add bispectrum

modules/QuickLook/Bispectrum.py

@@ -0,0 +1,329 @@
+import panel as pn
+import holoviews as hv
+from utils.globals import loaded_event_data
+import pandas as pd
+import warnings
+import hvplot.pandas
+from stingray.bispectrum import Bispectrum
+from stingray import Lightcurve
+import matplotlib.pyplot as plt
+from utils.DashboardClasses import (
+    MainHeader,
+    MainArea,
+    OutputBox,
+    WarningBox,
+    HelpBox,
+    Footer,
+    WarningHandler,
+    FloatingPlot,
+    PlotsContainer,
+)
+
+colors = [
+    "#1f77b4",
+    "#ff7f0e",
+    "#2ca02c",
+    "#d62728",
+    "#9467bd",
+    "#8c564b",
+    "#e377c2",
+    "#7f7f7f",
+    "#bcbd22",
+    "#17becf",
+    "#aec7e8",
+    "#ffbb78",
+    "#98df8a",
+    "#ff9896",
+    "#c5b0d5",
+    "#c49c94",
+    "#f7b6d2",
+    "#c7c7c7",
+    "#dbdb8d",
+    "#9edae5",
+]
+
+windows = [
+    "uniform", "parzen", "hamming", "hanning", "triangular", 
+    "blackmann", "welch", "flat-top"
+]
+
+
+# Create a warning handler
+def create_warning_handler():
+    warning_handler = WarningHandler()
+    warnings.showwarning = warning_handler.warn
+    return warning_handler
+
+
+""" Header Section """
+
+
+def create_quicklook_bispectrum_header(
+    header_container,
+    main_area_container,
+    output_box_container,
+    warning_box_container,
+    plots_container,
+    help_box_container,
+    footer_container,
+):
+    home_heading_input = pn.widgets.TextInput(
+        name="Heading", value="QuickLook Bispectrum"
+    )
+    home_subheading_input = pn.widgets.TextInput(name="Subheading", value="")
+
+    return MainHeader(heading=home_heading_input, subheading=home_subheading_input)
+
+
+""" Output Box Section """
+
+
+def create_loadingdata_output_box(content):
+    return OutputBox(output_content=content)
+
+
+""" Warning Box Section """
+
+
+def create_loadingdata_warning_box(content):
+    return WarningBox(warning_content=content)
+
+
+""" Main Area Section """
+
+
+def create_bispectrum_tab(
+    output_box_container,
+    warning_box_container,
+    warning_handler,
+    plots_container,
+    header_container,
+    float_panel_container,
+):
+    event_list_dropdown = pn.widgets.Select(
+        name="Select Event List(s)",
+        options={name: i for i, (name, event) in enumerate(loaded_event_data)},
+    )
+
+    dt_input = pn.widgets.FloatInput(
+        name="Select dt",
+        value=1.0,
+        step=0.0001,
+        start=0.0000000001,  # Prevents negative and zero values
+        end=1000.0,
+    )
+
+    maxlag_input = pn.widgets.IntInput(
+        name="Max Lag",
+        value=25,
+        step=1,
+        start=1,
+        end=100,
+    )
+
+    scale_select = pn.widgets.Select(
+        name="Scale",
+        options=["biased", "unbiased"],
+        value="unbiased",
+    )
+
+    window_select = pn.widgets.Select(
+        name="Window Type",
+        options=windows,
+        value="uniform",
+    )
+
+    floatpanel_plots_checkbox = pn.widgets.Checkbox(
+        name="Add Plot to FloatingPanel", value=False
+    )
+
+    dataframe_checkbox = pn.widgets.Checkbox(
+        name="Add DataFrame to FloatingPanel", value=False
+    )
+
+    def create_holoviews_panes(plot):
+        return pn.pane.HoloViews(plot, width=600, height=600, linked_axes=False)
+
+    def create_holoviews_plots(df, label, dt, window, scale, color_key=None):
+        plot = df.hvplot(x="Frequency", y="Magnitude", shared_axes=False, label=label)
+        return plot.opts(tools=['hover'], cmap=[color_key] if color_key else "viridis")
+
+    def create_dataframe_panes(df, title):
+        return pn.FlexBox(
+            pn.pane.Markdown(f"**{title}**"),
+            pn.pane.DataFrame(df, width=600, height=600),
+            align_items="center",
+            justify_content="center",
+            flex_wrap="nowrap",
+            flex_direction="column",
+        )
+
+    def create_dataframe(selected_event_list_index, dt, maxlag, scale, window):
+        if selected_event_list_index is not None:
+            event_list = loaded_event_data[selected_event_list_index][1]
+            lc = Lightcurve(event_list.time, event_list.counts)
+
+            bs = Bispectrum(lc, maxlag=maxlag, window=window, scale=scale)
+
+            df = pd.DataFrame(
+                {
+                    "Frequency": bs.freq,
+                    "Magnitude": bs.bispec_mag.flatten(),
+                    "Phase": bs.bispec_phase.flatten(),
+                }
+            )
+            return df, bs
+        return None, None
+
+    """ Float Panel """
+
+
+    def create_floatpanel_area(content, title):
+        return FloatingPlot(content=content, title=title)
+
+    def show_dataframe(event=None):
+        if not loaded_event_data:
+            output_box_container[:] = [
+                create_loadingdata_output_box("No loaded event data available.")
+            ]
+            return
+
+        selected_event_list_index = event_list_dropdown.value
+        if selected_event_list_index is None:
+            output_box_container[:] = [
