Jul 12, 2024 · Jan 11, 2024 · Jan 11, 2024 · Jan 11, 2024 · Jan 11, 2024 · Jan 11, 2024
diff --git a/docs/changelog.rst b/docs/changelog.rst
 Changelog
 =========

 2.1.0
 -----
 New features
 ~~~~~~~~~~~~
 - Added a GUI element to manually set the number of bins in the histogram widgets.

 2.0.3
 -----
 Bug fixes
diff --git a/src/napari_matplotlib/histogram.py b/src/napari_matplotlib/histogram.py
 from napari.layers._multiscale_data import MultiScaleData
 from qtpy.QtWidgets import (
    QComboBox,
    QFormLayout,
    QGroupBox,
    QLabel,
    QSpinBox,
    QVBoxLayout,
    QWidget,
 )
 _COLORS = {"r": "tab:red", "g": "tab:green", "b": "tab:blue"}


 def _get_bins(data: npt.NDArray[Any]) -> npt.NDArray[Any]:
 def _get_bins(
    data: npt.NDArray[Any],
    num_bins: int = 100,
 ) -> npt.NDArray[Any]:
    """Create evenly spaced bins with a given interval.

    Parameters
    ----------
    data : napari.layers.Layer.data
        Napari layer data.
    num_bins : integer, optional
        Number of evenly-spaced bins to create. Defaults to 100.

    Returns
    -------
    bin_edges : numpy.ndarray
        Array of evenly spaced bin edges.
    """
    if data.dtype.kind in {"i", "u"}:
        # Make sure integer data types have integer sized bins
        step = np.ceil(np.ptp(data) /100)
        step = np.ceil(np.ptp(data) /num_bins)
        return np.arange(np.min(data), np.max(data) + step, step)
    else:
        # For other data types, just have 100 evenly spaced bins
        # (and101 bin edges)
        return np.linspace(np.min(data), np.max(data),101)
        # For other data types we can use exactly `num_bins` bins
        # (and`num_bins` + 1 bin edges)
        return np.linspace(np.min(data), np.max(data),num_bins + 1)


 class HistogramWidget(SingleAxesWidget):
        parent: QWidget | None = None,
    ):
        super().__init__(napari_viewer, parent=parent)

        num_bins_widget = QSpinBox()
        num_bins_widget.setRange(1, 100_000)
        num_bins_widget.setValue(101)
        num_bins_widget.setWrapping(False)
        num_bins_widget.setKeyboardTracking(False)

        # Set bins widget layout
        bins_selection_layout = QFormLayout()
        bins_selection_layout.addRow("num bins", num_bins_widget)

        # Group the widgets and add to main layout
        params_widget_group = QGroupBox("Params")
        params_widget_group_layout = QVBoxLayout()
        params_widget_group_layout.addLayout(bins_selection_layout)
        params_widget_group.setLayout(params_widget_group_layout)
        self.layout().addWidget(params_widget_group)

        # Add callbacks
        num_bins_widget.valueChanged.connect(self._draw)

        # Store widgets for later usage
        self.num_bins_widget = num_bins_widget

        self._update_layers(None)
        self.viewer.events.theme.connect(self._on_napari_theme_changed)

                self._update_contrast_lims
            )

        if not self.layers:
            return

        # Reset the num bins based on new layer data
        layer_data = self._get_layer_data(self.layers[0])
        self._set_widget_nums_bins(data=layer_data)

    def _update_contrast_lims(self) -> None:
        for lim, line in zip(
            self.layers[0].contrast_limits, self._contrast_lines, strict=False

        self.figure.canvas.draw()

    def draw(self) -> None:
        """
        Clear the axes and histogram the currently selected layer/slice.
        """
        layer: Image = self.layers[0]
    def _set_widget_nums_bins(self, data: npt.NDArray[Any]) -> None:
        """Update num_bins widget with bins determined from the image data"""
        bins = _get_bins(data)
        self.num_bins_widget.setValue(bins.size - 1)

    def _get_layer_data(self, layer: napari.layers.Layer) -> npt.NDArray[Any]:
        """Get the data associated with a given layer"""
        data = layer.data

        if isinstance(layer.data, MultiScaleData):
        # Read data into memory if it's a dask array
        data = np.asarray(data)

        return data

    def draw(self) -> None:
        """
        Clear the axes and histogram the currently selected layer/slice.
        """
        layer: Image = self.layers[0]
        data = self._get_layer_data(layer)

        # Important to calculate bins after slicing 3D data, to avoid reading
        # whole cube into memory.
        bins = _get_bins(data)
        bins = _get_bins(
            data,
            num_bins=self.num_bins_widget.value(),
        )

        if layer.rgb:
            # Histogram RGB channels independently
diff --git a/src/napari_matplotlib/tests/baseline/test_histogram_2D_bins.png b/src/napari_matplotlib/tests/baseline/test_histogram_2D_bins.png
diff --git a/src/napari_matplotlib/tests/test_histogram.py b/src/napari_matplotlib/tests/test_histogram.py
 )


 @pytest.mark.mpl_image_compare
 def test_histogram_2D_bins(make_napari_viewer, astronaut_data):
    viewer = make_napari_viewer()
    viewer.theme = "light"
    viewer.add_image(astronaut_data[0], **astronaut_data[1])
    widget = HistogramWidget(viewer)
    viewer.window.add_dock_widget(widget)
    widget.num_bins_widget.setValue(25)
    fig = widget.figure
    # Need to return a copy, as original figure is too eagerley garbage
    # collected by the widget
    return deepcopy(fig)


 @pytest.mark.mpl_image_compare
 def test_histogram_2D(make_napari_viewer, astronaut_data):
    viewer = make_napari_viewer()
Original file line number	Diff line number	Diff line change
		@@ -1,6 +1,12 @@
		Changelog
		=========

		2.1.0
		-----
		New features
		~~~~~~~~~~~~
		- Added a GUI element to manually set the number of bins in the histogram widgets.

