[GRASS-SVN] r51265 - in grass/trunk/temporal: . t.rast.aggregate
svn_grass at osgeo.org
svn_grass at osgeo.org
Thu Apr 5 16:23:52 EDT 2012
Author: huhabla
Date: 2012-04-05 13:23:52 -0700 (Thu, 05 Apr 2012)
New Revision: 51265
Added:
grass/trunk/temporal/t.rast.aggregate/
grass/trunk/temporal/t.rast.aggregate/t.rast.aggregate.html
grass/trunk/temporal/t.rast.aggregate/t.rast.aggregate.py
grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.relative_time.sh
grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.sh
Removed:
grass/trunk/temporal/t.rast.aggregate/test.tr.aggregate.relative_time.sh
grass/trunk/temporal/t.rast.aggregate/test.tr.aggregate.sh
grass/trunk/temporal/t.rast.aggregate/tr.aggregate.html
grass/trunk/temporal/t.rast.aggregate/tr.aggregate.py
Modified:
grass/trunk/temporal/t.rast.aggregate/Makefile
Log:
Using new naming scheme
Modified: grass/trunk/temporal/t.rast.aggregate/Makefile
===================================================================
--- grass/trunk/temporal/tr.aggregate/Makefile 2012-04-04 21:20:55 UTC (rev 51264)
+++ grass/trunk/temporal/t.rast.aggregate/Makefile 2012-04-05 20:23:52 UTC (rev 51265)
@@ -1,6 +1,6 @@
MODULE_TOPDIR = ../../
-PGM = tr.aggregate
+PGM = t.rast.aggregate
include $(MODULE_TOPDIR)/include/Make/Script.make
Copied: grass/trunk/temporal/t.rast.aggregate/t.rast.aggregate.html (from rev 51264, grass/trunk/temporal/tr.aggregate/tr.aggregate.html)
===================================================================
Copied: grass/trunk/temporal/t.rast.aggregate/t.rast.aggregate.py (from rev 51264, grass/trunk/temporal/tr.aggregate/tr.aggregate.py)
===================================================================
--- grass/trunk/temporal/t.rast.aggregate/t.rast.aggregate.py (rev 0)
+++ grass/trunk/temporal/t.rast.aggregate/t.rast.aggregate.py 2012-04-05 20:23:52 UTC (rev 51265)
@@ -0,0 +1,176 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+############################################################################
+#
+# MODULE: tr.aggregate
+# AUTHOR(S): Soeren Gebbert
+#
+# PURPOSE: Create a new space time raster dataset from the aggregated data of an existing space time raster dataset
+# COPYRIGHT: (C) 2011 by the GRASS Development Team
+#
+# This program is free software under the GNU General Public
+# License (version 2). Read the file COPYING that comes with GRASS
+# for details.
+#
+#############################################################################
+
+#%module
+#% description: Create a new space time raster dataset from the aggregated data of an existing space time raster dataset
+#% keywords: temporal
+#% keywords: aggregation
+#%end
+
+#%option G_OPT_STRDS_INPUT
+#%end
+
+#%option G_OPT_T_WHERE
+#%end
+
+#%option
+#% key: granularity
+#% type: string
+#% description: The aggregation granularity, format absolute time "x years, x months, x weeks, x days, x hours, x minutes, x seconds" or a double value for relative time
+#% required: yes
+#% multiple: no
+#%end
+
+#%option
+#% key: output
+#% type: string
+#% description: Name of the output space time raster dataset
+#% required: yes
+#% multiple: no
+#%end
+
+#%option
+#% key: method
+#% type: string
+#% description: Aggregate operation to be performed on the raster maps
+#% required: yes
+#% multiple: no
+#% options: average,count,median,mode,minimum,min_raster,maximum,max_raster,stddev,range,sum,variance,diversity,slope,offset,detcoeff,quart1,quart3,perc90,quantile,skewness,kurtosis
+#% answer: average
+#%end
+
+#%option G_OPT_T_SAMPLE
+#%end
+
+#%option G_OPT_R_BASE
+#%end
+
+#%option
+#% key: nprocs
+#% type: integer
