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Merge branch 'main' into add-feature-histogram
2 parents 20300a4 + 3a8261a commit ad86b38

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‎.github/workflows/docs.yml

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name: Build docs
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on:
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pull_request:
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branches:
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- main
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push:
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branches:
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- main
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tags:
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- "v*" # Push events to matching v*, i.e. v1.0, v20.15.10
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jobs:
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build-docs:
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name: Upload docs to GitHub pages
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runs-on: ubuntu-latest
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needs: build-docs
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if: github.event_name == 'push' && github.ref_name == 'main'
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if: contains(github.ref, 'tags')
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steps:
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- uses: actions/checkout@v3
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- uses: actions/download-artifact@v3
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with:
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folder: html
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ssh-key: ${{ secrets.DEPLOY_KEY }}
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repository-name: dstansby/napari-matplotlib-docs
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repository-name: napari-matplotlib/napari-matplotlib.github.io

‎.github/workflows/test_and_deploy.yml

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needs: [test]
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runs-on: ubuntu-latest
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if: contains(github.ref, 'tags')
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environment: pypi-deploy
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permissions:
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id-token: write
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steps:
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- uses: actions/checkout@v2
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- name: Set up Python
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uses: actions/setup-python@v2
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with:
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python-version: "3.x"
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- name: Install dependencies
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- name: Install build
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run: |
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python -m pip install --upgrade pip
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pip install -U setuptools setuptools_scm wheel twine build
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- name: Build and publish
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.TWINE_API_KEY }}
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python -m pip install --upgrade build
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- name: Build package
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run: |
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git tag
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python -m build .
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twine upload dist/*
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- name: Publish package
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uses: pypa/gh-action-pypi-publish@release/v1

‎.pre-commit-config.yaml

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- id: end-of-file-fixer
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- id: trailing-whitespace
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- repo: https://github.com/asottile/setup-cfg-fmt
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rev: v2.3.0
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hooks:
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- id: setup-cfg-fmt
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- repo: https://github.com/psf/black
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rev: 23.3.0
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rev: 23.7.0
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hooks:
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- id: black
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- id: napari-plugin-checks
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v1.3.0
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rev: v1.5.1
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hooks:
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- id: mypy
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additional_dependencies: [numpy, matplotlib]
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- repo: https://github.com/charliermarsh/ruff-pre-commit
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- repo: https://github.com/astral-sh/ruff-pre-commit
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# Ruff version.
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rev: 'v0.0.272'
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rev: 'v0.0.285'
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hooks:
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- id: ruff
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‎README.md

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[![Python Version](https://img.shields.io/pypi/pyversions/napari-matplotlib.svg?color=green)](https://python.org)
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[![tests](https://github.com/matplotlib/napari-matplotlib/workflows/tests/badge.svg)](https://github.com/matplotlib/napari-matplotlib/actions)
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[![codecov](https://codecov.io/gh/matplotlib/napari-matplotlib/branch/main/graph/badge.svg)](https://codecov.io/gh/matplotlib/napari-matplotlib)
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[![readthedocs](https://readthedocs.org/projects/napari-matplotlib/badge/?version=latest)](https://napari-matplotlib.readthedocs.io/en/latest/)
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[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/matplotlib/pytest-mpl/master.svg)](https://results.pre-commit.ci/latest/github/matplotlib/pytest-mpl/master)
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[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-matplotlib)](https://napari-hub.org/plugins/napari-matplotlib)
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‎docs/_static/hist.png

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‎docs/_static/logo.png

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‎docs/changelog.rst

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Changelog
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=========
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1.0.3
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-----
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Changes
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~~~~~~~
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- The slice widget is now limited to slicing along the x/y dimensions. Support
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for slicing along z has been removed for now to make the code simpler.
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- The slice widget now uses a slider to select the slice value.
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Bug fixes
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~~~~~~~~~
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- Fixed creating 1D slices of 2D images.
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- Removed the limitation that only the first 99 indices could be sliced using
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the slice widget.
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1.0.2
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-----
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Bug fixes
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~~~~~~~~~
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- A full dataset is no longer read into memory when using ``HistogramWidget``.
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Only the current slice is loaded.
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- Fixed compatibility with napari 0.4.18.
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Changes
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~~~~~~~
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- Histogram bin limits are now caclualted from the slice being histogrammed, and
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not the whole dataset. This is as a result of the above bug fix.
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1.0.1
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-----
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Bug fixes
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~~~~~~~~~
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- Pinned that maximum version of `napari` to 0.4.17, since ``napari-matplotlib``
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does not yet work with ``napari`` 0.4.18.
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0.3.0
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1.0.0
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-----
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New features
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~~~~~~~~~~~~~~~~~~~
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- The background of ``napari-matplotlib`` figures and axes is now transparent, and the text and axis colour respects the ``napari`` theme.
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- The icons in the Matplotlib toolbar are now the same size as icons in the napari window.
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- Custom style sheets can now be set to customise plots. See the user guide
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for more information.
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Changes
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~~~~~~~

‎docs/conf.py

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# a list of builtin themes.
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#
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html_theme = "pydata_sphinx_theme"
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html_logo = "_static/logo.png"
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# Add any paths that contain custom static files (such as style sheets) here,
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# relative to this directory. They are copied after the builtin static files,