		2.0.3
		-----
		Bug fixes
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -8,7 +8,10 @@
		from napari.layers._multiscale_data import MultiScaleData
		from qtpy.QtWidgets import (
		QComboBox,
		QFormLayout,
		QGroupBox,
		QLabel,
		QSpinBox,
		QVBoxLayout,
		QWidget,
		)
Expand All		@@ -22,15 +25,32 @@
		_COLORS = {"r": "tab:red", "g": "tab:green", "b": "tab:blue"}


		def _get_bins(data: npt.NDArray[Any]) -> npt.NDArray[Any]:
		def _get_bins(
		data: npt.NDArray[Any],
		num_bins: int = 100,
		) -> npt.NDArray[Any]:
		"""Create evenly spaced bins with a given interval.

		Parameters
		----------
		data : napari.layers.Layer.data
		Napari layer data.
		num_bins : integer, optional
		Number of evenly-spaced bins to create. Defaults to 100.

		Returns
		-------
		bin_edges : numpy.ndarray
		Array of evenly spaced bin edges.
		"""
		if data.dtype.kind in {"i", "u"}:
		# Make sure integer data types have integer sized bins
		step = np.ceil(np.ptp(data) /100)
		step = np.ceil(np.ptp(data) /num_bins)
		return np.arange(np.min(data), np.max(data) + step, step)
		else:
		# For other data types, just have 100 evenly spaced bins
		# (and101 bin edges)
		return np.linspace(np.min(data), np.max(data),101)
		# For other data types we can use exactly `num_bins` bins
		# (and`num_bins` + 1 bin edges)
		return np.linspace(np.min(data), np.max(data),num_bins + 1)


		class HistogramWidget(SingleAxesWidget):
Expand All		@@ -47,6 +67,30 @@ def __init__(
		parent: QWidget \| None = None,
		):
		super().__init__(napari_viewer, parent=parent)

		num_bins_widget = QSpinBox()
		num_bins_widget.setRange(1, 100_000)
		num_bins_widget.setValue(101)
		num_bins_widget.setWrapping(False)
		num_bins_widget.setKeyboardTracking(False)

		# Set bins widget layout
		bins_selection_layout = QFormLayout()
		bins_selection_layout.addRow("num bins", num_bins_widget)

		# Group the widgets and add to main layout
		params_widget_group = QGroupBox("Params")
		params_widget_group_layout = QVBoxLayout()
		params_widget_group_layout.addLayout(bins_selection_layout)
		params_widget_group.setLayout(params_widget_group_layout)
		self.layout().addWidget(params_widget_group)

		# Add callbacks
		num_bins_widget.valueChanged.connect(self._draw)

		# Store widgets for later usage
		self.num_bins_widget = num_bins_widget

		self._update_layers(None)
		self.viewer.events.theme.connect(self._on_napari_theme_changed)

Expand All		@@ -60,6 +104,13 @@ def on_update_layers(self) -> None:
		self._update_contrast_lims
		)

		if not self.layers:
		return

		# Reset the num bins based on new layer data
		layer_data = self._get_layer_data(self.layers[0])
		self._set_widget_nums_bins(data=layer_data)

		def _update_contrast_lims(self) -> None:
		for lim, line in zip(
		self.layers[0].contrast_limits, self._contrast_lines, strict=False
Expand All		@@ -68,11 +119,13 @@ def _update_contrast_lims(self) -> None:

		self.figure.canvas.draw()

		def draw(self) -> None:
		"""
		Clear the axes and histogram the currently selected layer/slice.
		"""
		layer: Image = self.layers[0]
		def _set_widget_nums_bins(self, data: npt.NDArray[Any]) -> None:
		"""Update num_bins widget with bins determined from the image data"""
		bins = _get_bins(data)
		self.num_bins_widget.setValue(bins.size - 1)

		def _get_layer_data(self, layer: napari.layers.Layer) -> npt.NDArray[Any]:
		"""Get the data associated with a given layer"""
		data = layer.data

		if isinstance(layer.data, MultiScaleData):
Expand All		@@ -87,9 +140,21 @@ def draw(self) -> None:
		# Read data into memory if it's a dask array
		data = np.asarray(data)

		return data

		def draw(self) -> None:
		"""
		Clear the axes and histogram the currently selected layer/slice.
		"""
		layer: Image = self.layers[0]
		data = self._get_layer_data(layer)

		# Important to calculate bins after slicing 3D data, to avoid reading
		# whole cube into memory.
		bins = _get_bins(data)
		bins = _get_bins(
		data,
		num_bins=self.num_bins_widget.value(),
		)

		if layer.rgb:
		# Histogram RGB channels independently
Expand Down
Original file line number	Diff line number	Diff line change
Expand Up		@@ -10,6 +10,20 @@
		)


		@pytest.mark.mpl_image_compare
		def test_histogram_2D_bins(make_napari_viewer, astronaut_data):
		viewer = make_napari_viewer()
		viewer.theme = "light"
		viewer.add_image(astronaut_data[0], **astronaut_data[1])
		widget = HistogramWidget(viewer)
		viewer.window.add_dock_widget(widget)
		widget.num_bins_widget.setValue(25)
		fig = widget.figure
		# Need to return a copy, as original figure is too eagerley garbage
		# collected by the widget
		return deepcopy(fig)


		@pytest.mark.mpl_image_compare
		def test_histogram_2D(make_napari_viewer, astronaut_data):
		viewer = make_napari_viewer()
Expand Down