs.python.org/3/library/venv.html)). + +The below instructions use [Mamba](https://github.com/mamba-org/mamba#the-fast-cross-platform-package-manager) which is a very fast implementation of `conda`. + +```bash +git clone +cd ipympl +mamba env create --file dev-environment.yml +conda activate ipympl-dev +pre-commit install +``` + +Install the Python Packge +```bash +pip install -e . +``` + +When developing your extensions, you need to manually enable your extensions with the +notebook / lab frontend. For lab, this is done by the command: + +```bash +jupyter labextension develop --overwrite . +yarn run build +``` + +For classic notebook, you need to run: +```bash +jupyter nbextension install --py --symlink --sys-prefix --overwrite ipympl +jupyter nbextension enable --py --sys-prefix ipympl +``` + + + +### How to see your changes + +**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. + +```bash +# Watch the source directory in one terminal, automatically rebuilding when needed +yarn run watch +# Run JupyterLab in another terminal +jupyter 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. + + +## Documentation + +Our documentation is built with [Sphinx](https://www.sphinx-doc.org) from the notebooks in the `docs` folder. It contains both Markdown files and Jupyter notebooks. + +Examples are best written as Jupyter notebooks. To write a new example, create in a notebook in the `docs/examples` directory and list its path under one of the [`toctree`s](https://www.sphinx-doc.org/en/master/usage/restructuredtext/directives.html#directive-toctree) in the `index.ipynb` file. When the docs are generated, they will be rendered as static html pages by [myst-nb](https://myst-nb.readthedocs.io). + +If you have installed all developer dependencies (see [above](#contributing)), you can rebuild the docs with the following `make` command run from inside the `docs` folder: + +``` +make html +``` + +Then you can open the `_build/index.html` file in your browser you should now be able to see the rendered documentation. + +Alternatively, you can use [sphinx-autobuild](https://github.com/executablebooks/sphinx-autobuild) to continuously watch source files for changes and rebuild the documentation for you. Sphinx-autobuild will be installed automatically in the dev environment you created earlier so all you need to do is run + +```bash +make watch +``` +from inside the `docs` folder + +In a few seconds your web browser should open up the documentation. Now whenever you save a file the documentation will automatically regenerate and the webpage will refresh for you! + +## Working with Git + +Using Git/GitHub can confusing (), so if you're new to Git, you may find it helpful to use a program like [GitHub Desktop](https://desktop.github.com) and to follow a [guide](https://github.com/firstcontributions/first-contributions#first-contributions). + +Also feel free to ask for help/advice on the relevant GitHub [issue](https://github.com/matplotlib/ipympl/issues). + + +## Getting Help contributing + +Feel free to ask questions about how to contribute on any Github Issue. You can also ask shorter questions on the [gitter chatroom](https://gitter.im/jupyter-widgets/Lobby). diff --git a/docs/index.ipynb b/docs/index.ipynb new file mode 100644 index 00000000..242e5546 --- /dev/null +++ b/docs/index.ipynb @@ -0,0 +1,118 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0bd21c1d-fda2-455d-b70d-e8b7ad0611f4", + "metadata": {}, + "source": [ + "# ipympl\n", + "\n", + "`ipympl` enables using the interactive features of matplotlib in Jupyter Notebooks, Jupyter Lab, Google Colab, VSCode notebooks, Google Colab\n", + "\n", + "Matplotlib requires a live Python kernel to have interactive plots so by default the outputs on this page will not be interactive. To try things out yourself you can either use [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/matplotlib/ipympl/stable?urlpath=retro/notebooks/examples/ipympl.ipynb) or make these docs interactive by clicking on the rocket icon in the top right of the page.\n", + "\n", + "\n", + "## Installation\n", + "The quickest way to install is either:\n", + "\n", + "```bash\n", + "pip install ipympl\n", + "```\n", + "or `conda install -c conda-forge ipympl`\n", + "\n", + "\n", + "For more detailed instructions see [Installing](installing.md).\n", + "\n", + "\n", + "## Basic Example\n", + "To activate the `ipympl` backend all you need to do is include the `%matplotlib ipympl` magic in the notebook. Alternatively you can use `%matplotlib widget` which will have have the same effect." