Create line.py

src/napari_matplotlib/line.py

@@ -0,0 +1,245 @@
+from typing import List, Optional, Tuple
+
+import matplotlib.colors as mcolor
+import napari
+import numpy as np
+import pandas as pd
+from magicgui import magicgui
+from magicgui.widgets import ComboBox
+
+from .base import NapariMPLWidget
+from .util import Interval
+
+__all__ = ["Line2DBaseWidget", "MetadataLine2DWidget"]
+
+
+class Line2DBaseWidget(NapariMPLWidget):
+    # opacity value for the lines
+    _line_alpha = 0.5
+    _lines = []
+
+    def __init__(self, napari_viewer: napari.viewer.Viewer):
+        super().__init__(napari_viewer)
+
+        self.axes = self.canvas.figure.subplots()
+        self.update_layers(None)
+
+    def clear(self) -> None:
+        """
+        Clear the axes.
+        """
+        self.axes.clear()
+
+    def draw(self) -> None:
+        """
+        Plot the currently selected layers.
+        """
+        data, x_axis_name, y_axis_name = self._get_data()
+
+
+        if len(data) == 0:
+            # don't plot if there isn't data
+            return
+        self._lines = []
+        x_data = data[0]
+        y_data = data[1]
+
+        if len(y_data) < len(x_data):
+            print("x_data bigger than y_data, plotting only first y_data")
+        for i, y in enumerate(y_data):
+            if len(x_data) == 1:
+                line = self.axes.plot(x_data[0], y, alpha=self._line_alpha)
+            else:
+                line = self.axes.plot(x_data[i], y, alpha=self._line_alpha)
+            self._lines += line
+
+        self.axes.set_xlabel(x_axis_name)
+        self.axes.set_ylabel(y_axis_name)
+
+    def _get_data(self) -> Tuple[List[np.ndarray], str, str]:
+        """Get the plot data.
+
+        This must be implemented on the subclass.
+
+        Returns
+        -------
+        data : np.ndarray
+            The list containing the line plot data.
+        x_axis_name : str
+            The label to display on the x axis
+        y_axis_name: str
+            The label to display on the y axis
+        """
+        raise NotImplementedError
+
+class MetadataLine2DWidget(Line2DBaseWidget):
+    n_layers_input = Interval(1, 1)
+
+    def __init__(self, napari_viewer: napari.viewer.Viewer):
+        super().__init__(napari_viewer)
+        self.setMinimumSize(200, 200)
+        self._plugin_name_widget = magicgui(
+            self._set_plugin_name,
+            plugin_name={"choices": self._get_plugin_metadata_key},
+            auto_call = True,
+        )
+        self._key_selection_widget = magicgui(
+            self._set_axis_keys,
+            x_axis_key={"choices": self._get_valid_axis_keys},
+            y_axis_key={"choices": self._get_valid_axis_keys},
+            call_button="plot",
+        )
+
+        self.ray_index = 0
+        self.dot_index = 0
+        self.layout().insertWidget(0, self._plugin_name_widget.native)
+        self.layout().addWidget(self._key_selection_widget.native)
+
+    @property
+    def x_axis_key(self) -> Optional[str]:
+        """Key to access x axis data from the Metadata"""
+        return self._x_axis_key
+
+    @x_axis_key.setter
+    def x_axis_key(self, key: Optional[str]) -> None:
+        self._x_axis_key = key
+        self._draw()
+
+    @property
+    def y_axis_key(self) -> Optional[str]:
+        """Key to access y axis data from the Metadata"""
+        return self._y_axis_key
+
+    @y_axis_key.setter
+    def y_axis_key(self, key: Optional[str]) -> None:
+        self._y_axis_key = key
+        self._draw()
+
+    def _set_axis_keys(self, x_axis_key: str, y_axis_key: str) -> None:
+        """Set both axis keys and then redraw the plot"""
+        self._x_axis_key = x_axis_key
+        self._y_axis_key = y_axis_key
+        self._draw()
+
+    @property
