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()