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2d7b9433-94df-4742-970e-7d9dbb1f6785", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "%matplotlib ipympl\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "fig, ax = plt.subplots()\n", + "\n", + "\n", + "x = np.linspace(0, 2*np.pi, 100)\n", + "y = np.sin(3*x)\n", + "ax.plot(x, y)\n" + ] + }, + { + "cell_type": "markdown", + "id": "52696782-2ecb-4fac-9d90-d5c8f81dac10", + "metadata": {}, + "source": [ + "With a working Kernel that simple example will give a plot with interactivity enabled in the notebook!\n", + "![A plot of sine wave, the user pans and zooms with the mouse](_static/basic.apng)" + ] + }, + { + "cell_type": "markdown", + "id": "eb0bcca2-f967-46a3-a0aa-9503312acd85", + "metadata": {}, + "source": [ + "## Install\n", + "\n", + "```bash\n", + "pip install ipympl\n", + "```\n", + "\n", + "\n", + "\n", + "```{toctree}\n", + ":maxdepth: 2\n", + "\n", + "installing.md\n", + "contributing.md\n", + "```\n", + "\n", + "```{toctree}\n", + ":caption: Examples\n", + ":maxdepth: 1\n", + "\n", + "examples/basic-example.ipynb\n", + "```\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.6" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/docs/installing.md b/docs/installing.md new file mode 100644 index 00000000..c02b5b45 --- /dev/null +++ b/docs/installing.md @@ -0,0 +1,66 @@ +# Installing + +In most cases all you need to do is +```bash +pip install ipympl +``` +or alternatively with `mamba`/`conda` + +```bash +mamba install -c conda-forge ipympl +``` + +and then restart Jupyter. + + +### Jupyterlab < 3 +If you use JupyterLab 2, you still need to install the labextension manually: + +```bash +conda install -c conda-forge nodejs +jupyter labextension install @jupyter-widgets/jupyterlab-manager jupyter-matplotlib +``` + + + + +### Google Colab + +To use `ipympl` in colab run these lines: + +```python +from google.colab import output +output.enable_custom_widget_manager() +``` + +## Mixing Frontend and Backend Versions + +`ipympl` provides both a Frontend (in javascript) which handles displaying the plots and handling interaction events, as well as a backend (in Python) that renders the plots and interfaces with user code. These two parts need to be able to communicate with each other for everything to work. In the most common situation that your frontend and backend are from the same Python environment then installing `ipympl` should have given you compatible versions. + +However, there are situations when you may have different versions of ipympl in the frontend and the backend. In this case you need to ensure that you have compatible versions of the frontend and backend. For details and an initial compatibility table see the discussion on this [Github issue](https://github.com/matplotlib/ipympl/issues/416). + + +## Compatibility Table + +Not all versions of `ipympl` are compatible with different version of Jupyterlab or all versions of Matplotlib. The below table provides a reference for which versions are compatible. + +| `ipympl` | `jupyter-matplotlib` | `JupyterLab` | `Matplotlib` | +|----------|----------------------|--------------|--------------| +| 0.8.8 | 0.10.x | 3 or 2 | 3.3.1>= | +| 0.8.0-7 | 0.10.x | 3 or 2 | 3.3.1>=, <3.6| +| 0.7.0 | 0.9.0 | 3 or 2 | 3.3.1>= | +| 0.6.x | 0.8.x | 3 or 2 | 3.3.1>=, <3.4| +| 0.5.8 | 0.7.4 | 1 or 2 | 3.3.1>=, <3.4| +| 0.5.7 | 0.7.3 | 1 or 2 | 3.2.* | +| ... | ... | ... | | +| 0.5.3 | 0.7.2 | 1 or 2 | | +| 0.5.2 | 0.7.1 | 1 | | +| 0.5.1 | 0.7.0 | 1 | | +| 0.5.0 | 0.6.0 | 1 | | +| 0.4.0 | 0.5.0 | 1 | | +| 0.3.3 | 0.4.2 | 1 | | +| 0.3.2 | 0.4.1 | 1 | | +| 0.3.1 | 0.4.0 | 0 or 1 | | diff --git a/docs/make.bat b/docs/make.bat new file mode 100644 index 00000000..922152e9 --- /dev/null +++ b/docs/make.bat @@ -0,0 +1,35 @@ +@ECHO OFF + +pushd %~dp0 + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set SOURCEDIR=. +set BUILDDIR=_build + +if "%1" == "" goto help + +%SPHINXBUILD% >NUL 2>NUL +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. Make sure you have Sphinx + echo.installed, then set the SPHINXBUILD environment variable to point + echo.to the full path of the 'sphinx-build' executable. Alternatively you + echo.may add the Sphinx directory to PATH. + echo. + echo.If you don't have Sphinx installed, grab it from + echo.http://sphinx-doc.org/ + exit /b 1 +) + +%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% +goto end + +:help +%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% + +:end +popd diff --git a/setup.py b/setup.py index 5360058a..76f6257b 100644 --- a/setup.py +++ b/setup.py @@ -66,6 +66,17 @@ 'ipywidgets>=7.6.0,<8', 'matplotlib>=2.0.0,<4', ], + extra_requires={ + "docs": [ + "myst-nb", + "Sphinx >= 1.5", + "sphinx-copybutton", + "sphinx-panels", + "sphinx-thebe", + "sphinx-togglebutton", + "sphinx-book-theme", + ] + }, packages=find_packages(), zip_safe=False, cmdclass=cmdclass, From 8158df049bce6c19773393e5a4ea3209d766f8e3 Mon Sep 17 00:00:00 2001 From: Ian Hunt-Isaak Date: Thu, 24 Feb 2022 23:57:00 -0500 Subject: [PATCH 2/4] move examples under docs --- README.md | 4 +- docs/examples/full-example.ipynb | 477 +++++++++++++++ docs/index.ipynb | 2 +- examples/ipympl.ipynb | 980 ------------------------------- pyproject.toml | 2 +- 5 files changed, 481 insertions(+), 984 deletions(-) create mode 100644 docs/examples/full-example.ipynb delete mode 100644 examples/ipympl.ipynb diff --git a/README.md b/README.md index cd5ddf92..a20f3dff 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ [![Latest PyPI version](https://img.shields.io/pypi/v/ipympl?logo=pypi)](https://pypi.python.org/pypi/ipympl) [![Latest conda-forge version](https://img.shields.io/conda/vn/conda-forge/ipympl?logo=conda-forge)](https://anaconda.org/conda-forge/ipympl) [![Latest npm version](https://img.shields.io/npm/v/jupyter-matplotlib?logo=npm)](https://www.npmjs.com/package/jupyter-matplotlib) -[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/matplotlib/ipympl/stable?urlpath=retro/notebooks/examples/ipympl.ipynb) +[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/matplotlib/ipympl/stable?urlpath=retro/notebooks/docs/examples/full-example.ipynb) [![Gitter](https://img.shields.io/badge/gitter-Join_chat-blue?logo=gitter)](https://gitter.im/jupyter-widgets/Lobby) Leveraging the Jupyter interactive widgets framework, `ipympl` enables the interactive features of matplotlib in the Jupyter notebook and in JupyterLab. @@ -21,7 +21,7 @@ magic: ``` ## Example -See the [example notebook](https://github.com/matplotlib/ipympl/blob/master/examples/ipympl.ipynb) for more! +See the [example notebook](https://github.com/matplotlib/ipympl/blob/master/docs/examples/ipympl.ipynb) for more! ![matplotlib screencast](matplotlib.gif) diff --git a/docs/examples/full-example.ipynb b/docs/examples/full-example.ipynb new file mode 100644 index 00000000..d036785c --- /dev/null +++ b/docs/examples/full-example.ipynb @@ -0,0 +1,477 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Comprehensive Example" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Enabling the `widget` backend.\n", + "# This requires jupyter-matplotlib a.k.a. ipympl.\n", + "# ipympl can be install via pip or conda.\n", + "%matplotlib widget\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Testing matplotlib interactions with a simple plot\n", + "fig = plt.figure()\n", + "plt.plot(np.sin(np.linspace(0, 20, 100)));" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Always hide the toolbar\n", + "fig.canvas.toolbar_visible = False" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Put it back to its default\n", + "fig.canvas.toolbar_visible = 'fade-in-fade-out'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Change the toolbar position\n", + "fig.canvas.toolbar_position = 'top'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Hide the Figure name at the top of the figure\n", + "fig.canvas.header_visible = False" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Hide the footer\n", + "fig.canvas.footer_visible = False" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Disable the resizing feature\n", + "fig.canvas.resizable = False" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# If true then scrolling while the mouse is over the canvas will not move the entire notebook\n", + "fig.canvas.capture_scroll = True" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "You can also call `display` on `fig.canvas` to display the interactive plot anywhere in the notebooke" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig.canvas.toolbar_visible = True\n", + "display(fig.canvas)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Or you can `display(fig)` to embed the current plot as a png" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "display(fig)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 3D plotting" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from mpl_toolkits.mplot3d import axes3d\n", + "\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "\n", + "# Grab some test data.