+#% description: The number of r.mapcalc processes to run in parallel
+#% required: no
+#% multiple: no
+#% answer: 2
+#%end
+
+#%flag
+#% key: n
+#% description: Register Null maps
+#%end
+
+from multiprocessing import Process
+import grass.script as grass
+import grass.temporal as tgis
+
+############################################################################
+
+def main():
+
+ # Get the options
+ input = options["input"]
+ output = options["output"]
+ where = options["where"]
+ gran = options["granularity"]
+ base = options["base"]
+ register_null = flags["n"]
+ method = options["method"]
+ sampling = options["sampling"]
+ nprocs = int(options["nprocs"])
+
+ # Make sure the temporal database exists
+ tgis.create_temporal_database()
+ # We need a database interface
+ dbif = tgis.sql_database_interface()
+ dbif.connect()
+
+ mapset = grass.gisenv()["MAPSET"]
+
+ if input.find("@") >= 0:
+ id = input
+ else:
+ id = input + "@" + mapset
+
+ sp = tgis.space_time_raster_dataset(id)
+
+ if sp.is_in_db() == False:
+ dbif.close()
+ grass.fatal(_("Space time %s dataset <%s> not found") % (sp.get_new_map_instance(None).get_type(), id))
+
+ sp.select(dbif)
+
+ if output.find("@") >= 0:
+ out_id = output
+ else:
+ out_id = output + "@" + mapset
+
+ # The new space time raster dataset
+ new_sp = tgis.space_time_raster_dataset(out_id)
+ if new_sp.is_in_db(dbif):
+ if grass.overwrite() == True:
+ new_sp.delete(dbif)
+ new_sp = tgis.space_time_raster_dataset(out_id)
+ else:
+ dbif.close()
+ grass.fatal(_("Space time raster dataset <%s> is already in the database, use overwrite flag to overwrite") % out_id)
+
+ temporal_type, semantic_type, title, description = sp.get_initial_values()
+ new_sp.set_initial_values(temporal_type, semantic_type, title, description)
+ new_sp.insert(dbif)
+
+ rows = sp.get_registered_maps("id,start_time", where, "start_time", dbif)
+
+ if not rows:
+ dbif.close()
+ grass.fatal(_("Space time raster dataset <%s> is empty") % out_id)
+
+ # Modify the start time to fit the granularity
+
+ if sp.is_time_absolute():
+ first_start_time = tgis.adjust_datetime_to_granularity( rows[0]["start_time"], gran)
+ else:
+ first_start_time = rows[0]["start_time"]
+
+ last_start_time = rows[len(rows) - 1]["start_time"]
+ next_start_time = first_start_time
+
+ count = 0
+ proc_count = 0
+ proc_list = []
+ while next_start_time <= last_start_time:
+ start = next_start_time
+ if sp.is_time_absolute():
+ end = tgis.increment_datetime_by_string(next_start_time, gran)
+ else:
+ end = next_start_time + int(gran)
+ next_start_time = end
+
+ input_map_names = tgis.collect_map_names(sp, dbif, start, end, sampling)
+
+ if input_map_names:
+ tgis.aggregate_raster_maps(sp, new_sp, mapset, input_map_names, base, start, end, count, method, register_null, dbif)
+
+ count += 1
+
+ # Update the spatio-temporal extent and the raster metadata table entries
+ new_sp.update_from_registered_maps(dbif)
+
+ dbif.close()
+
+if __name__ == "__main__":
+ options, flags = grass.parser()
+ main()
+
Copied: grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.relative_time.sh (from rev 51264, grass/trunk/temporal/tr.aggregate/test.tr.aggregate.relative_time.sh)
===================================================================
--- grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.relative_time.sh (rev 0)
+++ grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.relative_time.sh 2012-04-05 20:23:52 UTC (rev 51265)
@@ -0,0 +1,43 @@
+# Test the extraction of a subset of a space time raster input
+
+# We need to set a specific region in the
+# @preprocess step of this test.
