def advanced_shallow_lake_filtering_driver(
input_unfilled_orography_file, input_unfilled_orography_fieldname,
input_filled_orography_file, input_filled_orography_fieldname,
output_unfilled_orography_file, output_unfilled_orography_fieldname,
minimum_depth_threshold):
input_unfilled_orography = \
iodriver.advanced_field_loader(input_unfilled_orography_file,
field_type='Orography',
fieldname=input_unfilled_orography_fieldname)
input_filled_orography = \
iodriver.advanced_field_loader(input_filled_orography_file,
field_type='Orography',
fieldname=input_filled_orography_fieldname)
output_unfilled_orography = \
field.Field(np.ascontiguousarray(input_unfilled_orography.get_data(),
dtype=np.float64),
grid=input_unfilled_orography.get_grid())
lake_operators_wrapper.filter_out_shallow_lakes(output_unfilled_orography.get_data(),
np.ascontiguousarray(input_filled_orography.\
get_data(),
dtype=np.float64),
minimum_depth_threshold)
iodriver.advanced_field_writer(
output_unfilled_orography_file,
output_unfilled_orography,
fieldname=output_unfilled_orography_fieldname)
def main(rdirs_filename, output_filename, grid_type, **grid_kwargs):
"""Top level function for cumulative flow to cell flow map generation
Inputs:
rdir_filename: string; full path to the file contain the input river
direction field
output_filename: string; full path of the target file to write the
generated cumulative flow to cell field to
grid_type: string; a keyword specifying the grid type of the input
and output fields
**grid_kwargs (optional): keyword dictionary; any parameters of the
input and output grid that are required
Returns: Nothing
"""
rdirs = iodriver.load_field(rdirs_filename,
iodriver.get_file_extension(rdirs_filename),
"Generic",
grid_type=grid_type,
**grid_kwargs)
nlat, nlong = rdirs.get_grid().get_grid_dimensions()
paths_map = field.Field(create_hypothetical_river_paths_map(
riv_dirs=rdirs.get_data(),
lsmask=None,
use_f2py_func=True,
use_f2py_sparse_iterator=True,
nlat=nlat,
nlong=nlong),
grid=grid_type,
**grid_kwargs)
iodriver.write_field(output_filename, paths_map,
iodriver.get_file_extension(output_filename))
def advanced_water_redistribution_driver(
input_lake_numbers_file, input_lake_numbers_fieldname,
input_lake_centers_file, input_lake_centers_fieldname,
input_water_to_redistribute_file,
input_water_to_redistribute_fieldname,
output_water_redistributed_to_lakes_file,
output_water_redistributed_to_lakes_fieldname,
output_water_redistributed_to_rivers_file,
output_water_redistributed_to_rivers_fieldname, coarse_grid_type,
**coarse_grid_kwargs):
lake_numbers = iodriver.advanced_field_loader(
input_lake_numbers_file,
field_type='Generic',
fieldname=input_lake_numbers_fieldname)
lake_centers = iodriver.advanced_field_loader(
input_lake_centers_file,
field_type='Generic',
fieldname=input_lake_centers_fieldname)
water_to_redistribute = \
iodriver.advanced_field_loader(input_water_to_redistribute_file,
field_type='Generic',
fieldname=input_water_to_redistribute_fieldname)
fine_grid = lake_numbers.get_grid()
fine_shape = lake_numbers.get_data().shape
coarse_grid = grid.makeGrid(coarse_grid_type, **coarse_grid_kwargs)
water_redistributed_to_lakes = field.Field(
np.zeros(fine_shape, dtype=np.float64, order='C'), fine_grid)
water_redistributed_to_rivers = field.Field(
coarse_grid.create_empty_field(np.float64), coarse_grid)
lake_operators_wrapper.redistribute_water(
np.ascontiguousarray(lake_numbers.get_data(), dtype=np.int32),
np.ascontiguousarray(lake_centers.get_data(), dtype=np.int32),
np.ascontiguousarray(water_to_redistribute.get_data(),
dtype=np.float64),
water_redistributed_to_lakes.get_data(),
water_redistributed_to_rivers.get_data())
iodriver.advanced_field_writer(
output_water_redistributed_to_lakes_file,
water_redistributed_to_lakes,
fieldname=output_water_redistributed_to_lakes_fieldname)
iodriver.advanced_field_writer(
output_water_redistributed_to_rivers_file,
water_redistributed_to_rivers,
fieldname=output_water_redistributed_to_rivers_fieldname)
def advanced_main(rdirs_filename, output_filename, rdirs_fieldname,
output_fieldname):
rdirs = iodriver.advanced_field_loader(rdirs_filename,
field_type="Generic",
fieldname=rdirs_fieldname)
nlat, nlong = rdirs.get_grid().get_grid_dimensions()
paths_map = field.Field(create_hypothetical_river_paths_map(
riv_dirs=rdirs.get_data(),
lsmask=None,
use_f2py_func=True,
use_f2py_sparse_iterator=True,
nlat=nlat,
nlong=nlong),
grid=rdirs.get_grid())
iodriver.advanced_field_writer(target_filename=output_filename,
field=paths_map,
fieldname=output_fieldname)
def main(filename,
output_filename,
loop_logfile,
use_cpp_code=True,
grid_type='HD',
**grid_kwargs):
"""Generates a file with numbered catchments from a given river flow direction file
Inputs:
filename: string; the input file of river directions
output_filename: string; the target file for the output numbered catchments
loop_logfile: string; an input file of catchments with loop to be updated
use_cpp_alg: bool; use the Cpp code if True otherwise use the Fortran code
grid_type: string; a keyword giving the type of grid being used
**grid_kwargs(optional): keyword dictionary; the parameter of the grid to
be used (if required)
Returns: Nothing
Produces the numbered catchments where the numbering is in descending order of size;
also update the loop log file to reflect the relabelling of catchements and runs a
check on the type of catchments generated (which are placed in a log file with the
same basename as the output catchments but with the extension '.log').
