def to_swan(
self,
filename,
append=False,
id="Created by wavespectra",
unique_times=False,
dircap_270=False,
):
"""Write spectra in SWAN ASCII format.
Args:
- filename (str): str, name for output SWAN ASCII file.
- append (bool): if True append to existing filename.
- id (str): used for header in output file.
- unique_times (bool): if True, only last time is taken from
duplicate indices.
- dircap_270 (bool): if True, ensure directions do not exceed 270 degrees
as requerid for swan to prescribe boundaries.
Note:
- Only datasets with lat/lon coordinates are currently supported.
- Extra dimensions other than time, site, lon, lat, freq, dim not yet
supported.
- Only 2D spectra E(f,d) are currently supported.
"""
# If grid reshape into site, otherwise ensure there is site dim to iterate over
dset = self._check_and_stack_dims()
# When prescribing bnds, SWAN doesn't like dir>270
if dircap_270:
direc = dset[attrs.DIRNAME].values
direc[direc > 270] = direc[direc > 270] - 360
dset = dset.update({attrs.DIRNAME: direc}).sortby("dir", ascending=False)
darray = dset[attrs.SPECNAME]
is_time = attrs.TIMENAME in darray.dims
# Instantiate swan object
try:
x = dset.lon.values
y = dset.lat.values
except NotImplementedError(
"lon/lat not found in dset, cannot dump SWAN file without locations"
):
raise
sfile = SwanSpecFile(
filename,
freqs=darray.freq,
dirs=darray.dir,
time=is_time,
x=x,
y=y,
append=append,
id=id,
)
# Dump each timestep
if is_time:
for t in darray.time:
darrout = darray.sel(time=t, method="nearest")
if darrout.time.size == 1:
sfile.write_spectra(
darrout.transpose(
attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME
).values,
time=to_datetime(t.values),
)
elif unique_times:
sfile.write_spectra(
darrout.isel(time=-1)
.transpose(attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME)
.values,
time=to_datetime(t.values),
)
else:
for it, tt in enumerate(darrout.time):
sfile.write_spectra(
darrout.isel(time=it)
.transpose(attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME)
.values,
time=to_datetime(t.values),
)
else:
sfile.write_spectra(
darray.transpose(attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME).values
)
sfile.close()
def to_octopus(self, filename, site_id="spec", fcut=0.125, missing_val=-99999):
"""Save spectra in Octopus format.
Args:
- filename (str): name for output OCTOPUS file.
- site_id (str): used to construct LPoint header.
- fcut (float): frequency for splitting spectra.
- missing_value (int): missing value in output file.
Note:
- dataset needs to have lon/lat/time coordinates.
- dataset with multiple locations dumped at same file with one location
header per site.
- 1D spectra not supported.
"""
assert attrs.TIMENAME in self.dims, "Octopus output requires time dimension"
# If grid reshape into site, otherwise ensure there is site dim to iterate over
dset = self._check_and_stack_dims()
fmt = ",".join(len(self.freq) * ["{:6.5f}"]) + ","
if len(dset.time) > 1:
dt = (
to_datetime(dset.time[1]) - to_datetime(dset.time[0])
).total_seconds() / 3600.0
else:
dt = 0.0
# Open output file
with open(filename, "w") as f:
# Looping over each site
for isite in range(len(dset.site)):
dsite = dset.isel(site=[isite])
# Site coordinates
try:
lat = float(dsite.lat)
lon = float(dsite.lon)
except NotImplementedError(
"lon/lat not found in dset, cannot dump OCTOPUS file without locations"
):
raise
# Update dataset with parameters
stats = ["hs", "tm01", "dm"]
dsite = (
xr.merge(
[
dsite,
dsite.spec.stats(stats + ["dpm", "dspr"]),
dsite.spec.stats(
stats, names=[s + "_swell" for s in stats], fmax=fcut
),
dsite.spec.stats(
stats, names=[s + "_sea" for s in stats], fmin=fcut
),
dsite.spec.momf(mom=1).sum(dim="dir").rename("momf1"),
dsite.spec.momf(mom=2).sum(dim="dir").rename("momf2"),
dsite.spec.momd(mom=0)[0].rename("momd"),
dsite.spec.to_energy(),
