def main(): # lazy imports import grass.temporal as tgis import grass.pygrass.modules as pymod # Get the options input = options["input"] output = options["output"] where = options["where"] size = options["size"] base = options["basename"] register_null = flags["n"] use_raster_region = flags["r"] method = options["method"] nprocs = options["nprocs"] time_suffix = options["suffix"] # Make sure the temporal database exists tgis.init() # We need a database interface dbif = tgis.SQLDatabaseInterfaceConnection() dbif.connect() overwrite = grass.overwrite() sp = tgis.open_old_stds(input, "strds", dbif) maps = sp.get_registered_maps_as_objects(where=where, dbif=dbif) if not maps: dbif.close() grass.warning( _("Space time raster dataset <%s> is empty") % sp.get_id()) return new_sp = tgis.check_new_stds(output, "strds", dbif=dbif, overwrite=overwrite) # Configure the r.neighbor module neighbor_module = pymod.Module("r.neighbors", input="dummy", output="dummy", run_=False, finish_=False, size=int(size), method=method, overwrite=overwrite, quiet=True) gregion_module = pymod.Module( "g.region", raster="dummy", run_=False, finish_=False, ) # The module queue for parallel execution process_queue = pymod.ParallelModuleQueue(int(nprocs)) count = 0 num_maps = len(maps) new_maps = [] # run r.neighbors all selected maps for map in maps: count += 1 if sp.get_temporal_type() == 'absolute' and time_suffix == 'gran': suffix = tgis.create_suffix_from_datetime( map.temporal_extent.get_start_time(), sp.get_granularity()) map_name = "{ba}_{su}".format(ba=base, su=suffix) elif sp.get_temporal_type() == 'absolute' and time_suffix == 'time': suffix = tgis.create_time_suffix(map) map_name = "{ba}_{su}".format(ba=base, su=suffix) else: map_name = tgis.create_numeric_suffix(base, count, time_suffix) new_map = tgis.open_new_map_dataset( map_name, None, type="raster", temporal_extent=map.get_temporal_extent(), overwrite=overwrite, dbif=dbif) new_maps.append(new_map) mod = copy.deepcopy(neighbor_module) mod(input=map.get_id(), output=new_map.get_id()) if use_raster_region is True: reg = copy.deepcopy(gregion_module) reg(raster=map.get_id()) print(reg.get_bash()) print(mod.get_bash()) mm = pymod.MultiModule([reg, mod], sync=False, set_temp_region=True) process_queue.put(mm) else: print(mod.get_bash()) process_queue.put(mod) # Wait for unfinished processes process_queue.wait() proc_list = process_queue.get_finished_modules() # Check return status of all finished modules error = 0 for proc in proc_list: if proc.popen.returncode != 0: grass.error( _("Error running module: %\n stderr: %s") % (proc.get_bash(), proc.outputs.stderr)) error += 1 if error > 0: grass.fatal(_("Error running modules.")) # Open the new space time raster dataset ttype, stype, title, descr = sp.get_initial_values() new_sp = tgis.open_new_stds(output, "strds", ttype, title, descr, stype, dbif, overwrite) num_maps = len(new_maps) # collect empty maps to remove them empty_maps = [] # Register the maps in the database count = 0 for map in new_maps: count += 1 if count % 10 == 0: grass.percent(count, num_maps, 1) # Do not register empty maps map.load() if map.metadata.get_min() is None and \ map.metadata.get_max() is None: if not register_null: empty_maps.append(map) continue # Insert map in temporal database map.insert(dbif) new_sp.register_map(map, dbif) # Update the spatio-temporal extent and the metadata table entries new_sp.update_from_registered_maps(dbif) grass.percent(1, 1, 1) # Remove empty maps if len(empty_maps) > 0: names = "" count = 0 for map in empty_maps: if count == 0: count += 1 names += "%s" % (map.get_name()) else: names += ",%s" % (map.get_name()) grass.run_command("g.remove", flags='f', type='raster', name=names, quiet=True) dbif.close()
