EmbedDimension

Description :
Evaluate Simplex prediction skill for embedding dimensions from 1 to maxE.

Python :

EmbedDimension(dataFrame=None, columns='', target='',
maxE=10, lib='', pred='', Tp=1, tau=-1, exclusionRadius=0, 
embedded=False, validLib=[], noTime=False, ignoreNan=True,
verbose=False, numProcess=4, showPlot=True)

R :

EmbedDimension(pathIn="./", dataFile="", dataFrame=NULL,
pathOut="", predictFile="", lib="", pred="",
maxE=10, Tp=1, tau=-1, exclusionRadius=0,
columns="", target="",  embedded=FALSE, verbose=FALSE,
validLib=vector(), numThreads=4, showPlot=TRUE, noTime=FALSE)

Parameter	Type	Default	Purpose
dataFrame	pyEDM: pandas DataFrame rEDM: data.frame	None	Input DataFrame
columns	string or []	""	Column names for library
target	string	""	Prediction target column name
maxE	int	10	Evaluate embedding up to maxE
lib	string or []	""	Pairs of library start stop row indices
pred	string or []	""	Pairs of prediction start stop row indices
Tp	int	1	Prediction Interval
tau	int	-1	Embedding time shift (time series rows)
exclusionRadius	int	0	Prediction vector exclusion radius
embedded	bool	False	Is data an embedding
verbose	bool	False	Echo messages
validLib	bool []	[] or None	Conditional embedding
numThreads	int	4	Number of threads to use
showPlot	bool	True	Show plot of E vs Rho (pyEDM, rEDM)
noTime	bool	False	Do not require first data column of time or index
pathIn	string	"./"	Input data file path
dataFile	string	""	Data file name
pathOut	string	"./"	Output file path
predictFile	string	""	Prediction output file

Refer to the parameters table for general parameter definitions.

Notes :
Version 1.x: numThreads defines the number of worker threads for the maxE embeddings.

Version 2.x: numProcess defines the number of processes for the maxE embeddings.

Returns :
DataFrame with columns E and rho.