setting up themes for scatter plot

src/sageworks/web_interface/components/plugins/confusion_matrix.py

@@ -183,4 +183,4 @@ def highlight_cm_square(click_data, current_figure):
 
     # Run the Unit Test on the Plugin
     model = CachedModel("wine-classification")
-    PluginUnitTest(ConfusionMatrix, input_data=model, theme="light").run()
+    PluginUnitTest(ConfusionMatrix, input_data=model, theme="dark").run()

src/sageworks/web_interface/components/plugins/scatter_plot.py

@@ -7,6 +7,7 @@
 # SageWorks Imports
 from sageworks.api import DataSource, FeatureSet
 from sageworks.web_interface.components.plugin_interface import PluginInterface, PluginPage, PluginInputType
+from sageworks.utils.theme_manager import ThemeManager
 
 
 class ScatterPlot(PluginInterface):
@@ -22,6 +23,9 @@ def __init__(self):
         self.hover_columns = []
         self.df = None
 
+        # Initialize the Theme Manager
+        self.theme_manager = ThemeManager()
+
         # Call the parent class constructor
         super().__init__()
 
@@ -178,14 +182,6 @@ def create_scatter_plot(self, df, x_col, y_col, color_col, regression_line=False
             go.Figure: A Plotly Figure object.
         """
 
-        # Define a custom color scale (blue -> yellow -> orange -> red)
-        color_scale = [
-            [0.0, "rgb(64, 64, 160)"],
-            [0.33, "rgb(48, 140, 140)"],
-            [0.67, "rgb(140, 140, 48)"],
-            [1.0, "rgb(160, 64, 64)"],
-        ]
-
         # Create an OpenGL Scatter Plot
         figure = go.Figure(
             data=go.Scattergl(
@@ -200,7 +196,7 @@ def create_scatter_plot(self, df, x_col, y_col, color_col, regression_line=False
                 marker=dict(
                     size=15,
                     color=df[color_col],  # Use the selected field for color
-                    colorscale=color_scale,
+                    colorscale=self.theme_manager.colorscale(),
                     colorbar=dict(title=color_col),
                     opacity=df[color_col].apply(
                         lambda x: 0.25 + 0.74 * (x - df[color_col].min()) / (df[color_col].max() - df[color_col].min())
@@ -216,36 +212,28 @@ def create_scatter_plot(self, df, x_col, y_col, color_col, regression_line=False
             max_val = max(df[x_col].max(), df[y_col].max())
             figure.add_shape(
                 type="line",
-                line=dict(width=4, color="rgba(1.0, 1.0, 1.0, 0.25)"),
+                line=dict(width=4, color="rgba(0.5, 0.5, 0.5, 0.5)"),
                 x0=min_val,
                 x1=max_val,
                 y0=min_val,
                 y1=max_val,
             )
 
-        # Apply the selected theme and set transparent background
-        plotly_theme = "plotly_dark" if self.dark_theme else "plotly"
+        # Update the layout
         figure.update_layout(
-            template=plotly_theme,
             margin={"t": 40, "b": 40, "r": 40, "l": 40, "pad": 0},
             xaxis=dict(
                 title=x_col,
                 tickformat=".2f",
                 showgrid=True,
-                gridcolor="rgba(100,100,100,0.25)",  # Medium grey
-                zerolinecolor="rgba(80, 80, 150, 0.5)",  # Blue color for the zero line
             ),
             yaxis=dict(
                 title=y_col,
                 tickformat=".2f",
                 showgrid=True,
-                gridcolor="rgba(100,100,100,0.25)",  # Medium grey
-                zerolinecolor="rgba(80, 80, 150, 0.5)",  # Blue color for the zero line
             ),
             showlegend=False,  # Remove legend
             dragmode="pan",
-            paper_bgcolor="rgba(0,0,0,0)",  # Set the paper background to transparent
-            plot_bgcolor="rgba(0,0,0,0)",  # Set the plot background to transparent
         )
         return figure
 
@@ -279,4 +267,4 @@ def update_graph(x_value, y_value, color_value, regression_line):
     from sageworks.web_interface.components.plugin_unit_test import PluginUnitTest
 
     # Run the Unit Test on the Plugin
-    PluginUnitTest(ScatterPlot).run()
+    PluginUnitTest(ScatterPlot, theme="light").run()