New raster and raster3d space time dataset map calculator

git-svn-id: https://svn.osgeo.org/grass/grass/trunk@51376 15284696-431f-4ddb-bdfa-cd5b030d7da7

lib/python/temporal/mapcalc.py

@@ -0,0 +1,323 @@
+"""!@package grass.temporal
+
+@brief GRASS Python scripting module (temporal GIS functions)
+
+Temporal GIS related functions to be used in Python scripts.
+
+Usage:
+
+@code
+import grass.temporal as tgis
+@endcode
+
+(C) 2008-2011 by the GRASS Development Team
+This program is free software under the GNU General Public
+License (>=v2). Read the file COPYING that comes with GRASS
+for details.
+
+@author Soeren Gebbert
+"""
+
+from space_time_datasets import *
+from multiprocessing import Process
+
+############################################################################
+
+def dataset_mapcalculator(inputs, output, type, expression, base, method, nprocs=1, register_null=False, spatial=False):
+    """!Perform map-calculations of maps from different space time raster/raster3d datasets, using
+       a specific sampling method to select temporal related maps.
+    
+       A mapcalc expression can be provided to process the temporal extracted maps.
+       Mapcalc expressions are supported for raster and raster3d maps.
+       
+       @param input The name of the input space time raster/raster3d dataset 
+       @param output The name of the extracted new space time raster/raster3d dataset
+       @param type The type of the dataset: "raster" or "raster3d"
+       @param method The method to be used for temporal sampling
+       @param expression The r(3).mapcalc expression
+       @param base The base name of the new created maps in case a mapclac expression is provided 
+       @param nprocs The number of parallel processes to be used for mapcalc processing
+       @param register_null Set this number True to register empty maps
+       @param spatial Check spatial overlap
+    """
+    
+    # We need a database interface for fast computation
+    dbif = sql_database_interface_connection()
+    dbif.connect()
+
+    mapset =  core.gisenv()["MAPSET"]
+    
+    input_name_list = inputs.split(",")
+    
+    # Process the first input
+    if input_name_list[0].find("@") >= 0:
+	id = input_name_list[0]
+    else:
+	id = input_name_list[0] + "@" + mapset
+	
+    if type == "raster":
+	first_input = space_time_raster_dataset(id)
+    else:
+	first_input = space_time_raster3d_dataset(id)
+    
+    if first_input.is_in_db(dbif) == False:
+	dbif.close()
+        core.fatal(_("Space time %s dataset <%s> not found") % (type, id))
+
+    # Fill the object with data from the temporal database
+    first_input.select(dbif)
+    
+    # All additional inputs in reverse sorted order to avoid wrong name substitution
+    input_name_list = input_name_list[1:]
+    input_name_list.sort()
+    input_name_list.reverse()
+    input_list = []
+        
+    for input in input_name_list:
+
+	if input.find("@") >= 0:
+	    id = input
+	else:
+	    id = input + "@" + mapset
+	    
+	sp = first_input.get_new_instance(id)
+	
+	if sp.is_in_db(dbif) == False:
+	    dbif.close()
+	    core.fatal(_("Space time %s dataset <%s> not found in temporal database") % (type, id))
+
+	sp.select(dbif)
+	
+	input_list.append(copy.copy(sp))
+
+    # Create the new space time dataset
+    if output.find("@") >= 0:
+        out_id = output
+    else:
+        out_id = output + "@" + mapset
+        
+    new_sp = first_input.get_new_instance(out_id)
+    
+    # Check if in database
+    if new_sp.is_in_db(dbif):
+        if core.overwrite() == False:
+	    dbif.close()
+            core.fatal(_("Space time %s dataset <%s> is already in database, use overwrite flag to overwrite") % (type, out_id))
+ 
+    # Sample all inputs by the first input and create a sample matrix
+    if spatial:
+        core.message(_("Start spatio-temporal sampling"))
+    else:
+        core.message(_("Start temporal sampling"))
+    map_matrix = []
+    id_list = []
+    sample_map_list = []
+    # First entry is the first dataset id
+    id_list.append(first_input.get_name())
+    
+    if len(input_list) > 0:
+	has_samples = False
+	for dataset in input_list:
+	    list = dataset.sample_by_dataset(stds=first_input, method=method, spatial=spatial, dbif=dbif)
+	    
+	    # In case samples are not found
+	    if not list and len(list) == 0:
+		dbif.close()
+		core.message(_("No samples found for map calculation"))
+		return 0
+	    
+	    # The fist entries are the samples
+	    map_name_list = []
+	    if has_samples == False:
+		for entry in list:
+		    granule = entry["granule"]
+		    # Do not consider gaps
+		    if granule.get_id() == None:
+			continue
+		    sample_map_list.append(granule)
+		    map_name_list.append(granule.get_name())
+		# Attach the map names
+		map_matrix.append(copy.copy(map_name_list))
+		has_samples = True
+		
+	    map_name_list = []
+	    for entry in list:
+		maplist = entry["samples"]
+		granule = entry["granule"]
+		
+		# Do not consider gaps in the sampler
+		if granule.get_id() == None:
+		    continue
+		
+		if len(maplist) > 1:
+		    core.warning(_("Found more than a single map in a sample granule. "\
+		    "Only the first map is used for computation. "\