\n", + "X, Y, Z = axes3d.get_test_data(0.05)\n", + "\n", + "# Plot a basic wireframe.\n", + "ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Subplots" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# A more complex example from the matplotlib gallery\n", + "np.random.seed(0)\n", + "\n", + "n_bins = 10\n", + "x = np.random.randn(1000, 3)\n", + "\n", + "fig, axes = plt.subplots(nrows=2, ncols=2)\n", + "ax0, ax1, ax2, ax3 = axes.flatten()\n", + "\n", + "colors = ['red', 'tan', 'lime']\n", + "ax0.hist(x, n_bins, density=1, histtype='bar', color=colors, label=colors)\n", + "ax0.legend(prop={'size': 10})\n", + "ax0.set_title('bars with legend')\n", + "\n", + "ax1.hist(x, n_bins, density=1, histtype='bar', stacked=True)\n", + "ax1.set_title('stacked bar')\n", + "\n", + "ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)\n", + "ax2.set_title('stack step (unfilled)')\n", + "\n", + "# Make a multiple-histogram of data-sets with different length.\n", + "x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]\n", + "ax3.hist(x_multi, n_bins, histtype='bar')\n", + "ax3.set_title('different sample sizes')\n", + "\n", + "fig.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig.canvas.toolbar_position = 'right'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fig.canvas.toolbar_visible = False" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Interactions with other widgets and layouting\n", + "\n", + "When you want to embed the figure into a layout of other widgets you should call `plt.ioff()` before creating the figure otherwise `plt.figure()` will trigger a display of the canvas automatically and outside of your layout. " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Without using `ioff`\n", + "\n", + "Here we will end up with the figure being displayed twice. The button won't do anything it just placed as an example of layouting." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import ipywidgets as widgets\n", + "\n", + "# ensure we are interactive mode \n", + "# this is default but if this notebook is executed out of order it may have been turned off\n", + "plt.ion()\n", + "\n", + "fig = plt.figure()\n", + "ax = fig.gca()\n", + "ax.imshow(Z)\n", + "\n", + "widgets.AppLayout(\n", + " center=fig.canvas,\n", + " footer=widgets.Button(icon='check'),\n", + " pane_heights=[0, 6, 1]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Fixing the double display with `ioff`\n", + "\n", + "If we make sure interactive mode is off when we create the figure then the figure will only display where we want it to.\n", + "\n", + "There is ongoing work to allow usage of `ioff` as a context manager, see the [ipympl issue](https://github.com/matplotlib/ipympl/issues/220) and the [matplotlib issue](https://github.com/matplotlib/matplotlib/issues/17013)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.ioff()\n", + "fig = plt.figure()\n", + "plt.ion()\n", + "\n", + "ax = fig.gca()\n", + "ax.imshow(Z)\n", + "\n", + "widgets.AppLayout(\n", + " center=fig.canvas,\n", + " footer=widgets.Button(icon='check'),\n", + " pane_heights=[0, 6, 1]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Interacting with other widgets\n", + "\n", + "## Changing a line plot with a slide" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# When using the `widget` backend from ipympl,\n", + "# fig.canvas is a proper Jupyter interactive widget, which can be embedded in\n", + "# an ipywidgets layout. See https://ipywidgets.readthedocs.io/en/stable/examples/Layout%20Templates.html\n", + "\n", + "# One can bound figure attributes to other widget values.\n", + "from ipywidgets import AppLayout, FloatSlider\n", + "\n", + "plt.ioff()\n", + "\n", + "slider = FloatSlider(\n", + " orientation='horizontal',\n", + " description='Factor:',\n", + " value=1.0,\n", + " min=0.02,\n", + " max=2.0\n", + ")\n", + "\n", + "slider.layout.margin = '0px 30% 0px 30%'\n", + "slider.layout.width = '40%'\n", + "\n", + "fig = plt.figure()\n", + "fig.canvas.header_visible = False\n", + "fig.canvas.layout.min_height = '400px'\n", + "plt.title('Plotting: y=sin({} * x)'.format(slider.value))\n", + "\n", + "x = np.linspace(0, 20, 500)\n", + "\n", + "lines = plt.plot(x, np.sin(slider.value * x))\n", + "\n", + "def update_lines(change):\n", + " plt.title('Plotting: y=sin({} * x)'.format(change.new))\n", + " lines[0].set_data(x, np.sin(change.new * x))\n", + " fig.canvas.draw()\n", + " fig.canvas.flush_events()\n", + "\n", + "slider.observe(update_lines, names='value')\n", + "\n", + "AppLayout(\n", + " center=fig.canvas,\n", + " footer=slider,\n", + " pane_heights=[0, 6, 1]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Update image data in a performant manner\n", + "\n", + "Two useful tricks to improve performance when updating an image displayed with matplolib are to:\n", + "1. Use the `set_data` method instead of calling imshow\n", + "2. Precompute and then index the array" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# precomputing all images\n", + "x = np.linspace(0,np.pi,200)\n", + "y = np.linspace(0,10,200)\n", + "X,Y = np.meshgrid(x,y)\n", + "parameter = np.linspace(-5,5)\n", + "example_image_stack = np.sin(X)[None,:,:]+np.exp(np.cos(Y[None,:,:]*parameter[:,None,None]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.ioff()\n", + "fig = plt.figure()\n", + "plt.ion()\n", + "im = plt.imshow(example_image_stack[0])\n", + "\n", + "def update(change):\n", + " im.set_data(example_image_stack[change['new']])\n", + " fig.canvas.draw_idle()\n", + " \n", + " \n", + "slider = widgets.IntSlider(value=0, min=0, max=len(parameter)-1)\n", + "slider.observe(update, names='value')\n", + "widgets.VBox([slider, fig.canvas])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Debugging widget updates and matplotlib callbacks\n", + "\n", + "If an error is raised in the `update` function then will not always display in the notebook which can make debugging difficult. This same issue is also true for matplotlib callbacks on user events such as mousemovement, for example see [issue](https://github.com/matplotlib/ipympl/issues/116). There are two ways to see the output:\n", + "1. In jupyterlab the output will show up in the Log Console (View > Show Log Console)\n", + "2. using `ipywidgets.Output`\n", + "\n", + "Here is an example of using an `Output` to capture errors in the update function from the previous example. To induce errors we changed the slider limits so that out of bounds errors will occur:\n", + "\n", + "From: `slider = widgets.IntSlider(value=0, min=0, max=len(parameter)-1)`\n", + "\n", + "To: `slider = widgets.IntSlider(value=0, min=0, max=len(parameter)+10)`\n", + "\n", + "If you move the slider all the way to the right you should see errors from the Output widget" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.ioff()\n", + "fig = plt.figure()\n", + "plt.ion()\n", + "im = plt.imshow(example_image_stack[0])\n", + "\n", + "out = widgets.Output()\n", + "@out.capture()\n", + "def update(change):\n", + " with out:\n", + " if change['name'] == 'value':\n", + " im.set_data(example_image_stack[change['new']])\n", + " fig.canvas.draw_idle\n", + " \n", + " \n", + "slider = widgets.IntSlider(value=0, min=0, max=len(parameter)+10)\n", + "slider.observe(update)\n", + "display(widgets.VBox([slider, fig.canvas]))\n", + "display(out)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.6" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": {}, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/docs/index.ipynb b/docs/index.ipynb index 242e5546..31e273e5 100644 --- a/docs/index.ipynb +++ b/docs/index.ipynb @@ -82,7 +82,7 @@ ":caption: Examples\n", ":maxdepth: 1\n", "\n", - "examples/basic-example.ipynb\n", + "examples/full-example.ipynb\n", "```\n" ] } diff --git a/examples/ipympl.ipynb b/examples/ipympl.ipynb deleted file mode 100644 index 7fb5fcea..00000000 --- a/examples/ipympl.ipynb +++ /dev/null @@ -1,980 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# The Matplotlib Jupyter Widget Backend\n", - "\n", - "Enabling interaction with matplotlib charts in the Jupyter notebook and JupyterLab\n", - "\n", - "https://github.com/matplotlib/ipympl" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Enabling the `widget` backend.\n", - "# This requires jupyter-matplotlib a.k.a. ipympl.\n", - "# ipympl can be install via pip or conda.