"""
rdirs = iodriver.load_field(
filename,
file_type=iodriver.get_file_extension(filename),
field_type='Generic',
grid_type=grid_type,
**grid_kwargs)
if use_cpp_code:
catchments = compute_catchments_cpp(rdirs.get_data(), loop_logfile)
else:
catchment_types, catchments = compute_catchments(
rdirs.get_data(), loop_logfile)
check_catchment_types(catchment_types,
logfile=path.splitext(output_filename)[0] +
".log")
numbered_catchments = field.Field(renumber_catchments_by_size(
catchments, loop_logfile),
grid=grid_type,
**grid_kwargs)
iodriver.write_field(
filename=output_filename,
field=numbered_catchments,
file_type=iodriver.get_file_extension(output_filename))
def reduce_connected_areas_to_points(input_minima_file,
input_minima_fieldname,
output_minima_file,
output_minima_fieldname,
use_diagonals=True):
input_minima = iodriver.advanced_field_loader(
input_minima_file,
field_type='Generic',
fieldname=input_minima_fieldname)
minima_array = np.ascontiguousarray(input_minima.get_data(),
dtype=np.int32)
lake_operators_wrapper.reduce_connected_areas_to_points(
minima_array, use_diagonals)
output_minima = field.Field(minima_array, grid=input_minima.get_grid())
iodriver.advanced_field_writer(output_minima_file,
output_minima,
fieldname=output_minima_fieldname)
def extract_lake_volumes(flood_volume_thresholds,
basin_catchment_numbers,merge_types):
lake_mask = basin_catchment_numbers.greater_than_value(0)
lake_volumes = field.makeEmptyField("Generic",np.float64,
grid_type=lake_mask.get_grid())
lake_mask_reduced = lake_mask.copy()
lake_mask_reduced.change_dtype(np.int32)
lake_operators_wrapper.reduce_connected_areas_to_points(lake_mask_reduced.get_data(),True)
lake_mask_inv = lake_mask.copy()
lake_mask_inv.invert_data()
orography = field.makeEmptyField("Generic",np.float64,
grid_type=lake_mask.get_grid())
orography.get_data()[lake_mask_inv.get_data()] = 3.0
orography.get_data()[lake_mask.get_data()] = 1.0
orography.get_data()[lake_mask_reduced.get_data().astype(bool)] = 0.0
lake_mask_inv.change_dtype(np.int32)
rdirs = determine_river_directions.determine_river_directions(orography,
lake_mask_reduced,
truesinks=None,
always_flow_to_sea=True,
use_diagonal_nbrs=True,
mark_pits_as_true_sinks=False)
rdirs.get_data()[lake_mask_inv.get_data()] = -1
simplified_basin_catchment_numbers = None
temporary_file = tempfile.NamedTemporaryFile(delete = False)
try:
temporary_file.close()
dummy_loop_log_filepath = temporary_file.name
simplified_basin_catchment_numbers = \
field.Field(cc.compute_catchments_cpp(rdirs.get_data(),loop_logfile=dummy_loop_log_filepath),
grid=lake_mask.get_grid())
finally:
os.remove(temporary_file.name)
for i in range(1,simplified_basin_catchment_numbers.find_maximum()+1):
if i in simplified_basin_catchment_numbers.get_data():
single_lake_mask = lake_mask.copy()
single_lake_mask.\
get_data()[simplified_basin_catchment_numbers.get_data() != i] = False
single_lake_flood_volume_thresholds = flood_volume_thresholds.copy()
single_lake_flood_volume_thresholds.\
get_data()[np.logical_not(single_lake_mask.get_data())] = 0.0
single_lake_flood_volume_thresholds.\
get_data()[np.logical_and(merge_types.get_data() != 10,
merge_types.get_data() != 11)] = 0.0
lake_volumes.get_data()[single_lake_mask.get_data()] = np.sum(single_lake_flood_volume_thresholds.get_data())
return lake_volumes
def advanced_burn_carved_rivers_driver(
input_orography_file,
input_orography_fieldname,
input_rdirs_file,
input_rdirs_fieldname,
input_minima_file,
input_minima_fieldname,
input_lakemask_file,
input_lakemask_fieldname,
output_orography_file,
output_orography_fieldname,
add_slope=False,
max_exploration_range=0,
minimum_height_change_threshold=0.0,
short_path_threshold=0,
short_minimum_height_change_threshold=0.0):
input_orography = iodriver.advanced_field_loader(
input_orography_file,
field_type='Orography',
fieldname=input_orography_fieldname)
input_rdirs = iodriver.advanced_field_loader(
input_rdirs_file,
field_type='Orography',
fieldname=input_rdirs_fieldname)
input_minima = iodriver.advanced_field_loader(
input_minima_file,
field_type='Orography',
fieldname=input_minima_fieldname)
input_lakemask = iodriver.advanced_field_loader(
input_lakemask_file,
field_type='Generic',
fieldname=input_lakemask_fieldname)
output_orography = field.Field(np.ascontiguousarray(
input_orography.get_data(), dtype=np.float64),
grid=input_orography.get_grid())
lake_operators_wrapper.burn_carved_rivers(
output_orography.get_data(),
np.ascontiguousarray(input_rdirs.get_data(), dtype=np.float64),
np.ascontiguousarray(input_minima.get_data(), dtype=np.int32),
np.ascontiguousarray(input_lakemask.get_data(), dtype=np.int32),
add_slope, max_exploration_range, minimum_height_change_threshold,
short_path_threshold, short_minimum_height_change_threshold)
iodriver.advanced_field_writer(output_orography_file,
output_orography,
fieldname=output_orography_fieldname)
def advanced_main(filename,
fieldname,
output_filename,
output_fieldname,
loop_logfile,
use_cpp_alg=True):
rdirs = iodriver.advanced_field_loader(filename,
field_type='Generic',
fieldname=fieldname)
nlat, nlon = rdirs.get_grid_dimensions()
if use_cpp_alg:
catchments = compute_catchments_cpp(rdirs.get_data(), loop_logfile)