(dsite.efth.spec.dfarr * dsite.spec.momd(mom=0)[0]).rename(
"fSpec"
),
]
)
.sortby("dir")
.fillna(missing_val)
)
if attrs.WDIRNAME not in dsite:
dsite[attrs.WDIRNAME] = 0 * dsite["hs"] + missing_val
if attrs.WSPDNAME not in dsite:
dsite[attrs.WSPDNAME] = 0 * dsite["hs"] + missing_val
if attrs.DEPNAME not in dsite:
dsite[attrs.DEPNAME] = 0 * dsite["hs"] + missing_val
# General header
f.write(
"Forecast valid for {:%d-%b-%Y %H:%M:%S}\n".format(
to_datetime(dsite.time[0])
)
)
f.write("nfreqs,{:d}\n".format(len(dsite.freq)))
f.write("ndir,{:d}\n".format(len(dsite.dir)))
f.write("nrecs,{:d}\n".format(len(dsite.time)))
f.write("Latitude,{:0.6f}\n".format(lat))
f.write("Longitude,{:0.6f}\n".format(lon))
f.write(
"Depth,{:0.2f}\n\n".format(float(dsite[attrs.DEPNAME].isel(time=0)))
)
# Dump each timestep
for i, t in enumerate(dsite.time):
ds = dsite.isel(time=i)
# Timestamp header
lp = "{}_{:%Y%m%d_%Hz}".format(site_id, to_datetime(t))
f.write(
"CCYYMM,DDHHmm,LPoint,WD,WS,ETot,TZ,VMD,ETotSe,TZSe,VMDSe,ETotSw,"
"TZSw,VMDSw,Mo1,Mo2,HSig,DomDr,AngSpr,Tau\n"
)
# Header and parameters
f.write(
"{:%Y%m,'%d%H%M},{},{:d},{:.2f},{:.4f},{:.2f},{:.1f},{:.4f},"
"{:.2f},{:.1f},{:.4f},{:.2f},{:.1f},{:.5f},{:.5f},{:.4f},{:d},"
"{:d},{:d}\n".format(
to_datetime(t),
lp,
int(ds[attrs.WDIRNAME]),
float(ds[attrs.WSPDNAME]),
0.25 * float(ds["hs"]) ** 2,
float(ds["tm01"]),
float(ds["dm"]),
0.25 * float(ds["hs_sea"]) ** 2,
float(ds["tm01_sea"]),
float(ds["dm_sea"]),
0.25 * float(ds["hs_swell"]) ** 2,
float(ds["tm01_swell"]),
float(ds["dm_swell"]),
float(ds["momf1"]),
float(ds["momf2"]),
float(ds["hs"]),
int(ds["dpm"]),
int(ds["dspr"]),
int(i * dt),
)
)
# Spectra
energy = ds["energy"].squeeze().T.values
specdump = ""
for idir, direc in enumerate(self.dir):
row = energy[idir]
specdump += "{:d},".format(int(direc))
specdump += fmt.format(*row)
specdump += "{:6.5f},\n".format(row.sum())
f.write(("freq," + fmt + "anspec\n").format(*ds.freq.values))
f.write(specdump)
f.write(("fSpec," + fmt + "\n").format(*ds["fSpec"].squeeze().values))
f.write(("den," + fmt + "\n\n").format(*ds["momd"].squeeze().values))
def to_swan(self,
filename,
append=False,
id='Created by wavespectra',
unique_times=False):
"""Write spectra in SWAN ASCII format.
Args:
- filename (str): str, name for output SWAN ASCII file.
- append (bool): if True append to existing filename.
- id (str): used for header in output file.
- unique_times (bool): if True, only last time is taken from
duplicate indices.
Note:
- Only datasets with lat/lon coordinates are currently supported.
- Extra dimensions other than time, site, lon, lat, freq, dim not yet
supported.
- Only 2D spectra E(f,d) are currently supported.
"""
# If grid reshape into site, otherwise ensure there is site dim to iterate over
dset = self._check_and_stack_dims()
darray = dset[attrs.SPECNAME]
is_time = attrs.TIMENAME in darray.dims
# Instantiate swan object
try:
x = dset.lon.values
y = dset.lat.values
except NotImplementedError(
'lon/lat not found in dset, cannot dump SWAN file without locations'
):
raise
sfile = SwanSpecFile(filename,
freqs=darray.freq,
dirs=darray.dir,
time=is_time,
x=x,
y=y,
append=append,
id=id)
# Dump each timestep
if is_time:
for t in darray.time:
darrout = darray.sel(time=t, method='nearest')
if darrout.time.size == 1:
sfile.write_spectra(darrout.transpose(attrs.SITENAME,
attrs.FREQNAME,
attrs.DIRNAME).values,
time=to_datetime(t.values))
elif unique_times:
sfile.write_spectra(darrout.isel(time=-1).transpose(
attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME).values,
time=to_datetime(t.values))
else:
for it, tt in enumerate(darrout.time):
sfile.write_spectra(darrout.isel(time=it).transpose(
attrs.SITENAME, attrs.FREQNAME, attrs.DIRNAME).values,
time=to_datetime(t.values))
else:
sfile.write_spectra(
darray.transpose(attrs.SITENAME, attrs.FREQNAME,
attrs.DIRNAME).values)
sfile.close()