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@@ -87,273 +87,8 @@ def main():
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# Make sure the temporal database exists
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tgis.create_temporal_database()
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- # We need a database interface for fast computation
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- dbif = tgis.sql_database_interface_connection()
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- dbif.connect()
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-
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- mapset = grass.gisenv()["MAPSET"]
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-
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- input_name_list = inputs.split(",")
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-
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- # Process the first input
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- if input_name_list[0].find("@") >= 0:
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- id = input_name_list[0]
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- else:
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- id = input_name_list[0] + "@" + mapset
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-
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- first_input = tgis.space_time_raster_dataset(id)
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-
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- if first_input.is_in_db(dbif) == False:
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- dbif.close()
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- grass.fatal(_("Space time %s dataset <%s> not found") % (sp.get_new_map_instance(None).get_type(), id))
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-
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- # Fill the object with data from the temporal database
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- first_input.select(dbif)
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+ tgis.dataset_mapcalculator(inputs, output, "raster", expression, base, method, nprocs, register_null, spatial)
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- # All additional inputs in reverse sorted order to avoid wrong name substitution
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- input_name_list = input_name_list[1:]
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- input_name_list.sort()
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- input_name_list.reverse()
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- input_list = []
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-
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- for input in input_name_list:
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-
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- if input.find("@") >= 0:
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- id = input
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- else:
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- id = input + "@" + mapset
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-
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- sp = tgis.space_time_raster_dataset(id)
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-
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- if sp.is_in_db(dbif) == False:
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- dbif.close()
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- grass.fatal(_("Space time raster dataset <%s> not found in temporal database") % (id))
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-
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- sp.select(dbif)
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-
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- input_list.append(copy.copy(sp))
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-
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- # Create the new space time raster dataset
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- if output.find("@") >= 0:
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- out_id = output
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- else:
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- out_id = output + "@" + mapset
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-
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- new_sp = tgis.space_time_raster_dataset(out_id)
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-
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- # Check if in database
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- if new_sp.is_in_db(dbif):
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- if grass.overwrite() == False:
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- dbif.close()
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- grass.fatal(_("Space time raster dataset <%s> is already in database, use overwrite flag to overwrite") % out_id)
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-
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- # Sample all inputs by the first input and create a sample matrix
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- if spatial:
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- grass.message(_("Start spatio-temporal sampling"))
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- else:
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- grass.message(_("Start temporal sampling"))
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- map_matrix = []
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- id_list = []
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- sample_map_list = []
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- # First entry is the first dataset id
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- id_list.append(first_input.get_name())
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-
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- if len(input_list) > 0:
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- has_samples = False
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- for dataset in input_list:
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- list = dataset.sample_by_dataset(stds=first_input, method=method, spatial=spatial, dbif=dbif)
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-
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- # In case samples are not found
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- if not list and len(list) == 0:
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- dbif.close()
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- grass.message(_("No samples found for map calculation"))
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- return 0
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-
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- # The fist entries are the samples
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- map_name_list = []
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- if has_samples == False:
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- for entry in list:
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- granule = entry["granule"]
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- # Do not consider gaps
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- if granule.get_id() == None:
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- continue
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- sample_map_list.append(granule)
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- map_name_list.append(granule.get_name())
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- # Attach the map names
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- map_matrix.append(copy.copy(map_name_list))
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- has_samples = True
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-
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- map_name_list = []
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- for entry in list:
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- maplist = entry["samples"]
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- granule = entry["granule"]
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-
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- # Do not consider gaps in the sampler
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- if granule.get_id() == None:
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- continue
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-
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- if len(maplist) > 1:
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- grass.warning(_("Found more than a single map in a sample granule. "\
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- "Only the first map is used for computation. "\
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- "Use t.rast.aggregate.ds to create synchronous datasets."))