else:
catchment_types, catchments = compute_catchments(
rdirs.get_data(), loop_logfile)
check_catchment_types(catchment_types,
logfile=path.splitext(output_filename)[0] +
".log")
numbered_catchments = field.Field(renumber_catchments_by_size(
catchments, loop_logfile),
grid=rdirs.get_grid())
iodriver.advanced_field_writer(target_filename=output_filename,
field=numbered_catchments,
fieldname=output_fieldname)
def advanced_basin_evaluation_driver(
input_minima_file,
input_minima_fieldname,
input_raw_orography_file,
input_raw_orography_fieldname,
input_corrected_orography_file,
input_corrected_orography_fieldname,
input_cell_areas_file,
input_cell_areas_fieldname,
input_prior_fine_rdirs_file,
input_prior_fine_rdirs_fieldname,
input_prior_fine_catchments_file,
input_prior_fine_catchments_fieldname,
input_coarse_catchment_nums_file,
input_coarse_catchment_nums_fieldname,
input_coarse_rdirs_file,
input_coarse_rdirs_fieldname,
combined_output_filename,
output_filepath,
output_filelabel,
output_basin_catchment_nums_filepath=None):
input_minima = iodriver.advanced_field_loader(
input_minima_file,
field_type='Generic',
fieldname=input_minima_fieldname)
input_raw_orography = iodriver.advanced_field_loader(
input_raw_orography_file,
field_type='Orography',
fieldname=input_raw_orography_fieldname)
input_corrected_orography = iodriver.advanced_field_loader(
input_corrected_orography_file,
field_type='Orography',
fieldname=input_corrected_orography_fieldname)
input_cell_areas = iodriver.advanced_field_loader(
input_cell_areas_file,
field_type='Generic',
fieldname=input_cell_areas_fieldname)
input_prior_fine_rdirs = iodriver.advanced_field_loader(
input_prior_fine_rdirs_file,
field_type='RiverDirections',
fieldname=input_prior_fine_rdirs_fieldname)
input_prior_fine_catchments = iodriver.advanced_field_loader(
input_prior_fine_catchments_file,
field_type='Generic',
fieldname=input_prior_fine_catchments_fieldname)
input_coarse_catchment_nums = iodriver.advanced_field_loader(
input_coarse_catchment_nums_file,
field_type='Generic',
fieldname=input_coarse_catchment_nums_fieldname)
input_coarse_rdirs = iodriver.advanced_field_loader(
input_coarse_rdirs_file,
field_type='Generic',
fieldname=input_coarse_rdirs_fieldname)
fine_grid = input_raw_orography.get_grid()
fine_shape = input_raw_orography.get_data().shape
connection_volume_thresholds = field.Field(
np.zeros(fine_shape, dtype=np.float64, order='C'), fine_grid)
flood_volume_thresholds = field.Field(
np.zeros(fine_shape, dtype=np.float64, order='C'), fine_grid)
flood_next_cell_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_next_cell_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_next_cell_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_next_cell_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_force_merge_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_force_merge_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_force_merge_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_force_merge_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_flood_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_flood_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_connect_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_connect_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_flood_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_connect_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
merge_points = field.Field(np.zeros(fine_shape, dtype=np.int32, order='C'),
fine_grid)
if output_basin_catchment_nums_filepath is not None:
basin_catchment_numbers = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
else:
basin_catchment_numbers = None
evaluate_basins_wrapper.evaluate_basins(
minima_in_int=np.ascontiguousarray(input_minima.get_data(),
dtype=np.int32),
raw_orography_in=np.ascontiguousarray(input_raw_orography.get_data(),
dtype=np.float64),
corrected_orography_in=np.ascontiguousarray(
input_corrected_orography.get_data(), dtype=np.float64),
cell_areas_in=np.ascontiguousarray(input_cell_areas.get_data(),
dtype=np.float64),
connection_volume_thresholds_in=connection_volume_thresholds.get_data(
),
flood_volume_thresholds_in=flood_volume_thresholds.get_data(),
prior_fine_rdirs_in=np.ascontiguousarray(
input_prior_fine_rdirs.get_data(), dtype=np.float64),
prior_coarse_rdirs_in=np.ascontiguousarray(
input_coarse_rdirs.get_data(), dtype=np.float64),
prior_fine_catchments_in=np.ascontiguousarray(
input_prior_fine_catchments.get_data(), dtype=np.int32),
coarse_catchment_nums_in=np.ascontiguousarray(
input_coarse_catchment_nums.get_data(), dtype=np.int32),
flood_next_cell_lat_index_in=flood_next_cell_lat_index.get_data(),
flood_next_cell_lon_index_in=flood_next_cell_lon_index.get_data(),
connect_next_cell_lat_index_in=connect_next_cell_lat_index.get_data(),
connect_next_cell_lon_index_in=connect_next_cell_lon_index.get_data(),
flood_force_merge_lat_index_in=flood_force_merge_lat_index.get_data(),
flood_force_merge_lon_index_in=flood_force_merge_lon_index.get_data(),
connect_force_merge_lat_index_in=connect_force_merge_lat_index.
get_data(),
connect_force_merge_lon_index_in=connect_force_merge_lon_index.
