diff --git a/docs/api.rst b/docs/api.rst
index dba583af..ae0d78d2 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -8,3 +8,5 @@ plots though the napari user interface.
.. automodapi:: napari_matplotlib
.. automodapi:: napari_matplotlib.base
+
+.. automodapi:: napari_matplotlib.features
diff --git a/src/napari_matplotlib/base.py b/src/napari_matplotlib/base.py
index 8c717d6a..5687895e 100644
--- a/src/napari_matplotlib/base.py
+++ b/src/napari_matplotlib/base.py
@@ -281,7 +281,9 @@ def __init__(
napari_viewer: napari.viewer.Viewer,
parent: Optional[QWidget] = None,
):
- super().__init__(napari_viewer=napari_viewer, parent=parent)
+ NapariMPLWidget.__init__(
+ self, napari_viewer=napari_viewer, parent=parent
+ )
self.add_single_axes()
def clear(self) -> None:
diff --git a/src/napari_matplotlib/features.py b/src/napari_matplotlib/features.py
new file mode 100644
index 00000000..3e1eb9ba
--- /dev/null
+++ b/src/napari_matplotlib/features.py
@@ -0,0 +1,153 @@
+from typing import Any, Dict, List, Optional, Tuple
+
+import napari
+import napari.layers
+import numpy as np
+import numpy.typing as npt
+import pandas as pd
+from qtpy.QtWidgets import QComboBox, QLabel, QVBoxLayout
+
+from napari_matplotlib.base import NapariMPLWidget
+from napari_matplotlib.util import Interval
+
+__all__ = ["FeaturesMixin"]
+
+
+class FeaturesMixin(NapariMPLWidget):
+ """
+ Mixin to help with widgets that plot data from a features table stored
+ in a single napari layer.
+
+ This provides:
+
+ - Setup for one or two combo boxes to select features to be plotted.
+ - An ``on_update_layers()`` callback that updates the combo box options
+ when the napari layer selection changes.
+ """
+
+ n_layers_input = Interval(1, 1)
+ # All layers that have a .features attributes
+ input_layer_types = (
+ napari.layers.Labels,
+ napari.layers.Points,
+ napari.layers.Shapes,
+ napari.layers.Tracks,
+ napari.layers.Vectors,
+ )
+
+ def __init__(self, *, ndim: int) -> None:
+ """
+ Parameters
+ ----------
+ ndim : int
+ Number of dimensions that are plotted by the widget.
+ Must be 1 or 2.
+ """
+ assert ndim in [1, 2]
+ self.dims = ["x", "y"][:ndim]
+ # Set up selection boxes
+ self.layout().addLayout(QVBoxLayout())
+
+ self._selectors: Dict[str, QComboBox] = {}
+ for dim in self.dims:
+ self._selectors[dim] = QComboBox()
+ # Re-draw when combo boxes are updated
+ self._selectors[dim].currentTextChanged.connect(self._draw)
+
+ self.layout().addWidget(QLabel(f"{dim}-axis:"))
+ self.layout().addWidget(self._selectors[dim])
+
+ def get_key(self, dim: str) -> Optional[str]:
+ """
+ Get key for a given dimension.
+
+ Parameters
+ ----------
+ dim : str
+ "x" or "y"
+ """
+ if self._selectors[dim].count() == 0:
+ return None
+ else:
+ return self._selectors[dim].currentText()
+
+ def set_key(self, dim: str, value: str) -> None:
+ """
+ Set key for a given dimension.
+
+ Parameters
+ ----------
+ dim : str
+ "x" or "y"
+ value : str
+ Value to set.
+ """
+ assert value in self._get_valid_axis_keys(), (
+ "value must be on of the columns "
+ "of the feature table on the currently seleted layer"
+ )
+ self._selectors[dim].setCurrentText(value)
+ self._draw()
+
+ def _get_valid_axis_keys(self) -> List[str]:
+ """
+ Get the valid axis keys from the features table column names.
+
+ Returns
+ -------
+ axis_keys : List[str]
+ The valid axis keys in the FeatureTable. If the table is empty
+ or there isn't a table, returns an empty list.
