def test_wave_class_1(self):
# Test with normal partitioning
file = 'tests/test_data//test_metdata_normal.txt'
met_data = windbins.get_met_data(file)
waves = windbins.Wave(met_data)
met_partitions = waves.partition(num_divisions=3)
compare_partitions = {
'Significant Wave Height': [1.58, 1.8, 1.77],
'Wave Direction': [98.0, 107.0, 116.0],
'Wave Period': [13.79, 13.79, 13.79]
}
compare_partitions = pd.DataFrame(data=compare_partitions)
assert compare_partitions.equals(met_partitions)
def test_wave_class_4(self):
# Test with custom partitioning, 1 wave climate consisting of only nans
file = 'tests/test_data//test_metdata_normal.txt'
met_data = windbins.get_met_data(file)
waves = windbins.Wave(met_data)
@mock.patch('fowt_force_gen.windbins.input', create=True)
def dummy_inputs(mocked_inputs):
mocked_inputs.side_effect = ['y', '1', '9 10 11']
met_partitions = waves.partition(custom_partitioning=True)
compare_partitions = {
'Significant Wave Height': [np.nan],
'Wave Direction': [np.nan],
'Wave Period': [np.nan]
}
compare_partitions = pd.DataFrame(data=compare_partitions)
assert compare_partitions.equals(met_partitions)
dummy_inputs()
def test_wave_class_3(self):
# Test with custom partitioning, 2 overlapping wave climates
file = 'tests/test_data//test_metdata_normal.txt'
met_data = windbins.get_met_data(file)
waves = windbins.Wave(met_data)
@mock.patch('fowt_force_gen.windbins.input', create=True)
def dummy_inputs(mocked_inputs):
mocked_inputs.side_effect = ['y', '2', '1 3 5 7 9', '1 2 3 5 7']
met_partitions = waves.partition(custom_partitioning=True)
compare_partitions = {
'Significant Wave Height': [1.723, 1.694],
'Wave Direction': [98.75, 98.6],
'Wave Period': [15.368, 15.256]
}
compare_partitions = pd.DataFrame(data=compare_partitions)
assert compare_partitions.equals(met_partitions)
dummy_inputs()
def test_wave_class_2(self, monkeypatch):
# Test with custom partitioning, 2 disparate wave climates
file = 'tests/test_data//test_metdata_normal.txt'
met_data = windbins.get_met_data(file)
waves = windbins.Wave(met_data)
@mock.patch('fowt_force_gen.windbins.input', create=True)
def dummy_inputs(mocked_inputs):
mocked_inputs.side_effect = ['y', '2', '0 1 2 3 4', '5 6 7 8']
met_partitions = waves.partition(custom_partitioning=True)
compare_partitions = {
'Significant Wave Height': [1.684, 1.740],
'Wave Direction': [107.4, 110.5],
'Wave Period': [13.816, 15.59]
}
compare_partitions = pd.DataFrame(data=compare_partitions)
assert compare_partitions.equals(met_partitions)
dummy_inputs()
def main():
# Step 1: The user enters in geographic location of buoy location off the coast of North America
parser = argparse.ArgumentParser(
description=
'Identifies nearest NOAA stationary buoy to input coordinates')
parser.add_argument(
'-lat',
'--latitude',
type=str,
required=True,
help=
'String input of latitude. Use decimals degrees and either N/S or +/- to notate direction.'
)
parser.add_argument(
'-lon',
'--longitude',
type=str,
required=True,
help=
'String input of longitude. Use decimal degrees and either E/W or +/- to notate direction.'