get_data(),
flood_redirect_lat_index_in=flood_redirect_lat_index.get_data(),
flood_redirect_lon_index_in=flood_redirect_lon_index.get_data(),
connect_redirect_lat_index_in=connect_redirect_lat_index.get_data(),
connect_redirect_lon_index_in=connect_redirect_lon_index.get_data(),
additional_flood_redirect_lat_index_in=
additional_flood_redirect_lat_index.get_data(),
additional_flood_redirect_lon_index_in=
additional_flood_redirect_lon_index.get_data(),
additional_connect_redirect_lat_index_in=
additional_connect_redirect_lat_index.get_data(),
additional_connect_redirect_lon_index_in=
additional_connect_redirect_lon_index.get_data(),
flood_local_redirect_out_int=flood_local_redirect.get_data(),
connect_local_redirect_out_int=connect_local_redirect.get_data(),
additional_flood_local_redirect_out_int=additional_flood_local_redirect
.get_data(),
additional_connect_local_redirect_out_int=
additional_connect_local_redirect.get_data(),
merge_points_out_int=merge_points.get_data(),
basin_catchment_numbers_in=basin_catchment_numbers.get_data())
connection_volume_thresholds_filename = path.join(
output_filepath, "connect_vts_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connection_volume_thresholds_filename,
connection_volume_thresholds,
fieldname='connection_volume_thresholds')
flood_volume_thresholds_filename = path.join(
output_filepath, "flood_vts_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_volume_thresholds_filename,
flood_volume_thresholds,
fieldname='flood_volume_thresholds')
flood_next_cell_lat_index_filename = path.join(
output_filepath, "flood_nci_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_next_cell_lat_index_filename,
flood_next_cell_lat_index,
fieldname='flood_next_cell_lat_index')
flood_next_cell_lon_index_filename = path.join(
output_filepath, "flood_nci_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_next_cell_lon_index_filename,
flood_next_cell_lon_index,
fieldname='flood_next_cell_lon_index')
connect_next_cell_lat_index_filename = path.join(
output_filepath, "connect_nci_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connect_next_cell_lat_index_filename,
connect_next_cell_lat_index,
fieldname='connect_next_cell_lat_index')
connect_next_cell_lon_index_filename = path.join(
output_filepath, "connect_nci_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connect_next_cell_lon_index_filename,
connect_next_cell_lon_index,
fieldname='connect_next_cell_lon_index')
flood_force_merge_lat_index_filename = path.join(
output_filepath, "flood_fmi_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_force_merge_lat_index_filename,
flood_force_merge_lat_index,
fieldname='flood_force_merge_lat_index')
flood_force_merge_lon_index_filename = path.join(
output_filepath, "flood_fmi_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_force_merge_lon_index_filename,
flood_force_merge_lon_index,
fieldname='flood_force_merge_lon_index')
connect_force_merge_lat_index_filename = path.join(
output_filepath, "connect_fmi_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connect_force_merge_lat_index_filename,
connect_force_merge_lat_index,
fieldname='connect_force_merge_lat_index')
connect_force_merge_lon_index_filename = path.join(
output_filepath, "connect_fmi_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connect_force_merge_lon_index_filename,
connect_force_merge_lon_index,
fieldname='connect_force_merge_lon_index')
flood_redirect_lat_index_filename = path.join(
output_filepath, "flood_ri_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_redirect_lat_index_filename,
flood_redirect_lat_index,
fieldname='flood_redirect_lat_index')
flood_redirect_lon_index_filename = path.join(
output_filepath, "flood_ri_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_redirect_lon_index_filename,
flood_redirect_lon_index,
fieldname='flood_redirect_lon_index')
connect_redirect_lat_index_filename = path.join(
output_filepath, "connect_ri_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connect_redirect_lat_index_filename,
connect_redirect_lat_index,
fieldname='connect_redirect_lat_index')
connect_redirect_lon_index_filename = path.join(
output_filepath, "connect_ri_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connect_redirect_lon_index_filename,
connect_redirect_lon_index,
fieldname='connect_redirect_lon_index')
additional_flood_redirect_lat_index_filename = path.join(
output_filepath, "additional_flood_ri_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(
additional_flood_redirect_lat_index_filename,
additional_flood_redirect_lat_index,
fieldname='additional_flood_redirect_lat_index')
additional_flood_redirect_lon_index_filename = path.join(
output_filepath, "additional_flood_ri_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(
additional_flood_redirect_lon_index_filename,
additional_flood_redirect_lon_index,
fieldname='additional_flood_redirect_lon_index')
additional_connect_redirect_lat_index_filename = path.join(
output_filepath,
"additional_connect_ri_lat_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(
additional_connect_redirect_lat_index_filename,
additional_connect_redirect_lat_index,
fieldname='additional_connect_redirect_lat_index')
additional_connect_redirect_lon_index_filename = path.join(
output_filepath,
"additional_connect_ri_lon_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(
additional_connect_redirect_lon_index_filename,
additional_connect_redirect_lon_index,
fieldname='additional_connect_redirect_lon_index')
flood_local_redirect_filename = path.join(
output_filepath, "flood_local_r_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(flood_local_redirect_filename,
flood_local_redirect,
fieldname='flood_local_redirect')
connect_local_redirect_filename = path.join(
output_filepath, "connect_local_r_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(connect_local_redirect_filename,
connect_local_redirect,
fieldname='connect_local_redirect')
additional_flood_local_redirect_filename = path.join(
output_filepath,
"additional_flood_local_r_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(additional_flood_local_redirect_filename,
additional_flood_local_redirect,
fieldname='additional_flood_local_redirect')
additional_connect_local_redirect_filename = path.join(
output_filepath,
"additional_connect_local_r_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(
additional_connect_local_redirect_filename,
additional_connect_local_redirect,
fieldname='additional_connect_local_redirect')
merge_points_filename = path.join(
output_filepath, "merge_points_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(merge_points_filename,
merge_points,
fieldname='merge_points')
lake_centers_filename = path.join(
output_filepath, "lake_centers_" + output_filelabel + ".nc")
iodriver.advanced_field_writer(lake_centers_filename,
input_minima,
fieldname="lake_centers")
individual_field_filenames = [
connection_volume_thresholds_filename,
flood_volume_thresholds_filename, flood_next_cell_lat_index_filename,
flood_next_cell_lon_index_filename,
connect_next_cell_lat_index_filename,
connect_next_cell_lon_index_filename,
flood_force_merge_lat_index_filename,