+ """
+ if len(self.layers) == 0 or not (hasattr(self.layers[0], "features")):
+ return []
+ else:
+ return self.layers[0].features.keys()
+
+ def _ready_to_plot(self) -> bool:
+ """
+ Return True if selected layer has a feature table we can plot with,
+ and the columns to plot have been selected.
+ """
+ if not hasattr(self.layers[0], "features"):
+ return False
+
+ feature_table = self.layers[0].features
+ valid_keys = self._get_valid_axis_keys()
+ return (
+ feature_table is not None
+ and len(feature_table) > 0
+ and all([self.get_key(dim) in valid_keys for dim in self.dims])
+ )
+
+ def _get_data_names(
+ self,
+ ) -> Tuple[List[npt.NDArray[Any]], List[str]]:
+ """
+ Get the plot data from the ``features`` attribute of the first
+ selected layer.
+
+ Returns
+ -------
+ data : List[np.ndarray]
+ List contains X and Y columns from the FeatureTable. Returns
+ an empty array if nothing to plot.
+ names : List[str]
+ Names for each axis.
+ """
+ feature_table: pd.DataFrame = self.layers[0].features
+
+ names = [str(self.get_key(dim)) for dim in self.dims]
+ data = [np.array(feature_table[key]) for key in names]
+ return data, names
+
+ def on_update_layers(self) -> None:
+ """
+ Called when the layer selection changes by ``self.update_layers()``.
+ """
+ # Clear combobox
+ for dim in self.dims:
+ while self._selectors[dim].count() > 0:
+ self._selectors[dim].removeItem(0)
+ # Add keys for newly selected layer
+ self._selectors[dim].addItems(self._get_valid_axis_keys())
diff --git a/src/napari_matplotlib/scatter.py b/src/napari_matplotlib/scatter.py
index 334f941c..4fa45798 100644
--- a/src/napari_matplotlib/scatter.py
+++ b/src/napari_matplotlib/scatter.py
@@ -1,10 +1,11 @@
-from typing import Any, Dict, List, Optional, Tuple, Union
+from typing import Any, Optional, Tuple
import napari
import numpy.typing as npt
-from qtpy.QtWidgets import QComboBox, QLabel, QVBoxLayout, QWidget
+from qtpy.QtWidgets import QWidget
from .base import SingleAxesWidget
+from .features import FeaturesMixin
from .util import Interval
__all__ = ["ScatterBaseWidget", "ScatterWidget", "FeaturesScatterWidget"]
@@ -85,144 +86,27 @@ def _get_data(self) -> Tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
return x, y, x_axis_name, y_axis_name
-class FeaturesScatterWidget(ScatterBaseWidget):
+class FeaturesScatterWidget(ScatterBaseWidget, FeaturesMixin):
"""
Widget to scatter data stored in two layer feature attributes.
"""
- n_layers_input = Interval(1, 1)
- # All layers that have a .features attributes
- input_layer_types = (
- napari.layers.Labels,
- napari.layers.Points,
- napari.layers.Shapes,
- napari.layers.Tracks,
- napari.layers.Vectors,
- )
-
def __init__(
self,
napari_viewer: napari.viewer.Viewer,
parent: Optional[QWidget] = None,
):
- super().__init__(napari_viewer, parent=parent)
-
- self.layout().addLayout(QVBoxLayout())
-
- self._selectors: Dict[str, QComboBox] = {}
- for dim in ["x", "y"]:
- self._selectors[dim] = QComboBox()
- # Re-draw when combo boxes are updated
- self._selectors[dim].currentTextChanged.connect(self._draw)
-
- self.layout().addWidget(QLabel(f"{dim}-axis:"))
- self.layout().addWidget(self._selectors[dim])
-
+ ScatterBaseWidget.__init__(self, napari_viewer, parent=parent)
+ FeaturesMixin.__init__(self, ndim=2)
self._update_layers(None)
- @property
- def x_axis_key(self) -> Union[str, None]:
- """
- Key for the x-axis data.
