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t.rast.list(1grass) GRASS GIS User's Manual t.rast.list(1grass)

NAME

t.rast.list - Lists registered maps of a space time raster dataset.

KEYWORDS

temporal, map management, raster, list, time

SYNOPSIS

t.rast.list
t.rast.list --help
t.rast.list [-u] input=name [order=string[,string,...]] [columns=string[,string,...]] [where=sql_query] [method=string] [granule=string] [format=string] [separator=character] [output=name] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:


Suppress printing of column names

Allow output files to overwrite existing files

Print usage summary

Verbose module output

Quiet module output

Force launching GUI dialog

Parameters:


Name of the input space time raster dataset

Sort the space time dataset by category
Options: id, name, semantic_label, creator, mapset, temporal_type, creation_time, start_time, end_time, north, south, west, east, nsres, ewres, cols, rows, number_of_cells, min, max

Columns to be printed to stdout
Options: id, name, semantic_label, creator, mapset, temporal_type, creation_time, start_time, end_time, north, south, west, east, nsres, ewres, cols, rows, number_of_cells, min, max, interval_length, distance_from_begin

WHERE conditions of SQL statement without ’where’ keyword used in the temporal GIS framework
Example: start_time > ’2001-01-01 12:30:00’

Method used for data listing
Options: list, cols, comma, delta, deltagaps, gran
Default: list

The granule to be used for listing. The granule must be specified as string eg.: absolute time "1 months" or relative time "1"

Output format
Options: plain, line, json, yaml, csv

Field separator character between the output columns
Special characters: pipe, comma, space, tab, newline
Default: pipe

Name for output file

DESCRIPTION

List time stamped raster map layers that are registered in a space time raster dataset. t.rast.list provides several options to list map layers and their metadata. Listing of map layer can be ordered by metadata, metadata columns can be specified and SQL where conditions can be provided to select a map layer subset of the input space time raster dataset. Most of the raster map specific metadata is available for column selection, sorting and SQL where statements. Using the method option allows the specification of different methods to list map layers. Method list is the default option and sensitive to the column,order and where options.

To print interval length in days and distance from the begin use method delta. Method deltagap will additionally print temporal gaps between map layer. The gran method allows the listing of map layer sampled by a user defined granule. As default the granularity of the space time raster dataset is used for sampling.

While method list supports all columns except for interval_length and distance_from_begin, methods delta, deltagap, and gran support only the following columns: id, name, mapset, start_time, end_time, interval_length, and distance_from_begin. The option order is only available with method list.

Methods cols and comma are depreciated. The cols method is replaced by the plain format and the comma method is replaced by the line format.

The format option specifies the format of the output data. The default plain format will simply print user specified metadata columns of one map layer per line separated by a pipe by default. The line format will list fully qualified map names (name and mapset) as a comma-separated list of values that can be used as input for spatial modules. The csv format will print data in the CSV format using comma as the value separator (delimiter) and double quote for text field quoting. The json format generates JSON and, if the PyYAML package is installed, The yaml format generates YAML. The column (or item) separator can be specified with the separator option for plain, line, and csv.

EXAMPLES

This example shows several options that are available for map layers listing.

Default query

The following command is the default one, returning standard information like name, mapset, start_time, end_time of each map in the space time dataset

t.rast.list tempmean_monthly
name|mapset|start_time|end_time
2009_01_tempmean|climate_2000_2012|2009-01-01 00:00:00|2009-02-01 00:00:00
2009_02_tempmean|climate_2000_2012|2009-02-01 00:00:00|2009-03-01 00:00:00
....
2012_11_tempmean|climate_2000_2012|2012-11-01 00:00:00|2012-12-01 00:00:00
2012_12_tempmean|climate_2000_2012|2012-12-01 00:00:00|2013-01-01 00:00:00

Add more info

The following command let the user to choose the columns to show

t.rast.list tempmean_monthly columns=name,start_time,min,max
name|start_time|min|max
2009_01_tempmean|2009-01-01 00:00:00|-3.380823|7.426054
2009_02_tempmean|2009-02-01 00:00:00|-1.820261|8.006386
...
2009_01_tempmean|2009-01-01 00:00:00|-3.380823|7.426054
2009_02_tempmean|2009-02-01 00:00:00|-1.820261|8.006386