flood_force_merge_lon_index_filename,
connect_force_merge_lat_index_filename,
connect_force_merge_lon_index_filename,
flood_redirect_lat_index_filename, flood_redirect_lon_index_filename,
connect_redirect_lat_index_filename,
connect_redirect_lon_index_filename,
additional_flood_redirect_lat_index_filename,
additional_flood_redirect_lon_index_filename,
additional_connect_redirect_lat_index_filename,
additional_connect_redirect_lon_index_filename,
flood_local_redirect_filename, connect_local_redirect_filename,
additional_flood_local_redirect_filename,
additional_connect_local_redirect_filename, merge_points_filename,
lake_centers_filename
]
cdo_inst = cdo.Cdo()
cdo_inst.merge(input=" ".join(individual_field_filenames),
output=combined_output_filename)
for individual_field_filename in individual_field_filenames:
os.remove(individual_field_filename)
if output_basin_catchment_nums_filepath is not None:
iodriver.advanced_field_writer(output_basin_catchment_nums_filepath,
basin_catchment_numbers,
fieldname="basin_catchment_numbers")
def no_intermediaries_combine_hydrosheds_plus_rdirs_from_corrected_orog_driver(
self):
"""Combines Hydrosheds river direction with those from a corrected orography and possibly removes sinks"""
config = self._read_and_validate_config()
final_loops_log_filename = path.splitext(
self.output_catchments_filename)[0] + '_loops.log'
if self.rerun_post_processing_only is not None:
final_rdirs = \
iodriver.advanced_field_loader(self.rerun_post_processing_only,
field_type="RiverDirections",
fieldname=config.get("input_fieldname_options",
"river_directions_to_reprocess_fieldname"))
else:
orography_filename = config.get(
"input_options", "ten_minute_corrected_orography_filename")
orography = iodriver.advanced_field_loader(
orography_filename,
field_type='Orography',
fieldname=config.get(
"input_fieldname_options",
"ten_minute_corrected_orography_fieldname"))
hydrosheds_rdirs_au_af_sa_10min_filename = \
config.get("input_options","ten_minute_hydrosheds_au_auf_sa_river_directions_filename")
hydrosheds_rdirs = \
iodriver.advanced_field_loader(hydrosheds_rdirs_au_af_sa_10min_filename,
field_type="RiverDirections",
fieldname=config.get("input_fieldname_options",
"ten_minute_hydrosheds_au_auf_sa_river_directions_fieldname"))
second_intermediate_loops_log_filename = tempfile.mkstemp(
suffix=".txt", prefix="loops_log_second_int", dir="")[1]
truesinks_dummy = field.makeEmptyField("Generic",
np.bool_,
grid_type="LatLong10min")
truesinks_dummy.set_all(False)
if self.true_sinks_filename is not None:
use_true_sinks = True
truesinks = iodriver.advanced_field_loader(
self.true_sinks_filename,
field_type="Generic",
fieldname=config.get("input_fieldname_options",
"input_truesinks_fieldname"))
else:
use_true_sinks = False
if config.getboolean(
"general_options",
"replace_internal_basins_with_rdirs_with_truesinks"):
warnings.warn(
"Option replace_internal_basins_with_rdirs_with_truesinks "
"ignored when no true sinks file is specified")
first_intermediate_rdirs = field.makeEmptyField(
"RiverDirections", np.float64, grid_type="LatLong10min")
if use_true_sinks:
first_intermediate_rdirs_no_sinks = field.makeEmptyField(
"RiverDirections", np.float64, grid_type="LatLong10min")
ls_mask = iodriver.advanced_field_loader(
self.ls_mask_filename,
field_type="Generic",
fieldname=config.get("input_fieldname_options",
"input_landsea_mask_fieldname"))
ls_mask.set_data(
np.ascontiguousarray(ls_mask.get_data(), dtype=np.int32))
next_cell_lat_index_in_dummy = np.zeros(ls_mask.get_data().shape,
dtype=np.int32,
order='C')
next_cell_lon_index_in_dummy = np.zeros(ls_mask.get_data().shape,
dtype=np.int32,
order='C')
catchment_nums_dummy = np.zeros(ls_mask.get_data().shape,
dtype=np.int32,
order='C')
fill_sinks_wrapper.fill_sinks_cpp_func(orography_array=
np.ascontiguousarray(orography.get_data(), #@UndefinedVariable
dtype=np.float64),
method = 4,
use_ls_mask = True,
landsea_in = np.ascontiguousarray(ls_mask.get_data(),
dtype=np.int32),
set_ls_as_no_data_flag = False,
use_true_sinks = False,
true_sinks_in = np.ascontiguousarray(truesinks_dummy.\
get_data(),
dtype=np.int32),
next_cell_lat_index_in = next_cell_lat_index_in_dummy,
next_cell_lon_index_in = next_cell_lon_index_in_dummy,
rdirs_in =
first_intermediate_rdirs.get_data() if not use_true_sinks else
first_intermediate_rdirs_no_sinks.get_data(),
catchment_nums_in = catchment_nums_dummy,
prefer_non_diagonal_initial_dirs = False)
if use_true_sinks:
fill_sinks_wrapper.fill_sinks_cpp_func(
orography_array=np.ascontiguousarray(
orography.get_data(), #@UndefinedVariable
dtype=np.float64),
method=4,
use_ls_mask=True,
landsea_in=np.ascontiguousarray(ls_mask.get_data(),
dtype=np.int32),
set_ls_as_no_data_flag=False,
use_true_sinks=True,
true_sinks_in=np.ascontiguousarray(truesinks.get_data(),
dtype=np.int32),
next_cell_lat_index_in=next_cell_lat_index_in_dummy,
next_cell_lon_index_in=next_cell_lon_index_in_dummy,
rdirs_in=first_intermediate_rdirs.get_data(),
catchment_nums_in=catchment_nums_dummy,
prefer_non_diagonal_initial_dirs=False)
second_intermediate_rdirs = utilities.splice_rdirs(
rdirs_matching_ls_mask=first_intermediate_rdirs,
ls_mask=ls_mask,
other_rdirs=hydrosheds_rdirs)
second_intermediate_catchments = comp_catchs.compute_catchments_cpp(
second_intermediate_rdirs.get_data(),
second_intermediate_loops_log_filename)
second_intermediate_catchments = field.Field(comp_catchs.\
renumber_catchments_by_size(second_intermediate_catchments,
second_intermediate_loops_log_filename),
grid="LatLong10min")
if config.getboolean("general_options",
"keep_all_internal_basins"):
third_intermediate_rdirs = second_intermediate_rdirs
else:
third_intermediate_rdirs = \
utilities.remove_endorheic_basins(rdirs=second_intermediate_rdirs,
catchments=second_intermediate_catchments,
rdirs_without_endorheic_basins=
first_intermediate_rdirs_no_sinks if
(use_true_sinks and not config.getboolean('general_options',
'replace_internal_basins_with_rdirs_with_truesinks'))
else first_intermediate_rdirs,
replace_only_catchments=([int(value) for value in
config.get('general_options',
'replace_only_catchments').\
split(",")]
if config.get('general_options',
'replace_only_catchments')
else []),
exclude_catchments=([int(value) for value in
config.get('general_options',
'exclude_catchments').\
split(",")]
if config.get('general_options',
'exclude_catchments')
else []) )
third_intermediate_flowtocell = field.\
CumulativeFlow(create_hypothetical_river_paths_map(riv_dirs=third_intermediate_rdirs.get_data(),
lsmask=None,
use_f2py_func=True,
use_f2py_sparse_iterator=True,
nlat=1080,nlong=2160),
grid='LatLong10min')
third_intermediate_rdirs.make_contiguous()
third_intermediate_flowtocell.make_contiguous()
first_intermediate_rdirs.make_contiguous()
if use_true_sinks:
first_intermediate_rdirs_no_sinks.make_contiguous()
final_rdirs = utilities.replace_streams_downstream_from_loop(
third_intermediate_rdirs,
cumulative_flow=third_intermediate_flowtocell,
other_rdirs=first_intermediate_rdirs
if not use_true_sinks else first_intermediate_rdirs_no_sinks)
final_catchments = comp_catchs.compute_catchments_cpp(
final_rdirs.get_data(), final_loops_log_filename)
final_catchments = field.Field(comp_catchs.\