\n", - "%matplotlib widget\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Testing matplotlib interactions with a simple plot\n", - "fig = plt.figure()\n", - "plt.plot(np.sin(np.linspace(0, 20, 100)));" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Always hide the toolbar\n", - "fig.canvas.toolbar_visible = False" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Put it back to its default\n", - "fig.canvas.toolbar_visible = 'fade-in-fade-out'" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Change the toolbar position\n", - "fig.canvas.toolbar_position = 'top'" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Hide the Figure name at the top of the figure\n", - "fig.canvas.header_visible = False" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Hide the footer\n", - "fig.canvas.footer_visible = False" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# Disable the resizing feature\n", - "fig.canvas.resizable = False" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# If true then scrolling while the mouse is over the canvas will not move the entire notebook\n", - "fig.canvas.capture_scroll = True" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "You can also call `display` on `fig.canvas` to display the interactive plot anywhere in the notebooke" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "fig.canvas.toolbar_visible = True\n", - "display(fig.canvas)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Or you can `display(fig)` to embed the current plot as a png" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "display(fig)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# 3D plotting" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "from mpl_toolkits.mplot3d import axes3d\n", - "\n", - "fig = plt.figure()\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "\n", - "# Grab some test data.\n", - "X, Y, Z = axes3d.get_test_data(0.05)\n", - "\n", - "# Plot a basic wireframe.\n", - "ax.plot_wireframe(X, Y, Z, rstride=10, cstride=10)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Subplots" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# A more complex example from the matplotlib gallery\n", - "np.random.seed(0)\n", - "\n", - "n_bins = 10\n", - "x = np.random.randn(1000, 3)\n", - "\n", - "fig, axes = plt.subplots(nrows=2, ncols=2)\n", - "ax0, ax1, ax2, ax3 = axes.flatten()\n", - "\n", - "colors = ['red', 'tan', 'lime']\n", - "ax0.hist(x, n_bins, density=1, histtype='bar', color=colors, label=colors)\n", - "ax0.legend(prop={'size': 10})\n", - "ax0.set_title('bars with legend')\n", - "\n", - "ax1.hist(x, n_bins, density=1, histtype='bar', stacked=True)\n", - "ax1.set_title('stacked bar')\n", - "\n", - "ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)\n", - "ax2.set_title('stack step (unfilled)')\n", - "\n", - "# Make a multiple-histogram of data-sets with different length.\n", - "x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]\n", - "ax3.hist(x_multi, n_bins, histtype='bar')\n", - "ax3.set_title('different sample sizes')\n", - "\n", - "fig.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "fig.canvas.toolbar_position = 'right'" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "fig.canvas.toolbar_visible = False" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Interactions with other widgets and layouting\n", - "\n", - "When you want to embed the figure into a layout of other widgets you should call `plt.ioff()` before creating the figure otherwise `plt.figure()` will trigger a display of the canvas automatically and outside of your layout. " - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Without using `ioff`\n", - "\n", - "Here we will end up with the figure being displayed twice. The button won't do anything it just placed as an example of layouting." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import ipywidgets as widgets\n", - "\n", - "# ensure we are interactive mode \n", - "# this is default but if this notebook is executed out of order it may have been turned off\n", - "plt.ion()\n", - "\n", - "fig = plt.figure()\n", - "ax = fig.gca()\n", - "ax.imshow(Z)\n", - "\n", - "widgets.AppLayout(\n", - " center=fig.canvas,\n", - " footer=widgets.Button(icon='check'),\n", - " pane_heights=[0, 6, 1]\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Fixing the double display with `ioff`\n", - "\n", - "If we make sure interactive mode is off when we create the figure then the figure will only display where we want it to.\n", - "\n", - "There is ongoing work to allow usage of `ioff` as a context manager, see the [ipympl issue](https://github.com/matplotlib/ipympl/issues/220) and the [matplotlib issue](https://github.com/matplotlib/matplotlib/issues/17013)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.ioff()\n", - "fig = plt.figure()\n", - "plt.ion()\n", - "\n", - "ax = fig.gca()\n", - "ax.imshow(Z)\n", - "\n", - "widgets.AppLayout(\n", - " center=fig.canvas,\n", - " footer=widgets.Button(icon='check'),\n", - " pane_heights=[0, 6, 1]\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Interacting with other widgets\n", - "\n", - "## Changing a line plot with a slide" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# When using the `widget` backend from ipympl,\n", - "# fig.canvas is a proper Jupyter interactive widget, which can be embedded in\n", - "# an ipywidgets layout. See https://ipywidgets.readthedocs.io/en/stable/examples/Layout%20Templates.html\n", - "\n", - "# One can bound figure attributes to other widget values.