feat: Improve colors robustness for n topics

app.py

@@ -7,7 +7,8 @@ import tweepy
 import hdbscan
 
 from bokeh.models import ColumnDataSource, HoverTool, Label
-from bokeh.palettes import Category10 as Pallete
+from bokeh.palettes import Colorblind as Pallete
+from bokeh.palettes import Set3 as AuxPallete
 from bokeh.plotting import Figure, figure
 from bokeh.transform import factor_cmap
 
@@ -53,8 +54,11 @@ def draw_interactive_scatter_plot(
     labels_list = labels.astype(str).tolist()
     source = ColumnDataSource(data=dict(x=xs, y=ys, text=texts, label=values_list, original_label=labels_list))
     hover = HoverTool(tooltips=[(text_column, "@text{safe}"), (label_column, "@original_label")])
+    n_colors = len(set(values_color_set))
+    if n_colors not in Pallete:
+        Palette = AuxPallete
     p = figure(plot_width=800, plot_height=800, tools=[hover], title='2D visualization of tweets', background_fill_color="#fafafa")
-    colors = factor_cmap("label", palette=[Pallete[int(id_)] for id_ in values_color_set], factors=values_set)
+    colors = factor_cmap("label", palette=[Pallete[n_colors][int(id_)] for id_ in values_color_set], factors=values_set)
     p.circle("x", "y", size=12, source=source, fill_alpha=0.4, line_color=colors, fill_color=colors)
     p.axis.visible = False
     p.xgrid.grid_line_dash = "dashed"