GUIBRUSHR.GUI.Input_Output_Panels.Input_Panels.Frame_Cross_Correlation.Frame_sum_CC module

Cross-Correlation Sum Analysis Module

This module provides functionality for summing and analyzing cross-correlation data from multiple observations to determine planetary radial velocity parameters. The analysis includes Kp (planetary radial velocity semi-amplitude) determination and signal-to-noise ratio calculations.

class GUIBRUSHR.GUI.Input_Output_Panels.Input_Panels.Frame_Cross_Correlation.Frame_sum_CC.FrameSumCC(parent, color, row, column, path_default, frame_input, window, width_GUI, height_GUI, filters_and_table, widget_nights, **kwargs)[source]

Bases: MyPanel

Cross-Correlation Sum Analysis Panel

This class provides a GUI interface for performing cross-correlation analysis on multiple observation nights to determine planetary atmospheric parameters. It supports both retrieval mode (multi-night tar extraction) and manual mode (night-based processing).

__init__(parent, color, row, column, path_default, frame_input, window, width_GUI, height_GUI, filters_and_table, widget_nights, **kwargs)[source]

Initialize the FrameSumCC panel.

Parameters:

  • parent – Parent widget

  • color – Panel background color

  • row – Grid row position

  • column – Grid column position

  • path_default – Default file path

  • frame_input – Input frame widget

  • window – Main window reference

  • width_GUI – GUI width

  • height_GUI – GUI height

  • filters_and_table – Filter and table widget (for retrieval mode)

  • widget_nights – Night selection widget (for manual mode)

  • **kwargs – Additional keyword arguments

sum_cc()[source]

Main entry point for cross-correlation sum analysis.

Determines whether the run is a retrieval (multi-night tar extraction) or a manual/night-based process, gathers the necessary file paths and metadata, saves an exchange pkl, and launches sum_cc_background.py as a subprocess.

check_proc()[source]

Poll the background subprocess and update the GUI when it finishes.

Called repeatedly via window.after(500, …) until the process exits. On success, reads result_sum_cc.pkl and updates the plot widgets. On error, reads error_sum_cc.pkl and shows an error dialog.

show_sum_cc()[source]

Display previously generated cross-correlation sum plots.

This method loads and displays the most recent cross-correlation analysis results without recomputing them.