- """
- if self._selectors["x"].count() == 0:
- return None
- else:
- return self._selectors["x"].currentText()
-
- @x_axis_key.setter
- def x_axis_key(self, key: str) -> None:
- self._selectors["x"].setCurrentText(key)
- self._draw()
-
- @property
- def y_axis_key(self) -> Union[str, None]:
- """
- Key for the y-axis data.
- """
- if self._selectors["y"].count() == 0:
- return None
- else:
- return self._selectors["y"].currentText()
-
- @y_axis_key.setter
- def y_axis_key(self, key: str) -> None:
- self._selectors["y"].setCurrentText(key)
- self._draw()
-
- def _get_valid_axis_keys(self) -> List[str]:
- """
- Get the valid axis keys from the layer FeatureTable.
-
- Returns
- -------
- axis_keys : List[str]
- The valid axis keys in the FeatureTable. If the table is empty
- or there isn't a table, returns an empty list.
- """
- if len(self.layers) == 0 or not (hasattr(self.layers[0], "features")):
- return []
- else:
- return self.layers[0].features.keys()
-
- def _ready_to_scatter(self) -> bool:
- """
- Return True if selected layer has a feature table we can scatter with,
- and the two columns to be scatterd have been selected.
- """
- if not hasattr(self.layers[0], "features"):
- return False
-
- feature_table = self.layers[0].features
- valid_keys = self._get_valid_axis_keys()
- return (
- feature_table is not None
- and len(feature_table) > 0
- and self.x_axis_key in valid_keys
- and self.y_axis_key in valid_keys
- )
-
def draw(self) -> None:
"""
Scatter two features from the currently selected layer.
"""
- if self._ready_to_scatter():
+ if self._ready_to_plot():
super().draw()
def _get_data(self) -> Tuple[npt.NDArray[Any], npt.NDArray[Any], str, str]:
- """
- Get the plot data from the ``features`` attribute of the first
- selected layer.
-
- Returns
- -------
- data : List[np.ndarray]
- List contains X and Y columns from the FeatureTable. Returns
- an empty array if nothing to plot.
- x_axis_name : str
- The title to display on the x axis. Returns
- an empty string if nothing to plot.
- y_axis_name: str
- The title to display on the y axis. Returns
- an empty string if nothing to plot.
- """
- feature_table = self.layers[0].features
-
- x = feature_table[self.x_axis_key]
- y = feature_table[self.y_axis_key]
-
- x_axis_name = str(self.x_axis_key)
- y_axis_name = str(self.y_axis_key)
-
- return x, y, x_axis_name, y_axis_name
-
- def on_update_layers(self) -> None:
- """
- Called when the layer selection changes by ``self.update_layers()``.
- """
- # Clear combobox
- for dim in ["x", "y"]:
- while self._selectors[dim].count() > 0:
- self._selectors[dim].removeItem(0)
- # Add keys for newly selected layer
- self._selectors[dim].addItems(self._get_valid_axis_keys())
+ data, names = self._get_data_names()
+ return data[0], data[1], names[0], names[1]
diff --git a/src/napari_matplotlib/tests/scatter/test_scatter_features.py b/src/napari_matplotlib/tests/scatter/test_scatter_features.py
index c211a064..0b3f7638 100644
--- a/src/napari_matplotlib/tests/scatter/test_scatter_features.py
+++ b/src/napari_matplotlib/tests/scatter/test_scatter_features.py
@@ -25,8 +25,8 @@ def test_features_scatter_widget_2D(
# Select points data and chosen features
viewer.layers.selection.add(viewer.layers[0]) # images need to be selected
- widget.x_axis_key = "feature_0"
- widget.y_axis_key = "feature_1"
+ widget.set_key("x", "feature_0")
+ widget.set_key("y", "feature_1")
fig = widget.figure
@@ -64,9 +64,9 @@ def test_features_scatter_get_data(make_napari_viewer):
viewer.layers.selection = [labels_layer]
x_column = "feature_0"
- scatter_widget.x_axis_key = x_column
y_column = "feature_2"
- scatter_widget.y_axis_key = y_column
+ scatter_widget.set_key("x", x_column)
+ scatter_widget.set_key("y", y_column)
x, y, x_axis_name, y_axis_name = scatter_widget._get_data()
np.testing.assert_allclose(x, feature_table[x_column])