\n", - "from ipywidgets import AppLayout, FloatSlider\n", - "\n", - "plt.ioff()\n", - "\n", - "slider = FloatSlider(\n", - " orientation='horizontal',\n", - " description='Factor:',\n", - " value=1.0,\n", - " min=0.02,\n", - " max=2.0\n", - ")\n", - "\n", - "slider.layout.margin = '0px 30% 0px 30%'\n", - "slider.layout.width = '40%'\n", - "\n", - "fig = plt.figure()\n", - "fig.canvas.header_visible = False\n", - "fig.canvas.layout.min_height = '400px'\n", - "plt.title('Plotting: y=sin({} * x)'.format(slider.value))\n", - "\n", - "x = np.linspace(0, 20, 500)\n", - "\n", - "lines = plt.plot(x, np.sin(slider.value * x))\n", - "\n", - "def update_lines(change):\n", - " plt.title('Plotting: y=sin({} * x)'.format(change.new))\n", - " lines[0].set_data(x, np.sin(change.new * x))\n", - " fig.canvas.draw()\n", - " fig.canvas.flush_events()\n", - "\n", - "slider.observe(update_lines, names='value')\n", - "\n", - "AppLayout(\n", - " center=fig.canvas,\n", - " footer=slider,\n", - " pane_heights=[0, 6, 1]\n", - ")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Update image data in a performant manner\n", - "\n", - "Two useful tricks to improve performance when updating an image displayed with matplolib are to:\n", - "1. Use the `set_data` method instead of calling imshow\n", - "2. Precompute and then index the array" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# precomputing all images\n", - "x = np.linspace(0,np.pi,200)\n", - "y = np.linspace(0,10,200)\n", - "X,Y = np.meshgrid(x,y)\n", - "parameter = np.linspace(-5,5)\n", - "example_image_stack = np.sin(X)[None,:,:]+np.exp(np.cos(Y[None,:,:]*parameter[:,None,None]))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.ioff()\n", - "fig = plt.figure()\n", - "plt.ion()\n", - "im = plt.imshow(example_image_stack[0])\n", - "\n", - "def update(change):\n", - " im.set_data(example_image_stack[change['new']])\n", - " fig.canvas.draw_idle()\n", - " \n", - " \n", - "slider = widgets.IntSlider(value=0, min=0, max=len(parameter)-1)\n", - "slider.observe(update, names='value')\n", - "widgets.VBox([slider, fig.canvas])" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Debugging widget updates and matplotlib callbacks\n", - "\n", - "If an error is raised in the `update` function then will not always display in the notebook which can make debugging difficult. This same issue is also true for matplotlib callbacks on user events such as mousemovement, for example see [issue](https://github.com/matplotlib/ipympl/issues/116). There are two ways to see the output:\n", - "1. In jupyterlab the output will show up in the Log Console (View > Show Log Console)\n", - "2. using `ipywidgets.Output`\n", - "\n", - "Here is an example of using an `Output` to capture errors in the update function from the previous example. To induce errors we changed the slider limits so that out of bounds errors will occur:\n", - "\n", - "From: `slider = widgets.IntSlider(value=0, min=0, max=len(parameter)-1)`\n", - "\n", - "To: `slider = widgets.IntSlider(value=0, min=0, max=len(parameter)+10)`\n", - "\n", - "If you move the slider all the way to the right you should see errors from the Output widget" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "plt.ioff()\n", - "fig = plt.figure()\n", - "plt.ion()\n", - "im = plt.imshow(example_image_stack[0])\n", - "\n", - "out = widgets.Output()\n", - "@out.capture()\n", - "def update(change):\n", - " with out:\n", - " if change['name'] == 'value':\n", - " im.set_data(example_image_stack[change['new']])\n", - " fig.canvas.draw_idle\n", - " \n", - " \n", - "slider = widgets.IntSlider(value=0, min=0, max=len(parameter)+10)\n", - "slider.observe(update)\n", - "display(widgets.VBox([slider, fig.canvas]))\n", - "display(out)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.0" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": { - "0f81ff97e38a42bc817642be40a5b088": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "1d8e39aba26f489797103338f306e335": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "1efdc4bda5354ce6bcbc85ca819d73b8": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - 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", 