def process_intersecting_tiles(intersecting_tiles, settings, gcm_delta_dir):
"""
Apply water use data to a WATER \*.txt file. The new file created is saved to the same
directory as the \*.xml file.
Parameters
----------
intersecting_tiles : dictionary
Dictionary containing lists of values for a particular field that were intersected by another shapefile.
settings : dictionary
Dictionary of user settings
gcm_delta_dir : string
string path to ecoflow directory
Notes
-----
Uses settings set in user_settings.py
"""
# create a file for the output
for featureid, tiles in intersecting_tiles.iteritems():
# get monthly average gcm delta values
deltas_data_list, deltas_avg_dict = deltas.get_deltas(delta_files = settings["gcm_delta_files"], tiles = tiles)
# print monthly output in nice format to info file
print("FeatureId: {}\n Tiles: {}\n Average GCM Deltas:\n".format(featureid, tiles))
for key in deltas_avg_dict.keys():
print(" {}\n".format(key))
helpers.print_monthly_dict(monthly_dict = deltas_avg_dict[key])
# get the txt data file that has a parent directory matching the current featureid
if settings["is_batch_simulation"]:
path = os.path.join(settings["simulation_directory"], featureid)
else:
path = settings["simulation_directory"]
# find the WATERSimulation.xml and WATER.txt files
waterxml_file = helpers.find_file(name = settings["water_database_file_name"], path = path)
watertxt_file = helpers.find_file(name = settings["water_text_file_name"], path = path)
# get file info
waterxml_dir, waterxml_filename = helpers.get_file_info(waterxml_file)
watertxt_dir, watertxt_filename = helpers.get_file_info(watertxt_file)
# create an output directory
output_dir = helpers.make_directory(path = waterxml_dir, directory_name = settings["gcm_delta_directory_name"])
# initialize error logging
waterapputils_logging.initialize_loggers(output_dir = output_dir)
# read the xml file
waterxml_tree = waterxml.read_file(waterxml_file)
watertxt_data = watertxt.read_file(watertxt_file)
# apply gcm delta
for key, value in deltas_avg_dict.iteritems():
if key == "Ppt":
waterxml.apply_factors(waterxml_tree = waterxml_tree, element = "ClimaticPrecipitationSeries", factors = deltas_avg_dict[key])
elif key == "Tmax":
waterxml.apply_factors(waterxml_tree = waterxml_tree, element = "ClimaticTemperatureSeries", factors = deltas_avg_dict[key])
elif key == "PET":
watertxt.apply_factors(watertxt_data, name = "PET", factors = deltas_avg_dict[key], is_additive = False)
# update the project name in the updated xml
project = waterxml.create_project_dict()
project = waterxml.fill_dict(waterxml_tree = waterxml_tree, data_dict = project, element = "Project", keys = project.keys())
waterxml.change_element_value(waterxml_tree = waterxml_tree, element = "Project", child = "ProjName" , new_value = settings["gcm_delta_prepend_name"] + project["ProjName"])
# write updated xml
waterxml_with_gcm_delta_file = settings["gcm_delta_prepend_name"] + waterxml_filename
waterxml.write_file(waterxml_tree = waterxml_tree, save_path = output_dir, filename = waterxml_with_gcm_delta_file)
# write the pet timeseries file
watertxt.write_timeseries_file(watertxt_data, name = "PET", save_path = output_dir, filename = settings["pet_timeseries_file_name"])
# plot
updated_waterxml_file = os.path.join(output_dir, waterxml_with_gcm_delta_file)
water_files_processing.process_water_files(file_list = [updated_waterxml_file ], settings = settings, print_data = False)
water_files_processing.process_cmp(file_list = [updated_waterxml_file, waterxml_file], settings = settings, print_data = False)
# plot the gcm deltas
for deltas_data in deltas_data_list:
deltas_viewer.plot_deltas_data(deltas_data = deltas_data, save_path = helpers.make_directory(path = gcm_delta_dir, directory_name = settings["gcm_delta_directory_name"]))
def process_intersecting_centroids(intersecting_centroids, settings,
ecoflow_dir, oasis_dir):
"""
Apply water use data to a WATER \*.txt file. The new file created is saved to the same
directory as the \*.xml file.
Parameters
----------
intersecting_centroids : dictionary
Dictionary containing lists of values for a particular field that were intersected by another shapefile.
settings : dictionary
Dictionary of user settings
ecoflow_dir : string
String path to directory that will contain output specific for ecoflow program
oasis_dir : string
String path to directory that will contain output specific for oasis
Notes
-----
Uses settings set in user_settings.py
"""
# create a file for the output
for featureid, centroids in intersecting_centroids.iteritems():
# get sum of the water use data
if settings["wateruse_factor_file"]:
total_wateruse_dict = wateruse.get_all_total_wateruse(
wateruse_files=settings["wateruse_files"],
id_list=centroids,
wateruse_factor_file=settings["wateruse_factor_file"],
in_cfs=True)
else:
total_wateruse_dict = wateruse.get_all_total_wateruse(
wateruse_files=settings["wateruse_files"],
id_list=centroids,
wateruse_factor_file=None,
in_cfs=True)
# print monthly output in nice format to info file
print(
"FeatureId: {}\n Centroids: {}\n Total Water Use:\n".format(
featureid, centroids))
helpers.print_monthly_dict(monthly_dict=total_wateruse_dict)
# get the txt data file that has a parent directory matching the current featureid
if settings["is_batch_simulation"]:
path = os.path.join(settings["simulation_directory"], featureid)
else:
path = settings["simulation_directory"]
# find the WATER.txt file
watertxt_file = helpers.find_file(
name=settings["water_text_file_name"], path=path)
# get file info
watertxt_dir, watertxt_filename = helpers.get_file_info(watertxt_file)
# create an output directory
output_dir = helpers.make_directory(
path=watertxt_dir,
directory_name=settings["wateruse_directory_name"])
# initialize error logging
waterapputils_logging.initialize_loggers(output_dir=output_dir)
# read the txt
watertxt_data = watertxt.read_file(watertxt_file)
# apply water use
watertxt_data = watertxt.apply_wateruse(
watertxt_data, wateruse_totals=total_wateruse_dict)
# write updated txt
watertxt_with_wateruse_file = settings[
"wateruse_prepend_name"] + watertxt_filename
watertxt.write_file(watertxt_data=watertxt_data,
save_path=output_dir,
filename=watertxt_with_wateruse_file)
# plot
updated_watertxt_file = os.path.join(output_dir,
watertxt_with_wateruse_file)
water_files_processing.process_water_files(
file_list=[updated_watertxt_file],
settings=settings,
print_data=True)
# write timeseries of discharge + water use for OASIS
watertxt.write_timeseries_file(watertxt_data=watertxt_data,
name=settings["ecoflow_parameter_name"],
save_path=oasis_dir,
filename="-".join([
watertxt_data["stationid"],
settings["oasis_file_name"]
]))
# write timeseries of dishcarge + water use for ecoflow program
watertxt.write_timeseries_file_stationid(
watertxt_data,
name=settings["ecoflow_parameter_name"],
save_path=ecoflow_dir,
filename="",
stationid=watertxt_data["stationid"])
def process_intersecting_tiles(intersecting_tiles, settings, gcm_delta_dir):
"""
Apply water use data to a WATER \*.txt file. The new file created is saved to the same
directory as the \*.xml file.
Parameters
----------
intersecting_tiles : dictionary
Dictionary containing lists of values for a particular field that were intersected by another shapefile.
settings : dictionary
Dictionary of user settings
gcm_delta_dir : string
string path to ecoflow directory
Notes
-----
Uses settings set in user_settings.py
"""
# create a file for the output
for featureid, tiles in intersecting_tiles.iteritems():
# get monthly average gcm delta values
deltas_data_list, deltas_avg_dict = deltas.get_deltas(
delta_files=settings["gcm_delta_files"], tiles=tiles)
# print monthly output in nice format to info file
print("FeatureId: {}\n Tiles: {}\n Average GCM Deltas:\n".format(
featureid, tiles))
for key in deltas_avg_dict.keys():
print(" {}\n".format(key))
helpers.print_monthly_dict(monthly_dict=deltas_avg_dict[key])
# get the txt data file that has a parent directory matching the current featureid
if settings["is_batch_simulation"]:
path = os.path.join(settings["simulation_directory"], featureid)
else:
path = settings["simulation_directory"]
# find the WATERSimulation.xml and WATER.txt files
waterxml_file = helpers.find_file(
name=settings["water_database_file_name"], path=path)
watertxt_file = helpers.find_file(
name=settings["water_text_file_name"], path=path)
# get file info
waterxml_dir, waterxml_filename = helpers.get_file_info(waterxml_file)
watertxt_dir, watertxt_filename = helpers.get_file_info(watertxt_file)
# create an output directory
output_dir = helpers.make_directory(
path=waterxml_dir,
directory_name=settings["gcm_delta_directory_name"])
# initialize error logging
waterapputils_logging.initialize_loggers(output_dir=output_dir)
# read the xml file
waterxml_tree = waterxml.read_file(waterxml_file)
watertxt_data = watertxt.read_file(watertxt_file)
# apply gcm delta
for key, value in deltas_avg_dict.iteritems():
if key == "Ppt":
waterxml.apply_factors(waterxml_tree=waterxml_tree,
element="ClimaticPrecipitationSeries",
factors=deltas_avg_dict[key])
elif key == "Tmax":
waterxml.apply_factors(waterxml_tree=waterxml_tree,
element="ClimaticTemperatureSeries",
factors=deltas_avg_dict[key])
elif key == "PET":
watertxt.apply_factors(watertxt_data,
name="PET",
factors=deltas_avg_dict[key],
is_additive=False)
# update the project name in the updated xml
project = waterxml.create_project_dict()
project = waterxml.fill_dict(waterxml_tree=waterxml_tree,
data_dict=project,
element="Project",
keys=project.keys())
waterxml.change_element_value(
waterxml_tree=waterxml_tree,
element="Project",
child="ProjName",
new_value=settings["gcm_delta_prepend_name"] + project["ProjName"])
# write updated xml
waterxml_with_gcm_delta_file = settings[
"gcm_delta_prepend_name"] + waterxml_filename
waterxml.write_file(waterxml_tree=waterxml_tree,
save_path=output_dir,
filename=waterxml_with_gcm_delta_file)
# write the pet timeseries file
watertxt.write_timeseries_file(
watertxt_data,
name="PET",
save_path=output_dir,
filename=settings["pet_timeseries_file_name"])
# plot
updated_waterxml_file = os.path.join(output_dir,
waterxml_with_gcm_delta_file)
water_files_processing.process_water_files(
file_list=[updated_waterxml_file],
settings=settings,
print_data=False)
water_files_processing.process_cmp(
file_list=[updated_waterxml_file, waterxml_file],
settings=settings,
print_data=False)
# plot the gcm deltas
for deltas_data in deltas_data_list:
deltas_viewer.plot_deltas_data(
deltas_data=deltas_data,
save_path=helpers.make_directory(
path=gcm_delta_dir,
directory_name=settings["gcm_delta_directory_name"]))
def process_intersecting_centroids(intersecting_centroids, settings, ecoflow_dir, oasis_dir):
"""
Apply water use data to a WATER \*.txt file. The new file created is saved to the same
directory as the \*.xml file.
Parameters
----------
intersecting_centroids : dictionary
Dictionary containing lists of values for a particular field that were intersected by another shapefile.
settings : dictionary
Dictionary of user settings
ecoflow_dir : string
String path to directory that will contain output specific for ecoflow program
oasis_dir : string
String path to directory that will contain output specific for oasis
Notes
-----
Uses settings set in user_settings.py
"""
# create a file for the output
for featureid, centroids in intersecting_centroids.iteritems():
# get sum of the water use data
if settings["wateruse_factor_file"]:
total_wateruse_dict = wateruse.get_all_total_wateruse(wateruse_files = settings["wateruse_files"], id_list = centroids, wateruse_factor_file = settings["wateruse_factor_file"], in_cfs = True)
else:
total_wateruse_dict = wateruse.get_all_total_wateruse(wateruse_files = settings["wateruse_files"], id_list = centroids, wateruse_factor_file = None, in_cfs = True)
# print monthly output in nice format to info file
print("FeatureId: {}\n Centroids: {}\n Total Water Use:\n".format(featureid, centroids))
helpers.print_monthly_dict(monthly_dict = total_wateruse_dict)
# get the txt data file that has a parent directory matching the current featureid
if settings["is_batch_simulation"]:
path = os.path.join(settings["simulation_directory"], featureid)
else:
path = settings["simulation_directory"]
# find the WATER.txt file
watertxt_file = helpers.find_file(name = settings["water_text_file_name"], path = path)
# get file info
watertxt_dir, watertxt_filename = helpers.get_file_info(watertxt_file)
# create an output directory
output_dir = helpers.make_directory(path = watertxt_dir, directory_name = settings["wateruse_directory_name"])
# initialize error logging
waterapputils_logging.initialize_loggers(output_dir = output_dir)
# read the txt
watertxt_data = watertxt.read_file(watertxt_file)
# apply water use
watertxt_data = watertxt.apply_wateruse(watertxt_data, wateruse_totals = total_wateruse_dict)
# write updated txt
watertxt_with_wateruse_file = settings["wateruse_prepend_name"] + watertxt_filename
watertxt.write_file(watertxt_data = watertxt_data, save_path = output_dir, filename = watertxt_with_wateruse_file)
# plot
updated_watertxt_file = os.path.join(output_dir, watertxt_with_wateruse_file)
water_files_processing.process_water_files(file_list = [updated_watertxt_file], settings = settings, print_data = True)
# write timeseries of discharge + water use for OASIS
watertxt.write_timeseries_file(watertxt_data = watertxt_data, name = settings["ecoflow_parameter_name"], save_path = oasis_dir, filename = "-".join([watertxt_data["stationid"], settings["oasis_file_name"]]))
# write timeseries of dishcarge + water use for ecoflow program
watertxt.write_timeseries_file_stationid(watertxt_data, name = settings["ecoflow_parameter_name"], save_path = ecoflow_dir, filename = "", stationid = watertxt_data["stationid"])