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NAME

t.rast.kappa - Calculate kappa parameter in a space time raster dataset

KEYWORDS

temporal, raster, statistics

SYNOPSIS

t.rast.kappa
t.rast.kappa --help
t.rast.kappa [-klp] strds=name [output=name] [weight=string] [where=sql_query] [splittingday=string] [separator=character] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-k
Use r.kappa module instead SciKit-Learn Laboratory metrics.kappa
-l
Use memory swap
-p
Pixel by pixel analysis along different years
--overwrite
Allow output files to overwrite existing files
--help
Print usage summary
--verbose
Verbose module output
--quiet
Quiet module output
--ui
Force launching GUI dialog

Parameters:

strds=name [required]
Name of the input space time raster dataset
output=name
Name for the output file or "-" in case stdout should be used
Default: -
weight=string
Specifies the weight matrix for the calculation
Options: linear, quadratic
where=sql_query
WHERE conditions of SQL statement without 'where' keyword used in the temporal GIS framework
Example: start_time > '2001-01-01 12:30:00'
splittingday=string
Specifies the day to split the space time raster dataset in two groups, isotime format
separator=character
Field separator
Special characters: pipe, comma, space, tab, newline
Default: pipe

Table of contents

DESCRIPTION

The t.rast.kappa calculate kappa parameter in a space time raster dataset. It can calculate kappa values using two different algorithm, the one provided by r.kappa and the one provided by SciKit-Learn metrics library

EXAMPLE

Using r.kappa as backend

In this example t.rast.kappa is using r.kappa as backend, it return the results inside the /tmpem> directory into files with mystrds as prefix. weight option is not considered using r.kappa as backend.
        t.rast.kappa -k strds=mystrds output=/tmp/mystrds
    

Using SciKit-Learn as backend, text as output

In this example t.rast.kappa is using SciKit-Learn metrics library as backend, without output option, the module print the results to standard output
        t.rast.kappa strds=mystrds where="start_time >= '1999-12-01' weight='linear'
    

Using SciKit-Learn as backend, map as output

In this example t.rast.kappa is using SciKit-Learn metrics library as backend, the output is a map with the kappa values calculated for each pixel. The splittingday option is required to split the space time raster dataset in two groups and analyze them; the two groups must have the same number of maps, otherwise and error will be reported.
        t.rast.kappa -p strds=mystrds output=mykappa splittingday='2005-01-01'
    

SEE ALSO

r.kappa

AUTHOR

Luca Delucchi, Fondazione Edmund Mach

SOURCE CODE

Available at: t.rast.kappa source code (history)


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© 2003-2017 GRASS Development Team, GRASS GIS 7.2.3svn Reference Manual