"rev59.3_64rel.exe"
if platform.system() == "Windows" else "swatplusrev59-static.exe"
}
executable_path = "{swatplus_wf_dir}editor_api/swat_exe/{swatplus_exe}".format(
**variables)
base = "{0}/{1}/Scenarios/Default".format(sys.argv[1], config.Project_Name)
working_dir = "{base_dir}/working".format(base_dir=base)
runs = config.Number_of_Runs
output_dir = working_dir + "/output/"
config_file_name = config.Calibration_Config_File
home_dir = sys.argv[1]
config_file_path = "{home_dir}/data/calibration/{config_file}".format(
config_file=config_file_name, home_dir=home_dir)
observation_filename = read_from(config_file_path)[2].split(",")[2]
observation_file_path = "{home_dir}/data/observations/{cal_obs_fn}".format(
cal_obs_fn=observation_filename, home_dir=sys.argv[1])
if not os.path.isfile(observation_file_path):
print("\t! the observation file was not found!\n\t path: {0}".format(
observation_file_path))
sys.exit(1)
unit_number = read_from(config_file_path)[3].split(",")[2]
print("\t> calibrating to channel number {0}".format(unit_number))
calibration_time_step = read_from(config_file_path)[4].split(",")[2]
calibration_variable = read_from(config_file_path)[5].split(",")[2]
core_count = config.Number_of_Processes
pool_cores = multiprocessing.Pool(core_count)
file_cio = read_from("{base}/TxtInOut/file.cio".format(base=base))
def run_parameter_set(parameter_set_list, core_number, chg_typ_dict, header,
calibration_header, working_dir):
"""
"""
report = "{0},NSE\n".format(",".join(header))
for parameter_set in parameter_set_list:
calibration_cal = set_calibration_cal(header, parameter_set,
chg_typ_dict, calibration_header)
# write to the correct location relative to the 'working' directory
write_to(
"{working_dir}/{core}/calibration.cal".format(
working_dir=working_dir, core=core_number),
calibration_cal,
report_=False,
)
os.chdir("{working_dir}/{core}".format(working_dir=working_dir,
core=core_number))
if not os.path.isfile("rev59.3_64rel.exe"):
shutil.copyfile(executable_path, "rev59.3_64rel.exe")
print("\t> running SWAT+ in process {0}".format(core_number))
if platform.system() == "Linux":
os.system("chmod 777 ./rev59.3_64rel.exe")
os.system("./rev59.3_64rel.exe")
else:
os.system("rev59.3_64rel.exe")
# subprocess.Popen('rev59.3_64rel.exe', stdout=subprocess.PIPE)
# extract flow for specified unit at specified timestep
sim_results = read_from(
"{working_dir}/{core}/channel_sd_day.csv".format(
working_dir=working_dir, core=core_number))[3:]
simulated_string = "Date,Simulated\n"
results_index = None
if calibration_variable == "1":
results_index = 47
if calibration_variable == "2":
results_index = 9
if not results_index is None:
for r_line in sim_results:
if r_line.split(",")[4] == str(unit_number):
day_val = r_line.split(",")[2]
simulated_string += "{dd}/{mm}/{yy},{val}\n".format(
dd=day_val,
mm=r_line.split(",")[1],
yy=r_line.split(",")[3],
val=r_line.split(",")[results_index],
)
simulated_fn = "{working_dir}/{core}/simulated.csv".format(
working_dir=working_dir, core=core_number)
report_fn = "{working_dir}/{core}/report.csv".format(
working_dir=working_dir, core=core_number)
observed_fn = "{home_dir}/data/observations/{cal_obs_fn}".format(
cal_obs_fn=observation_filename, home_dir=sys.argv[1])
write_to(simulated_fn, simulated_string)
# calculate nse and append to list table
if calibration_time_step == '1':
print("\t > calculating NSE at daily timestep")
NSE = calculate_nse(simulated_fn, observed_fn, t_step=1)
if calibration_time_step == '2':
print("\t > calculating NSE at monthly timestep")
NSE = calculate_nse(simulated_fn, observed_fn, t_step=2)
if calibration_time_step == '3':
print("\t > calculating NSE at yearly timestep")
NSE = calculate_nse(simulated_fn, observed_fn, t_step=3)
if not NSE is None:
front_string = ""
for item in parameter_set:
front_string += str(item) + ","
report += front_string + str(NSE) + "\n"
# report += "{0},{1}\n".format(",".join(parameter_set), NSE)
write_to(report_fn, report)
lsu_shapefile_gpd = geopandas.read_file(lsus_shapefile)
new_lsu_shapefile_gpd = lsu_shapefile_gpd
new_lsu_shapefile_gpd["precip"] = 0.0
new_lsu_shapefile_gpd["surq_gen"] = 0.0
new_lsu_shapefile_gpd["latq"] = 0.0
new_lsu_shapefile_gpd["wateryld"] = 0.0
new_lsu_shapefile_gpd["perc"] = 0.0
new_lsu_shapefile_gpd["et"] = 0.0
new_lsu_shapefile_gpd["cn"] = 0.0
new_lsu_shapefile_gpd["pet"] = 0.0
new_lsu_shapefile_gpd["irr"] = 0.0
# read output data into dictionary
log.info("reading annual average LSU results", keep_log)
wb_aa_data_list = read_from(aa_lsu_wb_file)
wb_aa_data_dict = {}
for wb_aa_line in wb_aa_data_list[3:]:
wb_aa_line_parts = wb_aa_line.split()
lsu_no = wb_aa_line_parts[4]
if not lsu_no in wb_aa_data_dict:
wb_aa_data_dict[lsu_no] = wb_result(wb_aa_line_parts)
# add output to shapefile
log.info("mapping annual average LSU results", keep_log)
for index, row in lsu_shapefile_gpd.iterrows():
new_lsu_shapefile_gpd.loc[index, "precip"] = float(
wb_aa_data_dict[str(row.Channel)].precip)
new_lsu_shapefile_gpd.loc[index, "surq_gen"] = float(
wb_aa_data_dict[str(row.Channel)].surq_gen)
new_lsu_shapefile_gpd.loc[index, "latq"] = float(
shutil.copyfile( # get outlets file
"{base}/{project_name}/Watershed/Shapes/{shp_base}.{ext}".
format(base=sys.argv[1],
project_name=selected_model,
shp_base=file_name(delin_data["burn"], extension=False),
ext=shapefile_extension),
"{base}/data/shapefiles/{shp_base}.{ext}".format(
base=sys.argv[1],
shp_base=file_name(delin_data["burn"], extension=False),
ext=shapefile_extension))
# retrieve weather
log.info("reading file.cio", keep_log)
file_cio = read_from(
"{base}/{project_name}/Scenarios/Default/TxtInOut/file.cio".format(
base=sys.argv[1], project_name=selected_model))
weather_dir = file_cio[-2].strip("\n").split()[1] if not \
file_cio[-2].strip("\n").split()[1] == "null" else \
""
log.info(
"weatherfiles are in: {fn}".format(
fn="{base}/{project_name}/Scenarios/Default/TxtInOut/{weather_dir}".
format(base=sys.argv[1],
project_name=selected_model,
weather_dir=weather_dir)), keep_log)
pcp_cli_file = "{base}/{project_name}/Scenarios/Default/TxtInOut/{weather_dir}pcp.cli".format(
def convert_weather(weather_source, weather_data_dir, file_count=None):
print("")
weather_dir = weather_source
destination = weather_data_dir
if not os.path.isdir(destination):
os.makedirs(destination)
forks = ["pcp.txt", "wnd.txt", "slr.txt", "hmd.txt", "tmp.txt"]
counting = 0
for fork_file in forks:
fork_path = "{0}/{1}".format(weather_dir, fork_file)
if os.path.isfile(fork_path):
fork_content = read_from(fork_path)
new_fork_string = "file names - file written by SWAT+ editor auto-workflow v1.0 [{0}]\nfilename\n".format(
str(datetime.datetime.now()).split(".")[0])
for line in fork_content:
if line == fork_content[0]:
continue
if not file_count is None:
counting += 1
show_progress(counting,
file_count,
string_before="\t formating weather: ")
filename = "{0}.{1}".format(
line.split(",")[1],
fork_file.split(".")[0])
new_fork_string += "{0}\n".format(filename)
file_2012 = ""
date_ = None
start_date = None
nyears = 1
version2012_station_content = read_from("{0}/{1}.txt".format(
weather_dir,
line.split(",")[1]))
for line_2012 in version2012_station_content:
if line_2012 == version2012_station_content[0]:
date_ = datetime.datetime(int(line_2012[:4]), 1, 1)
start_date = datetime.datetime(int(line_2012[:4]), 1,
1)
continue
else:
if date_.year - start_date.year > 0:
start_date = datetime.datetime(date_.year, 1, 1)
nyears += 1
if fork_file == "tmp.txt":
min_tmp = float(line_2012.split(",")[1])
max_tmp = float(line_2012.split(",")[0])
tmp_values = "{0}{1}".format(
"{0}".format(max_tmp).rjust(10),
"{0}".format(min_tmp).rjust(10))
file_2012 += "{0}{1}{2}\n".format(
date_.year,
str(int((date_ - start_date).days) +
1).rjust(5), tmp_values)
else:
file_2012 += "{0}{1}{2}\n".format(
date_.year,
str(int((date_ - start_date).days) +
1).rjust(5),
str(float(line_2012)).rjust(9))
date_ += datetime.timedelta(days=1)
station_info = "{z}{o}{t}{th}{f}".format(
z=str(nyears).rjust(4),
o="0".rjust(10),
t=line.split(",")[2].rjust(10),
th=line.split(",")[3].rjust(10),
f=line.split(",")[4].rjust(11))
file_header_ = \
"{1}: data - file written by SWAT+ editor auto-workflow v1.0 [{0}]\nnbyr tstep lat lon elev\n{2}".format(
str(datetime.datetime.now()).split(".")[0], filename, station_info)
file_header_ += file_2012
write_to(
"{dest}/{fname}".format(fname=filename, dest=destination),
file_header_)
write_to(
"{0}/{1}.cli".format(destination,
fork_file.split(".")[0]), new_fork_string)
# else:
# print("\t! could not find {0} in {1}".format(fork_file, weather_dir))
print("\n\t finished.\n")
str(datetime.datetime.now()).split(".")[0], filename, station_info)
file_header_ += file_2012
write_to(
"{dest}/{fname}".format(fname=filename, dest=destination),
file_header_)
write_to(
"{0}/{1}.cli".format(destination,
fork_file.split(".")[0]), new_fork_string)
# else:
# print("\t! could not find {0} in {1}".format(fork_file, weather_dir))
print("\n\t finished.\n")
if __name__ == "__main__":
forks = ["pcp.txt", "wnd.txt", "slr.txt", "hmd.txt", "tmp.txt"]
weather_source = argv[1]
weather_data_dir = argv[2]
all_files = 0
for fork in forks:
try:
all_files += len(read_from("{0}/{1}".format(weather_source,
fork))) - 1
except:
pass
convert_weather(weather_source, weather_data_dir, all_files)
'{base}/{project_name}/{project_name}.sqlite'.format(
base=sys.argv[1], project_name=project_name))
project_database = sqlite_connection(
'{base}/{project_name}/{project_name}.sqlite'.format(
base=sys.argv[1], project_name=project_name))
# - copy templates
log.info("importing usersoil into project database", keep_log)
project_database.connect()
if project_database.table_exists("{usersoil}".format(usersoil=usersoil)):
project_database.delete_table("{usersoil}".format(usersoil=usersoil))
# - get_data into database
# - - usersoil
usersoil_rows = read_from("{base_dir}/data/tables/{usersoil_file}".format(
base_dir=sys.argv[1], usersoil_file=config.Usersoil))
column_types_usersoil = {
"OBJECTID": 'INTEGER',
"TEXTURE": 'TEXT',
"HYDGRP": 'TEXT',
"CMPPCT": 'TEXT',
"S5ID": 'TEXT',
"SNAM": 'TEXT',
"SEQN": 'TEXT',
"MUID": 'TEXT',
}
project_database.create_table(
"{usersoil}".format(usersoil=usersoil),
usersoil_rows[0].replace('"', "").split(",")[0],