def main(options, flags): # lazy imports import grass.temporal as tgis import grass.pygrass.modules as pymod # Get the options input = options["input"] output = options["output"] where = options["where"] base = options["basename"] nprocs = int(options["nprocs"]) step = options["step"] levels = options["levels"] minlevel = options["minlevel"] maxlevel = options["maxlevel"] cut = options["cut"] time_suffix = options["suffix"] register_null = flags["n"] t_flag = flags["t"] # Make sure the temporal database exists tgis.init() # We need a database interface dbif = tgis.SQLDatabaseInterfaceConnection() dbif.connect() overwrite = gscript.overwrite() sp = tgis.open_old_stds(input, "strds", dbif) maps = sp.get_registered_maps_as_objects(where=where, dbif=dbif) if not maps: dbif.close() gscript.warning( _("Space time raster dataset <%s> is empty") % sp.get_id()) return # Check the new stvds new_sp = tgis.check_new_stds(output, "stvds", dbif=dbif, overwrite=overwrite) # Setup the flags flags = "" if t_flag is True: flags += "t" # Configure the r.to.vect module contour_module = pymod.Module("r.contour", input="dummy", output="dummy", run_=False, finish_=False, flags=flags, overwrite=overwrite, quiet=True) if step: contour_module.inputs.step = float(step) if minlevel: contour_module.inputs.minlevel = float(minlevel) if maxlevel: contour_module.inputs.maxlevel = float(maxlevel) if levels: contour_module.inputs.levels = levels.split(",") if cut: contour_module.inputs.cut = int(cut) # The module queue for parallel execution, except if attribute tables should # be created. Then force single process use if t_flag is False: if nprocs > 1: nprocs = 1 gscript.warning( _("The number of parellel r.contour processes was " "reduced to 1 because of the table attribute " "creation")) process_queue = pymod.ParallelModuleQueue(int(nprocs)) count = 0 num_maps = len(maps) new_maps = [] # run r.to.vect all selected maps for map in maps: count += 1 if sp.get_temporal_type() == 'absolute' and time_suffix == 'gran': suffix = tgis.create_suffix_from_datetime( map.temporal_extent.get_start_time(), sp.get_granularity()) map_name = "{ba}_{su}".format(ba=base, su=suffix) elif sp.get_temporal_type() == 'absolute' and time_suffix == 'time': suffix = tgis.create_time_suffix(map) map_name = "{ba}_{su}".format(ba=base, su=suffix) else: map_name = tgis.create_numeric_suffix(base, count, time_suffix) new_map = tgis.open_new_map_dataset( map_name, None, type="vector", temporal_extent=map.get_temporal_extent(), overwrite=overwrite, dbif=dbif) new_maps.append(new_map) mod = copy.deepcopy(contour_module) mod(input=map.get_id(), output=new_map.get_id()) sys.stderr.write(mod.get_bash() + "\n") process_queue.put(mod) if count % 10 == 0: gscript.percent(count, num_maps, 1) # Wait for unfinished processes process_queue.wait() # Open the new space time vector dataset ttype, stype, title, descr = sp.get_initial_values() new_sp = tgis.open_new_stds(output, "stvds", ttype, title, descr, stype, dbif, overwrite) # collect empty maps to remove them num_maps = len(new_maps) empty_maps = [] # Register the maps in the database count = 0 for map in new_maps: count += 1 if count % 10 == 0: gscript.percent(count, num_maps, 1) # Do not register empty maps try: if map.load() is not True: continue except FatalError: continue if map.metadata.get_number_of_primitives() == 0: if not register_null: empty_maps.append(map) continue # Insert map in temporal database map.insert(dbif) new_sp.register_map(map, dbif) # Update the spatio-temporal extent and the metadata table entries new_sp.update_from_registered_maps(dbif) gscript.percent(1, 1, 1) # Remove empty maps if len(empty_maps) > 0: names = "" count = 0 for map in empty_maps: if count == 0: count += 1 names += "%s" % (map.get_name()) else: names += ",%s" % (map.get_name()) gscript.run_command("g.remove", flags='f', type='vector', name=names, quiet=True) dbif.close()
def main(): # lazy imports import grass.temporal as tgis from grass.pygrass.modules import Module # Get the options input = options["input"] output = options["output"] start = options["start"] stop = options["stop"] base = options["basename"] cycle = options["cycle"] lower = options["lower"] upper = options["upper"] offset = options["offset"] limits = options["limits"] shift = options["shift"] scale = options["scale"] method = options["method"] granularity = options["granularity"] register_null = flags["n"] reverse = flags["r"] time_suffix = options["suffix"] # Make sure the temporal database exists tgis.init() # We need a database interface dbif = tgis.SQLDatabaseInterfaceConnection() dbif.connect() mapset = tgis.get_current_mapset() if input.find("@") >= 0: id = input else: id = input + "@" + mapset input_strds = tgis.SpaceTimeRasterDataset(id) if input_strds.is_in_db() == False: dbif.close() grass.fatal(_("Space time raster dataset <%s> not found") % (id)) input_strds.select(dbif) if output.find("@") >= 0: out_id = output else: out_id = output + "@" + mapset # The output space time raster dataset output_strds = tgis.SpaceTimeRasterDataset(out_id) if output_strds.is_in_db(dbif): if not grass.overwrite(): dbif.close() grass.fatal( _("Space time raster dataset <%s> is already in the " "database, use overwrite flag to overwrite") % out_id) if tgis.check_granularity_string(granularity, input_strds.get_temporal_type()) == False: dbif.close() grass.fatal(_("Invalid granularity")) if tgis.check_granularity_string(cycle, input_strds.get_temporal_type()) == False: dbif.close() grass.fatal(_("Invalid cycle")) if offset: if tgis.check_granularity_string( offset, input_strds.get_temporal_type()) == False: dbif.close() grass.fatal(_("Invalid offset")) # The lower threshold space time raster dataset if lower: if not range: dbif.close() grass.fatal( _("You need to set the range to compute the occurrence" " space time raster dataset")) if lower.find("@") >= 0: lower_id = lower else: lower_id = lower + "@" + mapset lower_strds = tgis.SpaceTimeRasterDataset(lower_id) if lower_strds.is_in_db() == False: dbif.close() grass.fatal( _("Space time raster dataset <%s> not found") % (lower_strds.get_id())) if lower_strds.get_temporal_type() != input_strds.get_temporal_type(): dbif.close() grass.fatal( _("Temporal type of input strds and lower strds must be equal") ) lower_strds.select(dbif) # The upper threshold space time raster dataset if upper: if not lower: dbif.close() grass.fatal( _("The upper option works only in conjunction with the lower option" )) if upper.find("@") >= 0: upper = upper else: upper_id = upper + "@" + mapset upper_strds = tgis.SpaceTimeRasterDataset(upper_id) if upper_strds.is_in_db() == False: dbif.close() grass.fatal( _("Space time raster dataset <%s> not found") % (upper_strds.get_id())) if upper_strds.get_temporal_type() != input_strds.get_temporal_type(): dbif.close() grass.fatal( _("Temporal type of input strds and upper strds must be equal") ) upper_strds.select(dbif) input_strds_start, input_strds_end = input_strds.get_temporal_extent_as_tuple( ) if input_strds.is_time_absolute(): start = tgis.string_to_datetime(start) if stop: stop = tgis.string_to_datetime(stop) else: stop = input_strds_end start = tgis.adjust_datetime_to_granularity(start, granularity) else: start = int(start) if stop: stop = int(stop) else: stop = input_strds_end if input_strds.is_time_absolute(): end = tgis.increment_datetime_by_string(start, cycle) else: end = start + cycle limit_relations = [ "EQUALS", "DURING", "OVERLAPS", "OVERLAPPING", "CONTAINS" ] count = 1 output_maps = [] while input_strds_end > start and stop > start: # Make sure that the cyclic computation will stop at the correct time if stop and end > stop: end = stop where = "start_time >= \'%s\' AND start_time < \'%s\'" % (str(start), str(end)) input_maps = input_strds.get_registered_maps_as_objects(where=where, dbif=dbif) grass.message(_("Processing cycle %s - %s" % (str(start), str(end)))) if len(input_maps) == 0: continue # Lets create a dummy list of maps with granularity conform intervals gran_list = [] gran_list_low = [] gran_list_up = [] gran_start = start while gran_start < end: map = input_strds.get_new_map_instance("%i@%i" % (count, count)) if input_strds.is_time_absolute(): gran_end = tgis.increment_datetime_by_string( gran_start, granularity) map.set_absolute_time(gran_start, gran_end) gran_start = tgis.increment_datetime_by_string( gran_start, granularity) else: gran_end = gran_start + granularity map.set_relative_time(gran_start, gran_end, input_strds.get_relative_time_unit()) gran_start = gran_start + granularity gran_list.append(copy(map)) gran_list_low.append(copy(map)) gran_list_up.append(copy(map)) # Lists to compute the topology with upper and lower datasets # Create the topology between the granularity conform list and all maps # of the current cycle gran_topo = tgis.SpatioTemporalTopologyBuilder() gran_topo.build(gran_list, input_maps) if lower: lower_maps = lower_strds.get_registered_maps_as_objects(dbif=dbif) gran_lower_topo = tgis.SpatioTemporalTopologyBuilder() gran_lower_topo.build(gran_list_low, lower_maps) if upper: upper_maps = upper_strds.get_registered_maps_as_objects(dbif=dbif) gran_upper_topo = tgis.SpatioTemporalTopologyBuilder() gran_upper_topo.build(gran_list_up, upper_maps) old_map_name = None # Aggregate num_maps = len(gran_list) for i in range(num_maps): if