def main():
strds = options["input"]
where = options["where"]
nprocs = int(options["nprocs"])
nullmod = pymod.Module("r.null")
nullmod.flags.quiet = True
if options["null"]:
nullmod.inputs.null = options["null"]
elif options["setnull"]:
nullmod.inputs.setnull = options["setnull"]
else:
gscript.fatal(_("Please set 'null' or 'setnull' option"))
tgis.init()
# We need a database interface
dbif = tgis.SQLDatabaseInterfaceConnection()
dbif.connect()
sp = tgis.open_old_stds(strds, "strds", dbif)
maps = sp.get_registered_maps_as_objects(where, "start_time", None)
if maps is None:
gscript.fatal(
_("Space time raster dataset {st} seems to be "
"empty".format(st=strds)))
return 1
# module queue for parallel execution
process_queue = pymod.ParallelModuleQueue(int(nprocs))
count = 0
num_maps = len(maps)
for mapp in maps:
count += 1
mod = copy.deepcopy(nullmod)
mod.inputs.map = mapp.get_id()
process_queue.put(mod)
if count % 10 == 0:
gscript.percent(count, num_maps, 1)
# Wait for unfinished processes
process_queue.wait()
def main():
# Get the options
input = options["input"]
output = options["output"]
where = options["where"]
size = options["size"]
base = options["basename"]
register_null = flags["n"]
method = options["method"]
nprocs = options["nprocs"]
# 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)
# 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
map_name = "%s_%i" % (base, count)
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())
print(mod.get_bash())
process_queue.put(mod)
# Wait for unfinished processes
process_queue.wait()
# 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):
# Get the options
points = options["points"]
coordinates = options["coordinates"]
strds = options["strds"]
output = options["output"]
where = options["where"]
order = options["order"]
layout = options["layout"]
null_value = options["null_value"]
separator = options["separator"]
nprocs = int(options["nprocs"])
write_header = flags["n"]
use_stdin = flags["i"]
#output_cat_label = flags["f"]
#output_color = flags["r"]
#output_cat = flags["i"]
overwrite = gscript.overwrite()
if coordinates and points:
gscript.fatal(_("Options coordinates and points are mutually exclusive"))
if not coordinates and not points and not use_stdin:
gscript.fatal(_("Please specify the coordinates, the points option or use the 's' option to pipe coordinate positions to t.rast.what from stdin, to provide the sampling coordinates"))
if use_stdin:
coordinates_stdin = str(sys.__stdin__.read())
# Check if coordinates are given with site names or IDs
stdin_length = len(coordinates_stdin.split('\n')[0].split())
if stdin_length <= 2:
site_input = False
elif stdin_length >= 3:
site_input = True
else:
site_input = False
# Make sure the temporal database exists
tgis.init()
# We need a database interface
dbif = tgis.SQLDatabaseInterfaceConnection()
dbif.connect()
sp = tgis.open_old_stds(strds, "strds", dbif)
maps = sp.get_registered_maps_as_objects(where=where, order=order,
dbif=dbif)
dbif.close()
if not maps:
gscript.fatal(_("Space time raster dataset <%s> is empty") % sp.get_id())
# Setup separator
if separator == "pipe":
separator = "|"
if separator == "comma":
separator = ","
if separator == "space":
separator = " "
if separator == "tab":
separator = "\t"
if separator == "newline":
separator = "\n"
# Setup flags are disabled due to test issues
flags = ""
#if output_cat_label is True:
# flags += "f"
#if output_color is True:
# flags += "r"
#if output_cat is True:
# flags += "i"
# Configure the r.what module
if points:
r_what = pymod.Module("r.what", map="dummy",
output="dummy", run_=False,
separator=separator, points=points,
overwrite=overwrite, flags=flags,
quiet=True)
