PredictNonlinear

Description :
Evaluate SMap prediction skill for localization parameter theta (default from 0.01 to 9).

Python :

PredictNonlinear(dataFrame=None, columns='', target='', 
theta='', lib='', pred='', E=1, Tp=1, knn=0, tau=-1,
exclusionRadius=0, solver=None, embedded=False, 
validLib=[], noTime=False, ignoreNan=True, 
verbose=False, numProcess=4, showPlot=True)

R :

PredictNonlinear(pathIn="./", dataFile="", dataFrame=NULL, 
pathOut="./", predictFile="", lib="", pred="", theta="",
E=1, Tp=1, knn=0, tau=-1, exclusionRadius=0,
columns="", target="", embedded=FALSE, verbose=FALSE,
validLib=vector(), ignoreNan=TRUE, 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
theta	string	""	`theta` is a string of theta values with a delimit
pred	string or []	""	Pairs of prediction start stop row indices
er of [',' , '\t', '\n'].
E	int	0	Embedding dimension
Tp	int	1	Prediction Interval
tau	int	-1	Embedding time shift (time series rows)
exclusionRadius	int	0	Prediction vector exclusion radius
solver	sklearn.linear_model	None	Linear system solver
embedded	bool	False	Is data an embedding? If False, embed to E
validLib	bool []	[] or None	Conditional embedding
noTime	bool	False	Do not require first data column of time or index
ignoreNan	bool	True	Adjust lib to exlcude NaN
verbose	bool	False	Echo messages
numThreads	int	4	Number of threads to use
showPlot	bool	True	Show plot of theta vs Rho
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 :
theta is a list or string of theta values with a delimiter of [',', '\t', '\n']. See the Parameters table for parameter definitions.

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

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

Returns :
DataFrame with columns theta and rho.