)
parser.add_argument(
'-pf',
'--platform',
type=str,
required=True,
help='Platform type. Either OC3 or OC4 (i.e. Hywind or DeepCwind)')
parser.add_argument(
'-fr',
'--fileroot',
type=str,
required=True,
help='Root of filenames that all output files will start with.')
args = parser.parse_args()
# Step 1.5: Define template OpenFAST files to be used later in custom file creation (Step 5)
# note: this ignores MoorDyn, which is created independently in Step 4
template_file_dir = 'template_files'
turbsim_file_dir = 'turbsim_files'
dat_file_dir = 'fast_input_files'
output_file_dir = 'output_files'
mat_file_dir = 'force_gen'
if not os.path.exists('force_gen'):
os.makedirs('force_gen')
if not os.path.exists('turbsim_files'):
os.makedirs('turbsim_files')
if not os.path.exists('output_files'):
os.makedirs('output_files')
if args.platform.lower() == 'oc3':
template_hd_file = template_file_dir + '/OC3Hywind_HydroDyn_template.dat'
template_fst_file = template_file_dir + '/OC3Hywind_OpenFAST_template.fst'
elif args.platform.lower() == 'oc4':
template_hd_file = template_file_dir + '/OC4Semi_HydroDyn_template.dat'
template_fst_file = template_file_dir + '/OC4Semi_OpenFAST_template.fst'
else:
raise ValueError(
"Platform type not recognized. Please specify either 'OC3' or 'OC4'"
)
template_inp_file = template_file_dir + '/IECKAI_template.inp'
template_ifw_file = template_file_dir + '/InflowWind_template.dat'
# Step 2: The nearest NOAA buoy is identified, and meteorological from the buoy is scraped and saved in text files
buoy_num = buoy.geo_match(args.latitude, args.longitude)
water_depth = buoy.get_water_depth(buoy_num)
buoy.data_scraper(buoy_num)
# Step 3: Read the text files and partition critical parameters into bins. If wind or current data does
# not exist, specify as such so it isn't accounted for in OpenFAST file creation. Prompt user for input
# to determine how to split wave climates, as separate HydroDyn files are created for each climate later.
met_file = parse.get_most_recent_file_containing(
'met_data_' + str(buoy_num), '.txt')
met_data = windbins.get_met_data(met_file)
os.remove(met_file)
try:
wind_file = parse.get_most_recent_file_containing(
'wind_data_' + str(buoy_num), '.txt')
wind_data = windbins.get_wind_data(wind_file)
wind = windbins.Wind(wind_data)
os.remove(wind_file)
except:
wind = windbins.Wind(met_data)
pass
try:
curr_file = parse.get_most_recent_file_containing(
'curr_data_' + str(buoy_num), '.txt')
curr_data, curr_depth = windbins.get_current_data(curr_file)
curr_speed = curr_data['Current Speed']
curr_dir = curr_data['Current Direction']
no_curr_file = False
os.remove(curr_file)
except:
no_curr_file = True
pass
bin_probabilities = wind.get_bin_probabilities()
waves = windbins.Wave(met_data)
wave_climates = waves.partition(custom_partitioning=True)
# Step 4: Tune the floating wind platform mooring system for the depth and platform used at the site, and generate
# the resulting MoorDyn input file
moortune.tune(water_depth, args.platform,
dat_file_dir + '/' + args.fileroot + '_MoorDyn.dat')
# Step 5: Generate the other needed OpenFAST input files for each permutation, and run OpenFAST
# Create INP files and run TurbSim
filegen.inp_bulk_filegen(template_inp_file,
turbsim_file_dir + '/' + args.fileroot,
bin_probabilities.index.values)
inp_files = parse.get_filenames('.inp', file_directory=turbsim_file_dir)
run_fast.run_turbsim(inp_files)
# Create InflowWind files from TurbSim BTS files and wind direction data
filegen.inflowwind_bulk_filegen(
template_ifw_file, dat_file_dir + '/' + args.fileroot + '_InflowWind',
turbsim_file_dir, bin_probabilities.columns)
# Create HydroDyn DAT files from custom wave climates
if no_curr_file:
filegen.hydrodyn_bulk_filegen(
template_hd_file, dat_file_dir + '/' + args.fileroot + '_HydroDyn',
water_depth, wave_climates)
else:
filegen.hydrodyn_bulk_filegen(
template_hd_file,
dat_file_dir + '/' + args.fileroot + '_HydroDyn',
water_depth,
wave_climates,
current_climate=[curr_depth, curr_speed, curr_dir])
# Create OpenFAST FST files from previous custom files
filegen.fst_bulk_filegen(
