When multiple input maps are given to *r.univar*, the overall statistics
are calculated. This is useful for a time series of the same variable, as well as
for the case of a segmented/tiled dataset. Allowing multiple raster maps to be
specified saves the user from using a temporary raster map for the result of
*r.series* or *r.patch*.

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.
Extended statistics can be calculated using
*r.stats.quantile*.

Without a **zones** input raster, the *r.quantile* module will
be significantly more efficient for calculating percentiles with large maps.

For calculating univariate statistics from a raster map based on vector polygon
map and uploads statistics to new attribute columns, see
*v.rast.stats*.

g.region raster=elevation -p # standard output, along with extended statistics r.univar -e elevation percentile=98 total null and non-null cells: 2025000 total null cells: 0 Of the non-null cells: ---------------------- n: 2025000 minimum: 55.5788 maximum: 156.33 range: 100.751 mean: 110.375 mean of absolute values: 110.375 standard deviation: 20.3153 variance: 412.712 variation coefficient: 18.4057 % sum: 223510266.558102 1st quartile: 94.79 median (even number of cells): 108.88 3rd quartile: 126.792 98th percentile: 147.727 # script style output, along with extended statistics r.univar -ge elevation percentile=98 n=2025000 null_cells=0 cells=2025000 min=55.5787925720215 max=156.329864501953 range=100.751071929932 mean=110.375440275606 mean_of_abs=110.375440275606 stddev=20.3153233205981 variance=412.712361620436 coeff_var=18.4056555243368 sum=223510266.558102 first_quartile=94.79 median=108.88 third_quartile=126.792 percentile_98=147.727

g.region raster=basins -p

projection: 99 (Lambert Conformal Conic) zone: 0 datum: nad83 ellipsoid: a=6378137 es=0.006694380022900787 north: 228500 south: 215000 west: 630000 east: 645000 nsres: 10 ewres: 10 rows: 1350 cols: 1500 cells: 2025000

r.category basins

2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

d.mon wx0 d.rast map=elevation r.colors map=elevation color=grey d.rast map=basins r.colors map=basins color=bgyr d.legend raster=basins use=2,4,6,8,10,12,14,16,18,20,22,24,26,28,30 d.barscale

Then statistics for elevation can be calculated separately for every
zone, i.e. basin found in the **zones** parameter:

r.univar -t map=elevation zones=basins separator=comma \ output=basin_elev_zonal.csv

zone,label,non_null_cells,null_cells,min,max,range,mean,mean_of_abs, stddev,variance,coeff_var,sum,sum_abs2,,116975,0,55.5787925720215, 133.147018432617,77.5682258605957,92.1196971445722,92.1196971445722, 15.1475301152556,229.447668592576,16.4433129773355,10775701.5734863, 10775701.57348634,,75480,0,61.7890930175781,110.348838806152, 48.5597457885742,83.7808205765268,83.7808205765268,11.6451777476995, 135.610164775515,13.8995747088232,6323776.33711624,6323776.33711624 6,,1137,0,66.9641571044922,83.2070922851562,16.2429351806641, 73.1900814395257,73.1900814395257,4.15733292896409,17.2834170822492, 5.68018623179036,83217.1225967407,83217.12259674078,,80506, 0,67.4670791625977,147.161514282227, ...

Extended statistics by Martin Landa

Multiple input map support by Ivan Shmakov

Zonal loop by Markus Metz

*Last changed: $Date$*