elif coordinates:
# Create a list of values
coord_list = coordinates.split(",")
r_what = pymod.Module("r.what", map="dummy",
output="dummy", run_=False,
separator=separator,
coordinates=coord_list,
overwrite=overwrite, flags=flags,
quiet=True)
elif use_stdin:
r_what = pymod.Module("r.what", map="dummy",
output="dummy", run_=False,
separator=separator,
stdin_=coordinates_stdin,
overwrite=overwrite, flags=flags,
quiet=True)
else:
grass.error(_("Please specify points or coordinates"))
if len(maps) < nprocs:
nprocs = len(maps)
# The module queue for parallel execution
process_queue = pymod.ParallelModuleQueue(int(nprocs))
num_maps = len(maps)
# 400 Maps is the absolute maximum in r.what
# We need to determie the number of maps that can be processed
# in parallel
# First estimate the number of maps per process. We use 400 maps
# simultaniously as maximum for a single process
num_loops = int(num_maps / (400 * nprocs))
remaining_maps = num_maps % (400 * nprocs)
if num_loops == 0:
num_loops = 1
remaining_maps = 0
# Compute the number of maps for each process
maps_per_loop = int((num_maps - remaining_maps) / num_loops)
maps_per_process = int(maps_per_loop / nprocs)
remaining_maps_per_loop = maps_per_loop % nprocs
# We put the output files in an ordered list
output_files = []
output_time_list = []
count = 0
for loop in range(num_loops):
file_name = gscript.tempfile() + "_%i"%(loop)
count = process_loop(nprocs, maps, file_name, count, maps_per_process,
remaining_maps_per_loop, output_files,
output_time_list, r_what, process_queue)
process_queue.wait()
gscript.verbose("Number of raster map layers remaining for sampling %i"%(remaining_maps))
if remaining_maps > 0:
# Use a single process if less then 100 maps
if remaining_maps <= 100:
mod = copy.deepcopy(r_what)
mod(map=map_names, output=file_name)
process_queue.put(mod)
else:
maps_per_process = int(remaining_maps / nprocs)
remaining_maps_per_loop = remaining_maps % nprocs
file_name = "out_remain"
process_loop(nprocs, maps, file_name, count, maps_per_process,
remaining_maps_per_loop, output_files,
output_time_list, r_what, process_queue)
# Wait for unfinished processes
process_queue.wait()
# Out the output files in the correct order together
if layout == "row":
one_point_per_row_output(separator, output_files, output_time_list,
output, write_header, site_input)
elif layout == "col":
one_point_per_col_output(separator, output_files, output_time_list,
output, write_header, site_input)
else:
one_point_per_timerow_output(separator, output_files, output_time_list,
output, write_header, site_input)
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 aggregate_by_topology(
granularity_list,
granularity,
map_list,
topo_list,
basename,
time_suffix,
offset=0,
method="average",
nprocs=1,
spatial=None,
dbif=None,
overwrite=False,
file_limit=1000,
):
"""Aggregate a list of raster input maps with r.series
:param granularity_list: A list of AbstractMapDataset objects.
The temporal extents of the objects are used
to build the spatio-temporal topology with the
map list objects
:param granularity: The granularity of the granularity list
:param map_list: A list of RasterDataset objects that contain the raster
maps that should be aggregated
:param topo_list: A list of strings of topological relations that are
used to select the raster maps for aggregation
:param basename: The basename of the new generated raster maps
:param time_suffix: Use the granularity truncated start time of the
actual granule to create the suffix for the basename
:param offset: Use a numerical offset for suffix generation
(overwritten by time_suffix)
:param method: The aggregation method of r.series (average,min,max, ...)
