def test_verify_AOTIM5_2018(self, parameters):
#-- model parameters for AOTIM-5-2018
modelpath = os.path.join(filepath, 'Arc5km2018')
grid_file = os.path.join(modelpath, parameters['grid'])
model_file = os.path.join(modelpath, parameters['model'])
TYPE = parameters['type']
GRID = 'OTIS'
EPSG = 'PSNorth'
#-- open Arctic Tidal Current Atlas list of records
with open(os.path.join(filepath, 'List_of_records.txt'), 'r') as f:
file_contents = f.read().splitlines()
#-- skip 2 header rows
count = 2
#-- iterate over number of stations
arctic_stations = len(file_contents) - count
stations = [None] * arctic_stations
shortname = [None] * arctic_stations
station_lon = np.zeros((arctic_stations))
station_lat = np.zeros((arctic_stations))
for s in range(arctic_stations):
line_contents = file_contents[count + s].split()
stations[s] = line_contents[1]
shortname[s] = line_contents[2]
station_lat[s] = np.float64(line_contents[10])
station_lon[s] = np.float64(line_contents[11])
#-- calculate daily results for a time period
#-- convert time to days since 1992-01-01T00:00:00
tide_time = np.arange(
pyTMD.time.convert_calendar_dates(2000, 1, 1),
pyTMD.time.convert_calendar_dates(2000, 12, 31) + 1)
#-- serial dates for matlab program (days since 0000-01-01T00:00:00)
SDtime = np.arange(convert_calendar_serial(2000, 1, 1),
convert_calendar_serial(2000, 12, 31) + 1)
#-- presently not converting times to dynamic times for model comparisons
deltat = np.zeros_like(tide_time)
#-- number of days
ndays = len(tide_time)
#-- extract amplitude and phase from tide model
amp, ph, D, c = pyTMD.read_tide_model.extract_tidal_constants(
station_lon,
station_lat,
grid_file,
model_file,
EPSG,
TYPE=TYPE,
METHOD='spline',
GRID=GRID)
#-- calculate complex phase in radians for Euler's
cph = -1j * ph * np.pi / 180.0
#-- will verify differences between model outputs are within tolerance
eps = np.finfo(np.float16).eps
#-- compare daily outputs at each station point
invalid_list = ['KS14']
#-- remove coastal stations from the list
valid_stations = [
i for i, s in enumerate(shortname) if s not in invalid_list
]
#-- compute validation data from Matlab TMD program using octave
#-- https://github.com/EarthAndSpaceResearch/TMD_Matlab_Toolbox_v2.5
TMDpath = os.path.join(filepath, '..', 'TMD_Matlab_Toolbox', 'TMD')
octave.addpath(octave.genpath(os.path.normpath(TMDpath)))
octave.addpath(filepath)
octave.addpath(modelpath)
#-- turn off octave warnings
octave.warning('off', 'all')
#-- input control file for model
CFname = os.path.join(filepath, 'Model_Arc5km2018')
assert os.access(CFname, os.F_OK)
#-- run Matlab TMD program with octave
#-- MODE: OB time series
validation, _ = octave.tmd_tide_pred_plus(CFname,
SDtime,
station_lat[valid_stations],
station_lon[valid_stations],
TYPE,
nout=2)
#-- for each valid station
for i, s in enumerate(valid_stations):
#-- calculate constituent oscillation for station
hc = amp[s, None, :] * np.exp(cph[s, None, :])
#-- allocate for out tides at point
tide = np.ma.zeros((ndays))
tide.mask = np.zeros((ndays), dtype=bool)
#-- predict tidal elevations at time and infer minor corrections
tide.mask[:] = np.any(hc.mask)
tide.data[:] = pyTMD.predict_tidal_ts(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=GRID)
minor = pyTMD.infer_minor_corrections(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=GRID)
tide.data[:] += minor.data[:]
#-- calculate differences between matlab and python version
difference = np.ma.zeros((ndays))
difference.data[:] = tide.data - validation[:, i]
difference.mask = (tide.mask | np.isnan(validation[:, i]))
difference.data[difference.mask] = 0.0
if not np.all(difference.mask):
assert np.all(np.abs(difference) < eps)
def test_verify_CATS2008(self, parameters):
#-- model parameters for CATS2008
modelpath = os.path.join(filepath, 'CATS2008')
grid_file = os.path.join(modelpath, parameters['grid'])
model_file = os.path.join(modelpath, parameters['model'])
TYPE = parameters['type']
GRID = 'OTIS'
EPSG = 'CATS2008'
#-- open Antarctic Tide Gauge (AntTG) database