reverse: map = gran_list[num_maps - i - 1] else: map = gran_list[i] # Select input maps based on temporal topology relations input_maps = [] if map.get_equal(): input_maps += map.get_equal() elif map.get_contains(): input_maps += map.get_contains() elif map.get_overlaps(): input_maps += map.get_overlaps() elif map.get_overlapped(): input_maps += map.get_overlapped() elif map.get_during(): input_maps += map.get_during() # Check input maps if len(input_maps) == 0: continue # New output map if input_strds.get_temporal_type( ) == 'absolute' and time_suffix == 'gran': suffix = tgis.create_suffix_from_datetime( map.temporal_extent.get_start_time(), input_strds.get_granularity()) output_map_name = "{ba}_{su}".format(ba=base, su=suffix) elif input_strds.get_temporal_type( ) == 'absolute' and time_suffix == 'time': suffix = tgis.create_time_suffix(map) output_map_name = "{ba}_{su}".format(ba=base, su=suffix) else: output_map_name = tgis.create_numeric_suffix( base, count, time_suffix) output_map_id = map.build_id(output_map_name, mapset) output_map = input_strds.get_new_map_instance(output_map_id) # Check if new map is in the temporal database if output_map.is_in_db(dbif): if grass.overwrite(): # Remove the existing temporal database entry output_map.delete(dbif) output_map = input_strds.get_new_map_instance( output_map_id) else: grass.fatal( _("Map <%s> is already registered in the temporal" " database, use overwrite flag to overwrite.") % (output_map.get_map_id())) map_start, map_end = map.get_temporal_extent_as_tuple() if map.is_time_absolute(): output_map.set_absolute_time(map_start, map_end) else: output_map.set_relative_time(map_start, map_end, map.get_relative_time_unit()) limits_vals = limits.split(",") limits_lower = float(limits_vals[0]) limits_upper = float(limits_vals[1]) lower_map_name = None if lower: relations = gran_list_low[i].get_temporal_relations() for relation in limit_relations: if relation in relations: lower_map_name = str(relations[relation][0].get_id()) break upper_map_name = None if upper: relations = gran_list_up[i].get_temporal_relations() for relation in limit_relations: if relation in relations: upper_map_name = str(relations[relation][0].get_id()) break input_map_names = [] for input_map in input_maps: input_map_names.append(input_map.get_id()) # Set up the module accmod = Module("r.series.accumulate", input=input_map_names, output=output_map_name, run_=False) if old_map_name: accmod.inputs["basemap"].value = old_map_name if lower_map_name: accmod.inputs["lower"].value = lower_map_name if upper_map_name: accmod.inputs["upper"].value = upper_map_name accmod.inputs["limits"].value = (limits_lower, limits_upper) if shift: accmod.inputs["shift"].value = float(shift) if scale: accmod.inputs["scale"].value = float(scale) if method: accmod.inputs["method"].value = method print(accmod) accmod.run() if accmod.popen.returncode != 0: dbif.close() grass.fatal(_("Error running r.series.accumulate")) output_maps.append(output_map) old_map_name = output_map_name count += 1 # Increment the cycle start = end if input_strds.is_time_absolute(): start = end if offset: start = tgis.increment_datetime_by_string(end, offset) end = tgis.increment_datetime_by_string(start, cycle) else: if offset: start = end + offset end = start + cycle # Insert the maps into the output space time dataset if output_strds.is_in_db(dbif): if grass.overwrite(): output_strds.delete(dbif) output_strds = input_strds.get_new_instance(out_id) temporal_type, semantic_type, title, description = input_strds.get_initial_values( ) output_strds.set_initial_values(temporal_type, semantic_type, title, description) output_strds.insert(dbif) empty_maps = [] # Register the maps in the database count = 0 for output_map in output_maps: count += 1 if count % 10 == 0: grass.percent(count, len(output_maps), 1) # Read the raster map data output_map.load() # In case of a empty map continue, do not register empty maps if not register_null: if output_map.metadata.get_min() is None and \ output_map.metadata.get_max() is None: empty_maps.append(output_map) continue # Insert map in temporal database output_map.insert(dbif) output_strds.register_map(output_map, dbif) # Update the spatio-temporal extent and the metadata table entries output_strds.update_from_registered_maps(dbif) grass.percent(1, 1, 1) dbif.close() # Remove empty maps if len(empty_maps) > 0: for map in empty_maps: grass.run_command("g.remove", flags='f', type="raster", name=map.get_name(), quiet=True)
