Version 1.0.1:

- In the network plot: added the option to define a custom colormap when using metadata with categorical features.

Author: inbalpaz

SynTrackerVis_app/config.py

@@ -92,18 +92,19 @@
                              'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia']
 
 categorical_colormap_dict = {
-    'cet_glasbey': cc.glasbey,
-    'cet_glasbey_light': cc.glasbey_light,
-    'cet_glasbey_category10': bp.Category10[10],
+    'Glasbey': cc.glasbey,
+    'Glasbey_light': cc.glasbey_light,
+    'Glasbey_category10': bp.Category10[10],
     'Set1': bp.Set1[9],
-    'Set3': bp.Set3[12]
+    'Set3': bp.Set3[12],
+    'Define custom colormap': ['#000000']
 }
 
 continuous_colormap_dict = {
-    'cet_rainbow4': cc.m_rainbow4,
-    'cet_isolum': cc.isolum,
-    'plasma': bp.Plasma256,
-    'viridis': bp.Viridis256,
+    'Rainbow4': cc.m_rainbow4,
+    'Isolum': cc.isolum,
+    'Plasma': bp.Plasma256,
+    'Viridis': bp.Viridis256,
     'Blues': bp.Blues256,
     'Reds': bp.Reds256,
     'Greens': bp.Greens256,

SynTrackerVis_app/manual.md

@@ -172,6 +172,11 @@ The variety of colormaps available for selection changes accordingly and a color
 Note that only features which numerical values can be checked as continuous.
 - **Select colormap for nodes:** Select a colormap from the drop-down menu to color the nodes by the different groups of the selected metadata feature.
 A different set of colormaps is provided for categorical data and for continuous data.
+- **Define custom colormap:** For categorical features, it is also possible to define a custom list of colors for the different groups.
+This option becomes active when selecting the 'Define custom colormap' option from the colormaps drop-down menu.
+A list of colors, separated by commas, can be entered to the text-input widget. 
+The colors can be provided as standard names (like: red, blue) or Hex-RGB values (like: #FF0000).  
+A detailed guide for color notations: https://www.w3.org/TR/css-color-4/#named-colors .
 - **Color edges by feature (same/different):** Checking this option enables to select a feature, by which the edges (connections) 
  are divided into two categories and can be colored differently. 
 One category is the connections between samples that belong to the same group and the other is the connections between samples that belong to a different group (of the selected feature).

SynTrackerVis_app/plots_single_genome.py

@@ -1,4 +1,5 @@
 import time
+import re
 import numpy as np
 import pandas as pd
 import networkx as nx
@@ -129,7 +130,7 @@ def create_clustermap(matrix, cmap):
     return clustermap.figure
 
 
-def cretae_network_plot(network, is_metadata, nodes_feature, is_continuous, cmap, node_color, edge_color,
+def cretae_network_plot(network, is_metadata, nodes_feature, is_continuous, cmap, custom_cmap, node_color, edge_color,
                         is_edge_colorby, edges_feature, within_edge_color, between_edge_color, iterations, pos_dict,
                         show_labels, metadata_dict):
     iter_num = int(iterations)
@@ -193,15 +194,27 @@ def cretae_network_plot(network, is_metadata, nodes_feature, is_continuous, cmap
             print("Categorical feature")
 
             # Prepare the colors mapping for the legend
-            unique_groups = list(set([str(network.nodes[node][nodes_feature]) for node in network.nodes()]))
+            unique_groups = sorted(list(set([str(network.nodes[node][nodes_feature]) for node in network.nodes()])))
             groups_num = len(unique_groups)
             # Move the 'nan' group (if any) to the end of the list
             if 'nan' in unique_groups:
                 unique_groups.remove('nan')
                 unique_groups.append('nan')
             print(unique_groups)
+
             cmap_length = len(cmap)
             print("Cmap length = " + str(cmap_length))
+
+            # If the user defined a custom cmap - process it and turn it into a cmap
+            if cmap_length == 1:
+                custom_colors_list = custom_cmap
+                #cmap = custom_colors_list.split(',')
+                cmap = re.split(r'\s*,\s*', custom_colors_list)
+                cmap_length = len(cmap)
+                print("Custom cmap:")
+                print(cmap)
+                print("custom cmap length: " + str(cmap_length))
+
             group_to_color = {group: cmap[i % cmap_length] for i, group in enumerate(unique_groups)}
             colors = [group_to_color[str(network.nodes[node][nodes_feature])] for node in network.nodes()]
 
@@ -256,9 +269,9 @@ def cretae_network_plot(network, is_metadata, nodes_feature, is_continuous, cmap
     return hv_layout
 
