Merge branch 'main' into extend_readme_zero_labels

README.md

@@ -4,7 +4,7 @@
 [![PyPI](https://img.shields.io/pypi/v/napari-clusters-plotter.svg?color=green)](https://pypi.org/project/napari-clusters-plotter)
 [![Python Version](https://img.shields.io/pypi/pyversions/napari-clusters-plotter.svg?color=green)](https://python.org)
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/napari-clusters-plotter/badges/version.svg)](https://anaconda.org/conda-forge/napari-clusters-plotter)
-[![tests](https://github.com/BiAPoL/napari-clusters-plotter/workflows/tests/badge.svg)](https://github.com/BiAPoL/napari-clusters-plotter/actions)
+[![tests](https://github.com/BiAPoL/napari-clusters-plotter/actions/workflows/test_and_deploy.yml/badge.svg)](https://github.com/BiAPoL/napari-clusters-plotter/actions/workflows/test_and_deploy.yml)
 [![codecov](https://codecov.io/gh/BiAPoL/napari-clusters-plotter/branch/main/graph/badge.svg?token=R6W2KO1NJ8)](https://codecov.io/gh/BiAPoL/napari-clusters-plotter)
 [![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
 [![Anaconda-Server Badge](https://anaconda.org/conda-forge/napari-clusters-plotter/badges/downloads.svg)](https://anaconda.org/conda-forge/napari-clusters-plotter)

napari_clusters_plotter/_Qt_code.py

@@ -11,7 +11,7 @@
 from matplotlib.figure import Figure
 from matplotlib.path import Path
 from matplotlib.widgets import LassoSelector, RectangleSelector, SpanSelector
-from napari.layers import Image, Labels
+from napari.layers import Image, Layer
 from qtpy.QtCore import QRect
 from qtpy.QtGui import QIcon
 from qtpy.QtWidgets import (
@@ -52,22 +52,22 @@ def measurements_container_and_list():
     return properties_container, properties_list
 
 
-def labels_container_and_selection():
+def layer_container_and_selection():
     """
-    Create a container and a dropdown widget to select the labels layer.
+    Create a container and a dropdown widget to select the layer.
 
     Returns
     -------
-    A tuple containing a QWidget for displaying the labels layer selection container,
-    and a QWidget containing the selection options for the labels layer.
+    A tuple containing a QWidget for displaying the layer selection container,
+    and a QWidget containing the selection options for the layer.
     """
-    labels_layer_selection_container = QWidget()
-    labels_layer_selection_container.setLayout(QHBoxLayout())
-    labels_layer_selection_container.layout().addWidget(QLabel("Labels layer"))
-    labels_select = create_widget(annotation=Labels, label="labels_layer")
-    labels_layer_selection_container.layout().addWidget(labels_select.native)
+    layer_selection_container = QWidget()
+    layer_selection_container.setLayout(QHBoxLayout())
+    layer_selection_container.layout().addWidget(QLabel("Layer"))
+    layer_select = create_widget(annotation=Layer, label="layer")
+    layer_selection_container.layout().addWidget(layer_select.native)
 
-    return labels_layer_selection_container, labels_select
+    return layer_selection_container, layer_select
 
 
 def image_container_and_selection():
@@ -528,6 +528,8 @@ def __init__(self, parent=None, width=7, height=4, manual_clustering_method=None
         self.match_napari_layout()
         self.xylim = None
         self.last_xy_labels = None
+        self.last_datax = None
+        self.last_datay = None
 
         super().__init__(self.fig)
         self.mpl_connect("draw_event", self.on_draw)
@@ -590,7 +592,17 @@ def make_2d_histogram(
         norm = None
         if log_scale:
             norm = "log"
-        h, xedges, yedges = np.histogram2d(data_x, data_y, bins=bin_number)
+        if (
+            self.histogram is not None
+            and np.array_equal(self.last_datax, data_x)
+            and np.array_equal(self.last_datay, data_y)
+        ):
+            (h, xedges, yedges) = self.histogram
+        else:
+            h, xedges, yedges = np.histogram2d(data_x, data_y, bins=bin_number)
+            self.last_datax = data_x
+            self.last_datay = data_y
+
         self.axes.imshow(
             h.T,
             extent=[xedges[0], xedges[-1], yedges[0], yedges[-1]],

napari_clusters_plotter/_clustering.py

@@ -9,13 +9,15 @@
 from napari_tools_menu import register_dock_widget
 from qtpy.QtWidgets import QHBoxLayout, QLabel, QLineEdit, QVBoxLayout, QWidget
 
+from ._defaults import DEFAULTS_CLUSTERING as DEFAULTS
+from ._defaults import ID_NAME
 from ._Qt_code import (
     button,
     checkbox,
     create_options_dropdown,
     float_sbox_containter_and_selection,
     int_sbox_containter_and_selection,
-    labels_container_and_selection,
+    layer_container_and_selection,
     measurements_container_and_list,
     title,
 )
@@ -30,21 +32,6 @@
     widgets_active,
 )
 