+    def plugin_name_key(self) -> Optional[str]:
+        """Key to plugin dictionary in the Metadata"""
+        return self._plugin_name_key
+
+    @plugin_name_key.setter
+    def plugin_name_key(self, key: Optional[str]) -> None:
+        self._plugin_name_key = key
+
+    def _set_plugin_name(self, plugin_name: str) -> None:
+        """Set plugin name from layer metadata"""
+        self._plugin_name_key = plugin_name
+
+    def _get_plugin_metadata_key(
+            self, combo_widget: Optional[ComboBox] = None
+        ) -> List[str]:
+        """Get plugin key from layer metadata"""
+        if len(self.layers) == 0:
+            return []
+        else:
+            return self._get_valid_metadata_keys() 
+
+    def _get_valid_metadata_keys(
+            self) -> List[str]:
+        """Get metadata keys if nested dictionaries"""
+        if len(self.layers) == 0:
+            return []
+        else:
+            metadata = self.layers[0].metadata
+            keys_with_nested_dicts = []
+            for key, value in metadata.items():
+                if isinstance(value, dict):
+                    keys_with_nested_dicts.append(key)
+            return keys_with_nested_dicts
+
+    def _get_valid_axis_keys(
+        self, combo_widget: Optional[ComboBox] = None
+    ) -> List[str]:
+        """
+        Get the valid axis keys from the layer Metadata.
+        Returns
+        -------
+        axis_keys : List[str]
+            The valid axis keys in the Metadata. If the table is empty
+            or there isn't a table, returns an empty list.
+        """
+
+        if len(self.layers) == 0:
+            return []
+        else:
+            valid_metadata = self._get_valid_metadata_keys()
+            if not valid_metadata:
+                return []
+            else:
+                if not hasattr(self, "plugin_name_key"):
+                    self.plugin_name_key = self._get_valid_metadata_keys()[0]
+                return self.layers[0].metadata[self.plugin_name_key].keys()
+
+    def _get_data(self) -> Tuple[List[np.ndarray], str, str]:
+        """Get the plot data.
+        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.
+        """
+        valid_metadata = self._get_valid_metadata_keys()
+
+        if (
+            (not valid_metadata)
+            or (self.x_axis_key is None)
+            or (self.y_axis_key is None)
+        ):
+            return [], "", ""
+
+        if not hasattr(self, "plugin_name_key"):
+            self.plugin_name_key = valid_metadata[0]
+
+        plugin_metadata_dict = self.layers[0].metadata[self.plugin_name_key]
+
+        data_x = warp_to_list(plugin_metadata_dict[self.x_axis_key])
+        data_y = warp_to_list(plugin_metadata_dict[self.y_axis_key])
+        data = [data_x, data_y]
+
+        x_axis_name = self.x_axis_key.replace("_", " ")
+        y_axis_name = self.y_axis_key.replace("_", " ")
+
+        return data, x_axis_name, y_axis_name
+
+    def _on_update_layers(self) -> None:
+        """
+        This is called when the layer selection changes by
+        ``self.update_layers()``.
+        """
+        # if hasattr(self, "_key_selection_widget"):
+        #     self._plugin_name_widget.reset_choices()
+        #     self._key_selection_widget.reset_choices()
+
+        # reset the axis keys
+        self._x_axis_key = None
+        self._y_axis_key = None
+
+def warp_to_list(data):
+    if isinstance(data, list):
+        return data
+    # If numpy array, make a list from axis=0
+    if isinstance(data, np.ndarray):
+        if len(data.shape) == 1:
+            data = data[np.newaxis,:]
+        data = data.tolist()
+    # If pandas dataframe, make a list from columns
+    if isinstance(data, pd.DataFrame):
+        data = data.T.values.tolist()
+    return data
+
+