def main(): # lazy imports import grass.temporal as tgis import grass.pygrass.modules as pymod # Get the options input = options["input"] base = options["basename"] where = options["where"] nprocs = options["nprocs"] tsuffix = options["suffix"] mapset = grass.encode(grass.gisenv()["MAPSET"]) # Make sure the temporal database exists tgis.init() # We need a database interface dbif = tgis.SQLDatabaseInterfaceConnection() dbif.connect() sp = tgis.open_old_stds(input, "strds") maps = sp.get_registered_maps_as_objects_with_gaps(where, dbif) num = len(maps) # Configure the r.to.vect module gapfill_module = pymod.Module( "r.series.interp", overwrite=grass.overwrite(), quiet=True, run_=False, finish_=False, ) process_queue = pymod.ParallelModuleQueue(int(nprocs)) gap_list = [] overwrite_flags = {} # Identify all gaps and create new names count = 0 for _map in maps: if _map.get_id() is None: count += 1 if sp.get_temporal_type() == 'absolute' and tsuffix in [ 'gran', 'time' ]: _id = "{ba}@{ma}".format(ba=base, ma=mapset) else: map_name = tgis.create_numeric_suffix(base, num + count, tsuffix) _id = "{name}@{ma}".format(name=map_name, ma=mapset) _map.set_id(_id) gap_list.append(_map) if len(gap_list) == 0: grass.message(_("No gaps found")) return # Build the temporal topology tb = tgis.SpatioTemporalTopologyBuilder() tb.build(maps) # Do some checks before computation for _map in gap_list: if not _map.get_precedes() or not _map.get_follows(): grass.fatal( _("Unable to determine successor " "and predecessor of a gap.")) if len(_map.get_precedes()) > 1: grass.warning( _("More than one successor of the gap found. " "Using the first found.")) if len(_map.get_follows()) > 1: grass.warning( _("More than one predecessor of the gap found. " "Using the first found.")) # Interpolate the maps using parallel processing result_list = [] for _map in gap_list: predecessor = _map.get_follows()[0] successor = _map.get_precedes()[0] gran = sp.get_granularity() tmpval, start = predecessor.get_temporal_extent_as_tuple() end, tmpval = successor.get_temporal_extent_as_tuple() # Now resample the gap map_matrix = tgis.AbstractSpaceTimeDataset.resample_maplist_by_granularity( (_map, ), start, end, gran) map_names = [] map_positions = [] increment = 1.0 / (len(map_matrix) + 1.0) position = increment count = 0 for intp_list in map_matrix: new_map = intp_list[0] count += 1 if sp.get_temporal_type() == 'absolute' and tsuffix == 'gran': suffix = tgis.create_suffix_from_datetime( new_map.temporal_extent.get_start_time(), sp.get_granularity()) new_id = "{ba}_{su}@{ma}".format(ba=new_map.get_name(), su=suffix, ma=mapset) elif sp.get_temporal_type() == 'absolute' and tsuffix == 'time': suffix = tgis.create_time_suffix(new_map) new_id = "{ba}_{su}@{ma}".format(ba=new_map.get_name(), su=suffix, ma=mapset) else: map_name = tgis.create_numeric_suffix(new_map.get_name(), count, tsuffix) new_id = "{name}@{ma}".format(name=map_name, ma=mapset) new_map.set_id(new_id) overwrite_flags[new_id] = False if new_map.map_exists() or new_map.is_in_db(dbif): if not grass.overwrite(): grass.fatal( _("Map with name <%s> already exists. " "Please use another base name." % (_id))) else: if new_map.is_in_db(dbif): overwrite_flags[new_id] = True map_names.append(new_map.get_name()) map_positions.append(position) position += increment result_list.append(new_map) mod = copy.deepcopy(gapfill_module) mod(input=(predecessor.get_map_id(), successor.get_map_id()), datapos=(0, 1), output=map_names, samplingpos=map_positions) sys.stderr.write(mod.get_bash() + "\n") process_queue.put(mod) # Wait for unfinished processes process_queue.wait() # Insert new interpolated maps in temporal database and dataset for _map in result_list: id = _map.get_id() if overwrite_flags[id] == True: if _map.is_time_absolute(): start, end = _map.get_absolute_time() if _map.is_in_db(): _map.delete(dbif) _map = sp.get_new_map_instance(id) _map.set_absolute_time(start, end) else: start, end, unit = _map.get_relative_time() if _map.is_in_db(): _map.delete(dbif) _map = sp.get_new_map_instance(id) _map.set_relative_time(start, end, unit) _map.load() _map.insert(dbif) sp.register_map(_map, dbif) sp.update_from_registered_maps(dbif) sp.update_command_string(dbif=dbif) dbif.close()