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-
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- # Store all maps! This includes non existent maps, identified by id == None
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- map_name_list.append(maplist[0].get_name())
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-
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- # Attach the map names
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- map_matrix.append(copy.copy(map_name_list))
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-
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- id_list.append(dataset.get_name())
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- else:
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- list = first_input.get_registered_maps_as_objects(dbif=dbif)
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-
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- if list == None:
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- dbif.close()
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- grass.message(_("No maps in input dataset"))
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- return 0
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-
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- map_name_list = []
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- for map in list:
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- map_name_list.append(map.get_name())
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- sample_map_list.append(map)
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-
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- # Attach the map names
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- map_matrix.append(copy.copy(map_name_list))
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-
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-
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- # Needed for map registration
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- map_list = []
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-
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- if len(map_matrix) > 0:
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-
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- grass.message(_("Start r.mapcalc computation"))
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-
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- count = 0
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- # Get the number of samples
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- num = len(map_matrix[0])
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-
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- # Parallel processing
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- proc_list = []
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- proc_count = 0
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-
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- # For all samples
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- for i in range(num):
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-
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- count += 1
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- grass.percent(count, num, 1)
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-
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- # Create the r.mapcalc statement for the current time step
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- map_name = "%s_%i" % (base, count)
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- expr = "%s = %s" % (map_name, expression)
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-
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- # Check that all maps are in the sample
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- valid_maps = True
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- # Replace all dataset names with their map names of the current time step
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- for j in range(len(map_matrix)):
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- if map_matrix[j][i] == None:
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- valid_maps = False
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- break
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- # Substitute the dataset name with the map name
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- expr = expr.replace(id_list[j], map_matrix[j][i])
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-
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- # Proceed with the next sample
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- if valid_maps == False:
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- continue
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-
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- # Create the new map id and check if the map is already in the database
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- map_id = map_name + "@" + mapset
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-
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- new_map = first_input.get_new_map_instance(map_id)
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-
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- # Check if new map is in the temporal database
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- if new_map.is_in_db(dbif):
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- if grass.overwrite() == True:
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- # Remove the existing temporal database entry
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- new_map.delete(dbif)
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- new_map = first_input.get_new_map_instance(map_id)
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- else:
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- grass.error(_("Raster map <%s> is already in temporal database, use overwrite flag to overwrite"))
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- continue
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-
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- # Set the time stamp
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- if sample_map_list[i].is_time_absolute():
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- start, end, tz = sample_map_list[i].get_absolute_time()
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- new_map.set_absolute_time(start, end, tz)
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- else:
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- start, end = sample_map_list[i].get_relative_time()
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- new_map.set_relative_time(start, end)
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-
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- map_list.append(new_map)
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-
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- # Start the parallel r.mapcalc computation
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- grass.verbose(_("Apply r.mapcalc expression: \"%s\"") % expr)
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-
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- proc_list.append(Process(target=run_mapcalc, args=(expr,)))
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- proc_list[proc_count].start()
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- proc_count += 1
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-
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- if proc_count == nprocs:
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- proc_count = 0
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- exitcodes = 0
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- for proc in proc_list:
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- proc.join()
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- exitcodes += proc.exitcode
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-
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- if exitcodes != 0:
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- dbif.close()
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- grass.fatal(_("Error while r.mapcalc computation"))
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-
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- # Empty process list
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- proc_list = []
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-
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- # Register the new maps in the output space time dataset
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- grass.message(_("Start map registration in temporal database"))
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-
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- # Overwrite an existing dataset if requested
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- if new_sp.is_in_db(dbif):
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- if grass.overwrite() == True:
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- new_sp.delete(dbif)
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- new_sp = tgis.space_time_raster_dataset(out_id)
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-
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- # Copy the ids from the first input
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- temporal_type, semantic_type, title, description = first_input.get_initial_values()
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- new_sp.set_initial_values(temporal_type, semantic_type, title, description)
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- # Insert the dataset in the temporal database
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- new_sp.insert(dbif)
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-
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- count = 0
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-
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- for new_map in map_list:
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-
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- count += 1
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- grass.percent(count, num, 1)
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-
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- # Read the raster map data
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- new_map.load()
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-
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- # In case of a null map continue, do not register null maps
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- if new_map.metadata.get_min() == None and new_map.metadata.get_max() == None:
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- if not register_null:
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- continue
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-
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- # Insert map in temporal database
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- new_map.insert(dbif)
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-
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- new_sp.register_map(new_map, dbif)
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-
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- # Update the spatio-temporal extent and the raster metadata table entries
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- new_sp.update_from_registered_maps(dbif)
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-
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- grass.percent(1, 1, 1)
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-
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- dbif.close()
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-
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-###############################################################################
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-
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-def run_mapcalc(expr):
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- """Helper function to run r.mapcalc in parallel"""
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- return grass.run_command("r.mapcalc", expression=expr, overwrite=grass.overwrite(), quiet=True)
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-
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###############################################################################
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if __name__ == "__main__":
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