1r.series(1)                   Grass User's Manual                  r.series(1)
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NAME

6       r.series   -  Makes  each  output  cell  value a function of the values
7       assigned to the corresponding cells in the input raster map layers.
8

KEYWORDS

10       raster, aggregation, series
11

SYNOPSIS

13       r.series
14       r.series --help
15       r.series    [-nz]     [input=name[,name,...]]      [file=name]     out‐
16       put=name[,name,...]          method=string[,string,...]          [quan‐
17       tile=float[,float,...]]    [weights=float[,float,...]]    [range=lo,hi]
18       [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]
19
20   Flags:
21       -n
22           Propagate NULLs
23
24       -z
25           Do not keep files open
26
27       --overwrite
28           Allow output files to overwrite existing files
29
30       --help
31           Print usage summary
32
33       --verbose
34           Verbose module output
35
36       --quiet
37           Quiet module output
38
39       --ui
40           Force launching GUI dialog
41
42   Parameters:
43       input=name[,name,...]
44           Name of input raster map(s)
45
46       file=name
47           Input  file  with  one  raster map name and optional one weight per
48           line, field separator between name and weight is |
49
50       output=name[,name,...] [required]
51           Name for output raster map
52
53       method=string[,string,...] [required]
54           Aggregate operation
55           Options: average, count, median, mode, minimum,  min_raster,  maxi‐
56           mum,  max_raster,  stddev,  range, sum, variance, diversity, slope,
57           offset, detcoeff, tvalue, quart1, quart3, perc90,  quantile,  skew‐
58           ness, kurtosis
59
60       quantile=float[,float,...]
61           Quantile to calculate for method=quantile
62           Options: 0.0-1.0
63
64       weights=float[,float,...]
65           Weighting  factor for each input map, default value is 1.0 for each
66           input map
67
68       range=lo,hi
69           Ignore values outside this range
70

DESCRIPTION

72       r.series makes each output cell value a function of the values assigned
73       to the corresponding cells in the input raster map layers.
74
75       Following methods are available:
76
77           ·   average: average value
78
79           ·   count: count of non-NULL cells
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81           ·   median: median value
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83           ·   mode: most frequently occurring value
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85           ·   minimum: lowest value
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87           ·   maximum: highest value
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89           ·   range: range of values (max - min)
90
91           ·   stddev: standard deviation
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93           ·   sum: sum of values
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95           ·   variance: statistical variance
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97           ·   diversity: number of different values
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99           ·   slope: linear regression slope
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101           ·   offset: linear regression offset
102
103           ·   detcoeff: linear regression coefficient of determination
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105           ·   tvalue: linear regression t-value
106
107           ·   min_raster:  raster  map  number  with  the minimum time-series
108               value
109
110           ·   max_raster: raster map  number  with  the  maximum  time-series
111               value
112       Note  that  most  parameters accept multiple answers, allowing multiple
113       aggregates to be computed in a single run, e.g.:
114
115       r.series input=map1,...,mapN \
116                output=map.mean,map.stddev \
117             method=average,stddev
118       or:
119
120       r.series input=map1,...,mapN \
121                output=map.p10,map.p50,map.p90 \
122                method=quantile,quantile,quantile \
123                quantile=0.1,0.5,0.9
124       The same number of values must be provided for all options.
125