with open(os.path.join(filepath, 'AntTG_ocean_height_v1.txt'),
'r') as f:
file_contents = f.read().splitlines()
#-- counts the number of lines in the header
count = 0
HEADER = True
#-- Reading over header text
while HEADER:
#-- check if file line at count starts with matlab comment string
HEADER = file_contents[count].startswith('%')
#-- add 1 to counter
count += 1
#-- rewind 1 line
count -= 1
#-- iterate over number of stations
antarctic_stations = (len(file_contents) - count) // 10
stations = [None] * antarctic_stations
shortname = [None] * antarctic_stations
station_type = [None] * antarctic_stations
station_lon = np.zeros((antarctic_stations))
station_lat = np.zeros((antarctic_stations))
for s in range(antarctic_stations):
i = count + s * 10
stations[s] = file_contents[i + 1].strip()
shortname[s] = file_contents[i + 3].strip()
lat, lon, _, _ = file_contents[i + 4].split()
station_type[s] = file_contents[i + 6].strip()
station_lon[s] = np.float64(lon)
station_lat[s] = np.float64(lat)
#-- calculate daily results for a time period
#-- convert time to days since 1992-01-01T00:00:00
tide_time = np.arange(
pyTMD.time.convert_calendar_dates(2000, 1, 1),
pyTMD.time.convert_calendar_dates(2000, 12, 31) + 1)
#-- serial dates for matlab program (days since 0000-01-01T00:00:00)
SDtime = np.arange(convert_calendar_serial(2000, 1, 1),
convert_calendar_serial(2000, 12, 31) + 1)
#-- presently not converting times to dynamic times for model comparisons
deltat = np.zeros_like(tide_time)
#-- number of days
ndays = len(tide_time)
#-- extract amplitude and phase from tide model
amp, ph, D, c = pyTMD.read_tide_model.extract_tidal_constants(
station_lon,
station_lat,
grid_file,
model_file,
EPSG,
TYPE=TYPE,
METHOD='spline',
GRID=GRID)
#-- calculate complex phase in radians for Euler's
cph = -1j * ph * np.pi / 180.0
#-- will verify differences between model outputs are within tolerance
eps = np.finfo(np.float16).eps
#-- compare daily outputs at each station point
invalid_list = [
'Ablation Lake', 'Amery', 'Bahia Esperanza', 'Beaver Lake',
'Cape Roberts', 'Casey', 'Doake Ice Rumples', 'EE4A', 'EE4B',
'Eklund Islands', 'Gerlache C', 'Groussac', 'Gurrachaga',
'Half Moon Is.', 'Heard Island', 'Hobbs Pool', 'Mawson', 'McMurdo',
'Mikkelsen', 'Palmer', 'Primavera', 'Rutford GL', 'Rutford GPS',
'Rothera', 'Scott Base', 'Seymour Is', 'Terra Nova Bay'
]
#-- remove coastal stations from the list
valid_stations = [
i for i, s in enumerate(shortname) if s not in invalid_list
]
#-- compute validation data from Matlab TMD program using octave
#-- https://github.com/EarthAndSpaceResearch/TMD_Matlab_Toolbox_v2.5
TMDpath = os.path.join(filepath, '..', 'TMD_Matlab_Toolbox', 'TMD')
octave.addpath(octave.genpath(os.path.normpath(TMDpath)))
octave.addpath(filepath)
octave.addpath(modelpath)
#-- turn off octave warnings
octave.warning('off', 'all')
#-- input control file for model
CFname = os.path.join(filepath, 'Model_CATS2008')
assert os.access(CFname, os.F_OK)
#-- run Matlab TMD program with octave
#-- MODE: OB time series
validation, _ = octave.tmd_tide_pred_plus(CFname,
SDtime,
station_lat[valid_stations],
station_lon[valid_stations],
TYPE,
nout=2)
#-- for each valid station
for i, s in enumerate(valid_stations):
#-- calculate constituent oscillation for station
hc = amp[s, None, :] * np.exp(cph[s, None, :])
#-- allocate for out tides at point
tide = np.ma.zeros((ndays))
tide.mask = np.zeros((ndays), dtype=bool)
#-- predict tidal elevations at time and infer minor corrections
tide.mask[:] = np.any(hc.mask)
tide.data[:] = pyTMD.predict_tidal_ts(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=GRID)
minor = pyTMD.infer_minor_corrections(tide_time,
hc,
c,
DELTAT=deltat,
CORRECTIONS=GRID)
tide.data[:] += minor.data[:]
#-- calculate differences between matlab and python version
difference = np.ma.zeros((ndays))
difference.data[:] = tide.data - validation[:, i]
difference.mask = (tide.mask | np.isnan(validation[:, i]))
difference.data[difference.mask] = 0.0
if not np.all(difference.mask):
assert np.all(np.abs(difference) < eps)