r3.univar (1grass)

raster3d, voxel, statistics

r3.univar

r3.univar help

r3.univar [-get] input=name [zones=name] [output=name] [percentile=float[,float,...]] [fs=character] [--verbose] [--quiet]

Flags:

-g

Print the stats in shell script style

-e

Calculate extended statistics

-t

Table output format instead of standard output format

--verbose

Verbose module output

--quiet

Quiet module output

Parameters:

input=name

Name of input raster3d map

zones=name

3D Raster map used for zoning, must be of type CELL

output=name

Name for output file (if omitted or "-" output to stdout)

percentile=float[,float,...]

Percentile to calculate (requires extended statistics flag)

Options: 0-100

Default: 90

fs=character

Field separator

Special characters: space, comma, tab

Default: |

r3.univar calculates the univariate statistics for raster3d maps. This includes the number of cells counted, minimum and maximum cell values, range, arithmetic mean, population variance, standard deviation, and coefficient of variation. Statistics are calculated separately for every category/zone found in the zones input map if given. If the -e extended statistics flag is given the 1st quartile, median, 3rd quartile, and given percentile are calculated. If the -g flag is given the results are presented in a format suitable for use in a shell script. If the -t flag is given the results are presented in tabular format with the given field separator. The table can immediately be converted to a vector attribute table which can then be linked to a vector, e.g. the vector that was rasterized to create the zones input raster.

As with most GRASS raster3d modules, r3.univar operates on the voxel array defined by the current 3d region settings, not the original extent and resolution of the input map. See g.region.

This module can use large amounts of system memory when the -e extended statistics flag is used with a very large region setting. If the region is too large the module should exit gracefully with a memory allocation error. Basic statistics can be calculated using any size input region.

mode, skewness, kurtosis

g.region, r.univar, r.average, r.median, r.mode, r.quantile, r.sum, r.series, r3.stats, v.rast.stats, r.statistics, v.univar

Soeren Gebbert

Code is based on r.univar from

Hamish Bowman, Otago University, New Zealand

and Martin Landa

Zonal loop by Markus Metz

Last changed: $Date: 2012-08-14 11:11:23 +0200 (Tue, 14 Aug 2012) $

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