+                create_loadingdata_output_box("No event list selected.")
+            ]
+            return
+
+        dt = dt_input.value
+        maxlag = maxlag_input.value
+        scale = scale_select.value
+        window = window_select.value
+        df, bs = create_dataframe(selected_event_list_index, dt, maxlag, scale, window)
+        if df is not None:
+            event_list_name = loaded_event_data[selected_event_list_index][0]
+            dataframe_title = f"{event_list_name} (dt={dt}, maxlag={maxlag}, scale={scale}, window={window})"
+            dataframe_output = create_dataframe_panes(df, dataframe_title)
+            if dataframe_checkbox.value:
+                float_panel_container.append(
+                    create_floatpanel_area(
+                        content=dataframe_output,
+                        title=f"DataFrame for {dataframe_title}",
+                    )
+                )
+            else:
+                plots_container.append(dataframe_output)
+        else:
+            output_box_container[:] = [
+                create_loadingdata_output_box("Failed to create dataframe.")
+            ]
+
+    def generate_bispectrum(event=None):
+        if not loaded_event_data:
+            output_box_container[:] = [
+                create_loadingdata_output_box("No loaded event data available.")
+            ]
+            return
+
+        selected_event_list_index = event_list_dropdown.value
+        if selected_event_list_index is None:
+            output_box_container[:] = [
+                create_loadingdata_output_box("No event list selected.")
+            ]
+            return
+
+        dt = dt_input.value
+        maxlag = maxlag_input.value
+        scale = scale_select.value
+        window = window_select.value
+        df, bs = create_dataframe(selected_event_list_index, dt, maxlag, scale, window)
+        if df is not None:
+            event_list_name = loaded_event_data[selected_event_list_index][0]
+
+            label = f"{event_list_name} (dt={dt}, maxlag={maxlag}, scale={scale}, window={window})"
+
+            plot_hv = create_holoviews_plots(df, label, dt, window, scale)
+            holoviews_output = create_holoviews_panes(plot_hv)
+
+            if floatpanel_plots_checkbox.value:
+                float_panel_container.append(
+                    create_floatpanel_area(
+                        content=holoviews_output,
+                        title=f"Bispectrum for {event_list_name} (dt={dt}, maxlag={maxlag}, scale={scale}, window={window})",
+                    )
+                )
+            else:
+                markdown_content = (
+                    f"## Bispectrum for {event_list_name} (dt={dt}, maxlag={maxlag}, scale={scale}, window={window})"
+                )
+                plots_container.append(
+                    pn.FlexBox(
+                        pn.pane.Markdown(markdown_content),
+                        holoviews_output,
+                        align_items="center",
+                        justify_content="center",
+                        flex_wrap="nowrap",
+                        flex_direction="column",
+                    )
+                )
+        else:
+            output_box_container[:] = [
+                create_loadingdata_output_box("Failed to create bispectrum.")
+            ]
+
+    generate_bispectrum_button = pn.widgets.Button(
+        name="Generate Bispectrum", button_type="primary"
+    )
+    generate_bispectrum_button.on_click(generate_bispectrum)
+
+    show_dataframe_button = pn.widgets.Button(
+        name="Show DataFrame", button_type="primary"
+    )
+    show_dataframe_button.on_click(show_dataframe)
+
+    tab1_content = pn.Column(
+        event_list_dropdown,
+        dt_input,
+        maxlag_input,
+        scale_select,
+        window_select,
+        floatpanel_plots_checkbox,
+        dataframe_checkbox,
+        pn.Row(generate_bispectrum_button, show_dataframe_button),
+    )
+    return tab1_content
+
+
+def create_quicklook_bispectrum_main_area(
+    header_container,
+    main_area_container,
+    output_box_container,
+    warning_box_container,
+    plots_container,
+    help_box_container,
+    footer_container,
+    float_panel_container,
+):
+    warning_handler = create_warning_handler()
+    tabs_content = {
+        "Bispectrum": create_bispectrum_tab(
+            output_box_container=output_box_container,
+            warning_box_container=warning_box_container,
+            warning_handler=warning_handler,
+            plots_container=plots_container,
+            header_container=header_container,
+            float_panel_container=float_panel_container,
+        ),
+    }
+
+    return MainArea(tabs_content=tabs_content)
+
+
+def create_quicklook_bispectrum_area():
+    """
+    Create the plots area for the quicklook bispectrum tab.
+
+    Returns:
+        PlotsContainer: An instance of PlotsContainer with the plots for the quicklook bispectrum tab.
+    """
+    return PlotsContainer()

