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import holoviews as hv
from utils.app_context import AppContext
import pandas as pd
import warnings
import hvplot.pandas
import numpy as np
from utils.DashboardClasses import (
MainHeader,
MainArea,
OutputBox,
WarningBox,
HelpBox,
Footer,
WarningHandler,
FloatingPlot,
PlotsContainer,
)
from stingray import Crossspectrum
# Create a warning handler
def create_warning_handler():
warning_handler = WarningHandler()
warnings.showwarning = warning_handler.warn
return warning_handler
""" Header Section """
def create_quicklook_cross_spectrum_header(context: AppContext):
home_heading_input = pn.widgets.TextInput(
name="Heading", value="QuickLook Cross Spectrum"
)
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)
""" Float Panel """
def create_floatpanel_area(content, title):
return FloatingPlot(content=content, title=title)
""" Main Area Section """
def create_cross_spectrum_tab(
context: AppContext,
warning_handler,
):
event_list_dropdown_1 = pn.widgets.Select(
name="Select Event List 1",
options={name: i for i, (name, event) in enumerate(context.state.get_event_data())},
)
event_list_dropdown_2 = pn.widgets.Select(
name="Select Event List 2",
options={name: i for i, (name, event) in enumerate(context.state.get_event_data())},
)
dt_slider = pn.widgets.FloatSlider(
name="Select dt",
start=0.1,
end=1000,
step=0.1,
value=1,
)
norm_select = pn.widgets.Select(
name="Normalization",
options=["frac", "leahy", "abs", "none"],
value="leahy",
)
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)
def create_holoviews_plots(cs, event_list_name_1, event_list_name_2, dt, norm):
label = f"{event_list_name_1} vs {event_list_name_2} (dt={dt}, norm={norm})"
return hv.Curve((cs.freq, np.abs(cs.power)), label=label).opts(
xlabel="Frequency (Hz)",
ylabel="Cross Spectral Amplitude",
title=label,
width=600,
height=600,
shared_axes=False,
)
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_1, selected_event_list_index_2, dt, norm):
if selected_event_list_index_1 is not None and selected_event_list_index_2 is not None:
event_list_1 = context.state.get_event_data()[selected_event_list_index_1][1]
event_list_2 = context.state.get_event_data()[selected_event_list_index_2][1]
# Use spectrum service to create cross spectrum
result = context.services.spectrum.create_cross_spectrum(
event_list_1=event_list_1,
event_list_2=event_list_2,
dt=dt,
norm=norm
)
if not result["success"]:
context.update_container('output_box',
create_loadingdata_output_box(f"Error: {result['message']}")
)
return None, None
cs = result["data"]
# Use export service to convert to DataFrame
df_result = context.services.export.to_dataframe_cross_spectrum(cs)
if df_result["success"]:
return df_result["data"], cs
else:
context.update_container('output_box',
create_loadingdata_output_box(f"Error: {df_result['message']}")
)
return None, None
return None, None
def show_dataframe(event=None):
if not context.state.get_event_data():
context.update_container('output_box',
create_loadingdata_output_box("No loaded event data available.")
)
return
selected_event_list_index_1 = event_list_dropdown_1.value
selected_event_list_index_2 = event_list_dropdown_2.value
if selected_event_list_index_1 is None or selected_event_list_index_2 is None:
context.update_container('output_box',
create_loadingdata_output_box("Both event lists must be selected.")
)
return
dt = dt_slider.value
norm = norm_select.value
df, cs = create_dataframe(selected_event_list_index_1, selected_event_list_index_2, dt, norm)
if df is not None:
event_list_name_1 = context.state.get_event_data()[selected_event_list_index_1][0]
event_list_name_2 = context.state.get_event_data()[selected_event_list_index_2][0]
dataframe_title = f"{event_list_name_1} vs {event_list_name_2} (dt={dt}, norm={norm})"
dataframe_output = create_dataframe_panes(df, dataframe_title)
if dataframe_checkbox.value:
context.append_to_container('float_panel',
create_floatpanel_area(
content=dataframe_output,
title=f"DataFrame for {dataframe_title}",
)
)
else:
context.append_to_container('plots', dataframe_output)
else:
context.update_container('output_box',
create_loadingdata_output_box("Failed to create dataframe.")
)
def generate_cross_spectrum(event=None):
if not context.state.get_event_data():
context.update_container('output_box',
create_loadingdata_output_box("No loaded event data available.")
)
return
selected_event_list_index_1 = event_list_dropdown_1.value
selected_event_list_index_2 = event_list_dropdown_2.value
if selected_event_list_index_1 is None or selected_event_list_index_2 is None:
context.update_container('output_box',
create_loadingdata_output_box("Both event lists must be selected.")
)
return
dt = dt_slider.value
norm = norm_select.value
df, cs = create_dataframe(selected_event_list_index_1, selected_event_list_index_2, dt, norm)
if df is not None:
event_list_name_1 = context.state.get_event_data()[selected_event_list_index_1][0]
event_list_name_2 = context.state.get_event_data()[selected_event_list_index_2][0]
plot_hv = create_holoviews_plots(cs, event_list_name_1, event_list_name_2, dt, norm)
holoviews_output = create_holoviews_panes(plot_hv)
if floatpanel_plots_checkbox.value:
context.append_to_container('float_panel',
create_floatpanel_area(
content=holoviews_output, title=f"Cross Spectrum for {event_list_name_1} vs {event_list_name_2} (dt={dt}, norm={norm})"
)
)
else:
markdown_content = f"## Cross Spectrum for {event_list_name_1} vs {event_list_name_2} (dt={dt}, norm={norm})"
context.append_to_container('plots',
pn.FlexBox(
pn.pane.Markdown(markdown_content),
holoviews_output,
align_items="center",
justify_content="center",
flex_wrap="nowrap",
flex_direction="column",
)
)
else:
context.update_container('output_box',
create_loadingdata_output_box("Failed to create cross spectrum.")
)
generate_cross_spectrum_button = pn.widgets.Button(
name="Generate Cross Spectrum", button_type="primary"
)
generate_cross_spectrum_button.on_click(generate_cross_spectrum)
show_dataframe_button = pn.widgets.Button(
name="Show DataFrame", button_type="primary"
)
show_dataframe_button.on_click(show_dataframe)
tab_content = pn.Column(
event_list_dropdown_1,
event_list_dropdown_2,
dt_slider,
norm_select,
floatpanel_plots_checkbox,
dataframe_checkbox,
pn.Row(generate_cross_spectrum_button, show_dataframe_button),
)
return tab_content
def create_quicklook_cross_spectrum_main_area(context: AppContext):
warning_handler = create_warning_handler()
tabs_content = {
"Cross Spectrum": create_cross_spectrum_tab(
context=context,
warning_handler=warning_handler,
),
}
return MainArea(tabs_content=tabs_content)
def create_quicklook_cross_spectrum_area():
return PlotsContainer()
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