 
-def cretae_network_plot_matplotlib(network, is_metadata, nodes_feature, is_continuous, cmap, node_color, edge_color,
-                                   is_edge_colorby, edges_feature, within_edge_color, between_edge_color, iterations,
-                                   pos_dict, show_labels, metadata_dict):
+def cretae_network_plot_matplotlib(network, is_metadata, nodes_feature, is_continuous, cmap, custom_cmap, node_color,
+                                   edge_color, is_edge_colorby, edges_feature, within_edge_color, between_edge_color,
+                                   iterations, pos_dict, show_labels, metadata_dict):
     iter_num = int(iterations)
     print("\nIn cretae_network_plot_matplotlib. Iterations number = " + str(iter_num))
     print("cmap: " + str(cmap))
@@ -340,7 +353,7 @@ def cretae_network_plot_matplotlib(network, is_metadata, nodes_feature, is_conti
         # Feature is categorical
         else:
             # Prepare the colors mapping for the matplotlib plot
-            unique_groups = list(set([str(network.nodes[node][nodes_feature]) for node in network.nodes()]))
+            unique_groups = sorted(list(set([str(network.nodes[node][nodes_feature]) for node in network.nodes()])))
             groups_num = len(unique_groups)
             # Move the 'nan' group (if any) to the end of the list
             if 'nan' in unique_groups:

SynTrackerVis_app/syntracker_vis_app.py

@@ -47,22 +47,15 @@ def change_collapse_state(selection_val):
         return False
 
 
-def change_continuous_state(chkbox_state):
-    if chkbox_state:
-        return config.continuous_colormap_dict
-    else:
-        return config.categorical_colormap_dict
-
-
-def change_continuous_state_for_value(chkbox_state):
-    if chkbox_state:
-        return config.continuous_colormap_dict['cet_rainbow4']
+def change_disabled_state_threshold(value):
+    if value == 'Define another threshold':
+        return False
     else:
-        return config.categorical_colormap_dict['cet_glasbey']
+        return True
 
 
-def change_disabled_state_threshold(value):
-    if value == 'Define another threshold':
+def change_disabled_state_custom_colormap(value):
+    if value == config.categorical_colormap_dict['Define custom colormap']:
         return False
     else:
         return True
@@ -152,6 +145,7 @@ def __init__(self):
         self.feature_select_watcher = ""
         self.continuous_watcher = ""
         self.colormap_watcher = ""
+        self.custom_colormap_watcher = ""
         self.nodes_colorby_watcher = ""
         self.visited_multi_genome_tab = 0
 
@@ -332,7 +326,7 @@ def __init__(self):
         self.use_metadata_network = pn.widgets.Checkbox(name='Use metadata for coloring', value=False)
         self.color_edges_by_feature = pn.widgets.Checkbox(name='Color edges by feature (same/different)', value=False)
         self.metadata_colorby_card = pn.Card(title='Set the coloring by metadata', header_background="#ffffff",
-                                             styles={'background': "#ffffff", 'margin': "10px", 'width': "300px"},
+                                             styles={'background': "#ffffff", 'margin': "10px", 'width': "335px"},
                                              hide_header=True, collapsed=pn.bind(change_disabled_state_inverse,
                                                                                  chkbox_state=self.use_metadata_network,
                                                                                  watch=True))
@@ -344,11 +338,18 @@ def __init__(self):
                                                          disabled=pn.bind(change_disabled_state_straight,
                                                                           chkbox_state=self.use_metadata_network,
                                                                           watch=True))
-        self.nodes_color_by = pn.widgets.Select(options=['Select feature'], name="Color nodes by:", width=100)
+        self.nodes_color_by = pn.widgets.Select(options=['Select feature'], name="Color nodes by:", width=130)
         self.is_continuous = pn.widgets.Checkbox(name='Continuous feature', value=False)
         self.nodes_colormap = pn.widgets.ColorMap(name="Select colormap for nodes:",
                                                   options=config.categorical_colormap_dict,
-                                                  value=config.categorical_colormap_dict['cet_glasbey'])
+                                                  value=config.categorical_colormap_dict['Glasbey'])
+        self.custom_colormap_input = pn.widgets.TextInput(name='Custom colormap: enter a list of colors separated by '
+                                                               'comma:',
+                                                          placeholder='color1, color2, color3, etc...',
+                                                          disabled=pn.bind(change_disabled_state_custom_colormap,
+                                                                           value=self.nodes_colormap,
+                                                                           watch=True)
+                                                          )
         self.edges_color_by = pn.widgets.Select(options=['Select feature'],
                                                 name="Color edges by:", width=100,
                                                 disabled=pn.bind(change_disabled_state_inverse,
@@ -532,6 +533,7 @@ def init_parameters(self):
         self.nodes_color_by.param.unwatch(self.nodes_colorby_watcher)
         self.is_continuous.param.unwatch(self.continuous_watcher)
         self.nodes_colormap.param.unwatch(self.colormap_watcher)
+        self.custom_colormap_input.param.unwatch(self.custom_colormap_watcher)
         self.box_plot_feature_select.param.unwatch(self.feature_select_watcher)
         self.genomes_select.param.unwatch(self.genomes_select_watcher)
         self.genomes_sort_select.param.unwatch(self.genomes_sort_select_watcher)
@@ -1057,11 +1059,12 @@ def create_single_genome_plots_by_APSS(self, event):
         if self.is_metadata:
             self.is_continuous.param.unwatch(self.continuous_watcher)
             self.nodes_colormap.param.unwatch(self.colormap_watcher)
+            self.custom_colormap_input.param.unwatch(self.custom_colormap_watcher)
             self.nodes_color_by.param.unwatch(self.nodes_colorby_watcher)
         self.network_threshold_input.value = config.APSS_connections_threshold_default
         self.is_continuous.value = False
         self.nodes_colormap.options = config.categorical_colormap_dict
-        self.nodes_colormap.value = config.categorical_colormap_dict['cet_glasbey']
+        self.nodes_colormap.value = config.categorical_colormap_dict['Glasbey']
 