NOTES

127   No-data (NULL) handling
128       With -n flag, any cell for which any of the corresponding  input  cells
129       are  NULL  is automatically set to NULL (NULL propagation).  The aggre‐
130       gate function is not called,  so  all  methods  behave  this  way  with
131       respect to the -n flag.
132
133       Without  -n  flag, the complete list of inputs for each cell (including
134       NULLs) is passed to the aggregate function. Individual  aggregates  can
135       handle  data  as  they  choose. Mostly, they just compute the aggregate
136       over the non-NULL values, producing a NULL result only  if  all  inputs
137       are NULL.
138
139   Minimum and maximum analysis
140       The min_raster and max_raster methods generate a map with the number of
141       the raster map that holds the minimum/maximum value of the time-series.
142       The  numbering  starts  at  0 up to n for the first and the last raster
143       listed in input=, respectively.
144
145   Range analysis
146       If the range= option is given, any values which fall outside that range
147       will be treated as if they were NULL. The range parameter can be set to
148       low,high thresholds: values outside of this range are treated  as  NULL
149       (i.e.,  they  will  be  ignored  by  most aggregates, or will cause the
150       result to be NULL if -n is given). The low,high thresholds are floating
151       point,  so use -inf or inf for a single threshold (e.g., range=0,inf to
152       ignore negative values, or range=-inf,-200.4  to  ignore  values  above
153       -200.4).
154
155   Linear regression
156       Linear   regression   (slope,  offset,  coefficient  of  determination,
157       t-value) assumes equal time intervals. If the data have irregular  time
158       intervals,  NULL  raster  maps can be inserted into time series to make
159       time intervals equal (see example).
160
161   Quantiles
162       r.series can calculate arbitrary quantiles.
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164   Memory consumption
165       Memory usage is not an issue, as r.series only needs to  hold  one  row
166       from each map at a time.
167
168   Management of open file limits
169       The maximum number of raster maps that can be processed is given by the
170       user-specific limit of the operating system. For example, the soft lim‐
171       its  for  users are typically 1024 files. The soft limit can be changed
172       with e.g.  ulimit -n 4096 (UNIX-based operating systems) but it  cannot
173       be  higher  than  the  hard limit. If the latter is too low, you can as
174       superuser add an entry in:
175       /etc/security/limits.conf
176       # <domain>      <type>  <item>         <value>
177       your_username  hard    nofile          4096
178       This will raise the hard limit to 4096 files. Also have a look  at  the
179       overall limit of the operating system
180       cat /proc/sys/fs/file-max
181       which on modern Linux systems is several 100,000 files.
182
183       For  each  map  a  weighting  factor can be specified using the weights
184       option. Using weights can be meaningful when computing the sum or aver‐
185       age  of maps with different temporal extent. The default weight is 1.0.
186       The number of weights must be identical to the number of input maps and
187       must  have  the  same order. Weights can also be specified in the input
188       file.
189
190       Use the -z flag to analyze large amounts of raster maps without hitting
191       open files limit and the file option to avoid hitting the size limit of
192       command line arguments.  Note  that  the  computation  using  the  file
193       option  is  slower than with the input option.  For every single row in
194       the output map(s) all input maps are opened and closed. The  amount  of
195       RAM  will  rise  linearly  with the number of specified input maps. The
196       input and file options are mutually exclusive: the former  is  a  comma
197       separated list of raster map names and the latter is a text file with a
198       new line separated list of raster map names and  optional  weights.  As
199       separator between the map name and the weight the character "|" must be
200       used.
201

EXAMPLES

203       Using r.series with wildcards:
204       r.series input="`g.list pattern=’insitu_data.*’ sep=,`" \
205                output=insitu_data.stddev method=stddev
206
207       Note the g.list script also supports regular expressions for  selecting
208       map names.
209
210       Using r.series with NULL raster maps (in order to consider a "complete"
211       time series):
212       r.mapcalc "dummy = null()"
213       r.series in=map2001,map2002,dummy,dummy,map2005,map2006,dummy,map2008 \
214                out=res_slope,res_offset,res_coeff meth=slope,offset,detcoeff
215
216       Example for multiple aggregates to be computed in one run (3  resulting
217       aggregates from two input maps):
218       r.series in=one,two out=result_avg,res_slope,result_count meth=sum,slope,count
219
220       Example to use the file option of r.series:
221       cat > input.txt << EOF
222       map1
223       map2
224       map3
225       EOF
226       r.series file=input.txt out=result_sum meth=sum
227
228       Example  to  use  the  file  option  of r.series including weights. The
229       weight 0.75 should be assigned to map2. As the other maps do  not  have
230       weights we can leave it out:
231       cat > input.txt << EOF
232       map1
233       map2|0.75
234       map3
235       EOF
236       r.series file=input.txt out=result_sum meth=sum
237
238       Example  for  counting  the  number of days above a certain temperature
239       using daily average maps (’???’ as DOY wildcard):
240       # Approach for shell based systems
241       r.series input=`g.list rast pattern="temp_2003_???_avg" sep=,` \
242                output=temp_2003_days_over_25deg range=25.0,100.0 method=count
243       # Approach in two steps (e.g., for Windows systems)
244       g.list rast pattern="temp_2003_???_avg" output=mapnames.txt
245       r.series file=mapnames.txt \
246                output=temp_2003_days_over_25deg range=25.0,100.0 method=count
247

SEE ALSO

249        g.list, g.region,  r.quantile,  r.series.accumulate,  r.series.interp,
250       r.univar
251
252       Hints for large raster data processing
253

AUTHOR

255       Glynn Clements
256

SOURCE CODE

258       Available at: r.series source code (history)
259
260       Main  index  | Raster index | Topics index | Keywords index | Graphical
261       index | Full index
262
263       © 2003-2019 GRASS Development Team, GRASS GIS 7.8.2 Reference Manual
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267GRASS 7.8.2                                                        r.series(1)
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