Filtering the result by value

In this example the result is filtered showing only the maps with max value major than 24

t.rast.list tempmean_monthly columns=name,start_time,min,max where="max > 24"
name|start_time|min|max
2009_06_tempmean|2009-06-01 00:00:00|15.962669|25.819681
2009_07_tempmean|2009-07-01 00:00:00|15.32852|26.103664
2009_08_tempmean|2009-08-01 00:00:00|16.37995|27.293282
....
2012_06_tempmean|2012-06-01 00:00:00|14.929379|24.000651
2012_07_tempmean|2012-07-01 00:00:00|18.455802|28.794653
2012_08_tempmean|2012-08-01 00:00:00|15.718526|26.151115

Filtering the result by time range

In this example the result is filtered showing only the maps which fall into a specified time range (from .. to):

t.rast.list tempmean_monthly columns=name,start_time,min,max \

where="start_time > ’2009-06-01 00:00:00’ and start_time < ’2012-08-01 00:00:00’" name|start_time|min|max 2009_06_tempmean|2009-06-01 00:00:00|15.962669|25.819681 2009_07_tempmean|2009-07-01 00:00:00|15.32852|26.103664 2009_08_tempmean|2009-08-01 00:00:00|16.37995|27.293282 .... 2012_06_tempmean|2012-06-01 00:00:00|14.929379|24.000651 2012_07_tempmean|2012-07-01 00:00:00|18.455802|28.794653 2012_08_tempmean|2012-08-01 00:00:00|15.718526|26.151115

Filtering the result by selecting recurring timestamps

In this example the result is filtered showing only the maps which fall into a specified recurring time range (here one month per year):

t.rast.list Tseasonal_fieldata_garda where="strftime(’%m’, start_time)=’06’"

Using method option

Method option is able to show raster in different way. By default cols value is used, the value comma will print only the list of maps inside the space time dataset:

t.rast.list method=comma input=tempmean_monthly
2009_01_tempmean@climate_2009_2012,2009_02_tempmean@climate_2009_2012,2009_03_tempmean@climate_2009_2012, \
2009_04_tempmean@climate_2009_2012,2009_05_tempmean@climate_2009_2012,2009_06_tempmean@climate_2009_2012, \
2009_07_tempmean@climate_2009_2012,2009_08_tempmean@climate_2009_2012,2009_09_tempmean@climate_2009_2012, \
2009_10_tempmean@climate_2009_2012,2009_11_tempmean@climate_2009_2012,2009_12_tempmean@climate_2009_2012, \
2010_01_tempmean@climate_2009_2012,2010_02_tempmean@climate_2009_2012,2010_03_tempmean@climate_2009_2012, \
2010_04_tempmean@climate_2009_2012,2010_05_tempmean@climate_2009_2012,2010_06_tempmean@climate_2009_2012, \
2010_07_tempmean@climate_2009_2012,2010_08_tempmean@climate_2009_2012,2010_09_tempmean@climate_2009_2012, \
2010_10_tempmean@climate_2009_2012,2010_11_tempmean@climate_2009_2012,2010_12_tempmean@climate_2009_2012, \
2011_01_tempmean@climate_2009_2012,2011_02_tempmean@climate_2009_2012,2011_03_tempmean@climate_2009_2012, \
2011_04_tempmean@climate_2009_2012,2011_05_tempmean@climate_2009_2012,2011_06_tempmean@climate_2009_2012, \
2011_07_tempmean@climate_2009_2012,2011_08_tempmean@climate_2009_2012,2011_09_tempmean@climate_2009_2012, \
2011_10_tempmean@climate_2009_2012,2011_11_tempmean@climate_2009_2012,2011_12_tempmean@climate_2009_2012, \
2012_01_tempmean@climate_2009_2012,2012_02_tempmean@climate_2009_2012,2012_03_tempmean@climate_2009_2012, \
2012_04_tempmean@climate_2009_2012,2012_05_tempmean@climate_2009_2012,2012_06_tempmean@climate_2009_2012, \
2012_07_tempmean@climate_2009_2012,2012_08_tempmean@climate_2009_2012,2012_09_tempmean@climate_2009_2012, \
2012_10_tempmean@climate_2009_2012,2012_11_tempmean@climate_2009_2012,2012_12_tempmean@climate_2009_2012
The delta value calculate the interval between maps and the distance from the first map:

t.rast.list method=delta input=tempmean_monthly
id|name|mapset|start_time|end_time|interval_length|distance_from_begin
2009_01_tempmean@climate_2000_2012|2009_01_tempmean|climate_2000_2012|2009-01-01 00:00:00|2009-02-01 00:00:00|31.0|0.0
2009_02_tempmean@climate_2000_2012|2009_02_tempmean|climate_2000_2012|2009-02-01 00:00:00|2009-03-01 00:00:00|28.0|31.0
2009_03_tempmean@climate_2000_2012|2009_03_tempmean|climate_2000_2012|2009-03-01 00:00:00|2009-04-01 00:00:00|31.0|59.0
...
2012_10_tempmean@climate_2000_2012|2012_10_tempmean|climate_2000_2012|2012-10-01 00:00:00|2012-11-01 00:00:00|31.0|1369.0
2012_11_tempmean@climate_2000_2012|2012_11_tempmean|climate_2000_2012|2012-11-01 00:00:00|2012-12-01 00:00:00|30.0|1400.0
2012_12_tempmean@climate_2000_2012|2012_12_tempmean|climate_2000_2012|2012-12-01 00:00:00|2013-01-01 00:00:00|31.0|1430.0
The gran value it is used to return data sampled by a user defined granule. As default the granularity of the space time raster dataset is used for sampling.

t.rast.list  method=gran input=tempmean_monthly
id|name|mapset|start_time|end_time|interval_length|distance_from_begin
2009_01_tempmean@climate_2009_2012|2009_01_tempmean|climate_2009_2012|2009-01-01 00:00:00|2009-02-01 00:00:00|31.0|0.0
2009_02_tempmean@climate_2009_2012|2009_02_tempmean|climate_2009_2012|2009-02-01 00:00:00|2009-03-01 00:00:00|28.0|31.0
2009_03_tempmean@climate_2009_2012|2009_03_tempmean|climate_2009_2012|2009-03-01 00:00:00|2009-04-01 00:00:00|31.0|59.0
2009_04_tempmean@climate_2009_2012|2009_04_tempmean|climate_2009_2012|2009-04-01 00:00:00|2009-05-01 00:00:00|30.0|90.0
....
2012_09_tempmean@climate_2009_2012|2012_09_tempmean|climate_2009_2012|2012-09-01 00:00:00|2012-10-01 00:00:00|30.0|1339.0
2012_10_tempmean@climate_2009_2012|2012_10_tempmean|climate_2009_2012|2012-10-01 00:00:00|2012-11-01 00:00:00|31.0|1369.0
2012_11_tempmean@climate_2009_2012|2012_11_tempmean|climate_2009_2012|2012-11-01 00:00:00|2012-12-01 00:00:00|30.0|1400.0
2012_12_tempmean@climate_2009_2012|2012_12_tempmean|climate_2009_2012|2012-12-01 00:00:00|2013-01-01 00:00:00|31.0|1430.0

t.rast.list  method=gran input=tempmean_monthly gran="2 months"
id|name|mapset|start_time|end_time|interval_length|distance_from_begin
2009_01_tempmean@climate_2009_2012|2009_01_tempmean|climate_2009_2012|2009-01-01 00:00:00|2009-03-01 00:00:00|59.0|0.0
2009_03_tempmean@climate_2009_2012|2009_03_tempmean|climate_2009_2012|2009-03-01 00:00:00|2009-05-01 00:00:00|61.0|59.0
2009_05_tempmean@climate_2009_2012|2009_05_tempmean|climate_2009_2012|2009-05-01 00:00:00|2009-07-01 00:00:00|61.0|120.0
....
2012_07_tempmean@climate_2009_2012|2012_07_tempmean|climate_2009_2012|2012-07-01 00:00:00|2012-09-01 00:00:00|62.0|1277.0
2012_09_tempmean@climate_2009_2012|2012_09_tempmean|climate_2009_2012|2012-09-01 00:00:00|2012-11-01 00:00:00|61.0|1339.0
2012_11_tempmean@climate_2009_2012|2012_11_tempmean|climate_2009_2012|2012-11-01 00:00:00|2013-01-01 00:00:00|61.0|1400.0
For the deltagaps value you can see the example for space time vector dataset t.vect.list

Reading raster names in Python

result = json.loads(

gs.read_command(
"t.rast.list", input="tempmean_monthly", format="json"
) ) for item in result["data"]:
print(item["name"])

Filtering the result by semantic label

Semantic label can be assigned to raster maps by r.semantic.label module or even when registrating raster maps into STRDS by t.register.

Name of STRDS can be extended by semantic label used for filtering. Name of STRDS and semantic label is split by a single dot.

t.rast.list input=test.S2_1
Note that semantic label filtering is supported by all temporal modules.

Also note that only STRDS can be filtered by semantic label, see r.semantic.label for current limitations.

SEE ALSO

g.list, t.create, t.info, t.list, t.rast3d.list, t.vect.list

Temporal data processing Wiki

AUTHOR

Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

SOURCE CODE

Available at: t.rast.list source code (history)

Accessed: Sunday Jan 22 07:37:45 2023

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