+# The region setting should work for UTM and LL test locations
+g.region s=0 n=80 w=0 e=120 b=0 t=50 res=10 res3=10 -p3
+# Data generation
+r.mapcalc --o expr="prec_1 = rand(0, 550)"
+r.mapcalc --o expr="prec_2 = rand(0, 450)"
+r.mapcalc --o expr="prec_3 = rand(0, 320)"
+r.mapcalc --o expr="prec_4 = rand(0, 510)"
+r.mapcalc --o expr="prec_5 = rand(0, 300)"
+r.mapcalc --o expr="prec_6 = rand(0, 650)"
+
+t.create --o type=strds temporaltype=relative output=precip_abs1 title="A test" descr="A test"
+t.register -i type=rast input=precip_abs1 maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6 start=0 unit=days increment=3
+
+# The first @test
+
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=6 method=average sampling=start,during
+t.info type=strds input=precip_abs2
+r.info prec_sum_0
+r.info prec_sum_1
+r.info prec_sum_2
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=9 method=maximum sampling=start,during
+t.info type=strds input=precip_abs2
+r.info prec_sum_0
+r.info prec_sum_1
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=4 method=minimum sampling=start,during
+t.info type=strds input=precip_abs2
+r.info prec_sum_0
+r.info prec_sum_1
+r.info prec_sum_2
+r.info prec_sum_3
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=5 method=sum sampling=start,during
+t.info type=strds input=precip_abs2
+r.info prec_sum_0
+r.info prec_sum_1
+r.info prec_sum_2
+r.info prec_sum_3
+
+t.unregister type=rast maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6
+t.remove type=strds input=precip_abs1,precip_abs2
Copied: grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.sh (from rev 51264, grass/trunk/temporal/tr.aggregate/test.tr.aggregate.sh)
===================================================================
--- grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.sh (rev 0)
+++ grass/trunk/temporal/t.rast.aggregate/test.t.rast.aggregate.sh 2012-04-05 20:23:52 UTC (rev 51265)
@@ -0,0 +1,30 @@
+# Test the extraction of a subset of a space time raster input
+
+# We need to set a specific region in the
+# @preprocess step of this test.
+# The region setting should work for UTM and LL test locations
+g.region s=0 n=80 w=0 e=120 b=0 t=50 res=10 res3=10 -p3
+# Generate data
+r.mapcalc --o expr="prec_1 = rand(0, 550)"
+r.mapcalc --o expr="prec_2 = rand(0, 450)"
+r.mapcalc --o expr="prec_3 = rand(0, 320)"
+r.mapcalc --o expr="prec_4 = rand(0, 510)"
+r.mapcalc --o expr="prec_5 = rand(0, 300)"
+r.mapcalc --o expr="prec_6 = rand(0, 650)"
+
+t.create --o type=strds temporaltype=absolute output=precip_abs1 title="A test" descr="A test"
+t.register -i type=rast input=precip_abs1 maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6 start="2001-01-15 12:05:45" increment="14 days"
+
+# The first @test
+
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="2 days" method=average sampling=start,during
+t.info type=strds input=precip_abs2
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="1 months" method=maximum sampling=start,during
+t.info type=strds input=precip_abs2
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="2 months" method=minimum sampling=start,during
+t.info type=strds input=precip_abs2
+t.rast.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="3 months" method=sum sampling=start,during
+t.info type=strds input=precip_abs2
+
+t.unregister type=rast maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6
+t.remove type=strds input=precip_abs1,precip_abs2
Deleted: grass/trunk/temporal/t.rast.aggregate/test.tr.aggregate.relative_time.sh
===================================================================
--- grass/trunk/temporal/tr.aggregate/test.tr.aggregate.relative_time.sh 2012-04-04 21:20:55 UTC (rev 51264)
+++ grass/trunk/temporal/t.rast.aggregate/test.tr.aggregate.relative_time.sh 2012-04-05 20:23:52 UTC (rev 51265)
@@ -1,43 +0,0 @@
-# Test the extraction of a subset of a space time raster input
-
-# We need to set a specific region in the
-# @preprocess step of this test.
