def initialize_landcover_parameters(landcover_file, landcover_initial_fields_file, dst_dir):
"""generate initial landcover_init_param parameters"""
lc_data_items = read_data_items_from_txt(landcover_initial_fields_file)
# print(lc_data_items)
field_names = lc_data_items[0]
lu_id = -1
for i, v in enumerate(field_names):
if StringClass.string_match(v, 'LANDUSE_ID'):
lu_id = i
break
data_items = lc_data_items[1:]
replace_dicts = dict()
for item in data_items:
for i, v in enumerate(item):
if i != lu_id:
if field_names[i].upper() not in list(replace_dicts.keys()):
replace_dicts[field_names[i].upper()] = {float(item[lu_id]): float(v)}
else:
replace_dicts[field_names[i].upper()][float(item[lu_id])] = float(v)
# print(replace_dicts)
# Generate GTIFF
for item, v in list(replace_dicts.items()):
filename = dst_dir + os.path.sep + item + '.tif'
print(filename)
RasterUtilClass.raster_reclassify(landcover_file, v, filename)
return list(replace_dicts['LANDCOVER'].values())
def convert_code(in_file, out_file, in_alg='taudem', out_alg='arcgis', datatype=None):
"""
convert D8 flow direction code from one algorithm to another.
Args:
in_file: input raster file path
out_file: output raster file path
in_alg: available algorithms are in FlowModelConst.d8_dirs. "taudem" is the default
out_alg: same as in_alg. "arcgis" is the default
datatype: default is None and use the datatype of the in_file
"""
FileClass.check_file_exists(in_file)
in_alg = in_alg.lower()
out_alg = out_alg.lower()
if in_alg not in FlowModelConst.d8_dirs or out_alg not in FlowModelConst.d8_dirs:
raise RuntimeError('The input algorithm name should one of %s' %
', '.join(list(FlowModelConst.d8_dirs.keys())))
convert_dict = dict()
in_code = FlowModelConst.d8_dirs.get(in_alg)
out_code = FlowModelConst.d8_dirs.get(out_alg)
assert len(in_code) == len(out_code)
for i, tmp_in_code in enumerate(in_code):
convert_dict[tmp_in_code] = out_code[i]
if datatype is not None and datatype in GDALDataType:
RasterUtilClass.raster_reclassify(in_file, convert_dict, out_file, datatype)
else:
RasterUtilClass.raster_reclassify(in_file, convert_dict, out_file)
def convert_code(in_file, out_file, in_alg='taudem', out_alg='arcgis', datatype=None):
"""
convert D8 flow direction code from one algorithm to another.
Args:
in_file: input raster file path
out_file: output raster file path
in_alg: available algorithms are in FlowModelConst.d8_dirs. "taudem" is the default
out_alg: same as in_alg. "arcgis" is the default
datatype: default is None and use the datatype of the in_file
"""
FileClass.check_file_exists(in_file)
in_alg = in_alg.lower()
out_alg = out_alg.lower()
if in_alg not in FlowModelConst.d8_dirs or out_alg not in FlowModelConst.d8_dirs:
raise RuntimeError('The input algorithm name should one of %s' %
', '.join(list(FlowModelConst.d8_dirs.keys())))
convert_dict = dict()
in_code = FlowModelConst.d8_dirs.get(in_alg)
out_code = FlowModelConst.d8_dirs.get(out_alg)
assert len(in_code) == len(out_code)
for i, tmp_in_code in enumerate(in_code):
convert_dict[tmp_in_code] = out_code[i]
if datatype is not None and datatype in GDALDataType:
RasterUtilClass.raster_reclassify(in_file, convert_dict, out_file, datatype)
else:
RasterUtilClass.raster_reclassify(in_file, convert_dict, out_file)
def reclassify_landcover_parameters(landuse_file, landcover_file, landcover_initial_fields_file,
landcover_lookup_file, attr_names, dst_dir):
"""relassify landcover_init_param parameters"""
land_cover_codes = LanduseUtilClass.initialize_landcover_parameters(
landuse_file, landcover_initial_fields_file, dst_dir)
attr_map = LanduseUtilClass.read_crop_lookup_table(landcover_lookup_file)
n = len(attr_names)
replace_dicts = list()
dst_crop_tifs = list()
for i in range(n):
cur_attr = attr_names[i]
cur_dict = dict()
dic = attr_map[cur_attr]
for code in land_cover_codes:
if MathClass.floatequal(code, DEFAULT_NODATA):
continue
if code not in list(cur_dict.keys()):
cur_dict[code] = dic.get(code)
replace_dicts.append(cur_dict)
dst_crop_tifs.append(dst_dir + os.path.sep + cur_attr + '.tif')
# print(replace_dicts)
# print(len(replace_dicts))
# print(dst_crop_tifs)
# print(len(dst_crop_tifs))
# Generate GTIFF
for i, v in enumerate(dst_crop_tifs):
# print(dst_crop_tifs[i])
RasterUtilClass.raster_reclassify(landcover_file, replace_dicts[i], v)
def reclassify_landcover_parameters(landuse_file, landcover_file,
landcover_initial_fields_file,
landcover_lookup_file, attr_names,
dst_dir):
"""relassify landcover_init_param parameters"""
land_cover_codes = LanduseUtilClass.initialize_landcover_parameters(
landuse_file, landcover_initial_fields_file, dst_dir)
attr_map = LanduseUtilClass.read_crop_lookup_table(
landcover_lookup_file)
n = len(attr_names)
replace_dicts = list()
dst_crop_tifs = list()
for i in range(n):
cur_attr = attr_names[i]
cur_dict = dict()
dic = attr_map[cur_attr]
for code in land_cover_codes:
if MathClass.floatequal(code, DEFAULT_NODATA):
continue
if code not in list(cur_dict.keys()):
cur_dict[code] = dic.get(code)
replace_dicts.append(cur_dict)
dst_crop_tifs.append(dst_dir + os.path.sep + cur_attr + '.tif')
# print(replace_dicts)
# print(len(replace_dicts))
# print(dst_crop_tifs)
# print(len(dst_crop_tifs))
# Generate GTIFF
for i, v in enumerate(dst_crop_tifs):
# print(dst_crop_tifs[i])
RasterUtilClass.raster_reclassify(landcover_file, replace_dicts[i],
v)
def initialize_landcover_parameters(landcover_file,
landcover_initial_fields_file,
dst_dir):
"""generate initial landcover_init_param parameters"""
lc_data_items = read_data_items_from_txt(landcover_initial_fields_file)
# print(lc_data_items)
field_names = lc_data_items[0]
lu_id = -1
for i, v in enumerate(field_names):
if StringClass.string_match(v, 'LANDUSE_ID'):
lu_id = i
break
data_items = lc_data_items[1:]
replace_dicts = dict()
for item in data_items:
for i, v in enumerate(item):
if i != lu_id:
if field_names[i].upper() not in list(
replace_dicts.keys()):
replace_dicts[field_names[i].upper()] = {
float(item[lu_id]): float(v)
}
else:
replace_dicts[field_names[i].upper()][float(
item[lu_id])] = float(v)
# print(replace_dicts)
# Generate GTIFF
for item, v in list(replace_dicts.items()):
filename = dst_dir + os.path.sep + item + '.tif'
print(filename)
RasterUtilClass.raster_reclassify(landcover_file, v, filename)
return list(replace_dicts['LANDCOVER'].values())
def post_process_of_delineated_data(cfg):
"""Do some necessary transfer for subbasin, stream, and flow direction raster."""
