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fix merge conflict
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‎README.md

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@@ -14,14 +14,19 @@ A plugin to create Matplotlib plots from napari layers
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## Introduction
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`napari-matplotlib` is a bridge between `napari` and `matplotlib`, making it easy to create publication quality `Matplotlib` plots based on the data loaded in `napari` layers.
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Currently you can:
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## Available widgets
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- Draw histograms of individual image layers
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- Scatter plot two image layers against each other
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### `Slice`
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Plots 1D slices of data along a specified axis.
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![](https://raw.githubusercontent.com/dstansby/napari-matplotlib/main/examples/slice.png)
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Here's a demo of the scatter widget:
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### `Histogram`
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Plots histograms of individual image layers, or RGB histograms of an RGB image
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![](https://raw.githubusercontent.com/dstansby/napari-matplotlib/main/examples/hist.png)
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![](https://raw.githubusercontent.com/dstansby/napari-matplotlib/main/examples/short_scatter.gif)
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### `Scatter`
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Scatters the values of two similarly sized images layers against each other.
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![](https://raw.githubusercontent.com/dstansby/napari-matplotlib/main/examples/scatter.png)
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## Installation
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‎examples/hist.png

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‎examples/scatter.png

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‎examples/short_scatter.gif

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‎examples/slice.png

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‎examples/slice.py

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"""
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1D slices
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=========
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"""
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import napari
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viewer = napari.Viewer()
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viewer.open_sample("napari", "kidney")
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viewer.window.add_plugin_dock_widget(
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plugin_name="napari-matplotlib", widget_name="1D slice"
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)
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if __name__ == "__main__":
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napari.run()

‎src/napari_matplotlib/__init__.py

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from .histogram import * # NoQA
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from .scatter import * # NoQA
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from .slice import * # NoQA

‎src/napari_matplotlib/base.py

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def update_layers(self, event: napari.utils.events.Event) -> None:
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"""
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Update the currently selected layers and re-draw.
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Update the layers attribute with currently selected layers and re-draw.
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"""
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self.layers = list(self.viewer.layers.selection)
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self._on_update_layers()

‎src/napari_matplotlib/napari.yaml

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python_name: napari_matplotlib:FeaturesScatterWidget
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title: Make a scatter plot of layer features
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- id: napari-matplotlib.slice
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python_name: napari_matplotlib:SliceWidget
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title: Plot a 1D slice
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widgets:
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- command: napari-matplotlib.histogram
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display_name: Histogram
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- command: napari-matplotlib.features_scatter
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display_name: FeaturesScatter
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- command: napari-matplotlib.slice
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display_name: 1D slice

‎src/napari_matplotlib/slice.py

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from typing import Dict, Tuple
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import napari
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import numpy as np
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from qtpy.QtWidgets import QComboBox, QHBoxLayout, QLabel, QSpinBox
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from napari_matplotlib.base import NapariMPLWidget
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__all__ = ["SliceWidget"]
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_dims_sel = ["x", "y"]
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_dims = ["x", "y", "z"]
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class SliceWidget(NapariMPLWidget):
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"""
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Plot a 1D slice along a given dimension.
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"""
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n_layers_input = 1
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def __init__(self, napari_viewer: napari.viewer.Viewer):
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# Setup figure/axes
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super().__init__(napari_viewer)
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self.axes = self.canvas.figure.subplots()
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button_layout = QHBoxLayout()
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self.layout().addLayout(button_layout)
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self.dim_selector = QComboBox()
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button_layout.addWidget(QLabel("Slice axis:"))
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button_layout.addWidget(self.dim_selector)
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self.dim_selector.addItems(_dims)
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self.slice_selectors = {}
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for d in _dims_sel:
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self.slice_selectors[d] = QSpinBox()
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button_layout.addWidget(QLabel(f"{d}:"))
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button_layout.addWidget(self.slice_selectors[d])
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# Setup callbacks
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# Re-draw when any of the combon/spin boxes are updated
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self.dim_selector.currentTextChanged.connect(self._draw)
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for d in _dims_sel:
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self.slice_selectors[d].textChanged.connect(self._draw)
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self.update_layers(None)
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@property
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def layer(self):
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return self.layers[0]
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@property
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def current_dim(self) -> str:
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"""
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Currently selected slice dimension.
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"""
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return self.dim_selector.currentText()
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@property
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def current_dim_index(self) -> int:
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"""
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Currently selected slice dimension index.
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"""
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# Note the reversed list because in napari the z-axis is the first
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# numpy axis
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return _dims[::-1].index(self.current_dim)
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@property
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def selector_values(self) -> Dict[str, int]:
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return {d: self.slice_selectors[d].value() for d in _dims_sel}
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def update_slice_selectors(self) -> None:
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"""
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Update range and enabled status of the slice selectors, and the value
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of the z slice selector.
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"""
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# Update min/max
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for i, dim in enumerate(_dims_sel):
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self.slice_selectors[dim].setRange(0, self.layer.data.shape[i])
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def get_xy(self) -> Tuple[np.ndarray, np.ndarray]:
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"""
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Get data for plotting.
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"""
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x = np.arange(self.layer.data.shape[self.current_dim_index])
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vals = self.selector_values
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vals.update({"z": self.current_z})
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slices = []
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for d in _dims:
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if d == self.current_dim:
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# Select all data along this axis
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slices.append(slice(None))
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else:
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# Select specific index
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val = vals[d]
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slices.append(slice(val, val + 1))
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# Reverse since z is the first axis in napari
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slices = slices[::-1]
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y = self.layer.data[tuple(slices)].ravel()
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return x, y
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def clear(self) -> None:
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self.axes.cla()
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def draw(self) -> None:
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"""
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Clear axes and draw a 1D plot.
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"""
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x, y = self.get_xy()
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self.axes.plot(x, y)
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self.axes.set_xlabel(self.current_dim)
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self.axes.set_title(self.layer.name)

‎src/napari_matplotlib/tests/test_slice.py

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import numpy as np
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from napari_matplotlib import SliceWidget
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def test_scatter(make_napari_viewer):
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# Smoke test adding a histogram widget
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viewer = make_napari_viewer()
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viewer.add_image(np.random.random((100, 100, 100)))
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SliceWidget(viewer)

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