NAME
r.quantile - Compute quantiles using two passes.
KEYWORDS
raster,
algebra,
statistics,
percentile,
quantile
SYNOPSIS
r.quantile
r.quantile --help
r.quantile [-r] input=name [quantiles=integer] [percentiles=float[,float,...]] [bins=integer] [file=name] [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:
- -r
- Generate recode rules based on quantile-defined intervals
- --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:
- input=name [required]
- Name of input raster map
- quantiles=integer
- Number of quantiles
- Default: 4
- percentiles=float[,float,...]
- List of percentiles
- bins=integer
- Number of bins to use
- Default: 1000000
- file=name
- Name for output file (if omitted or "-" output to stdout)
r.quantile computes quantiles in a manner suitable
for use with large amounts of data. It is using two passes.
Quantiles are calculated following algorithm 7 from Hyndman and Fan (1996),
which is also the default in R and numpy.
Calculation of elevation quantiles (printed to standard-out):
g.region raster=elevation -p
r.quantile input=elevation percentiles=0.1,1,10,25,50,75,90,99,99.9
The output of
r.quantile can be used for quantile classification:
g.region raster=elevation -p
r.quantile elevation quantiles=5 -r --quiet | r.recode elevation \
out=elev_quant5 rules=-
r.mode,
r.quant,
r.recode,
r.series,
r.stats,
r.stats.quantile,
r.stats.zonal,
r.statistics,
r.univar,
v.rast.stats
Glynn Clements
Markus Metz
SOURCE CODE
Available at:
r.quantile source code
(history)
Latest change: Thursday Jan 26 14:10:26 2023 in commit: cdd84c130cea04b204479e2efdc75c742efc4843
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GRASS Development Team,
GRASS GIS 8.4.1dev Reference Manual