# inputs
stream_net_file = cfg.taudems.streamnet_shp
subbasin_file = cfg.taudems.subbsn_m
flow_dir_file_tau = cfg.taudems.d8flow_m
stream_raster_file = cfg.taudems.stream_m
# outputs
# -- shapefile
shp_dir = cfg.dirs.geoshp
UtilClass.mkdir(shp_dir)
# ---- outlet, copy from DirNameUtils.TauDEM
FileClass.copy_files(cfg.taudems.outlet_m, cfg.vecs.outlet)
# ---- reaches
output_reach_file = cfg.vecs.reach
# ---- subbasins
subbasin_vector_file = cfg.vecs.subbsn
# -- raster file
output_subbasin_file = cfg.spatials.subbsn
output_flow_dir_file = cfg.spatials.d8flow
output_stream_link_file = cfg.spatials.stream_link
output_hillslope_file = cfg.spatials.hillslope
id_map = StreamnetUtil.serialize_streamnet(stream_net_file,
output_reach_file)
RasterUtilClass.raster_reclassify(subbasin_file, id_map,
output_subbasin_file, GDT_Int32)
StreamnetUtil.assign_stream_id_raster(stream_raster_file,
output_subbasin_file,
output_stream_link_file)
# Convert D8 encoding rule to ArcGIS
D8Util.convert_code(flow_dir_file_tau, output_flow_dir_file)
# convert raster to shapefile (for subbasin and basin)
print('Generating subbasin vector...')
VectorUtilClass.raster2shp(output_subbasin_file, subbasin_vector_file,
'subbasin', FieldNames.subbasin_id)
mask_file = cfg.spatials.mask
basin_vector = cfg.vecs.bsn
print('Generating basin vector...')
VectorUtilClass.raster2shp(mask_file, basin_vector, 'basin',
FieldNames.basin)
# delineate hillslope
DelineateHillslope.downstream_method_whitebox(output_stream_link_file,
flow_dir_file_tau,
output_hillslope_file)
def post_process_of_delineated_data(cfg):
"""Do some necessary transfer for subbasin, stream, and flow direction raster."""
# inputs
stream_net_file = cfg.taudems.streamnet_shp
subbasin_file = cfg.taudems.subbsn_m
flow_dir_file_tau = cfg.taudems.d8flow_m
stream_raster_file = cfg.taudems.stream_m
# outputs
# -- shapefile
shp_dir = cfg.dirs.geoshp
UtilClass.mkdir(shp_dir)
# ---- outlet, copy from DirNameUtils.TauDEM
FileClass.copy_files(cfg.taudems.outlet_m, cfg.vecs.outlet)
# ---- reaches
output_reach_file = cfg.vecs.reach
# ---- subbasins
subbasin_vector_file = cfg.vecs.subbsn
# -- raster file
output_subbasin_file = cfg.spatials.subbsn
output_flow_dir_file = cfg.spatials.d8flow
output_stream_link_file = cfg.spatials.stream_link
output_hillslope_file = cfg.spatials.hillslope
id_map = StreamnetUtil.serialize_streamnet(stream_net_file, output_reach_file)
RasterUtilClass.raster_reclassify(subbasin_file, id_map, output_subbasin_file, GDT_Int32)
StreamnetUtil.assign_stream_id_raster(stream_raster_file, output_subbasin_file,
output_stream_link_file)
# Convert D8 encoding rule to ArcGIS
D8Util.convert_code(flow_dir_file_tau, output_flow_dir_file)
# convert raster to shapefile (for subbasin and basin)
print('Generating subbasin vector...')
VectorUtilClass.raster2shp(output_subbasin_file, subbasin_vector_file, 'subbasin',
FieldNames.subbasin_id)
mask_file = cfg.spatials.mask
basin_vector = cfg.vecs.bsn
print('Generating basin vector...')
VectorUtilClass.raster2shp(mask_file, basin_vector, 'basin', FieldNames.basin)
# delineate hillslope
DelineateHillslope.downstream_method_whitebox(output_stream_link_file, flow_dir_file_tau,
output_hillslope_file)
def lookup_soil_parameters(dstdir, soiltype_file, soil_lookup_file):
"""Reclassify soil parameters by lookup table."""
# Read soil properties from txt file
soil_lookup_data = read_data_items_from_txt(soil_lookup_file)
soil_instances = list()
soil_prop_flds = soil_lookup_data[0][:]
for i in range(1, len(soil_lookup_data)):
cur_soil_data_item = soil_lookup_data[i][:]
cur_seqn = cur_soil_data_item[0]
cur_sname = cur_soil_data_item[1]
cur_soil_ins = SoilProperty(cur_seqn, cur_sname)
for j in range(2, len(soil_prop_flds)):
cur_flds = StringClass.split_string(cur_soil_data_item[j],
'-') # Get field values
for k, tmpfld in enumerate(cur_flds):
cur_flds[k] = float(tmpfld) # Convert to float
if StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._NLYRS):
cur_soil_ins.SOILLAYERS = int(cur_flds[0])
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._Z):
cur_soil_ins.SOILDEPTH = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._OM):
cur_soil_ins.OM = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._CLAY):
cur_soil_ins.CLAY = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._SILT):
cur_soil_ins.SILT = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._SAND):
cur_soil_ins.SAND = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._ROCK):
cur_soil_ins.ROCK = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._ZMX):
cur_soil_ins.SOL_ZMX = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._ANIONEXCL):
cur_soil_ins.ANION_EXCL = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._CRK):
cur_soil_ins.SOL_CRK = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._BD):
cur_soil_ins.DENSITY = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._K):
cur_soil_ins.CONDUCTIVITY = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._WP):
cur_soil_ins.WILTINGPOINT = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._FC):
cur_soil_ins.FIELDCAP = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._AWC):
cur_soil_ins.AWC = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._POROSITY):
cur_soil_ins.POROSITY = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._USLE_K):
cur_soil_ins.USLE_K = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._ALB):
cur_soil_ins.SOL_ALB = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._ESCO):
cur_soil_ins.ESCO = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._NO3):
cur_soil_ins.SOL_NO3 = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._NH4):
cur_soil_ins.SOL_NH4 = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._ORGN):
cur_soil_ins.SOL_ORGN = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._SOLP):
cur_soil_ins.SOL_SOLP = cur_flds
elif StringClass.string_match(soil_prop_flds[j],
SoilUtilClass._ORGP):
cur_soil_ins.SOL_ORGP = cur_flds
cur_soil_ins.check_data_validation()
soil_instances.append(cur_soil_ins)
soil_prop_dict = dict()
for sol in soil_instances:
cur_sol_dict = sol.soil_dict()
for fld in cur_sol_dict:
if fld in soil_prop_dict:
soil_prop_dict[fld].append(cur_sol_dict[fld])
else:
soil_prop_dict[fld] = [cur_sol_dict[fld]]
# print(list(soilPropDict.keys()))
# print(list(soilPropDict.values()))
replace_dicts = list()
dst_soil_tifs = list()
seqns = soil_prop_dict[SoilUtilClass._SEQN]
max_lyr_num = int(numpy.max(soil_prop_dict[SoilUtilClass._NLYRS]))
for key in soil_prop_dict:
if key != SoilUtilClass._SEQN and key != SoilUtilClass._NAME:
key_l = 1
for key_v in soil_prop_dict[key]:
if isinstance(key_v, list):
if len(key_v) > key_l:
key_l = len(key_v)
if key_l == 1:
cur_dict = {}
for i, tmpseq in enumerate(seqns):
cur_dict[float(tmpseq)] = soil_prop_dict[key][i]
replace_dicts.append(cur_dict)
dst_soil_tifs.append(dstdir + os.path.sep + key + '.tif')
else:
for i in range(max_lyr_num):
cur_dict = dict()
for j, tmpseq in enumerate(seqns):
if i < soil_prop_dict[SoilUtilClass._NLYRS][j]:
cur_dict[float(
tmpseq)] = soil_prop_dict[key][j][i]
else:
cur_dict[float(seqns[j])] = DEFAULT_NODATA
replace_dicts.append(cur_dict)
dst_soil_tifs.append(dstdir + os.path.sep + key + '_' +
str(i + 1) + '.tif')
# print(replaceDicts)
# print(len(replaceDicts))
# print(dstSoilTifs)
# print(len(dstSoilTifs))
# Generate GTIFF
for i, soil_tif in enumerate(dst_soil_tifs):
print(soil_tif)
RasterUtilClass.raster_reclassify(soiltype_file, replace_dicts[i],
soil_tif)
def watershed_delineation(np, dem, outlet_file=None, thresh=0, singlebasin=False,
workingdir=None, mpi_bin=None, bin_dir=None,
logfile=None, runtime_file=None, hostfile=None,
avoid_redo=False):
"""Watershed Delineation based on D8 flow direction.
Args:
np: process number for MPI
dem: DEM path
outlet_file: predefined outlet shapefile path
thresh: predefined threshold for extracting stream from accumulated flow direction
singlebasin: when set True, only extract subbasins that drains into predefined outlets
workingdir: directory that store outputs
mpi_bin: directory of MPI executable binary, e.g., mpiexec, mpirun
bin_dir: directory of TauDEM and other executable binaries
logfile: log file path
runtime_file: runtime file path
hostfile: host list file path for MPI
avoid_redo: avoid executing some functions that do not depend on input arguments
when repeatedly invoke this function
"""
# 1. Check directories
if not os.path.exists(dem):
TauDEM.error('DEM: %s is not existed!' % dem)
dem = os.path.abspath(dem)
if workingdir is None or workingdir is '':
workingdir = os.path.dirname(dem)
nc = TauDEMFilesUtils(workingdir) # predefined names
workingdir = nc.workspace
UtilClass.mkdir(workingdir)
# 2. Check log file
if logfile is not None and FileClass.is_file_exists(logfile):
os.remove(logfile)
# 3. perform calculation
# Filling DEM
if not (avoid_redo and FileClass.is_file_exists(nc.filldem)):
UtilClass.writelog(logfile, '[Output] %s' % 'remove pit...', 'a')
TauDEM.pitremove(np, dem, nc.filldem, workingdir, mpi_bin, bin_dir,
log_file=logfile, runtime_file=runtime_file, hostfile=hostfile)
# Flow direction based on D8 algorithm
if not (avoid_redo and FileClass.is_file_exists(nc.d8flow)):
UtilClass.writelog(logfile, '[Output] %s' % 'D8 flow direction...', 'a')
TauDEM.d8flowdir(np, nc.filldem, nc.d8flow, nc.slp, workingdir,
mpi_bin, bin_dir, log_file=logfile,
runtime_file=runtime_file, hostfile=hostfile)
# Flow accumulation without stream skeleton as weight
if not (avoid_redo and FileClass.is_file_exists(nc.d8acc)):
UtilClass.writelog(logfile, '[Output] %s' % 'D8 flow accumulation...', 'a')
TauDEM.aread8(np, nc.d8flow, nc.d8acc, None, None, False, workingdir, mpi_bin, bin_dir,
log_file=logfile, runtime_file=runtime_file, hostfile=hostfile)
# Initial stream network using mean accumulation as threshold
UtilClass.writelog(logfile, '[Output] %s' % 'Generating stream raster initially...', 'a')
min_accum, max_accum, mean_accum, std_accum = RasterUtilClass.raster_statistics(nc.d8acc)
TauDEM.threshold(np, nc.d8acc, nc.stream_raster, mean_accum, workingdir,
mpi_bin, bin_dir, log_file=logfile,
runtime_file=runtime_file, hostfile=hostfile)
# Outlets position initialization and adjustment
UtilClass.writelog(logfile, '[Output] %s' % 'Moving outlet to stream...', 'a')
if outlet_file is None: # if not given, take cell with maximum accumulation as outlet
outlet_file = nc.outlet_pre
TauDEM.connectdown(np, nc.d8flow, nc.d8acc, outlet_file, nc.outlet_m, wtsd=None,
workingdir=workingdir, mpiexedir=mpi_bin, exedir=bin_dir,
log_file=logfile, runtime_file=runtime_file, hostfile=hostfile)
TauDEM.moveoutletstostrm(np, nc.d8flow, nc.stream_raster, outlet_file,
nc.outlet_m, workingdir=workingdir,
mpiexedir=mpi_bin, exedir=bin_dir,
log_file=logfile, runtime_file=runtime_file, hostfile=hostfile)
# Stream skeleton by peuker-douglas algorithm
UtilClass.writelog(logfile, '[Output] %s' % 'Generating stream skeleton ...', 'a')
TauDEM.peukerdouglas(np, nc.filldem, nc.stream_pd, workingdir,
mpi_bin, bin_dir, log_file=logfile,
runtime_file=runtime_file, hostfile=hostfile)
# Weighted flow acculation with outlet
UtilClass.writelog(logfile, '[Output] %s' % 'Flow accumulation with outlet...', 'a')
tmp_outlet = None
if singlebasin:
tmp_outlet = nc.outlet_m
TauDEM.aread8(np, nc.d8flow, nc.d8acc_weight, tmp_outlet, nc.stream_pd, False,
workingdir, mpi_bin, bin_dir, log_file=logfile,
runtime_file=runtime_file, hostfile=hostfile)
# Determine threshold by input argument or dropanalysis function
if thresh <= 0: # find the optimal threshold using dropanalysis function
UtilClass.writelog(logfile, '[Output] %s' %
'Drop analysis to select optimal threshold...', 'a')
min_accum, max_accum, mean_accum, std_accum = \
RasterUtilClass.raster_statistics(nc.d8acc_weight)
if mean_accum - std_accum < 0:
minthresh = mean_accum
else:
minthresh = mean_accum - std_accum
maxthresh = mean_accum + std_accum
TauDEM.dropanalysis(np, nc.filldem, nc.d8flow, nc.d8acc_weight,
nc.d8acc_weight, nc.outlet_m, minthresh, maxthresh,
20, 'true', nc.drptxt, workingdir, mpi_bin, bin_dir,
log_file=logfile, runtime_file=runtime_file, hostfile=hostfile)
if not FileClass.is_file_exists(nc.drptxt):
# raise RuntimeError('Dropanalysis failed and drp.txt was not created!')
UtilClass.writelog(logfile, '[Output] %s' %
'dropanalysis failed!', 'a')
thresh = 0.5 * (maxthresh - minthresh) + minthresh
else:
with open(nc.drptxt, 'r', encoding='utf-8') as drpf:
temp_contents = drpf.read()
(beg, thresh) = temp_contents.rsplit(' ', 1)
thresh = float(thresh)
UtilClass.writelog(logfile, '[Output] %s: %f' %
('Selected optimal threshold: ', thresh), 'a')
# Final stream network
UtilClass.writelog(logfile, '[Output] %s' % 'Generating stream raster...', 'a')
TauDEM.threshold(np, nc.d8acc_weight, nc.stream_raster, thresh,
workingdir, mpi_bin, bin_dir, log_file=logfile,
runtime_file=runtime_file, hostfile=hostfile)
UtilClass.writelog(logfile, '[Output] %s' % 'Generating stream net...', 'a')
TauDEM.streamnet(np, nc.filldem, nc.d8flow, nc.d8acc_weight, nc.stream_raster,
nc.outlet_m, nc.stream_order, nc.channel_net,
nc.channel_coord, nc.streamnet_shp, nc.subbsn,
workingdir, mpi_bin, bin_dir,
log_file=logfile, runtime_file=runtime_file, hostfile=hostfile)
# Serialize IDs of subbasins and the corresponding streams
UtilClass.writelog(logfile, '[Output] %s' % 'Serialize subbasin&stream IDs...', 'a')
id_map = StreamnetUtil.serialize_streamnet(nc.streamnet_shp, nc.streamnet_m)
RasterUtilClass.raster_reclassify(nc.subbsn, id_map, nc.subbsn_m, GDT_Int32)
StreamnetUtil.assign_stream_id_raster(nc.stream_raster, nc.subbsn_m, nc.stream_m)
# convert raster to shapefile (for subbasin and basin)
UtilClass.writelog(logfile, '[Output] %s' % 'Generating subbasin vector...', 'a')
VectorUtilClass.raster2shp(nc.subbsn_m, nc.subbsn_shp, 'subbasin', 'SUBBASINID')
# Finish the workflow
UtilClass.writelog(logfile, '[Output] %s' %
'Original subbasin delineation is finished!', 'a')
def lookup_soil_parameters(dstdir, soiltype_file, soil_lookup_file):
"""Reclassify soil parameters by lookup table."""