+		    "Use t.rast.aggregate.ds to create synchronous raster datasets."))
+		
+		# Store all maps! This includes non existent maps, identified by id == None 
+		map_name_list.append(maplist[0].get_name())
+	    
+	    # Attach the map names
+	    map_matrix.append(copy.copy(map_name_list))
+
+	    id_list.append(dataset.get_name())
+    else:
+	list = first_input.get_registered_maps_as_objects(dbif=dbif)
+	
+	if list == None:
+	    dbif.close()
+            core.message(_("No maps in input dataset"))
+            return 0
+	
+	map_name_list = []
+	for map in list:
+	    map_name_list.append(map.get_name())
+	    sample_map_list.append(map)
+	
+	# Attach the map names
+	map_matrix.append(copy.copy(map_name_list))
+    
+   
+    # Needed for map registration
+    map_list = []
+	
+    if len(map_matrix) > 0:
+	
+	core.message(_("Start mapcalc computation"))
+	    
+	count = 0
+	# Get the number of samples
+	num = len(map_matrix[0])
+	
+	# Parallel processing
+        proc_list = []
+        proc_count = 0
+	
+	# For all samples
+        for i in range(num):
+            
+            count += 1
+	    core.percent(count, num, 1)
+
+	    # Create the r.mapcalc statement for the current time step
+	    map_name = "%s_%i" % (base, count)   
+	    expr = "%s = %s" % (map_name, expression)
+            
+            # Check that all maps are in the sample
+            valid_maps = True
+            # Replace all dataset names with their map names of the current time step
+            for j in range(len(map_matrix)):
+		if map_matrix[j][i] == None:
+		    valid_maps = False
+		    break
+		# Substitute the dataset name with the map name
+		expr = expr.replace(id_list[j], map_matrix[j][i])
+
+	    # Proceed with the next sample
+	    if valid_maps == False:
+		continue
+		
+	    # Create the new map id and check if the map is already in the database
+	    map_id = map_name + "@" + mapset
+
+	    new_map = first_input.get_new_map_instance(map_id)
+
+	    # Check if new map is in the temporal database
+	    if new_map.is_in_db(dbif):
+		if core.overwrite() == True:
+		    # Remove the existing temporal database entry
+		    new_map.delete(dbif)
+		    new_map = first_input.get_new_map_instance(map_id)
+		else:
+		    core.error(_("Map <%s> is already in temporal database, use overwrite flag to overwrite"))
+		    continue
+
+	    # Set the time stamp
+	    if sample_map_list[i].is_time_absolute():
+		start, end, tz = sample_map_list[i].get_absolute_time()
+		new_map.set_absolute_time(start, end, tz)
+	    else:
+		start, end = sample_map_list[i].get_relative_time()
+		new_map.set_relative_time(start, end)
+	    
+	    map_list.append(new_map)
+	    
+	    # Start the parallel r.mapcalc computation
+	    core.verbose(_("Apply mapcalc expression: \"%s\"") % expr)
+
+	    if type == "raster":
+		proc_list.append(Process(target=run_mapcalc2d, args=(expr,)))
+	    else:
+		proc_list.append(Process(target=run_mapcalc3d, args=(expr,)))
+	    proc_list[proc_count].start()
+	    proc_count += 1
+	    
+	    if proc_count == nprocs:
+		proc_count = 0
+		exitcodes = 0
+		for proc in proc_list:
+		    proc.join()
+		    exitcodes += proc.exitcode
+		    
+		if exitcodes != 0:
+		    dbif.close()
+		    core.fatal(_("Error while mapcalc computation"))
+		    
+		# Empty process list
+		proc_list = []
+		
+	# Register the new maps in the output space time dataset
+	core.message(_("Start map registration in temporal database"))
+	    
+	# Overwrite an existing dataset if requested
+	if new_sp.is_in_db(dbif):
+	    if core.overwrite() == True:
+		new_sp.delete(dbif)
+		new_sp = first_input.get_new_instance(out_id)
+		
+	# Copy the ids from the first input
+	temporal_type, semantic_type, title, description = first_input.get_initial_values()
+	new_sp.set_initial_values(temporal_type, semantic_type, title, description)
+	# Insert the dataset in the temporal database
+	new_sp.insert(dbif)
+    
+	count = 0
+	
+	# Insert maps in the temporal database and in the new space time dataset
+	for new_map in map_list:
+
+            count += 1
+	    core.percent(count, num, 1)
+	    
+	    # Read the map data
+	    new_map.load()
+	    
+	    # In case of a null map continue, do not register null maps
+	    if new_map.metadata.get_min() == None and new_map.metadata.get_max() == None:
+		if not register_null:
+		    continue
+
+	    # Insert map in temporal database
+	    new_map.insert(dbif)
+
+	    new_sp.register_map(new_map, dbif)
+
+        # Update the spatio-temporal extent and the metadata table entries
+        new_sp.update_from_registered_maps(dbif)
+	
+	core.percent(1, 1, 1)
+        
+    dbif.close()
+
+
+###############################################################################
+
+def run_mapcalc2d(expr):
+    """Helper function to run r.mapcalc in parallel"""
+    return core.run_command("r.mapcalc", expression=expr, overwrite=core.overwrite(), quiet=True)
+
+###############################################################################
+
+def run_mapcalc3d(expr):
+    """Helper function to run r3.mapcalc in parallel"""
+    return core.run_command("r3.mapcalc", expression=expr, overwrite=core.overwrite(), quiet=True)