xenial (1) r.series.1grass.gz

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NAME

       r.series   - Makes each output cell value a function of the values assigned to the corresponding cells in
       the input raster map layers.

KEYWORDS

       raster, aggregation, series

SYNOPSIS

       r.series
       r.series --help
       r.series [-nz]  [input=name[,name,...]]   [file=name]  output=name[,name,...]  method=string[,string,...]
       [quantile=float[,float,...]]     [weights=float[,float,...]]    [range=lo,hi]    [--overwrite]   [--help]
       [--verbose]  [--quiet]  [--ui]

   Flags:
       -n
           Propagate NULLs

       -z
           Do not keep files open

       --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[,name,...]
           Name of input raster map(s)

       file=name
           Input file with one raster map name and optional one weight per line, field  separator  between  name
           and weight is |

       output=name[,name,...] [required]
           Name for output raster map

       method=string[,string,...] [required]
           Aggregate operation
           Options:  average, count, median, mode, minimum, min_raster, maximum, max_raster, stddev, range, sum,
           variance, diversity, slope, offset, detcoeff, tvalue, quart1,  quart3,  perc90,  quantile,  skewness,
           kurtosis

       quantile=float[,float,...]
           Quantile to calculate for method=quantile
           Options: 0.0-1.0

       weights=float[,float,...]
           Weighting factor for each input map, default value is 1.0 for each input map

       range=lo,hi
           Ignore values outside this range

DESCRIPTION

       r.series makes each output cell value a function of the values assigned to the corresponding cells in the
       input raster map layers.

       Following methods are available:

           •   average: average value

           •   count: count of non-NULL cells

           •   median: median value

           •   mode: most frequently occurring value

           •   minimum: lowest value

           •   maximum: highest value

           •   range: range of values (max - min)

           •   stddev: standard deviation

           •   sum: sum of values

           •   variance: statistical variance

           •   diversity: number of different values

           •   slope: linear regression slope

           •   offset: linear regression offset

           •   detcoeff: linear regression coefficient of determination

           •   tvalue: linear regression t-value

           •   min_raster: raster map number with the minimum time-series value

           •   max_raster: raster map number with the maximum time-series value
       Note that most parameters accept multiple answers, allowing multiple  aggregates  to  be  computed  in  a
       single run, e.g.:

       r.series input=map1,...,mapN \
                output=map.mean,map.stddev \
             method=average,stddev
       or:

       r.series input=map1,...,mapN \
                output=map.p10,map.p50,map.p90 \
                method=quantile,quantile,quantile \
                quantile=0.1,0.5,0.9
       The same number of values must be provided for all options.

NOTES

   No-data (NULL) handling
       With  -n  flag,  any cell for which any of the corresponding input cells are NULL is automatically set to
       NULL (NULL propagation).  The aggregate function is not called, so  all  methods  behave  this  way  with
       respect to the -n flag.

       Without  -n  flag, the complete list of inputs for each cell (including NULLs) is passed to the aggregate
       function. Individual aggregates can handle data as they choose. Mostly, they just compute  the  aggregate
       over the non-NULL values, producing a NULL result only if all inputs are NULL.

   Minimum and maximum analysis
       The  min_raster  and  max_raster  methods generate a map with the number of the raster map that holds the
       minimum/maximum value of the time-series. The numbering starts at 0 up to n for the first  and  the  last
       raster listed in input=, respectively.

   Range analysis
       If  the  range= option is given, any values which fall outside that range will be treated as if they were
       NULL. The range parameter can be set to low,high thresholds: values outside of this range are treated  as
       NULL (i.e., they will be ignored by most aggregates, or will cause the result to be NULL if -n is given).
       The low,high thresholds are floating point, so use -inf or inf for a single threshold (e.g.,  range=0,inf
       to ignore negative values, or range=-inf,-200.4 to ignore values above -200.4).

   Linear regression
       Linear regression (slope, offset, coefficient of determination, t-value) assumes equal time intervals. If
       the data have irregular time intervals, NULL raster maps can be inserted into time series  to  make  time
       intervals equal (see example).

   Quantiles
       r.series can calculate arbitrary quantiles.

   Memory consumption
       Memory usage is not an issue, as r.series only needs to hold one row from each map at a time.

   Management of open file limits
       Number  of  raster  maps to be processed is given by the limit of the operating system. For example, both
       the hard and soft limits are typically 1024. The soft limit can be  changed  with  e.g.  ulimit  -n  1500
       (UNIX-based operating systems) but not higher than the hard limit. If it is too low, you can as superuser
       add an entry in
       /etc/security/limits.conf
       # <domain>      <type>  <item>         <value>
       your_username  hard    nofile          1500
       This would raise the hard limit to 1500 file. Be warned that more files open need more RAM. See also  the
       Wiki page Hints for large raster data processing.

       For  each  map  a  weighting  factor  can  be  specified  using  the weights option. Using weights can be
       meaningful when computing sum or average of maps with different temporal extent. The  default  weight  is
       1.0.  The number of weights must be identical with the number of input maps and must have the same order.
       Weights can also be specified in the input file.

       Use the file option to analyze large amount of raster maps without hitting open files limit and the  size
       limit of command line arguments. The computation is slower than the input option method. For every sinlge
       row in the output map(s) all input maps are opened and closed. The amount of RAM will  rise  linear  with
       the  number  of  specified input maps. The input and file options are mutually exclusive. Input is a text
       file with a new line separated list of raster map names and optional weights. As  separator  between  the
       map name and the weight the character "|" must be used.

EXAMPLES

       Using r.series with wildcards:
       r.series input="`g.list pattern=’insitu_data.*’ sep=,`" \
                output=insitu_data.stddev method=stddev

       Note the g.list script also supports regular expressions for selecting map names.

       Using r.series with NULL raster maps (in order to consider a "complete" time series):
       r.mapcalc "dummy = null()"
       r.series in=map2001,map2002,dummy,dummy,map2005,map2006,dummy,map2008 \
                out=res_slope,res_offset,res_coeff meth=slope,offset,detcoeff

       Example for multiple aggregates to be computed in one run (3 resulting aggregates from two input maps):
       r.series in=one,two out=result_avg,res_slope,result_count meth=sum,slope,count

       Example to use the file option of r.series:
       cat > input.txt << EOF
       map1
       map2
       map3
       EOF
       r.series file=input.txt out=result_sum meth=sum

       Example to use the file option of r.series including weights. The weight 0.75 should be assigned to map2.
       As the other maps do not have weights we can leave it out:
       cat > input.txt << EOF
       map1
       map2|0.75
       map3
       EOF
       r.series file=input.txt out=result_sum meth=sum

       Example for counting the number of days above a certain temperature using daily average  maps  (’???’  as
       DOY wildcard):
       # Approach for shell based systems
       r.series input=`g.list rast pattern="temp_2003_???_avg" sep=,` \
                output=temp_2003_days_over_25deg range=25.0,100.0 method=count
       # Approach in two steps (e.g., for Windows systems)
       g.list rast pattern="temp_2003_???_avg" output=mapnames.txt
       r.series file=mapnames.txt \
                output=temp_2003_days_over_25deg range=25.0,100.0 method=count

SEE ALSO

        g.list, g.region, r.quantile, r.series.accumulate, r.series.interp, r.univar

       Hints for large raster data processing

AUTHOR

       Glynn Clements

       Last changed: $Date: 2014-10-27 17:31:30 +0100 (Mon, 27 Oct 2014) $

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