:param nprocs: The number of processes used for parallel computation
:param spatial: This indicates if the spatial topology is created as
well: spatial can be None (no spatial topology), "2D"
using west, east, south, north or "3D" using west,
east, south, north, bottom, top
:param dbif: The database interface to be used
:param overwrite: Overwrite existing raster maps
:param file_limit: The maximum number of raster map layers that
should be opened at once by r.series
:return: A list of RasterDataset objects that contain the new map names
and the temporal extent for map registration
"""
import grass.pygrass.modules as pymod
import copy
msgr = get_tgis_message_interface()
dbif, connection_state_changed = init_dbif(dbif)
topo_builder = SpatioTemporalTopologyBuilder()
topo_builder.build(mapsA=granularity_list, mapsB=map_list, spatial=spatial)
# The module queue for parallel execution
process_queue = pymod.ParallelModuleQueue(int(nprocs))
# Dummy process object that will be deep copied
# and be put into the process queue
r_series = pymod.Module(
"r.series",
output="spam",
method=[method],
overwrite=overwrite,
quiet=True,
run_=False,
finish_=False,
)
g_copy = pymod.Module(
"g.copy", raster=["spam", "spamspam"], quiet=True, run_=False, finish_=False
)
output_list = []
count = 0
for granule in granularity_list:
msgr.percent(count, len(granularity_list), 1)
count += 1
aggregation_list = []
if "equal" in topo_list and granule.equal:
for map_layer in granule.equal:
aggregation_list.append(map_layer.get_name())
if "contains" in topo_list and granule.contains:
for map_layer in granule.contains:
aggregation_list.append(map_layer.get_name())
if "during" in topo_list and granule.during:
for map_layer in granule.during:
aggregation_list.append(map_layer.get_name())
if "starts" in topo_list and granule.starts:
for map_layer in granule.starts:
aggregation_list.append(map_layer.get_name())
if "started" in topo_list and granule.started:
for map_layer in granule.started:
aggregation_list.append(map_layer.get_name())
if "finishes" in topo_list and granule.finishes:
for map_layer in granule.finishes:
aggregation_list.append(map_layer.get_name())
if "finished" in topo_list and granule.finished:
for map_layer in granule.finished:
aggregation_list.append(map_layer.get_name())
if "overlaps" in topo_list and granule.overlaps:
for map_layer in granule.overlaps:
aggregation_list.append(map_layer.get_name())
if "overlapped" in topo_list and granule.overlapped:
for map_layer in granule.overlapped:
aggregation_list.append(map_layer.get_name())
if aggregation_list:
msgr.verbose(
_("Aggregating %(len)i raster maps from %(start)s to" " %(end)s")
% (
{
"len": len(aggregation_list),
"start": str(granule.temporal_extent.get_start_time()),
"end": str(granule.temporal_extent.get_end_time()),
}
)
)
if granule.is_time_absolute() is True and time_suffix == "gran":
suffix = create_suffix_from_datetime(
granule.temporal_extent.get_start_time(), granularity
)
output_name = "{ba}_{su}".format(ba=basename, su=suffix)
elif granule.is_time_absolute() is True and time_suffix == "time":
suffix = create_time_suffix(granule)
output_name = "{ba}_{su}".format(ba=basename, su=suffix)
else:
output_name = create_numeric_suffix(
basename, count + int(offset), time_suffix
)
map_layer = RasterDataset("%s@%s" % (output_name, get_current_mapset()))
map_layer.set_temporal_extent(granule.get_temporal_extent())
if map_layer.map_exists() is True and overwrite is False:
msgr.fatal(
_(
"Unable to perform aggregation. Output raster "
"map <%(name)s> exists and overwrite flag was "
"not set" % ({"name": output_name})
)
)
output_list.append(map_layer)
if len(aggregation_list) > 1:
# Create the r.series input file
filename = gscript.tempfile(True)
file = open(filename, "w")
for name in aggregation_list:
string = "%s\n" % (name)
file.write(string)
file.close()
mod = copy.deepcopy(r_series)
mod(file=filename, output=output_name)
if len(aggregation_list) > int(file_limit):
msgr.warning(
_(
"The limit of open files (%i) was "
"reached (%i). The module r.series will "
"be run with flag z, to avoid open "
"files limit exceeding."
% (int(file_limit), len(aggregation_list))
)
)
mod(flags="z")
process_queue.put(mod)
else:
mod = copy.deepcopy(g_copy)
mod(raster=[aggregation_list[0], output_name])
process_queue.put(mod)
process_queue.wait()
if connection_state_changed:
dbif.close()
msgr.percent(1, 1, 1)
return output_list
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
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()
def main(options, flags):
# Get the options
input = options["input"]
output = options["output"]
where = options["where"]
base = options["basename"]
method = options["type"]
nprocs = int(options["nprocs"])
column = options["column"]
register_null = flags["n"]
t_flag = flags["t"]
s_flag = flags["s"]
v_flag = flags["v"]
b_flag = flags["b"]
z_flag = flags["z"]
# 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"
if s_flag is True:
flags += "s"
if v_flag is True:
flags += "v"
if b_flag is True:
flags += "b"
if z_flag is True:
flags += "z"
# Configure the r.to.vect module
to_vector_module = pymod.Module("r.to.vect", input="dummy",
output="dummy", run_=False,
finish_=False, flags=flags,
type=method, overwrite=overwrite,
quiet=True)
# 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.to.vect 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
map_name = "%s_%i" % (base, count)
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(to_vector_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
map.load()
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()