-# The region setting should work for UTM and LL test locations
-g.region s=0 n=80 w=0 e=120 b=0 t=50 res=10 res3=10 -p3
-# Data generation
-r.mapcalc --o expr="prec_1 = rand(0, 550)"
-r.mapcalc --o expr="prec_2 = rand(0, 450)"
-r.mapcalc --o expr="prec_3 = rand(0, 320)"
-r.mapcalc --o expr="prec_4 = rand(0, 510)"
-r.mapcalc --o expr="prec_5 = rand(0, 300)"
-r.mapcalc --o expr="prec_6 = rand(0, 650)"
-
-t.create --o type=strds temporaltype=relative output=precip_abs1 title="A test" descr="A test"
-t.register -i type=rast input=precip_abs1 maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6 start=0 unit=days increment=3
-
-# The first @test
-
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=6 method=average sampling=start,during
-t.info type=strds input=precip_abs2
-r.info prec_sum_0
-r.info prec_sum_1
-r.info prec_sum_2
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=9 method=maximum sampling=start,during
-t.info type=strds input=precip_abs2
-r.info prec_sum_0
-r.info prec_sum_1
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=4 method=minimum sampling=start,during
-t.info type=strds input=precip_abs2
-r.info prec_sum_0
-r.info prec_sum_1
-r.info prec_sum_2
-r.info prec_sum_3
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity=5 method=sum sampling=start,during
-t.info type=strds input=precip_abs2
-r.info prec_sum_0
-r.info prec_sum_1
-r.info prec_sum_2
-r.info prec_sum_3
-
-t.unregister type=rast maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6
-t.remove type=strds input=precip_abs1,precip_abs2
Deleted: grass/trunk/temporal/t.rast.aggregate/test.tr.aggregate.sh
===================================================================
--- grass/trunk/temporal/tr.aggregate/test.tr.aggregate.sh 2012-04-04 21:20:55 UTC (rev 51264)
+++ grass/trunk/temporal/t.rast.aggregate/test.tr.aggregate.sh 2012-04-05 20:23:52 UTC (rev 51265)
@@ -1,30 +0,0 @@
-# Test the extraction of a subset of a space time raster input
-
-# We need to set a specific region in the
-# @preprocess step of this test.
-# The region setting should work for UTM and LL test locations
-g.region s=0 n=80 w=0 e=120 b=0 t=50 res=10 res3=10 -p3
-# Generate data
-r.mapcalc --o expr="prec_1 = rand(0, 550)"
-r.mapcalc --o expr="prec_2 = rand(0, 450)"
-r.mapcalc --o expr="prec_3 = rand(0, 320)"
-r.mapcalc --o expr="prec_4 = rand(0, 510)"
-r.mapcalc --o expr="prec_5 = rand(0, 300)"
-r.mapcalc --o expr="prec_6 = rand(0, 650)"
-
-t.create --o type=strds temporaltype=absolute output=precip_abs1 title="A test" descr="A test"
-t.register -i type=rast input=precip_abs1 maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6 start="2001-01-15 12:05:45" increment="14 days"
-
-# The first @test
-
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="2 days" method=average sampling=start,during
-t.info type=strds input=precip_abs2
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="1 months" method=maximum sampling=start,during
-t.info type=strds input=precip_abs2
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="2 months" method=minimum sampling=start,during
-t.info type=strds input=precip_abs2
-tr.aggregate --o --v input=precip_abs1 output=precip_abs2 base=prec_sum granularity="3 months" method=sum sampling=start,during
-t.info type=strds input=precip_abs2
-
-t.unregister type=rast maps=prec_1,prec_2,prec_3,prec_4,prec_5,prec_6
-t.remove type=strds input=precip_abs1,precip_abs2
Deleted: grass/trunk/temporal/t.rast.aggregate/tr.aggregate.html
===================================================================
Deleted: grass/trunk/temporal/t.rast.aggregate/tr.aggregate.py
===================================================================
--- grass/trunk/temporal/tr.aggregate/tr.aggregate.py 2012-04-04 21:20:55 UTC (rev 51264)
+++ grass/trunk/temporal/t.rast.aggregate/tr.aggregate.py 2012-04-05 20:23:52 UTC (rev 51265)
@@ -1,176 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-############################################################################
-#
-# MODULE: tr.aggregate
-# AUTHOR(S): Soeren Gebbert
-#
-# PURPOSE: Create a new space time raster dataset from the aggregated data of an existing space time raster dataset
-# COPYRIGHT: (C) 2011 by the GRASS Development Team
-#
-# This program is free software under the GNU General Public
-# License (version 2). Read the file COPYING that comes with GRASS
-# for details.
