Geografic-Information-System/raster/r.univar/r.univar.html

<h2>DESCRIPTION</h2>

<em>r.univar</em> calculates the univariate statistics of one or several raster
map(s). 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 <b>zones</b> input map if given.
If the <b>-e</b> extended statistics flag is given the 1st quartile, median,
3rd quartile, and given <b>percentile</b> are calculated.
If the <b>-g</b> flag is given the results are presented in a format suitable
for use in a shell script.
If the <b>-t</b> 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 <b>zones</b> input raster.
<p>
When multiple input maps are given to <em>r.univar</em>, 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 
<em>r.series</em> or <em>r.patch</em>.

<h2>NOTES</h2>

As with most GRASS raster modules, <em>r.univar</em> operates on the raster
array defined by the current region settings, not the original extent and
resolution of the input map. See <em><a href="g.region.html">g.region</a></em>.
<p>
This module can use large amounts of system memory when the <b>-e</b>
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.
<p>
Without a <b>zones</b> input raster, the <em>r.quantile</em> module will
be significantly more efficient for calculating percentiles with large maps.

<h2>EXAMPLE</h2>

Calculate the raster statistics for zones within a vector map coverage
and upload the results for mean, min and max back to the vector map:

<div class="code"><pre>
#### set the raster region to match the map
g.region vect=fields res=10 -ap

#### create rasterized version of vector map
v.to.rast in=fields out=fields.10m use=cat type=area labelcolumn=label
r.colors fields.10m color=random

#### perform analysis
r.univar -t map=elevation.10m zones=fields.10m | \
  cut -f1,5,6,8 -d'|' > fields_stats.txt


#### populate vector DB with stats

# create working copy of vector map
g.copy vect=fields,fields_stats

# create new attribute columns to hold output
v.db.addcol map=fields_stats \
  columns='mean_elev DOUBLE PRECISION, min_elev DOUBLE PRECISION, max_elev DOUBLE PRECISION'

# create SQL command file, and execute it
sed -e '1d' fields_stats.txt | awk -F'|' \
  '{print "UPDATE fields_stats SET min_elev = "$2", max_elev = "$3", \
  mean_elev = "$4" WHERE cat = "$1";"}' \
   > fields_stats_sqlcmd.txt

db.execute input=fields_stats_sqlcmd.txt
<!--

###### alternate method with db.in.ogr:  (needs work) ######

#### convert text file table to a database table
# not safe for commas in the label
tr '|' ',' &lt; fields_stats.txt > fields_stats.csv
echo '"Integer","String","Real","Real","Real"' > fields_stats.csvt

# import table
db.in.ogr dsn=fields_stats.csv output=fields_data

# view table
db.select fields_data

# remove temporary files
rm fields_stats.csv fields_stats.csvt fields_stats.txt


#### populate vector DB with stats

# create working copy of vector map
g.copy vect=fields,fields_stats

# create new attribute columns to hold output
v.db.addcol map=fields_stats \
  columns='mean_elev DOUBLE PRECISION, min_elev DOUBLE PRECISION, max_elev DOUBLE PRECISION'

# perform DB step  (broken)
## how to automatically collate by key column, ie copy between tables?
## SELECT INTO? JOIN?
echo "INSERT INTO fields_stats (mean_elev,min_elev,max_elev) SELECT mean,min,max FROM fields_data" | db.execute
-->

#### view completed table
v.db.select fields_stats
</pre></div>


<h2>TODO</h2>

<i>mode, skewness, kurtosis</i>

<h2>SEE ALSO</h2>

<em>
<a href="g.region.html">g.region</a>,
<a href="r3.univar.html">r3.univar</a>,
<a href="r.mode.html">r.mode</a>,
<a href="r.quantile.html">r.quantile</a>,
<a href="r.series.html">r.series</a>,
<a href="r.stats.html">r.stats</a>,
<a href="r.statistics.html">r.statistics</a>,
<a href="v.rast.stats.html">v.rast.stats</a>,
<a href="v.univar.html">v.univar</a>
</em>


<h2>AUTHORS</h2>

Hamish Bowman, Otago University, New Zealand<br>
Extended statistics by Martin Landa<br>
Multiple input map support by Ivan Shmakov<br>
Zonal loop by Markus Metz

<p><i>Last changed: $Date$</i>