modules/QuickLook/LightCurve.py

@@ -130,11 +130,13 @@ def create_holoviews_plots(df, label, dt, color_key=None):
             x="Time", y="Counts", shared_axes=False, label=f"{label} (dt={dt})"
         )
         if color_key:
-            return hd.datashade(
-                plot, aggregator=hd.ds.mean("Counts"), color_key=color_key
+            return hd.rasterize(plot, aggregator=hd.ds.mean("Counts"), color_key=color_key).opts(
+                tools=['hover'], cmap=[color_key], width=600, height=600
             )
         else:
-            return hd.datashade(plot, aggregator=hd.ds.mean("Counts"))
+            return hd.rasterize(plot, aggregator=hd.ds.mean("Counts")).opts(
+                tools=['hover'], width=600, height=600
+            )
 
     def create_dataframe_panes(df, title, dt):
         return pn.FlexBox(
@@ -254,7 +256,7 @@ def combine_selected_plots(event=None):
 
         # Define a color key for distinct colors
         color_key = {
-            index: color for index, color in zip(selected_event_list_indices, colors)
+            index: colors[i % len(colors)] for i, index in enumerate(selected_event_list_indices)
         }
 
         for index in selected_event_list_indices:
@@ -263,18 +265,20 @@ def combine_selected_plots(event=None):
             if df is not None:
                 event_list_name = loaded_event_data[index][0]
                 plot_hv = create_holoviews_plots(
-                    df, label=event_list_name, dt=dt, color_key={0: color_key[index]}
+                    df, label=event_list_name, dt=dt, color_key=color_key[index]
                 )
                 combined_plots.append(plot_hv)
                 combined_title.append(event_list_name)
 
         if combined_plots:
-            combined_plot = hv.Overlay(combined_plots).opts(shared_axes=False).collate()
+            # Use hv.Overlay and add legend manually
+            combined_plot = hv.Overlay(combined_plots).opts(
+                shared_axes=False, legend_position='right', width=600, height=600
+            ).collate()
+
             combined_pane = create_holoviews_panes(combined_plot)
 
             combined_title_str = " + ".join(combined_title)
-            # The line `if floatpanel_plots_checkbox.value:` is checking the value of a checkbox
-            # widget named `floatpanel_plots_checkbox`.
             if floatpanel_plots_checkbox.value:
                 new_floatpanel = create_floating_plot_container(
                     content=combined_pane, title=combined_title_str