r3.univar(1)

NAME
r3.univar - Calculates univariate statistics from the non-null cells of a 3D raster map.
Statistics include number of cells counted, minimum and maximum cell values, range, arithmetic mean, population variance, standard deviation, coefficient of variation, and sum.

KEYWORDS
raster3d, statistics, univariate statistics

SYNOPSIS
r3.univar
r3.univar --help
r3.univar [-get] map=name [zones=name] [output=name] [percentile=float[,float,...]] [separator=character] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

  Flags:

-g
    Print the stats in shell script style

-e
    Calculate extended statistics

-t
    Table output format instead of standard output format

--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:

map=name [required]
    Name of 3D raster 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

separator=character
    Field separator
    Special characters: pipe, comma, space, tab, newline
    Default: pipe

DESCRIPTION
r3.univar calculates the univariate statistics for a 3D raster map. This includes the number of cells counted, minimum and maximum cell values, range, arithmetic mean, population variance, standard deviation, coefficient of variation, and sum. 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.

NOTES
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.

EXAMPLE
Computing univariate statistics of a 3D raster with randomly generated values:

# define volume
g.region n=10 s=0 w=0 e=10 b=0 t=10 res=1 res3=1 -p3
# generate random map
r3.mapcalc "random_0_1 = rand(0., 1)" -s
# compute univariate statistics, along with extended statistics
r3.univar -e map=random_0_1 percentile=98
 100%
total null and non-null cells: 1000
total null cells: 0
Of the non-null cells:
----------------------
n: 1000
minimum: 0.00053905
maximum: 0.998322
range: 0.997783
mean: 0.513676
mean of absolute values: 0.513676
standard deviation: 0.289969
variance: 0.0840821
variation coefficient: 56.4498 %
sum: 513.676463040334
1st quartile: 0.257654
median (even number of cells): 0.524313
3rd quartile: 0.763637
98th percentile: 0.982924
# script style output, along with extended statistics
r3.univar -ge map=random_0_1 percentile=98
n=1000
null_cells=0
cells=1000
min=0.000539049520323687
max=0.998322037540536
range=0.997782988020212
mean=0.513676463040334
mean_of_abs=0.513676463040334
stddev=0.289969154194666
variance=0.0840821103843701
coeff_var=56.4497646005434
sum=513.676463040334
first_quartile=0.257654
median=0.524313
third_quartile=0.763637
percentile_98=0.982924

TODO
To be implemented mode, skewness, kurtosis.

SEE ALSO
g.region, r.univar, r.mode, r.quantile, r.series, r3.stats, r.statistics, v.rast.stats, v.univar

AUTHORS
Soeren Gebbert
Code is based on r.univar from
Hamish Bowman, Otago University, New Zealand
and Martin Landa
Zonal loop by Markus Metz

SOURCE CODE

Available at: r3.univar source code (history)

Accessed: Saturday May 09 11:17:31 2026

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