template_fst_file, args.fileroot,
dat_file_dir + '/' + args.fileroot + '_MoorDyn.dat', dat_file_dir,
dat_file_dir)
# Run OpenFAST for all created FST files and move output files to specified directories
fst_files = parse.get_filenames('.fst')
run_fast.run_fast(fst_files)
os.remove(fst_files)
outb_files = parse.get_filenames('.outb')
parse.move_files(outb_files, output_file_dir)
md_out_files = parse.get_filenames('.out')
parse.move_files(md_out_files, output_file_dir)
# Do post-processing for all tests
all_output_roots = [
filenames.replace('.outb', '') for filenames in outb_files
]
for test in all_output_roots:
# Step 6: Parse the OpenFAST outputs into mooring/anchor tension and platform surge/sway into numpy arrays
# containing the relevant statistical occurrences
ptfm_surge, ptfm_sway, anchor_tension, line1_tension, line2_tension, line3_tension = \
parse.output_parse(output_file_dir+'/'+test)
surge_stats = parse.make_distributions(ptfm_surge,
calculate_stdev=False)
sway_stats = parse.make_distributions(ptfm_sway, calculate_stdev=False)
anchor_stats = parse.make_distributions(anchor_tension)
line1_stats = parse.make_distributions(line1_tension)
line2_stats = parse.make_distributions(line2_tension)
line3_stats = parse.make_distributions(line3_tension)
# Step 7: Create MAT files matching the format of the external reliability code
reliability_results_filename = mat_file_dir + '/' + 'ReliabilityResults_' + test + '.mat'
surge_results_filename = mat_file_dir + '/' + 'Surge_' + test + '.mat'
filegen.create_mat_files(reliability_results_filename,
surge_results_filename, line1_stats,
line2_stats, line3_stats, anchor_stats[0, :],
anchor_stats[1, :], anchor_stats[2, :],
surge_stats, sway_stats)
def main():
# Step 1: The user enters in geographic location of buoy location off the coast of North America
parser = argparse.ArgumentParser(
description=
'Identifies nearest NOAA stationary buoy to input coordinates')
parser.add_argument(
'-lat',
'--latitude',
type=str,
required=True,
help=
'String input of latitude. Use decimals degrees and either N/S or +/- to notate direction.'
)
parser.add_argument(
'-lon',
'--longitude',
type=str,
required=True,
help=
'String input of longitude. Use decimal degrees and either E/W or +/- to notate direction.'
)
parser.add_argument(
'-pf',
'--platform',
type=str,
required=True,
help='Platform type. Either OC3 or OC4 (i.e. Hywind or DeepCwind)')
parser.add_argument(
'-fr',
'--fileroot',
type=str,
required=True,
help='Root of filenames that all output files will start with.')
parser.add_argument(
'-ex',
'--example',
type=int,
help=
'Example MoorDyn files to use (optional). Overwrites fileroot if used.'
)
args = parser.parse_args()
# Step 1.5: Define template OpenFAST files to be used later in custom file creation (Step 5)
# note: this ignores MoorDyn, which is created independently in Step 4
if args.example:
fileroot = 'example' + str(args.example)
ex_file_dir = 'example_files'
else:
fileroot = args.fileroot
template_file_dir = 'template_files'
turbsim_file_dir = 'turbsim_files'
dat_file_dir = 'fast_input_files'
if not os.path.exists('force_gen'):
os.makedirs('force_gen')
if not os.path.exists('turbsim_files'):
os.makedirs('turbsim_files')
if args.platform.lower() == 'oc3':
template_hd_file = template_file_dir + '/OC3Hywind_HydroDyn_template.dat'
template_fst_file = template_file_dir + '/OC3Hywind_OpenFAST_template.fst'
elif args.platform.lower() == 'oc4':
template_hd_file = template_file_dir + '/OC4Semi_HydroDyn_template.dat'
template_fst_file = template_file_dir + '/OC4Semi_OpenFAST_template.fst'
else:
raise ValueError(
"Platform type not recognized. Please specify either 'OC3' or 'OC4'"
)
template_inp_file = template_file_dir + '/IECKAI_template.inp'
template_ifw_file = template_file_dir + '/InflowWind_template.dat'
# Step 2: The nearest NOAA buoy is identified, and meteorological from the buoy is scraped and saved in text files
buoy_num = buoy.geo_match(args.latitude, args.longitude)
water_depth = buoy.get_water_depth(buoy_num)
buoy.data_scraper(buoy_num)
