Calculate recurrence quantification

Name : Calculate recurrence quantification

Description: This function performs Recurrence Quantification Analysis (RQA) on two specified signal columns from a DataFrame. RQA is a method used to analyze the recurrence patterns in time series data, providing insights into the dynamics and structure of the signals

Input : Dataframe - The latest version of uploaded data

Output : Dataframe - Link to the saved Dataframe and Summary of the actions performed

Mandatory and Non-mandatory/Advanced hyperparameters required for the function are listed below

Mandatory	Non-mandatory/Advanced hyperparameters
Columns	Threshold
Time col	Embedding dim
	Resample freq
	Save As New Table

Details of Hyperparameters are provided below

Name	Description	Accepted range/ values	Display Name
Columns	Numerical columns to select	Columns in the Dataframe	Columns to select
Time col	The time column used for resampling	Date time columns in the Dataframe	Datetime format columns
Embedding dim	The embedding dimension used for phase space reconstruction. This determines how the time series data is represented in a higher-dimensional space	(0,inf]	Embedding dimension
Resample freq	Parameter specifies the frequency at which the signal data should be resampled	'S','T','H','D',2D','M','Y' etc.	Resample frequency
Threshold	The distance threshold for defining recurrences. Distances below this threshold indicate a recurrence between the two signals	(0,1]	Threshold
Save As New Table	Option to choose whether the dataframe is to be saved as a new table	-