-#
-#############################################################################
-
-#%module
-#% description: Create a new space time raster dataset from the aggregated data of an existing space time raster dataset
-#% keywords: temporal
-#% keywords: aggregation
-#%end
-
-#%option G_OPT_STRDS_INPUT
-#%end
-
-#%option G_OPT_T_WHERE
-#%end
-
-#%option
-#% key: granularity
-#% type: string
-#% description: The aggregation granularity, format absolute time "x years, x months, x weeks, x days, x hours, x minutes, x seconds" or a double value for relative time
-#% required: yes
-#% multiple: no
-#%end
-
-#%option
-#% key: output
-#% type: string
-#% description: Name of the output space time raster dataset
-#% required: yes
-#% multiple: no
-#%end
-
-#%option
-#% key: method
-#% type: string
-#% description: Aggregate operation to be performed on the raster maps
-#% required: yes
-#% multiple: no
-#% options: average,count,median,mode,minimum,min_raster,maximum,max_raster,stddev,range,sum,variance,diversity,slope,offset,detcoeff,quart1,quart3,perc90,quantile,skewness,kurtosis
-#% answer: average
-#%end
-
-#%option G_OPT_T_SAMPLE
-#%end
-
-#%option G_OPT_R_BASE
-#%end
-
-#%option
-#% key: nprocs
-#% type: integer
-#% description: The number of r.mapcalc processes to run in parallel
-#% required: no
-#% multiple: no
-#% answer: 2
-#%end
-
-#%flag
-#% key: n
-#% description: Register Null maps
-#%end
-
-from multiprocessing import Process
-import grass.script as grass
-import grass.temporal as tgis
-
-############################################################################
-
-def main():
-
- # Get the options
- input = options["input"]
- output = options["output"]
- where = options["where"]
- gran = options["granularity"]
- base = options["base"]
- register_null = flags["n"]
- method = options["method"]
- sampling = options["sampling"]
- nprocs = int(options["nprocs"])
-
- # Make sure the temporal database exists
- tgis.create_temporal_database()
- # We need a database interface
- dbif = tgis.sql_database_interface()
- dbif.connect()
-
- mapset = grass.gisenv()["MAPSET"]
-
- if input.find("@") >= 0:
- id = input
- else:
- id = input + "@" + mapset
-
- sp = tgis.space_time_raster_dataset(id)
-
- if sp.is_in_db() == False:
- dbif.close()
- grass.fatal(_("Space time %s dataset <%s> not found") % (sp.get_new_map_instance(None).get_type(), id))
-
- sp.select(dbif)
-
- if output.find("@") >= 0:
- out_id = output
- else:
- out_id = output + "@" + mapset
-
- # The new space time raster dataset
- new_sp = tgis.space_time_raster_dataset(out_id)
- if new_sp.is_in_db(dbif):
- if grass.overwrite() == True:
- new_sp.delete(dbif)
- new_sp = tgis.space_time_raster_dataset(out_id)
- else:
- dbif.close()
- grass.fatal(_("Space time raster dataset <%s> is already in the database, use overwrite flag to overwrite") % out_id)
-
- temporal_type, semantic_type, title, description = sp.get_initial_values()
- new_sp.set_initial_values(temporal_type, semantic_type, title, description)
- new_sp.insert(dbif)
-
- rows = sp.get_registered_maps("id,start_time", where, "start_time", dbif)
-
- if not rows:
- dbif.close()
- grass.fatal(_("Space time raster dataset <%s> is empty") % out_id)
-
- # Modify the start time to fit the granularity
-
- if sp.is_time_absolute():
- first_start_time = tgis.adjust_datetime_to_granularity( rows[0]["start_time"], gran)
- else:
- first_start_time = rows[0]["start_time"]
-
- last_start_time = rows[len(rows) - 1]["start_time"]
- next_start_time = first_start_time
-
- count = 0
- proc_count = 0
- proc_list = []
- while next_start_time <= last_start_time:
- start = next_start_time
- if sp.is_time_absolute():
- end = tgis.increment_datetime_by_string(next_start_time, gran)
- else:
- end = next_start_time + int(gran)
- next_start_time = end
-
- input_map_names = tgis.collect_map_names(sp, dbif, start, end, sampling)
-
- if input_map_names:
- tgis.aggregate_raster_maps(sp, new_sp, mapset, input_map_names, base, start, end, count, method, register_null, dbif)
-
- count += 1
-
- # Update the spatio-temporal extent and the raster metadata table entries
- new_sp.update_from_registered_maps(dbif)
-
- dbif.close()
-
-if __name__ == "__main__":
- options, flags = grass.parser()
- main()
-
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