         # Check if the requested genome and size have already been calculated. If so, fetch the specific dataframe
         if self.calculated_APSS_genome_size_dict[self.sampling_size]:
@@ -1408,18 +1411,22 @@ def change_continuous_state(self, event):
             # Feature is indeed really continuous
             else:
                 self.nodes_colormap.options = config.continuous_colormap_dict
-                self.nodes_colormap.value = config.continuous_colormap_dict['cet_rainbow4']
+                self.nodes_colormap.value = config.continuous_colormap_dict['Rainbow4']
 
         # Categorical feature
         else:
             #print("\nIn change_continuous_state. Categorical feature")
             self.nodes_colormap.options = config.categorical_colormap_dict
-            self.nodes_colormap.value = config.categorical_colormap_dict['cet_glasbey']
+            self.nodes_colormap.value = config.categorical_colormap_dict['Glasbey']
 
     def change_colormap(self, event):
         #print("\nIn change_colormap. Continuous state = " + str(self.is_continuous.value))
         self.update_network_plot()
 
+    def get_custom_colormap(self, event):
+        #print("\nIn change_colormap. Continuous state = " + str(self.is_continuous.value))
+        self.update_network_plot()
+
     def set_not_continuous(self, event):
         #print("\nIn set_not_continuous")
         self.is_continuous.value = False
@@ -1438,6 +1445,7 @@ def create_network_pane(self, selected_genome_and_size_avg_df):
                                     self.network_between_color)
         metadata_coloring_col = pn.Column(nodes_color_by_row,
                                           self.nodes_colormap,
+                                          self.custom_colormap_input,
                                           pn.Spacer(height=10),
                                           self.color_edges_by_feature,
                                           edges_color_by_row,
@@ -1580,6 +1588,8 @@ def create_network_pane(self, selected_genome_and_size_avg_df):
                                                                          onlychanged=True)
                 self.colormap_watcher = self.nodes_colormap.param.watch(self.change_colormap, 'value',
                                                                         onlychanged=True)
+                self.custom_colormap_watcher = self.custom_colormap_input.param.watch(self.get_custom_colormap,
+                                                                                      'value', onlychanged=True)
 
                 # Insert the features information as nodes attributes
                 for node in self.nodes_list:
@@ -1602,7 +1612,9 @@ def create_network_pane(self, selected_genome_and_size_avg_df):
                                            is_metadata=self.use_metadata_network,
                                            nodes_feature=self.nodes_color_by.value,
                                            is_continuous=self.is_continuous.value,
-                                           cmap=self.nodes_colormap.value, node_color=self.network_node_color,
+                                           cmap=self.nodes_colormap.value,
+                                           custom_cmap=self.custom_colormap_input.value,
+                                           node_color=self.network_node_color,
                                            edge_color=self.network_edge_color,
                                            is_edge_colorby=self.color_edges_by_feature,
                                            edges_feature=self.edges_color_by,
@@ -1654,7 +1666,9 @@ def download_network(self, event):
                                                is_metadata=self.use_metadata_network,
                                                nodes_feature=self.nodes_color_by.value,
                                                is_continuous=self.is_continuous.value,
-                                               cmap=self.nodes_colormap.value_name, node_color=self.network_node_color,
+                                               cmap=self.nodes_colormap.value_name,
+                                               custom_cmap=self.custom_colormap_input.value,
+                                               node_color=self.network_node_color,
                                                edge_color=self.network_edge_color,
                                                is_edge_colorby=self.color_edges_by_feature,
                                                edges_feature=self.edges_color_by,
@@ -1785,6 +1799,7 @@ def update_network_plot(self):
         self.network_plot_hv = pn.bind(ps.cretae_network_plot, network=self.network,
                                        is_metadata=self.use_metadata_network, nodes_feature=self.nodes_color_by.value,
                                        is_continuous=self.is_continuous.value, cmap=self.nodes_colormap.value,
+                                       custom_cmap=self.custom_colormap_input.value,
                                        node_color=self.network_node_color, edge_color=self.network_edge_color,
                                        is_edge_colorby=self.color_edges_by_feature, edges_feature=self.edges_color_by,
                                        within_edge_color=self.network_within_color,