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", - "_figure_label": "Figure 1", - "_size": [ - 932, - 409 - ], - "layout": "IPY_MODEL_8f46a27a21324c5baac56bd42b7bda15", - "toolbar": "IPY_MODEL_7feed35324274f078384bd8b165dc7da", - "toolbar_position": "left" - } - }, - "c4d45a8399c743b7add76e74f0adb826": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "cc665d7c08fd495fa15fd9c6b72149db": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - }, - "d6ca011c6b4848fca4f54792db6e1810": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": {} - } - }, - "version_major": 2, - "version_minor": 0 - } - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/pyproject.toml b/pyproject.toml index 02ab5bca..234fd2ab 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta" [tool.pytest.ini_options] testpaths = [ - "examples", + "docs/examples", ] norecursedirs = [ "node_modules", From 49d1c1eb311642aec10a19194feae0cfc93377bd Mon Sep 17 00:00:00 2001 From: Ian Hunt-Isaak Date: Tue, 15 Mar 2022 12:08:04 -0400 Subject: [PATCH 3/4] add workflow to build docs --- .github/workflows/docs.yml | 33 +++++++++++++++++++++++++++++++++ docs/conf.py | 4 ---- setup.py | 3 +-- 3 files changed, 34 insertions(+), 6 deletions(-) create mode 100644 .github/workflows/docs.yml diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml new file mode 100644 index 00000000..7128f32c --- /dev/null +++ b/.github/workflows/docs.yml @@ -0,0 +1,33 @@ +name: Docs + +on: [push, pull_request] + + +defaults: + run: + shell: bash -l {0} +jobs: + build: + runs-on: ubuntu-20.04 + steps: + - uses: actions/checkout@v2 + - name: Setup conda + uses: conda-incubator/setup-miniconda@v2 + with: + activate-environment: ipympl-dev + environment-file: dev-environment.yml + python-version: ${{ matrix.python-version }} + mamba-version: "*" + auto-activate-base: false + channels: conda-forge + - name: Install + run: python -m pip install -v .[docs] + - name: Build + run: make -C docs html + - name: Publish + if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }} + uses: peaceiris/actions-gh-pages@v3 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + publish_dir: ./docs/_build/html + force_orphan: true diff --git a/docs/conf.py b/docs/conf.py index babdb420..b7766a70 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -34,13 +34,11 @@ # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ - "jupyter_sphinx", "myst_nb", "sphinx.ext.intersphinx", "sphinx.ext.linkcode", "sphinx.ext.mathjax", "sphinx_copybutton", - "sphinx_panels", "sphinx_thebe", "sphinx_togglebutton", ] @@ -59,8 +57,6 @@ "python": ("https://docs.python.org/3", None), } -# remove panels css to get wider main content -panels_add_bootstrap_css = False # Settings for copybutton copybutton_prompt_is_regexp = True diff --git a/setup.py b/setup.py index 76f6257b..43481296 100644 --- a/setup.py +++ b/setup.py @@ -66,12 +66,11 @@ 'ipywidgets>=7.6.0,<8', 'matplotlib>=2.0.0,<4', ], - extra_requires={ + extras_require={ "docs": [ "myst-nb", "Sphinx >= 1.5", "sphinx-copybutton", - "sphinx-panels", "sphinx-thebe", "sphinx-togglebutton", "sphinx-book-theme", From c3b777ba929ebb94e5dbb84a87719258e7bd1999 Mon Sep 17 00:00:00 2001 From: Ian Hunt-Isaak Date: Tue, 15 Mar 2022 12:18:30 -0400 Subject: [PATCH 4/4] update for main branch --- .github/workflows/docs.yml | 2 +- .github/workflows/main.yml | 4 ++-- .github/workflows/mpl-latest.yml | 4 ++-- 3 files changed, 5 insertions(+), 5 deletions(-) diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 7128f32c..7ace4355 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -25,7 +25,7 @@ jobs: - name: Build run: make -C docs html - name: Publish - if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/master' }} + if: ${{ github.event_name == 'push' && github.ref == 'refs/heads/main' }} uses: peaceiris/actions-gh-pages@v3 with: github_token: ${{ secrets.GITHUB_TOKEN }} diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml index a03391bd..b75187c1 100644 --- a/.github/workflows/main.yml +++ b/.github/workflows/main.yml @@ -3,10 +3,10 @@ name: Tests on: push: branches: - - master + - main pull_request: branches: - - master + - main defaults: run: diff --git a/.github/workflows/mpl-latest.yml b/.github/workflows/mpl-latest.yml index 68f1355d..bb12725d 100644 --- a/.github/workflows/mpl-latest.yml +++ b/.github/workflows/mpl-latest.yml @@ -5,10 +5,10 @@ on: - cron: "0 12 * * 1" # monday at noon UTC push: branches: - - master + - main pull_request: branches: - - master + - main jobs: run: