def run_inundation(args):
rem = args[0]
catchments = args[1]
magnitude_flows_csv = args[2]
huc = args[3]
hydroTable = args[4]
output_extent_grid = args[5]
output_depth_grid = args[6]
ahps_site = args[7]
magnitude = args[8]
log_file = args[9]
try:
inundate(rem,catchments,catchment_poly,hydroTable,magnitude_flows_csv,mask_type,hucs=hucs,hucs_layerName=hucs_layerName,
subset_hucs=huc,num_workers=1,aggregate=False,inundation_raster=output_extent_grid,inundation_polygon=None,
depths=output_depth_grid,out_raster_profile=None,out_vector_profile=None,quiet=True
)
except:
# Log errors and their tracebacks
f = open(log_file, 'a+')
f.write(f"{output_extent_grid} - inundation error: {traceback.format_exc()}\n")
f.close()
#Inundation.py appends the huc code to the supplied output_extent_grid.
#Modify output_extent_grid to match inundation.py saved filename.
#Search for this file, if it didn't create, send message to log file.
base_file_path,extension = os.path.splitext(output_extent_grid)
saved_extent_grid_filename = "{}_{}{}".format(base_file_path,huc,extension)
if not os.path.exists(saved_extent_grid_filename):
with open(log_file, 'a+') as f:
f.write('FAILURE_huc_{}:{}:{} map failed to create\n'.format(huc,ahps_site,magnitude))
def run_alpha_test(fim_run_dir, branch_name, test_id, mask_type, return_interval, compare_to_previous=False, run_structure_stats=False, run_levee_stats=False, archive_results=False):
# Construct paths to development test results if not existent.
if archive_results:
branch_test_case_dir_parent = os.path.join(TEST_CASES_DIR, test_id, 'performance_archive', 'previous_versions', branch_name)
else:
branch_test_case_dir_parent = os.path.join(TEST_CASES_DIR, test_id, 'performance_archive', 'development_versions', branch_name)
# Delete the entire directory if it already exists.
if os.path.exists(branch_test_case_dir_parent):
shutil.rmtree(branch_test_case_dir_parent)
print("Running the alpha test for test_id: " + test_id + ", " + branch_name + "...")
stats_modes_list = ['total_area']
if run_structure_stats: stats_modes_list.append('structures')
if run_levee_stats: stats_modes_list.append('levees')
fim_run_parent = os.path.join(os.environ['outputDataDir'], fim_run_dir)
assert os.path.exists(fim_run_parent), "Cannot locate " + fim_run_parent
# Create paths to fim_run outputs for use in inundate().
rem = os.path.join(fim_run_parent, 'rem_zeroed_masked.tif')
catchments = os.path.join(fim_run_parent, 'gw_catchments_reaches_filtered_addedAttributes.tif')
catchment_poly = os.path.join(fim_run_parent, 'gw_catchments_reaches_filtered_addedAttributes_crosswalked.gpkg')
current_huc = test_id.split('_')[0]
hucs, hucs_layerName = os.path.join(INPUTS_DIR, 'wbd', 'WBD_National.gpkg'), 'WBDHU8'
hydro_table = os.path.join(fim_run_parent, 'hydroTable.csv')
# Create list of shapefile paths to use as exclusion areas.
zones_dir = os.path.join(TEST_CASES_DIR, 'other', 'zones')
exclusion_mask_dict = {'levees': {'path': os.path.join(zones_dir, 'leveed_areas_conus.shp'),
'buffer': None
},
'waterbodies': {'path': os.path.join(zones_dir, 'nwm_v2_reservoirs.shp'),
'buffer': None,
}
}
# # Crosswalk feature_ids to hydroids.
# hydro_table_data = pd.read_csv(hydro_table, header=0)
# ht_feature_id_list = list(hydro_table_data.feature_id)
# ht_hydro_id_list = list(hydro_table_data.HydroID)
# lake_id_list = list(hydro_table_data.LakeID)
#
# # Get list of feature_ids_to_mask.
# feature_ids_to_mask = []
# for f in range(0, len(lake_id_list)):
# if lake_id_list[f] != -999:
# lake_feature_id = ht_feature_id_list[f]
# if lake_feature_id not in feature_ids_to_mask:
# feature_ids_to_mask.append(lake_feature_id)
# Remove duplicates and create list of hydro_ids to use as waterbody mask.
# reduced_ht_feature_id_list, reduced_ht_hydro_id_list, hydro_ids_to_mask = [], [], []
#
# for i in range(0, len(ht_hydro_id_list)):
# if ht_hydro_id_list[i] not in reduced_ht_hydro_id_list:
# reduced_ht_hydro_id_list.append(ht_hydro_id_list[i])
# reduced_ht_feature_id_list.append(ht_feature_id_list[i])
# for i in range(0, len(reduced_ht_feature_id_list)):
# ht_feature_id = reduced_ht_feature_id_list[i]
# ht_hydro_id = reduced_ht_hydro_id_list[i]
# if ht_feature_id in feature_ids_to_mask:
# hydro_ids_to_mask.append(ht_hydro_id)
# Check if return interval is list of return intervals or single value.
return_interval_list = return_interval
if type(return_interval_list) != list:
return_interval_list = [return_interval_list]
for return_interval in return_interval_list:
# Construct path to validation raster and forecast file.
benchmark_category = test_id.split('_')[1]
benchmark_raster_path = os.path.join(TEST_CASES_DIR, 'validation_data_' + benchmark_category, current_huc, return_interval, benchmark_category + '_huc_' + current_huc + '_depth_' + return_interval + '.tif')
if not os.path.exists(benchmark_raster_path): # Skip loop instance if the benchmark raster doesn't exist.
continue
branch_test_case_dir = os.path.join(branch_test_case_dir_parent, return_interval)
os.makedirs(branch_test_case_dir)
# Define paths to inundation_raster and forecast file.
inundation_raster = os.path.join(branch_test_case_dir, 'inundation_extent.tif')
forecast = os.path.join(TEST_CASES_DIR, 'validation_data_' + benchmark_category, current_huc, return_interval, benchmark_category + '_huc_' + current_huc + '_flows_' + return_interval + '.csv')
# Run inundate.
print("-----> Running inundate() to produce modeled inundation extent for the " + return_interval + " return period...")
inundate(
rem,catchments,catchment_poly,hydro_table,forecast,mask_type,hucs=hucs,hucs_layerName=hucs_layerName,
subset_hucs=current_huc,num_workers=1,aggregate=False,inundation_raster=inundation_raster,inundation_polygon=None,
depths=None,out_raster_profile=None,out_vector_profile=None,quiet=True
)
print("-----> Inundation mapping complete.")
predicted_raster_path = os.path.join(os.path.split(inundation_raster)[0], os.path.split(inundation_raster)[1].replace('.tif', '_' + current_huc + '.tif')) # The inundate adds the huc to the name so I account for that here.
# Define outputs for agreement_raster, stats_json, and stats_csv.
agreement_raster, stats_json, stats_csv = os.path.join(branch_test_case_dir, 'total_area_agreement.tif'), os.path.join(branch_test_case_dir, 'stats.json'), os.path.join(branch_test_case_dir, 'stats.csv')
test_version_dictionary = compute_contingency_stats_from_rasters(predicted_raster_path,
benchmark_raster_path,
agreement_raster,
stats_csv=stats_csv,
stats_json=stats_json,
mask_values=[],
stats_modes_list=stats_modes_list,
test_id=test_id,
exclusion_mask_dict=exclusion_mask_dict
)
print(" ")
print("Evaluation complete. All metrics for " + test_id + ", " + branch_name + ", " + return_interval + " are available at " + CYAN_BOLD + branch_test_case_dir + ENDC)
print(" ")
if compare_to_previous:
text_block = []
# Compare to previous stats files that are available.
archive_to_check = os.path.join(TEST_CASES_DIR, test_id, 'performance_archive', 'previous_versions')
for stats_mode in stats_modes_list:
archive_dictionary = profile_test_case_archive(archive_to_check, return_interval, stats_mode)
if archive_dictionary == {}:
break
# Create header for section.
header = [stats_mode]
for previous_version, paths in archive_dictionary.items():
header.append(previous_version)
header.append(branch_name)
text_block.append(header)
# Loop through stats in PRINTWORTHY_STATS for left.
for stat in PRINTWORTHY_STATS:
stat_line = [stat]
for previous_version, paths in archive_dictionary.items():
# Load stats for previous version.
previous_version_stats_json_path = paths['stats_json']
previous_version_stats_dict = json.load(open(previous_version_stats_json_path))
# Append stat for the version to state_line.
stat_line.append(previous_version_stats_dict[stat])
# Append stat for the current version to stat_line.
stat_line.append(test_version_dictionary[stats_mode][stat])
text_block.append(stat_line)
text_block.append([" "])
regression_report_csv = os.path.join(branch_test_case_dir, 'stats_summary.csv')
with open(regression_report_csv, 'w', newline='') as csvfile:
csv_writer = csv.writer(csvfile)
csv_writer.writerows(text_block)
print()
print("--------------------------------------------------------------------------------------------------")
stats_mode = stats_modes_list[0]
try:
last_version_index = text_block[0].index('dev_latest')
except ValueError:
try:
last_version_index = text_block[0].index('fim_2_3_3')
except ValueError:
try:
last_version_index = text_block[0].index('fim_1_0_0')
except ValueError:
print(TRED_BOLD + "Warning: " + ENDC + "Cannot compare " + branch_name + " to a previous version because no authoritative versions were found in previous_versions directory. Future version of run_test_case may allow for comparisons between dev branches.")
print()
continue
current_version_index = text_block[0].index(branch_name)
for line in text_block:
first_item = line[0]
if first_item in stats_modes_list:
if first_item != stats_mode: # Update the stats_mode and print a separator.
print()
print()
print("--------------------------------------------------------------------------------------------------")
print()
stats_mode = first_item
print(CYAN_BOLD + current_huc + ": " + return_interval.upper(), ENDC)
print(CYAN_BOLD + stats_mode.upper().replace('_', ' ') + " METRICS" + ENDC)
print()
color = WHITE_BOLD
metric_name = ' '.center(len(max(PRINTWORTHY_STATS, key=len)))
percent_change_header = '% CHG'
difference_header = 'DIFF'
current_version_header = line[current_version_index].upper()
last_version_header = line[last_version_index].upper()
# Print Header.
print(color + metric_name + " " + percent_change_header.center((7)) + " " + difference_header.center((15)) + " " + current_version_header.center(18) + " " + last_version_header.center(18), ENDC)
# Format and print stat row.
elif first_item in PRINTWORTHY_STATS:
stat_name = first_item.upper().center(len(max(PRINTWORTHY_STATS, key=len))).replace('_', ' ')
current_version = round((line[current_version_index]), 3)
last_version = round((line[last_version_index]) + 0.000, 3)
difference = round(current_version - last_version, 3)
if difference > 0:
symbol = '+'
if first_item in GO_UP_STATS:
color = TGREEN_BOLD
elif first_item in GO_DOWN_STATS:
color = TRED_BOLD
else:
color = TWHITE
if difference < 0:
symbol = '-'
if first_item in GO_UP_STATS:
color = TRED_BOLD
elif first_item in GO_DOWN_STATS:
color = TGREEN_BOLD
else:
color = TWHITE
if difference == 0 :
symbol, color = '+', TGREEN
percent_change = round((difference / last_version)*100,2)
print(WHITE_BOLD + stat_name + ENDC + " " + color + (symbol + " {:5.2f}".format(abs(percent_change)) + " %").rjust(len(percent_change_header)), ENDC + " " + color + ("{:12.3f}".format((difference))).rjust(len(difference_header)), ENDC + " " + "{:15.3f}".format(current_version).rjust(len(current_version_header)) + " " + "{:15.3f}".format(last_version).rjust(len(last_version_header)) + " ")
print()
print()
print()
print("--------------------------------------------------------------------------------------------------")
print()
def run_recurr_test(fim_run_dir,
branch_name,
huc_id,
magnitude,
mask_type='huc',
output_dir=None):
# Construct paths to development test results if not existent.
huc_id_dir_parent = os.path.join(INUN_REVIEW_DIR, huc_id)
if not os.path.exists(huc_id_dir_parent):
os.mkdir(huc_id_dir_parent)
if output_dir == None:
branch_test_case_dir_parent = os.path.join(INUN_REVIEW_DIR, huc_id,
branch_name)
else:
branch_test_case_dir_parent = os.path.join(output_dir, huc_id,
branch_name)
# Delete the entire directory if it already exists.
if os.path.exists(branch_test_case_dir_parent):
shutil.rmtree(branch_test_case_dir_parent)
print("Running the NWM recurrence intervals for huc_id: " + huc_id + ", " +
branch_name + "...")
fim_run_parent = os.path.join(fim_run_dir)
assert os.path.exists(fim_run_parent), "Cannot locate " + fim_run_parent
# Create paths to fim_run outputs for use in inundate().
if "previous_fim" in fim_run_parent and "fim_2" in fim_run_parent:
rem = os.path.join(fim_run_parent, 'rem_clipped_zeroed_masked.tif')
catchments = os.path.join(
fim_run_parent,
'gw_catchments_reaches_clipped_addedAttributes.tif')
else:
rem = os.path.join(fim_run_parent, 'rem_zeroed_masked.tif')
catchments = os.path.join(
fim_run_parent,
'gw_catchments_reaches_filtered_addedAttributes.tif')
if mask_type == 'huc':
catchment_poly = ''
else:
catchment_poly = os.path.join(
fim_run_parent,
'gw_catchments_reaches_filtered_addedAttributes_crosswalked.gpkg')
hydro_table = os.path.join(fim_run_parent, 'hydroTable.csv')
# Map necessary inputs for inundation().
hucs, hucs_layerName = os.path.join(INPUTS_DIR, 'wbd',
'WBD_National.gpkg'), 'WBDHU8'
#benchmark_category = huc_id.split('_')[1]
current_huc = huc_id.split('_')[
0] # Break off HUC ID and assign to variable.
if not os.path.exists(branch_test_case_dir_parent):
os.mkdir(branch_test_case_dir_parent)
# Check if magnitude is list of magnitudes or single value.
magnitude_list = magnitude
if type(magnitude_list) != list:
magnitude_list = [magnitude_list]
for magnitude in magnitude_list:
# Construct path to validation raster and forecast file.
branch_test_case_dir = os.path.join(branch_test_case_dir_parent,
magnitude)
os.makedirs(branch_test_case_dir) # Make output directory for branch.
# Define paths to inundation_raster and forecast file.
inundation_raster = os.path.join(branch_test_case_dir,
branch_name + '_inund_extent.tif')
forecast = os.path.join(INUN_REVIEW_DIR, 'nwm_recurr_flow_data',
'recurr_' + magnitude + '_cms.csv')
# Run inundate.
print(
"-----> Running inundate() to produce modeled inundation extent for the "
+ magnitude + " magnitude...")
inundate(rem,
catchments,
catchment_poly,
hydro_table,
forecast,
mask_type,
hucs=hucs,
hucs_layerName=hucs_layerName,
subset_hucs=current_huc,
num_workers=1,
aggregate=False,
inundation_raster=inundation_raster,
inundation_polygon=None,
depths=None,
out_raster_profile=None,
out_vector_profile=None,
quiet=True)
print("-----> Inundation mapping complete.")
def run_alpha_test(fim_run_dir, version, test_id, magnitude, compare_to_previous=False, archive_results=False, mask_type='huc', inclusion_area='', inclusion_area_buffer=0, light_run=False, overwrite=True):
benchmark_category = test_id.split('_')[1] # Parse benchmark_category from test_id.
current_huc = test_id.split('_')[0] # Break off HUC ID and assign to variable.
# Construct paths to development test results if not existent.
if archive_results:
version_test_case_dir_parent = os.path.join(TEST_CASES_DIR, benchmark_category + '_test_cases', test_id, 'official_versions', version)
else:
version_test_case_dir_parent = os.path.join(TEST_CASES_DIR, benchmark_category + '_test_cases', test_id, 'testing_versions', version)
# Delete the entire directory if it already exists.
if os.path.exists(version_test_case_dir_parent):
if overwrite == True:
shutil.rmtree(version_test_case_dir_parent)
else:
print("Metrics for ({version}: {test_id}) already exist. Use overwrite flag (-o) to overwrite metrics.".format(version=version, test_id=test_id))
return
os.mkdir(version_test_case_dir_parent)
print("Running the alpha test for test_id: " + test_id + ", " + version + "...")
stats_modes_list = ['total_area']
fim_run_parent = os.path.join(os.environ['outputDataDir'], fim_run_dir)
assert os.path.exists(fim_run_parent), "Cannot locate " + fim_run_parent
# Create paths to fim_run outputs for use in inundate().
rem = os.path.join(fim_run_parent, 'rem_zeroed_masked.tif')
if not os.path.exists(rem):
rem = os.path.join(fim_run_parent, 'rem_clipped_zeroed_masked.tif')
catchments = os.path.join(fim_run_parent, 'gw_catchments_reaches_filtered_addedAttributes.tif')
if not os.path.exists(catchments):
catchments = os.path.join(fim_run_parent, 'gw_catchments_reaches_clipped_addedAttributes.tif')
if mask_type == 'huc':
catchment_poly = ''
else:
catchment_poly = os.path.join(fim_run_parent, 'gw_catchments_reaches_filtered_addedAttributes_crosswalked.gpkg')
hydro_table = os.path.join(fim_run_parent, 'hydroTable.csv')
# Map necessary inputs for inundation().
hucs, hucs_layerName = os.path.join(INPUTS_DIR, 'wbd', 'WBD_National.gpkg'), 'WBDHU8'
# Create list of shapefile paths to use as exclusion areas.
zones_dir = os.path.join(TEST_CASES_DIR, 'other', 'zones')
mask_dict = {'levees':
{'path': os.path.join(zones_dir, 'leveed_areas_conus.shp'),
'buffer': None,
'operation': 'exclude'
},
'waterbodies':
{'path': os.path.join(zones_dir, 'nwm_v2_reservoirs.shp'),
'buffer': None,
'operation': 'exclude',
},
}
if inclusion_area != '':
inclusion_area_name = os.path.split(inclusion_area)[1].split('.')[0] # Get layer name
mask_dict.update({inclusion_area_name: {'path': inclusion_area,
'buffer': int(inclusion_area_buffer),
'operation': 'include'}})
# Append the concatenated inclusion_area_name and buffer.
if inclusion_area_buffer == None:
inclusion_area_buffer = 0
stats_modes_list.append(inclusion_area_name + '_b' + str(inclusion_area_buffer) + 'm')
# Check if magnitude is list of magnitudes or single value.
magnitude_list = magnitude
if type(magnitude_list) != list:
magnitude_list = [magnitude_list]
# Get path to validation_data_{benchmark} directory and huc_dir.
validation_data_path = os.path.join(TEST_CASES_DIR, benchmark_category + '_test_cases', 'validation_data_' + benchmark_category)
for magnitude in magnitude_list:
version_test_case_dir = os.path.join(version_test_case_dir_parent, magnitude)
if not os.path.exists(version_test_case_dir):
os.mkdir(version_test_case_dir)
# Construct path to validation raster and forecast file.
if benchmark_category in AHPS_BENCHMARK_CATEGORIES:
benchmark_raster_path_list, forecast_list = [], []
lid_dir_list = os.listdir(os.path.join(validation_data_path, current_huc))
lid_list, inundation_raster_list, domain_file_list = [], [], []
for lid in lid_dir_list:
lid_dir = os.path.join(validation_data_path, current_huc, lid)
benchmark_lid_raster_path = os.path.join(lid_dir, magnitude, 'ahps_' + lid + '_huc_' + current_huc + '_extent_' + magnitude + '.tif')
# Only compare if the benchmark data exist.
if os.path.exists(benchmark_lid_raster_path):
benchmark_raster_path_list.append(benchmark_lid_raster_path) # TEMP
forecast_list.append(os.path.join(lid_dir, magnitude, 'ahps_' + lid + '_huc_' + current_huc + '_flows_' + magnitude + '.csv')) # TEMP
lid_list.append(lid)
inundation_raster_list.append(os.path.join(version_test_case_dir, lid + '_inundation_extent.tif'))
domain_file_list.append(os.path.join(lid_dir, lid + '_domain.shp'))
else:
benchmark_raster_file = os.path.join(TEST_CASES_DIR, benchmark_category + '_test_cases', 'validation_data_' + benchmark_category, current_huc, magnitude, benchmark_category + '_huc_' + current_huc + '_extent_' + magnitude + '.tif')
benchmark_raster_path_list = [benchmark_raster_file]
forecast_path = os.path.join(TEST_CASES_DIR, benchmark_category + '_test_cases', 'validation_data_' + benchmark_category, current_huc, magnitude, benchmark_category + '_huc_' + current_huc + '_flows_' + magnitude + '.csv')
forecast_list = [forecast_path]
inundation_raster_list = [os.path.join(version_test_case_dir, 'inundation_extent.tif')]
for index in range(0, len(benchmark_raster_path_list)):
benchmark_raster_path = benchmark_raster_path_list[index]
forecast = forecast_list[index]
inundation_raster = inundation_raster_list[index]
# Only need to define ahps_lid and ahps_extent_file for AHPS_BENCHMARK_CATEGORIES.
if benchmark_category in AHPS_BENCHMARK_CATEGORIES:
ahps_lid = lid_list[index]
ahps_domain_file = domain_file_list[index]
mask_dict.update({ahps_lid:
{'path': ahps_domain_file,
'buffer': None,
'operation': 'include'}
})
if not os.path.exists(benchmark_raster_path) or not os.path.exists(ahps_domain_file) or not os.path.exists(forecast): # Skip loop instance if the benchmark raster doesn't exist.
continue
else: # If not in AHPS_BENCHMARK_CATEGORIES.
if not os.path.exists(benchmark_raster_path) or not os.path.exists(forecast): # Skip loop instance if the benchmark raster doesn't exist.
continue
# Run inundate.
# print("-----> Running inundate() to produce modeled inundation extent for the " + magnitude + " magnitude...")
try:
inundate_test = inundate(
rem,catchments,catchment_poly,hydro_table,forecast,mask_type,hucs=hucs,hucs_layerName=hucs_layerName,
subset_hucs=current_huc,num_workers=1,aggregate=False,inundation_raster=inundation_raster,inundation_polygon=None,
depths=None,out_raster_profile=None,out_vector_profile=None,quiet=True
)
if inundate_test == 0:
# print("-----> Inundation mapping complete.")
predicted_raster_path = os.path.join(os.path.split(inundation_raster)[0], os.path.split(inundation_raster)[1].replace('.tif', '_' + current_huc + '.tif')) # The inundate adds the huc to the name so I account for that here.
# Define outputs for agreement_raster, stats_json, and stats_csv.
if benchmark_category in AHPS_BENCHMARK_CATEGORIES:
agreement_raster, stats_json, stats_csv = os.path.join(version_test_case_dir, lid + 'total_area_agreement.tif'), os.path.join(version_test_case_dir, 'stats.json'), os.path.join(version_test_case_dir, 'stats.csv')
else:
agreement_raster, stats_json, stats_csv = os.path.join(version_test_case_dir, 'total_area_agreement.tif'), os.path.join(version_test_case_dir, 'stats.json'), os.path.join(version_test_case_dir, 'stats.csv')
compute_contingency_stats_from_rasters(predicted_raster_path,
benchmark_raster_path,
agreement_raster,
stats_csv=stats_csv,
stats_json=stats_json,
mask_values=[],
stats_modes_list=stats_modes_list,
test_id=test_id,
mask_dict=mask_dict,
)
if benchmark_category in AHPS_BENCHMARK_CATEGORIES:
del mask_dict[ahps_lid]
print(" ")
print("Evaluation metrics for " + test_id + ", " + version + ", " + magnitude + " are available at " + CYAN_BOLD + version_test_case_dir + ENDC)
print(" ")
elif inundate_test == 1:
pass
print (f"No matching feature IDs between forecast and hydrotable for magnitude: {magnitude}")
#return
except Exception as e:
print(e)
if benchmark_category in AHPS_BENCHMARK_CATEGORIES:
# -- Delete temp files -- #
# List all files in the output directory.
output_file_list = os.listdir(version_test_case_dir)
for output_file in output_file_list:
if "total_area" in output_file:
full_output_file_path = os.path.join(version_test_case_dir, output_file)
os.remove(full_output_file_path)
def run_inundation(args):
"""
This script is basically a wrapper for the inundate function and is designed for multiprocessing.
Args:
args (list): [fim_run_dir (str), huc (str), magnitude (str), magnitude_output_dir (str), config (str)]
"""
fim_run_dir = args[0]
huc = args[1]
magnitude = args[2]
magnitude_output_dir = args[3]
config = args[4]
# Define file paths for use in inundate().
fim_run_parent = os.path.join(fim_run_dir, huc)
rem = os.path.join(fim_run_parent, 'rem_zeroed_masked.tif')
catchments = os.path.join(
fim_run_parent, 'gw_catchments_reaches_filtered_addedAttributes.tif')
mask_type = 'huc'
catchment_poly = ''
hydro_table = os.path.join(fim_run_parent, 'hydroTable.csv')
catchment_poly = os.path.join(
fim_run_parent,
'gw_catchments_reaches_filtered_addedAttributes_crosswalked.gpkg')
inundation_raster = os.path.join(
magnitude_output_dir, magnitude + '_' + config + '_inund_extent.tif')
depth_raster = os.path.join(magnitude_output_dir,
magnitude + '_' + config + '_inund_depth.tif')
forecast = os.path.join(INUN_REVIEW_DIR, 'nwm_recurr_flow_data',
'recurr_' + magnitude + '_cms.csv')
hucs, hucs_layerName = os.path.join(INPUTS_DIR, 'wbd',
'WBD_National.gpkg'), 'WBDHU8'
# Run inundate() once for depth and once for extent.
if not os.path.exists(depth_raster):
print("Running the NWM recurrence intervals for HUC: " + huc + ", " +
magnitude + "...")
inundate(rem,
catchments,
catchment_poly,
hydro_table,
forecast,
mask_type,
hucs=hucs,
hucs_layerName=hucs_layerName,
subset_hucs=huc,
num_workers=1,
aggregate=False,
inundation_raster=None,
inundation_polygon=None,
depths=depth_raster,
out_raster_profile=None,
out_vector_profile=None,
quiet=True)
if not os.path.exists(inundation_raster):
inundate(rem,
catchments,
catchment_poly,
hydro_table,
forecast,
mask_type,
hucs=hucs,
hucs_layerName=hucs_layerName,
subset_hucs=huc,
num_workers=1,
aggregate=False,
inundation_raster=inundation_raster,
inundation_polygon=None,
depths=None,
out_raster_profile=None,
out_vector_profile=None,
quiet=True)
def run_alpha_test(fim_run_dir,
branch_name,
test_id,
magnitude,
compare_to_previous=False,
archive_results=False,
mask_type='huc',
inclusion_area='',
inclusion_area_buffer=0,
light_run=False):
# Construct paths to development test results if not existent.
if archive_results:
branch_test_case_dir_parent = os.path.join(TEST_CASES_DIR, test_id,
'performance_archive',
'previous_versions',
branch_name)
else:
branch_test_case_dir_parent = os.path.join(TEST_CASES_DIR, test_id,
'performance_archive',
'development_versions',
branch_name)
# Delete the entire directory if it already exists.
if os.path.exists(branch_test_case_dir_parent):
shutil.rmtree(branch_test_case_dir_parent)
print("Running the alpha test for test_id: " + test_id + ", " +
branch_name + "...")
stats_modes_list = ['total_area']
fim_run_parent = os.path.join(os.environ['outputDataDir'], fim_run_dir)
assert os.path.exists(fim_run_parent), "Cannot locate " + fim_run_parent
# Create paths to fim_run outputs for use in inundate().
rem = os.path.join(fim_run_parent, 'rem_zeroed_masked.tif')
catchments = os.path.join(
fim_run_parent, 'gw_catchments_reaches_filtered_addedAttributes.tif')
if mask_type == 'huc':
catchment_poly = ''
else:
catchment_poly = os.path.join(
fim_run_parent,
'gw_catchments_reaches_filtered_addedAttributes_crosswalked.gpkg')
hydro_table = os.path.join(fim_run_parent, 'hydroTable.csv')
# Map necessary inputs for inundation().
hucs, hucs_layerName = os.path.join(INPUTS_DIR, 'wbd',
'WBD_National.gpkg'), 'WBDHU8'
benchmark_category = test_id.split('_')[1]
current_huc = test_id.split('_')[
0] # Break off HUC ID and assign to variable.
# Create list of shapefile paths to use as exclusion areas.
zones_dir = os.path.join(TEST_CASES_DIR, 'other', 'zones')
mask_dict = {
'levees': {
'path': os.path.join(zones_dir, 'leveed_areas_conus.shp'),
'buffer': None,
'operation': 'exclude'
},
'waterbodies': {
'path': os.path.join(zones_dir, 'nwm_v2_reservoirs.shp'),
'buffer': None,
'operation': 'exclude',
},
}
if not os.path.exists(branch_test_case_dir_parent):
os.mkdir(branch_test_case_dir_parent)
# If the test_id is AHPS, then identify possible inclusion zones in the HUC.
if benchmark_category == 'ahps':
ahps_inclusion_zones_dir = os.path.join(branch_test_case_dir_parent,
'ahps_domains')
print(ahps_inclusion_zones_dir)
if not os.path.exists(ahps_inclusion_zones_dir):
os.mkdir(ahps_inclusion_zones_dir)
ahps_domain_shapefile = os.path.join(TEST_CASES_DIR, 'other', 'zones',
'ahps_domains.shp')
# Open shapefile, determine the polys in the huc, create a different shapefile for each poly--name according to AHPS.
ahps_domain_obj = gpd.read_file(ahps_domain_shapefile)
ahps_domain_gdf = gpd.GeoDataFrame(ahps_domain_obj)
# Loop through entries and compare against the huc4_list to get available HUCs within the geopackage domain.
for index, row in ahps_domain_gdf.iterrows():
huc8_code = row['huc8_code']
ahps = row['ahps_code']
if huc8_code == current_huc:
ahps_domain_subset = ahps_domain_obj[ahps_domain_obj.ahps_code
== ahps]
#.query("ahps_code=='{ahps_code}'".format(ahps_code=ahps_code))
ahps_domain_subset_output = os.path.join(
ahps_inclusion_zones_dir, ahps + '.shp')
ahps_domain_subset.to_file(ahps_domain_subset_output,
driver='ESRI Shapefile')
mask_dict.update({
ahps: {
'path': ahps_domain_subset_output,
'buffer': None,
'operation': 'include'
}
})
if inclusion_area != '':
inclusion_area_name = os.path.split(inclusion_area)[1].split('.')[
0] # Get layer name
mask_dict.update({
inclusion_area_name: {
'path': inclusion_area,
'buffer': int(inclusion_area_buffer),
'operation': 'include'
}
})
# Append the concatenated inclusion_area_name and buffer.
if inclusion_area_buffer == None:
inclusion_area_buffer = 0
stats_modes_list.append(inclusion_area_name + '_b' +
str(inclusion_area_buffer) + 'm')
# Check if magnitude is list of magnitudes or single value.
magnitude_list = magnitude
if type(magnitude_list) != list:
magnitude_list = [magnitude_list]
for magnitude in magnitude_list:
# Construct path to validation raster and forecast file.
benchmark_raster_path = os.path.join(
TEST_CASES_DIR, 'validation_data_' + benchmark_category,
current_huc, magnitude, benchmark_category + '_huc_' +
current_huc + '_depth_' + magnitude + '.tif')
if not os.path.exists(
benchmark_raster_path
): # Skip loop instance if the benchmark raster doesn't exist.
continue
branch_test_case_dir = os.path.join(branch_test_case_dir_parent,
magnitude)
os.makedirs(branch_test_case_dir) # Make output directory for branch.
# Define paths to inundation_raster and forecast file.
inundation_raster = os.path.join(branch_test_case_dir,
'inundation_extent.tif')
forecast = os.path.join(
TEST_CASES_DIR, 'validation_data_' + benchmark_category,
current_huc, magnitude, benchmark_category + '_huc_' +
current_huc + '_flows_' + magnitude + '.csv')
# Run inundate.
print(
"-----> Running inundate() to produce modeled inundation extent for the "
+ magnitude + " magnitude...")
inundate(rem,
catchments,
catchment_poly,
hydro_table,
forecast,
mask_type,
hucs=hucs,
hucs_layerName=hucs_layerName,
subset_hucs=current_huc,
num_workers=1,
aggregate=False,
inundation_raster=inundation_raster,
inundation_polygon=None,
depths=None,
out_raster_profile=None,
out_vector_profile=None,
quiet=True)
print("-----> Inundation mapping complete.")
predicted_raster_path = os.path.join(
os.path.split(inundation_raster)[0],
os.path.split(inundation_raster)[1].replace(
'.tif', '_' + current_huc + '.tif')
) # The inundate adds the huc to the name so I account for that here.
# Define outputs for agreement_raster, stats_json, and stats_csv.
agreement_raster, stats_json, stats_csv = os.path.join(
branch_test_case_dir, 'total_area_agreement.tif'), os.path.join(
branch_test_case_dir,
'stats.json'), os.path.join(branch_test_case_dir, 'stats.csv')
test_version_dictionary = compute_contingency_stats_from_rasters(
predicted_raster_path,
benchmark_raster_path,
agreement_raster,
stats_csv=stats_csv,
stats_json=stats_json,
mask_values=[],
stats_modes_list=stats_modes_list,
test_id=test_id,
mask_dict=mask_dict,
)
print(" ")
print("Evaluation complete. All metrics for " + test_id + ", " +
branch_name + ", " + magnitude + " are available at " +
CYAN_BOLD + branch_test_case_dir + ENDC)
print(" ")
if compare_to_previous:
text_block = []
# Compare to previous stats files that are available.
archive_to_check = os.path.join(TEST_CASES_DIR, test_id,
'performance_archive',
'previous_versions')
for stats_mode in stats_modes_list:
archive_dictionary = profile_test_case_archive(
archive_to_check, magnitude, stats_mode)
if archive_dictionary == {}:
break
# Create header for section.
header = [stats_mode]
for previous_version, paths in archive_dictionary.items():
header.append(previous_version)
header.append(branch_name)
text_block.append(header)
# Loop through stats in PRINTWORTHY_STATS for left.
for stat in PRINTWORTHY_STATS:
stat_line = [stat]
for previous_version, paths in archive_dictionary.items():
# Load stats for previous version.
previous_version_stats_json_path = paths['stats_json']
if os.path.exists(previous_version_stats_json_path):
previous_version_stats_dict = json.load(
open(previous_version_stats_json_path))
# Append stat for the version to state_line.
stat_line.append(previous_version_stats_dict[stat])
# Append stat for the current version to stat_line.
stat_line.append(test_version_dictionary[stats_mode][stat])
text_block.append(stat_line)
text_block.append([" "])
regression_report_csv = os.path.join(branch_test_case_dir,
'stats_summary.csv')
with open(regression_report_csv, 'w', newline='') as csvfile:
csv_writer = csv.writer(csvfile)
csv_writer.writerows(text_block)
print()
print(
"--------------------------------------------------------------------------------------------------"
)
stats_mode = stats_modes_list[0]
try:
last_version_index = text_block[0].index('dev_latest')
except ValueError:
try:
last_version_index = text_block[0].index('fim_2_3_3')
except ValueError:
try:
last_version_index = text_block[0].index('fim_1_0_0')
except ValueError:
print(
TRED_BOLD + "Warning: " + ENDC +
"Cannot compare " + branch_name +
" to a previous version because no authoritative versions were found in previous_versions directory. Future version of run_test_case may allow for comparisons between dev branches."
)
print()
continue
for line in text_block:
first_item = line[0]
if first_item in stats_modes_list:
current_version_index = line.index(branch_name)
if first_item != stats_mode: # Update the stats_mode and print a separator.
print()
print()
print(
"--------------------------------------------------------------------------------------------------"
)
print()
stats_mode = first_item
print(CYAN_BOLD + current_huc + ": " + magnitude.upper(),
ENDC)
print(CYAN_BOLD + stats_mode.upper().replace('_', ' ') +
" METRICS" + ENDC)
print()
color = WHITE_BOLD
metric_name = ' '.center(
len(max(PRINTWORTHY_STATS, key=len)))
percent_change_header = '% CHG'
difference_header = 'DIFF'
current_version_header = line[current_version_index].upper(
)
last_version_header = line[last_version_index].upper()
# Print Header.
print(
color + metric_name + " " +
percent_change_header.center(
(7)) + " " + difference_header.center((15)) +
" " + current_version_header.center(18) + " " +
last_version_header.center(18), ENDC)
# Format and print stat row.
elif first_item in PRINTWORTHY_STATS:
stat_name = first_item.upper().center(
len(max(PRINTWORTHY_STATS,
key=len))).replace('_', ' ')
current_version = round((line[current_version_index]), 3)
last_version = round((line[last_version_index]) + 0.000, 3)
difference = round(current_version - last_version, 3)
if difference > 0:
symbol = '+'
if first_item in GO_UP_STATS:
color = TGREEN_BOLD
elif first_item in GO_DOWN_STATS:
color = TRED_BOLD
else:
color = TWHITE
if difference < 0:
symbol = '-'
if first_item in GO_UP_STATS:
color = TRED_BOLD
elif first_item in GO_DOWN_STATS:
color = TGREEN_BOLD
else:
color = TWHITE
if difference == 0:
symbol, color = '+', TGREEN
percent_change = round((difference / last_version) * 100,
2)
print(
WHITE_BOLD + stat_name + ENDC + " " + color +
(symbol + " {:5.2f}".format(abs(percent_change)) +
" %").rjust(len(percent_change_header)),
ENDC + " " + color + ("{:12.3f}".format(
(difference))).rjust(len(difference_header)),
ENDC + " " +
"{:15.3f}".format(current_version).rjust(
len(current_version_header)) + " " +
"{:15.3f}".format(last_version).rjust(
len(last_version_header)) + " ")
print()
print()
print()
print(
"--------------------------------------------------------------------------------------------------"
)
print()
def run_recurr_test(fim_run_dir,
branch_name,
huc_id,
input_flow_csv,
mask_type='huc'):
# Construct paths to development test results if not existent.
huc_id_dir_parent = os.path.join(TEST_CASES_DIR, huc_id)
if not os.path.exists(huc_id_dir_parent):
os.mkdir(huc_id_dir_parent)
branch_test_case_dir_parent = os.path.join(TEST_CASES_DIR, huc_id,
branch_name)
# Delete the entire directory if it already exists.
if os.path.exists(branch_test_case_dir_parent):
shutil.rmtree(branch_test_case_dir_parent)
print("Running the NWM recurrence intervals for HUC: " + huc_id + ", " +
branch_name + "...")
assert os.path.exists(fim_run_dir), "Cannot locate " + fim_run_dir
# Create paths to fim_run outputs for use in inundate().
if "previous_fim" in fim_run_dir and "fim_2" in fim_run_dir:
rem = os.path.join(fim_run_dir, 'rem_clipped_zeroed_masked.tif')
catchments = os.path.join(
fim_run_dir, 'gw_catchments_reaches_clipped_addedAttributes.tif')
if not os.path.isfile(rem):
print('Can not find REM file: ' + str(rem))
if not os.path.isfile(catchments):
print('Can not find catchments file: ' + str(catchments))
else:
rem = os.path.join(fim_run_dir, 'rem_zeroed_masked.tif')
catchments = os.path.join(
fim_run_dir, 'gw_catchments_reaches_filtered_addedAttributes.tif')
if not os.path.isfile(rem):
print('Can not find REM file: ' + str(rem))
if not os.path.isfile(catchments):
print('Can not find catchments file: ' + str(catchments))
if mask_type == 'huc':
catchment_poly = ''
print(
'Not using the catchment polygon input layer -- FIM version < 3??')
else:
catchment_poly = os.path.join(
fim_run_dir,
'gw_catchments_reaches_filtered_addedAttributes_crosswalked.gpkg')
if not os.path.isfile(catchment_poly):
print('Can not find catchments polygon file: ' + str(catchments))
hydro_table = os.path.join(fim_run_dir, 'hydroTable.csv')
if not os.path.isfile(hydro_table):
print('Can not find hydro_table file: ' + str(hydro_table))
#benchmark_category = huc_id.split('_')[1]
current_huc = huc_id.split('_')[
0] # Break off HUC ID and assign to variable.
wbd_huc = 'WBDHU' + str(
len(huc_id)) # check if the input huc is 2,4,6,8 etc
# Map necessary inputs for inundation().
hucs, hucs_layerName = os.path.join(INPUTS_DIR, 'wbd',
'WBD_National.gpkg'), wbd_huc
if not os.path.exists(branch_test_case_dir_parent):
os.mkdir(branch_test_case_dir_parent)
#branch_test_case_dir = os.path.join(branch_test_case_dir_parent)
#os.makedirs(branch_test_case_dir) # Make output directory for branch.
# Define paths to inundation_raster and forecast file.
inundation_raster = os.path.join(branch_test_case_dir_parent,
branch_name + '_inund_extent.tif')
forecast = os.path.join(TEST_CASES_DIR, "_input_flow_files",
input_flow_csv)
if not os.path.isfile(forecast):
print('Can not find input flow file: ' + str(forecast))
# Copy forecast flow file into the outputs directory to all viewer to reference the flows used to create inundation_raster
shutil.copyfile(forecast,
os.path.join(branch_test_case_dir_parent, input_flow_csv))
# Run inundate.
print(
"-----> Running inundate() to produce modeled inundation extent for the "
+ input_flow_csv)
inundate(rem,
catchments,
catchment_poly,
hydro_table,
forecast,
mask_type,
hucs=hucs,
hucs_layerName=hucs_layerName,
subset_hucs=current_huc,
num_workers=1,
aggregate=False,
inundation_raster=inundation_raster,
inundation_polygon=None,
depths=None,
out_raster_profile=None,
out_vector_profile=None,
quiet=False)
print("-----> Inundation mapping complete.")
if not os.path.isfile(inundation_raster):
print('Warning!! Inundation Raster not produced: ' +
str(inundation_raster))