renumber_catchments_by_size(final_catchments,
final_loops_log_filename),
grid="LatLong10min")
final_flowtocell = field.CumulativeFlow(
create_hypothetical_river_paths_map(
riv_dirs=final_rdirs.get_data(),
lsmask=None,
use_f2py_func=True,
use_f2py_sparse_iterator=True,
nlat=1080,
nlong=2160),
grid='LatLong10min')
if self.rerun_post_processing_only is None:
iodriver.advanced_field_writer(
self.output_rdirs_filename,
final_rdirs,
fieldname=config.get("output_fieldname_options",
"output_river_directions_fieldname"))
iodriver.advanced_field_writer(self.output_catchments_filename,
final_catchments,
fieldname=config.get(
"output_fieldname_options",
"output_catchments_fieldname"))
iodriver.advanced_field_writer(self.output_cumulative_flow_filename,
final_flowtocell,
fieldname=config.get(
"output_fieldname_options",
"output_cumulative_flow_fieldname"))
if self.rerun_post_processing_only is None:
os.remove(second_intermediate_loops_log_filename)
def generate_test_data(self):
coarse_grid = grid.makeGrid(grid_type="LatLong", nlat=4, nlong=4)
fine_grid = grid.makeGrid(grid_type="LatLong", nlat=20, nlong=20)
fine_shape = (20, 20)
input_minima = field.Field(
np.array([[
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, True, False, False, False,
True, False, False, False, False, False, False, False, False,
True, False, False, False, False, True, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, True, False,
False, False, False, True, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, True, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False, False, False
]]), fine_grid)
input_raw_orography = field.Field(
np.array([[
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0
],
[
9.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0, 1.0, 1.0, 9.0,
1.0, 1.0, 1.0, 1.0, 9.0, 9.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 3.0, 3.0, 3.0, 6.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 7.0, 7.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 3.0, 3.0, 3.0, 9.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 9.0, 9.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 1.0, 1.0, 1.0, 9.0, 9.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 1.0, 1.0, 1.0, 9.0, 9.0, 9.0, 6.0, 9.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 5.0, 9.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 8.0, 9.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
9.0, 9.0, 9.0, 9.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
6.0, 6.0, 6.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
6.0, 6.0, 6.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
6.0, 6.0, 6.0, 8.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
]]), fine_grid)
input_corrected_orography = field.Field(
np.array([[
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0
],
[
9.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0, 1.0, 1.0, 9.0,
1.0, 1.0, 1.0, 1.0, 9.0, 9.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 3.0, 3.0, 3.0, 6.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 7.0, 7.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 3.0, 3.0, 3.0, 9.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 9.0, 9.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 1.0, 1.0, 1.0, 9.0, 9.0, 2.0, 2.0, 2.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 1.0, 1.0, 1.0, 9.0, 9.0, 9.0, 6.0, 9.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 5.0, 9.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 4.0, 4.0, 4.0, 9.0, 9.0, 3.0, 3.0, 3.0, 9.0
],
[
9.0, 7.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 8.0, 9.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
9.0, 9.0, 9.0, 9.0, 7.0, 7.0, 7.0, 7.0, 7.0, 7.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
6.0, 6.0, 6.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
6.0, 6.0, 6.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0, 6.0,
6.0, 6.0, 6.0, 8.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0, 9.0,
9.0, 9.0, 9.0, 9.0, 7.0, 0.0, 0.0, 0.0, 0.0, 0.0
]]), fine_grid)
input_cell_areas = field.Field(
np.ones(fine_shape, dtype=np.float64, order='C'), fine_grid)
input_lsmask = field.Field(
np.array([[
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
]]), fine_grid)
input_truesinks = field.Field(
np.array([[
False, False, False, False, False, False, False, False, False,
False, False, False, False, False, False, False, False, False,
False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
],
[
False, False, False, False, False, False, False,
False, False, False, False, False, False, False,
False, False, False, False, False, False
]]), fine_grid)
input_prior_fine_rdirs = determine_river_directions(
input_corrected_orography,
input_lsmask,
input_truesinks,
always_flow_to_sea=True,
use_diagonal_nbrs=True,
mark_pits_as_true_sinks=True)
input_prior_fine_catchments = \
field.Field(compute_catchments_cpp(input_prior_fine_rdirs.get_data(),
"/Users/thomasriddick/Documents/"
"data/temp/loop_from_test_data_gen.log"),
fine_grid)
input_coarse_catchment_nums = field.Field(
np.array([[4, 1, 2, 3], [4, 4, 6, 5], [4, 4, 6, 5], [7, 7, 7, 8]]),
coarse_grid)
input_coarse_rdirs = field.Field(
np.array([[5, 5, 5, 5], [2, 2, 5, 5], [5, 4, 8, 8], [8, 7, 4, 0]]),
coarse_grid)
connection_volume_thresholds = field.Field(
np.zeros(fine_shape, dtype=np.float64, order='C'), fine_grid)
flood_volume_thresholds = field.Field(
np.zeros(fine_shape, dtype=np.float64, order='C'), fine_grid)
flood_next_cell_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_next_cell_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_next_cell_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_next_cell_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_force_merge_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_force_merge_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_force_merge_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_force_merge_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_flood_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_flood_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_connect_redirect_lat_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_connect_redirect_lon_index = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
flood_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
connect_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_flood_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
additional_connect_local_redirect = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
merge_points = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
basin_catchment_numbers = field.Field(
np.zeros(fine_shape, dtype=np.int32, order='C'), fine_grid)
evaluate_basins_wrapper.evaluate_basins(
minima_in_int=np.ascontiguousarray(input_minima.get_data(),
dtype=np.int32),
raw_orography_in=np.ascontiguousarray(
input_raw_orography.get_data(), dtype=np.float64),
corrected_orography_in=np.ascontiguousarray(
input_corrected_orography.get_data(), dtype=np.float64),
cell_areas_in=np.ascontiguousarray(input_cell_areas.get_data(),
dtype=np.float64),
connection_volume_thresholds_in=connection_volume_thresholds.