‎docs/guide/index.rst

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‎docs/index.rst

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napari-matplotlib
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=================
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``napari-matplotlib`` is a `Napari <https://napari.org>`_ plugin for generating
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A `napari <https://napari.org>`_ plugin for generating
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`Matplotlib <https://matplotlib.org/>`_ plots from one or more ``napari`` Layers.
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Design
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------
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``napari-matplotlib`` contains a number of different ``napari`` Widgets. Each
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widget is designed to map one or more ``napari`` Layers on to a ``matplotlib`` plot.
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This plugin provides a number of different ``napari`` Widgets. Each
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widget is designed to map one or more ``napari`` Layers on to a ``Matplotlib`` plot.
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As an example, the `~.HistogramWidget` is used to
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map one or more Image layers on to a 1D histogram plot.
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.. toctree::
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:maxdepth: 1
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guide/index
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.. image:: _static/hist.png
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:alt: Screenshot of the napari viewer showing the napari-matplotlib histogram widget on the right hand side of the screen.
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.. toctree::
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:maxdepth: 1
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:caption: Reference
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:hidden:
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user_guide
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auto_examples/index
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third_party
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api
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changelog

‎docs/guide/third_party.rst renamed to ‎docs/third_party.rst

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Third-party plugins
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===================
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This page explains how ``napari-matplotlib`` can be used within third party plugins.
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``napari-matplotlib`` provides a ready-to-go widget with a Matplotlib toolbar and figure to third party plugin developers
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``napari-matplotlib`` provides a ready-to-go widget with a Matplotlib toolbar and figure to third party plugin developers.
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This widget is customised to match the theme of the main napari window.
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The widget can be found at `napari_matplotlib.base.NapariMPLWidget`.

‎docs/guide/user_guide.rst renamed to ‎docs/user_guide.rst

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1. Open the desired widget using the ``Plugins > napari-matplotlib`` menu in napari.
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2. Select a single layer that has a features table using the napari layers list in the bottom left-hand side of the window.
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3. Use the drop down menu(s) under the Matplotlib figure to select the feature(s) to plot.
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Customising plots
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-----------------
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`Matplotlib style sheets <https://matplotlib.org/stable/tutorials/introductory/customizing.html#defining-your-own-style>`__ can be used to customise
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the plots generated by ``napari-matplotlib``.
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To use a custom style sheet:
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1. Save it as ``napari-matplotlib.mplstyle``
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2. Put it in the Matplotlib configuration directory.
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The location of this directory varies on different computers,
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and can be found by calling :func:`matplotlib.get_configdir()`.

‎examples/README.rst

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Examples
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========
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Gallery
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=======

‎examples/features_scatter.py

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import napari
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import numpy as np
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import numpy.typing as npt
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from skimage.measure import regionprops_table
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# make a test label image
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label_image = np.zeros((100, 100), dtype=np.uint16)
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label_image: npt.NDArray[np.uint16] = np.zeros((100, 100), dtype=np.uint16)
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label_image[10:20, 10:20] = 1
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label_image[50:70, 50:70] = 2

‎setup.cfg

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Topic :: Software Development :: Testing
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project_urls =
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Bug Tracker = https://github.com/matplotlib/napari-matplotlib/issues
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Documentation = https://github.com/matplotlib/napari-matplotlib#README.md
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Documentation = https://napari-matplotlib.github.io
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Source Code = https://github.com/matplotlib/napari-matplotlib
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User Support = https://github.com/matplotlib/napari-matplotlib/issues
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[options.extras_require]
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docs =
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napari[all]
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napari[all]==0.4.17
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numpydoc
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pydata-sphinx-theme
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qtgallery
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sphinx
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sphinx-automodapi
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sphinx-gallery
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testing =
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napari[pyqt6-experimental]
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napari[pyqt6_experimental]>=0.4.18
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pooch
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pyqt6
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pytest

‎src/napari_matplotlib/base.py

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from pathlib import Path
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from typing import List, Optional, Tuple
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import matplotlib
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import matplotlib.style as mplstyle
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import napari
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from matplotlib.backends.backend_qtagg import (
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__all__ = ["BaseNapariMPLWidget", "NapariMPLWidget", "SingleAxesWidget"]
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_CUSTOM_STYLE_PATH = (
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Path(matplotlib.get_configdir()) / "napari-matplotlib.mplstyle"
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)
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class BaseNapariMPLWidget(QWidget):
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"""
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with mplstyle.context(self.mpl_style_sheet_path):
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self.canvas = FigureCanvas()
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self.canvas.figure.patch.set_facecolor("none")
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self.canvas.figure.set_layout_engine("constrained")
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self.toolbar = NapariNavigationToolbar(
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self.canvas, parent=self
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"""
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elif (_CUSTOM_STYLE_PATH).exists():
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return _CUSTOM_STYLE_PATH
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elif self._napari_theme_has_light_bg():
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return Path(__file__).parent / "styles" / "light.mplstyle"
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‎src/napari_matplotlib/histogram.py

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Clear the axes and histogram the currently selected layer/slice.
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"""
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layer = self.layers[0]
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bins = np.linspace(np.min(layer.data), np.max(layer.data), 100)
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if layer.data.ndim - layer.rgb == 3:
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# 3D data, can be single channel or RGB
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data = layer.data[self.current_z]
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self.axes.set_title(f"z={self.current_z}")
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else:
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data = layer.data
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# Read data into memory if it's a dask array
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data = np.asarray(data)
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# Important to calculate bins after slicing 3D data, to avoid reading
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# whole cube into memory.
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bins = np.linspace(np.min(data), np.max(data), 100)
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if layer.rgb:
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# Histogram RGB channels independently

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