Merge pull request #4 from melonora/jose_branch1

Jose branch1

README.md

@@ -33,6 +33,38 @@ You can install `napari-cell-gater` via [pip]:
 
 
 
+## How to use
+Writing this helps me organize my thoughts on what to do next
+
+1. Users will select the necesary directories: images, masks, and quantification directories.
+
+Assumptions:
+files inside these directories are named according to the samples name.
+For example, the image for sample 1, should be named "1.ome.tif"; the mask file should be named "1.tif"; and the quantification file "1.csv"
+
+2. Users will then select which channels to gate, default is all of them.
+
+3. Users will then select a sample, and a marker from dropdown menus.
+    Upon selecting sample and marker.
+    3 layers will load:
+        1. the nuclear stain of the image (we assume it is channel 0, perhaps we can allow users to pick which one to use with dropdown)
+        2. the segmentation mask (as a labels layer) (for large images this might be a problem; Cylinter solves this by pyrimidazing a binary label)
+        3. the channel_to_be_gated
+    a Widget will appear showing a scatter plot (default: x-axis=channel_to_be_gated intensity, y-axis=Area) (y-axis could be change to another column)
+    underneath the scatterplot a slider will appear, the position of the slider will show up as a vertical line in the scatter plot
+
+4. Users will then adjust the contrast with the Napari menu
+
+5. Users will drag the slider to what they think is correct
+
+6. User will click a button, which will then plot a points layer on top of the image.
+The points should be on the x,y coordenates of cells that have a channel intensity larger than the threshold picked by the slider.
+
+7. User will repeat steps 5 and 6 until satisfied
+
+8. User wil then click a button to save the gate for the current marker and sample.
+    Here either the next marker will load, or if all markers for a sample are done, go to next sample.
+    I prefer an automated switch, but we should allow a user to go back to sample_marker of interest for review.
 
 ## Contributing
 

src/cell_gater/model/data_model.py

@@ -21,7 +21,12 @@ class DataModel:
     _lower_bound_marker: str | None = field(default=None, init=False)
     _upper_bound_marker: str | None = field(default=None, init=False)
     _markers: Sequence[str] = field(default_factory=list, init=False)
+
     _active_marker: str | None = field(default=None, init=False)
+    _active_sample: str | None = field(default=None, init=False)
+
+    _gates: pd.DataFrame = field(default_factory=pd.DataFrame, init=False)
+    _current_gate: float = field(default_factory=float, init=False)
 
     def __post_init__(self) -> None:
         """Allow fields in the dataclass to emit events when changed."""

src/cell_gater/widgets/scatter_widget.py

@@ -1,15 +1,20 @@
 from typing import Any
 
+# for scatter plot
+import matplotlib.pyplot as plt
+from matplotlib.widgets import Slider
 from qtpy.QtCore import Qt
 from qtpy.QtWidgets import (
     QComboBox,
     QLabel,
+    QPushButton,
     QSizePolicy,
     QVBoxLayout,
     QWidget,
 )
 
 from cell_gater.model.data_model import DataModel
+from cell_gater.utils.misc import napari_notification
 
 
 class ScatterWidget(QWidget):
@@ -33,7 +38,8 @@ def __init__(self, model: DataModel) -> None:
         self.layout().addWidget(self.sample_selection_dropdown, 4, 1)
 
     def _on_sample_changed(self):
-        pass
+        """Set the active sample."""
+        self.model.active_sample = self.sample_selection_dropdown.currentText()
 
     def _set_samples_dropdown(self, event: Any) -> None:
         """Set the items for the samples dropdown QComboBox."""
@@ -45,3 +51,82 @@ def _set_samples_dropdown(self, event: Any) -> None:
             if len(self.model.samples) > 0:
                 self.sample_selection_dropdown.addItems([None])
                 self.sample_selection_dropdown.addItems(self.model.samples)
+
+    def plot_scatter_plot(self, model: DataModel) -> None:
+        """Plot the scatter plot."""
+        # check if sample and marker are selected
+        assert self.model.active_marker is not None
+        assert self.model.active_sample is not None
+
+        # get the data for the scatter plot
+        df = self.model.regionprops_df
+        df = df[df["sample_id"] == self.model.active_sample]
+
+        # plot the scatter plot
+        fig, ax = plt.subplots()
+        # plot scatter on canvas axis
+
+        # if desired_y_axis is None:
+        #     desired_y_axis = "Area"
+        # should this be through a dropdown widget? or datamodel attribute?
+
+        ax.scatter(
+            x=df[self.active_marker],
+            y=df["Area"],  # later change to desired_y_axis
+            color="steelblue",
+            ec="white",
+            lw=0.1,
+            alpha=1.0,
+            s=80000 / int(df.shape[0]),
+        )
+
+        ax.set_ylabel("Area")  # later change to desired_y_axis
+        ax.set_xlabel(f"{self.active_marker} intensity")
+
+        # add vertical line at current gate if it exists
+        if self.model.current_gate is not None:
+            ax.axvline(x=self.model.current_gate, color="red", linewidth=1.0, linestyle="--")
+
+        minimum = df[self.model.active_marker].min()
+        maximum = df[self.model.active_marker].max()
+        value_initial = df[self.model.active_marker].median()
+        value_step = minimum / 100
+
+        # add slider as an axis, underneath the scatter plot
+        axSlider = fig.add_axes([0.1, 0.01, 0.8, 0.03], facecolor="yellow")
+        slider = Slider(axSlider, "Gate", minimum, maximum, valinit=value_initial, valstep=value_step, color="black")
+
+        def update_gate(val):
+            self.model.current_gate = val
+            ax.axvline(x=self.model.current_gate, color="red", linewidth=1.0, linestyle="--")
+            napari_notification(f"Gate set to {val}")
+
+        slider.on_changed(update_gate)
+
+    # TODO add the plot to a widget and display it
+
+    def plot_points(self, model: DataModel) -> None:
+        """Plot positive cells in Napari."""
+        if self.model.active_marker is not None:
+            marker = self.model.active_marker
+        if self.model.active_sample is not None:
+            sample = self.model.active_sample
+
+        viewer = self.model.viewer
+        df = self.model.regionprops_df
+        df = df[df["sample_id"] == self.model.active_sample]
+        gate = self.model.gates.loc[marker, sample]
+
+        viewer.add_points(
+            df[df[marker] > gate][["X_centroid", "Y_centroid"]],
+            name=f"{gate} and its positive cells",
+            face_color="red",
+            edge_color="black",
+            size=15,
+        )
+
+    def plot_points_button(self):
+        """Plot points button."""
+        self.plot_points_button = QPushButton("Plot Points")
+        self.plot_points_button.clicked.connect(self.plot_points)
+        self.layout().addWidget(self.plot_points_button, 1, 2)  # not sure where to put this button