-DEFAULTS = {
-    "kmeans_nr_clusters": 2,
-    "kmeans_nr_iterations": 300,
-    "standardization": False,
-    "hdbscan_min_clusters_size": 5,
-    "hdbscan_min_nr_samples": 5,
-    "gmm_nr_clusters": 2,
-    "ms_quantile": 0.2,
-    "ms_n_samples": 50,
-    "ac_n_clusters": 2,
-    "ac_n_neighbors": 2,
-    "custom_name": "",
-}
-ID_NAME = "_CLUSTER_ID"
-
 
 @register_dock_widget(menu="Measurement post-processing > Clustering (ncp)")
 class ClusteringWidget(QWidget):
@@ -64,11 +51,11 @@ def __init__(self, napari_viewer):
 
         title_container = title("<b>Clustering</b>")
 
-        # widget for the selection of labels layer
+        # widget for the selection of layer
         (
-            labels_layer_selection_container,
-            self.labels_select,
-        ) = labels_container_and_selection()
+            layer_selection_container,
+            self.layer_select,
+        ) = layer_container_and_selection()
 
         # widget for the selection of properties to perform clustering
         (
@@ -215,7 +202,7 @@ def __init__(self, napari_viewer):
 
         # adding all widgets to the layout
         self.layout().addWidget(title_container)
-        self.layout().addWidget(labels_layer_selection_container)
+        self.layout().addWidget(layer_selection_container)
         self.layout().addWidget(choose_properties_container)
         self.layout().addWidget(update_container)
         self.layout().addWidget(self.clust_method_container)
@@ -235,7 +222,7 @@ def __init__(self, napari_viewer):
         self.layout().setSpacing(0)
 
         def run_clicked():
-            if self.labels_select.value is None:
+            if self.layer_select.value is None:
                 warnings.warn("No labels image was selected!")
                 return
 
@@ -248,7 +235,7 @@ def run_clicked():
                 return
 
             self.run(
-                self.labels_select.value,
+                self.layer_select.value,
                 [i.text() for i in self.properties_list.selectedItems()],
                 self.clust_method_choice_list.current_choice,
                 self.kmeans_nr_clusters.value,
@@ -271,14 +258,14 @@ def run_clicked():
         self.defaults_button.clicked.connect(partial(restore_defaults, self, DEFAULTS))
 
         # update measurements list when a new labels layer is selected
-        self.labels_select.changed.connect(
+        self.layer_select.changed.connect(
             partial(update_properties_list, self, [ID_NAME])
         )
 
         # update axes combo boxes automatically if features of
         # layer are changed
         self.last_connected = None
-        self.labels_select.changed.connect(self.activate_property_autoupdate)
+        self.layer_select.changed.connect(self.activate_property_autoupdate)
 
         # go through all widgets and change spacing
         for i in range(self.layout().count()):
@@ -343,17 +330,17 @@ def activate_property_autoupdate(self):
             self.last_connected.events.properties.disconnect(
                 partial(update_properties_list, self, [ID_NAME])
             )
-        self.labels_select.value.events.properties.connect(
+        self.layer_select.value.events.properties.connect(
             partial(update_properties_list, self, [ID_NAME])
         )
-        self.last_connected = self.labels_select.value
+        self.last_connected = self.layer_select.value
 
     def showEvent(self, event) -> None:
         super().showEvent(event)
         self.reset_choices()
 
     def reset_choices(self, event=None):
-        self.labels_select.reset_choices(event)
+        self.layer_select.reset_choices(event)
 
     # this function runs after the run button is clicked
     def run(

napari_clusters_plotter/_defaults.py

@@ -0,0 +1,36 @@
+DEFAULTS_CLUSTERING = {
+    "kmeans_nr_clusters": 2,
+    "kmeans_nr_iterations": 300,
+    "standardization": False,
+    "hdbscan_min_clusters_size": 5,
+    "hdbscan_min_nr_samples": 5,
+    "gmm_nr_clusters": 2,
+    "ms_quantile": 0.2,
+    "ms_n_samples": 50,
+    "ac_n_clusters": 2,
+    "ac_n_neighbors": 2,
+    "custom_name": "",
+}
+
+DEFAULTS_DIM_REDUCTION = {
+    "n_neighbors": 15,
+    "perplexity": 30,
+    "standardization": True,
+    "pca_components": 0,
+    "explained_variance": 95.0,
+    "n_components": 2,
+    # enabling multithreading for UMAP can result in crashing kernel if napari is opened from the Jupyter notebook,
+    # therefore by default the following value is False.
+    # See more: https://github.com/BiAPoL/napari-clusters-plotter/issues/169
+    "umap_separate_thread": False,
+    "min_distance_umap": 0.1,
+    "mds_n_init": 4,
+    "mds_metric": True,
+    "mds_max_iter": 300,
+    "mds_eps": 0.001,
+    "custom_name": "",
+}
+
+ID_NAME = "_CLUSTER_ID"
+_POINTER = "frame"
+EXCLUDE = [ID_NAME, _POINTER, "UMAP", "t-SNE", "PCA"]