# Step 3: Read the text files and partition critical parameters into bins. If wind or current data does
# not exist, specify as such so it isn't accounted for in OpenFAST file creation. Prompt user for input
# to determine how to split wave climates, as separate HydroDyn files are created for each climate later.
met_file = parse.get_most_recent_file_containing(
'met_data_' + str(buoy_num), '.txt')
met_data = windbins.get_met_data(met_file)
os.remove(met_file)
try:
wind_file = parse.get_most_recent_file_containing(
'wind_data_' + str(buoy_num), '.txt')
wind_data = windbins.get_wind_data(wind_file)
wind = windbins.Wind(wind_data)
os.remove(wind_file)
except:
wind = windbins.Wind(met_data)
pass
try:
curr_file = parse.get_most_recent_file_containing(
'curr_data_' + str(buoy_num), '.txt')
curr_data, curr_depth = windbins.get_current_data(curr_file)
curr_speed = curr_data['Current Speed']
curr_dir = curr_data['Current Direction']
no_curr_file = False
os.remove(curr_file)
except:
no_curr_file = True
pass
bin_probabilities = wind.get_bin_probabilities()
waves = windbins.Wave(met_data)
wave_climates = waves.partition(custom_partitioning=True)
# Step 4: Tune the floating wind platform mooring system for the depth and platform used at the site, and generate
# the resulting MoorDyn input file
if not args.example:
moortune.tune(water_depth, args.platform,
dat_file_dir + '/' + fileroot + '_MoorDyn.dat')
# Step 5: Generate the other needed OpenFAST input files for each permutation, and run OpenFAST
# Create INP files
filegen.inp_bulk_filegen(template_inp_file,
turbsim_file_dir + '/' + fileroot,
bin_probabilities.index.values)
inp_files = parse.get_filenames('.inp', file_directory=turbsim_file_dir)
# Run TurbSim and create InflowWind files from BTS files and wind direction data
if args.example:
filegen.inflowwind_bulk_filegen(template_ifw_file,
dat_file_dir + '/' + fileroot +
'_InflowWind',
turbsim_file_dir,
bin_probabilities.columns,
no_turbsim=True)
else:
run_fast.run_turbsim(inp_files)
filegen.inflowwind_bulk_filegen(
template_ifw_file, dat_file_dir + '/' + fileroot + '_InflowWind',
turbsim_file_dir, bin_probabilities.columns)
# Create HydroDyn DAT files from custom wave climates
if no_curr_file:
filegen.hydrodyn_bulk_filegen(
template_hd_file, dat_file_dir + '/' + fileroot + '_HydroDyn',
water_depth, wave_climates)
else:
filegen.hydrodyn_bulk_filegen(
template_hd_file,
dat_file_dir + '/' + fileroot + '_HydroDyn',
water_depth,
wave_climates,
current_climate=[curr_depth, curr_speed, curr_dir])
# Create OpenFAST FST files from previous custom files
if args.example:
filegen.fst_bulk_filegen(template_fst_file, 'force_gen/' + fileroot,
ex_file_dir + '/' + fileroot + '_MoorDyn.dat',
dat_file_dir, dat_file_dir)
else:
filegen.fst_bulk_filegen(
template_fst_file, 'force_gen/' + fileroot,
dat_file_dir + '/' + fileroot + '_MoorDyn.dat', dat_file_dir,
dat_file_dir)
bin_probabilities.to_csv(fileroot + '_bin_probabilities.csv')