# Read soil properties from txt file
soil_lookup_data = read_data_items_from_txt(soil_lookup_file)
soil_instances = list()
soil_prop_flds = soil_lookup_data[0][:]
for i in range(1, len(soil_lookup_data)):
cur_soil_data_item = soil_lookup_data[i][:]
cur_seqn = cur_soil_data_item[0]
cur_sname = cur_soil_data_item[1]
cur_soil_ins = SoilProperty(cur_seqn, cur_sname)
for j in range(2, len(soil_prop_flds)):
cur_flds = StringClass.split_string(cur_soil_data_item[j], '-') # Get field values
for k, tmpfld in enumerate(cur_flds):
cur_flds[k] = float(tmpfld) # Convert to float
if StringClass.string_match(soil_prop_flds[j], SoilUtilClass._NLYRS):
cur_soil_ins.SOILLAYERS = int(cur_flds[0])
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._Z):
cur_soil_ins.SOILDEPTH = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._OM):
cur_soil_ins.OM = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._CLAY):
cur_soil_ins.CLAY = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._SILT):
cur_soil_ins.SILT = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._SAND):
cur_soil_ins.SAND = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._ROCK):
cur_soil_ins.ROCK = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._ZMX):
cur_soil_ins.SOL_ZMX = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._ANIONEXCL):
cur_soil_ins.ANION_EXCL = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._CRK):
cur_soil_ins.SOL_CRK = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._BD):
cur_soil_ins.DENSITY = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._K):
cur_soil_ins.CONDUCTIVITY = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._WP):
cur_soil_ins.WILTINGPOINT = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._FC):
cur_soil_ins.FIELDCAP = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._AWC):
cur_soil_ins.AWC = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._POROSITY):
cur_soil_ins.POROSITY = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._USLE_K):
cur_soil_ins.USLE_K = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._ALB):
cur_soil_ins.SOL_ALB = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._ESCO):
cur_soil_ins.ESCO = cur_flds[0]
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._NO3):
cur_soil_ins.SOL_NO3 = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._NH4):
cur_soil_ins.SOL_NH4 = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._ORGN):
cur_soil_ins.SOL_ORGN = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._SOLP):
cur_soil_ins.SOL_SOLP = cur_flds
elif StringClass.string_match(soil_prop_flds[j], SoilUtilClass._ORGP):
cur_soil_ins.SOL_ORGP = cur_flds
cur_soil_ins.check_data_validation()
soil_instances.append(cur_soil_ins)
soil_prop_dict = dict()
for sol in soil_instances:
cur_sol_dict = sol.soil_dict()
for fld in cur_sol_dict:
if fld in soil_prop_dict:
soil_prop_dict[fld].append(cur_sol_dict[fld])
else:
soil_prop_dict[fld] = [cur_sol_dict[fld]]
# print(list(soilPropDict.keys()))
# print(list(soilPropDict.values()))
replace_dicts = list()
dst_soil_tifs = list()
seqns = soil_prop_dict[SoilUtilClass._SEQN]
max_lyr_num = int(numpy.max(soil_prop_dict[SoilUtilClass._NLYRS]))
for key in soil_prop_dict:
if key != SoilUtilClass._SEQN and key != SoilUtilClass._NAME:
key_l = 1
for key_v in soil_prop_dict[key]:
if isinstance(key_v, list):
if len(key_v) > key_l:
key_l = len(key_v)
if key_l == 1:
cur_dict = {}
for i, tmpseq in enumerate(seqns):
cur_dict[float(tmpseq)] = soil_prop_dict[key][i]
replace_dicts.append(cur_dict)
dst_soil_tifs.append(dstdir + os.path.sep + key + '.tif')
else:
for i in range(max_lyr_num):
cur_dict = dict()
for j, tmpseq in enumerate(seqns):
if i < soil_prop_dict[SoilUtilClass._NLYRS][j]:
cur_dict[float(tmpseq)] = soil_prop_dict[key][j][i]
else:
cur_dict[float(seqns[j])] = DEFAULT_NODATA
replace_dicts.append(cur_dict)
dst_soil_tifs.append(dstdir + os.path.sep + key + '_' + str(i + 1) + '.tif')
# print(replaceDicts)
# print(len(replaceDicts))
# print(dstSoilTifs)
# print(len(dstSoilTifs))
# Generate GTIFF
for i, soil_tif in enumerate(dst_soil_tifs):
print(soil_tif)
RasterUtilClass.raster_reclassify(soiltype_file, replace_dicts[i], soil_tif)