get_data(),
flood_volume_thresholds_in=flood_volume_thresholds.get_data(),
prior_fine_rdirs_in=np.ascontiguousarray(
input_prior_fine_rdirs.get_data(), dtype=np.float64),
prior_coarse_rdirs_in=np.ascontiguousarray(
input_coarse_rdirs.get_data(), dtype=np.float64),
prior_fine_catchments_in=np.ascontiguousarray(
input_prior_fine_catchments.get_data(), dtype=np.int32),
coarse_catchment_nums_in=np.ascontiguousarray(
input_coarse_catchment_nums.get_data(), dtype=np.int32),
flood_next_cell_lat_index_in=flood_next_cell_lat_index.get_data(),
flood_next_cell_lon_index_in=flood_next_cell_lon_index.get_data(),
connect_next_cell_lat_index_in=connect_next_cell_lat_index.
get_data(),
connect_next_cell_lon_index_in=connect_next_cell_lon_index.
get_data(),
flood_force_merge_lat_index_in=flood_force_merge_lat_index.
get_data(),
flood_force_merge_lon_index_in=flood_force_merge_lon_index.
get_data(),
connect_force_merge_lat_index_in=connect_force_merge_lat_index.
get_data(),
connect_force_merge_lon_index_in=connect_force_merge_lon_index.
get_data(),
flood_redirect_lat_index_in=flood_redirect_lat_index.get_data(),
flood_redirect_lon_index_in=flood_redirect_lon_index.get_data(),
connect_redirect_lat_index_in=connect_redirect_lat_index.get_data(
),
connect_redirect_lon_index_in=connect_redirect_lon_index.get_data(
),
additional_flood_redirect_lat_index_in=
additional_flood_redirect_lat_index.get_data(),
additional_flood_redirect_lon_index_in=
additional_flood_redirect_lon_index.get_data(),
additional_connect_redirect_lat_index_in=
additional_connect_redirect_lat_index.get_data(),
additional_connect_redirect_lon_index_in=
additional_connect_redirect_lon_index.get_data(),
flood_local_redirect_out_int=flood_local_redirect.get_data(),
connect_local_redirect_out_int=connect_local_redirect.get_data(),
additional_flood_local_redirect_out_int=
additional_flood_local_redirect.get_data(),
additional_connect_local_redirect_out_int=
additional_connect_local_redirect.get_data(),
merge_points_out_int=merge_points.get_data(),
basin_catchment_numbers_in=basin_catchment_numbers.get_data())
self.print_field_for_julia(connection_volume_thresholds,
"connection_volume_thresholds",
"Float64",
grid_in="lake_grid")
self.print_field_for_julia(flood_volume_thresholds,
"flood_volume_thresholds",
"Float64",
grid_in="lake_grid")
self.print_field_for_julia(flood_next_cell_lat_index,
"flood_next_cell_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(flood_next_cell_lon_index,
"flood_next_cell_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(connect_next_cell_lat_index,
"connect_next_cell_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(connect_next_cell_lon_index,
"connect_next_cell_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(flood_force_merge_lat_index,
"flood_force_merge_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(flood_force_merge_lon_index,
"flood_force_merge_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(connect_force_merge_lat_index,
"connect_force_merge_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(connect_force_merge_lon_index,
"connect_force_merge_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(flood_redirect_lat_index,
"flood_redirect_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(flood_redirect_lon_index,
"flood_redirect_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(connect_redirect_lat_index,
"connect_redirect_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(connect_redirect_lon_index,
"connect_redirect_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(additional_flood_redirect_lat_index,
"additional_flood_redirect_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(additional_flood_redirect_lon_index,
"additional_flood_redirect_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(additional_connect_redirect_lat_index,
"additional_connect_redirect_lat_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(additional_connect_redirect_lon_index,
"additional_connect_redirect_lon_index",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(flood_local_redirect,
"flood_local_redirect",
"Bool",
grid_in="lake_grid")
self.print_field_for_julia(connect_local_redirect,
"connect_local_redirect",
"Bool",
grid_in="lake_grid")
self.print_field_for_julia(additional_flood_local_redirect,
"additional_flood_local_redirect",
"Bool",
grid_in="lake_grid")
self.print_field_for_julia(additional_connect_local_redirect,
"additional_connect_local_redirect",
"Bool",
grid_in="lake_grid")
self.print_field_for_julia(merge_points,
"merge_points",
"Int64",
grid_in="lake_grid")
self.print_field_for_julia(input_minima,
"input_minima",
"Bool",
grid_in="lake_grid")
def connect_coarse_lake_catchments(coarse_catchments,lake_centers,basin_catchment_numbers,
flood_next_cell_index_lat,flood_next_cell_index_lon,
flood_redirect_lat,flood_redirect_lon,
additional_flood_redirect_lat,additional_flood_redirect_lon,
local_redirect,additional_local_redirect,
merge_types,river_directions,scale_factor = 3,
correct_cumulative_flow=False,
cumulative_flow=None):
if correct_cumulative_flow:
if cumulative_flow is None or river_directions is None:
raise RuntimeError("Required input files for cumulative flow correction not provided")
old_coarse_catchments = coarse_catchments.copy()
lake_centers_array = np.argwhere(lake_centers.get_data())
lake_centers_list = [lake_centers_array[i,:].tolist()
for i in range(lake_centers_array.shape[0])]
overflow_catchments = field.makeEmptyField(field_type='Generic',dtype=np.int64,
grid_type=lake_centers.get_grid())
overflow_coords_lats = field.makeEmptyField(field_type='Generic',dtype=np.int64,
grid_type=lake_centers.get_grid())
overflow_coords_lons = field.makeEmptyField(field_type='Generic',dtype=np.int64,
grid_type=lake_centers.get_grid())
for lake_center_coords in lake_centers_list:
basin_number = basin_catchment_numbers.get_data()[tuple(lake_center_coords)]
while True:
secondary_merge_coords = np.argwhere(
np.logical_and(
np.logical_or(merge_types.get_data() == 10,
merge_types.get_data() == 11),
basin_catchment_numbers.get_data() == basin_number))[0,:].tolist()
double_merge = np.any(np.logical_and(merge_types.get_data() == 11,
basin_catchment_numbers.get_data() == basin_number))
basin_number = basin_catchment_numbers.get_data()[flood_next_cell_index_lat.get_data()[tuple(secondary_merge_coords)],
flood_next_cell_index_lon.get_data()[tuple(secondary_merge_coords)]]
if basin_number == 0:
is_local_redirect = ((local_redirect.get_data()[tuple(secondary_merge_coords)]) if not double_merge else
(additional_local_redirect.get_data()[tuple(secondary_merge_coords)]))
if is_local_redirect:
if double_merge:
basin_number = \
basin_catchment_numbers.\
get_data()[additional_flood_redirect_lat.get_data()[tuple(secondary_merge_coords)],
additional_flood_redirect_lon.get_data()[tuple(secondary_merge_coords)]]
else:
basin_number = \
basin_catchment_numbers.\
get_data()[flood_redirect_lat.get_data()[tuple(secondary_merge_coords)],
flood_redirect_lon.get_data()[tuple(secondary_merge_coords)]]
else:
if double_merge:
overflow_catchment = \
coarse_catchments.get_data()[additional_flood_redirect_lat.get_data()[tuple(secondary_merge_coords)],
additional_flood_redirect_lon.get_data()[tuple(secondary_merge_coords)]]
overflow_coords = (additional_flood_redirect_lat.get_data()[tuple(secondary_merge_coords)],
additional_flood_redirect_lon.get_data()[tuple(secondary_merge_coords)])
else:
overflow_catchment = \
coarse_catchments.get_data()[flood_redirect_lat.get_data()[tuple(secondary_merge_coords)],
flood_redirect_lon.get_data()[tuple(secondary_merge_coords)]]
overflow_coords = (flood_redirect_lat.get_data()[tuple(secondary_merge_coords)],
flood_redirect_lon.get_data()[tuple(secondary_merge_coords)])
break
overflow_catchments.get_data()[tuple(lake_center_coords)] = overflow_catchment
overflow_coords_lats.get_data()[tuple(lake_center_coords)] = overflow_coords[0]
overflow_coords_lons.get_data()[tuple(lake_center_coords)] = overflow_coords[1]
#specific to latlon grid
sink_points_array = np.argwhere(np.logical_or(river_directions.get_data() == 5,
river_directions.get_data() == -2))
sink_points_list = [sink_points_array[i,:].tolist()
for i in range(sink_points_array.shape[0])]
catchment_trees = CatchmentTrees()
sink_point_cumulative_flow_redirect_lat = field.makeEmptyField(field_type='Generic',dtype=np.int64,
grid_type=coarse_catchments.get_grid())
sink_point_cumulative_flow_redirect_lon = field.makeEmptyField(field_type='Generic',dtype=np.int64,
grid_type=coarse_catchments.get_grid())
for sink_point in sink_points_list:
sink_point_coarse_catchment = coarse_catchments.get_data()[tuple(sink_point)]
#Specific to lat-lon grids
overflow_catch_fine_cells_in_coarse_cell = overflow_catchments.get_data()[sink_point[0]*scale_factor:(sink_point[0]+1)*scale_factor,
sink_point[1]*scale_factor:(sink_point[1]+1)*scale_factor]
overflow_coords_lat_fine_cells_in_coarse_cell = overflow_coords_lats.get_data()[sink_point[0]*scale_factor:(sink_point[0]+1)*scale_factor,
sink_point[1]*scale_factor:(sink_point[1]+1)*scale_factor]
overflow_coords_lon_fine_cells_in_coarse_cell = overflow_coords_lons.get_data()[sink_point[0]*scale_factor:(sink_point[0]+1)*scale_factor,
sink_point[1]*scale_factor:(sink_point[1]+1)*scale_factor]
overflow_catchment_list = overflow_catch_fine_cells_in_coarse_cell[overflow_catch_fine_cells_in_coarse_cell != 0].tolist()
if not overflow_catchment_list:
continue
overflow_catchment_counters = Counter(overflow_catchment_list)
highest_count = max(overflow_catchment_counters.values())
overflow_catchment = [ value for value,count in overflow_catchment_counters.items() if count == highest_count][0]
if sink_point_coarse_catchment == overflow_catchment:
continue
overflow_catchment_fine_coords_within_coarse_cell = \
tuple(np.argwhere(overflow_catch_fine_cells_in_coarse_cell == overflow_catchment)[0,:].tolist())
sink_point_cumulative_flow_redirect_lat.get_data()[tuple(sink_point)] = \
overflow_coords_lat_fine_cells_in_coarse_cell[overflow_catchment_fine_coords_within_coarse_cell]
sink_point_cumulative_flow_redirect_lon.get_data()[tuple(sink_point)] = \
overflow_coords_lon_fine_cells_in_coarse_cell[overflow_catchment_fine_coords_within_coarse_cell]
catchment_trees.add_link(sink_point_coarse_catchment,overflow_catchment)
for supercatchment_number,tree in catchment_trees.primary_catchments.items():
for subcatchments_num in tree.get_all_subcatchment_nums():
coarse_catchments.get_data()[subcatchments_num == coarse_catchments.get_data()] = \
supercatchment_number
if correct_cumulative_flow:
while catchment_trees.all_catchments:
upstream_catchments = catchment_trees.pop_leaves()
for upstream_catchment in upstream_catchments:
if np.any(np.logical_and(np.logical_or(river_directions.get_data() == 5,
river_directions.get_data() == -2),
old_coarse_catchments.get_data() == upstream_catchment)):
upstream_catchment_center = \
tuple(np.argwhere(np.logical_and(np.logical_or(river_directions.get_data() == 5,
river_directions.get_data() == -2),
old_coarse_catchments.get_data() == upstream_catchment))[0,:].tolist())
update_cumulative_flow(upstream_catchment_center,
(sink_point_cumulative_flow_redirect_lat.get_data()[upstream_catchment_center],
sink_point_cumulative_flow_redirect_lon.get_data()[upstream_catchment_center]),
cumulative_flow,river_directions)
return field.Field(cc.renumber_catchments_by_size(coarse_catchments.get_data()),type="Generic",
grid=coarse_catchments.get_grid()),cumulative_flow
return field.Field(cc.renumber_catchments_by_size(coarse_catchments.get_data()),type="Generic",
grid=coarse_catchments.get_grid()),None