def test_zarr(self):
"""Check reading of zarr dataset in ww3 format."""
filename = os.path.join(FILES_DIR, "ww3file.zarr")
dset = read_ww3(filename, file_format="zarr")
outfile = os.path.join(self.tmp_dir, "tmp.nc")
dset.spec.to_netcdf(outfile)
dset2 = read_netcdf(outfile)
dset.equals(dset2)
def test_ww3(self):
for testfile in WW3_TEST_FILES:
print("Reading %s" % testfile)
self.s = read_ww3(testfile)
fileout = os.path.join(
TMP_DIR,
os.path.basename(testfile).replace('.nc', '.oct'))
print("Writing %s" % fileout)
SpecDataset(self.s.isel(site=0)).to_octopus(fileout)
def test_ww3(self):
for testfile in WW3_TEST_FILES:
print("Reading %s" % testfile)
self.s = read_ww3(testfile)
fileout = os.path.join(
TMP_DIR,
os.path.basename(testfile).replace('.nc', '.json'))
print("Writing %s" % fileout)
self.s.spec.to_json(fileout)
def setup_class(self):
"""Read test spectra from file."""
self.dset = read_ww3(os.path.join(FILES_DIR, "ww3file.nc"))
# First two sites are exact matches, third site is in between
self.lons = [92.00, 92.10, 92.05]
self.lats = [19.80, 19.95, 19.88]
self.lons_exact = self.lons[:2]
self.lats_exact = self.lats[:2]
self.lons_inexact = self.lons[-1:]
self.lats_inexact = self.lats[-1:]
"""
Watershed parameters
====================
Partition spectra and plot parameters
"""
import matplotlib.pyplot as plt
from wavespectra import read_ww3
dset = read_ww3("../_static/ww3file.nc")
dspart = dset.spec.partition(dset.wspd, dset.wdir, dset.dpt)
pstats = dspart.spec.stats(["hs", "tp", "dpm"])
fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(8, 8))
# Hs
p1 = dset.spec.hs().isel(site=0).plot(ax=ax1, label="Full spectrum", marker="o")
p2 = pstats.hs.isel(part=0, site=0).plot(ax=ax1, label="Partition 0 (sea)", marker="o")
p3 = pstats.hs.isel(part=1, site=0).plot(
ax=ax1, label="Partition 1 (swell 1)", marker="o"
)
p4 = pstats.hs.isel(part=2, site=0).plot(
ax=ax1, label="Partition 2 (swell 2)", marker="o"
)
p5 = pstats.hs.isel(part=3, site=0).plot(
ax=ax1, label="Partition 3 (swell 3)", marker="o"
)
ax1.set_ylabel("$Hs$ (m)")
def setup_class(self):
"""Read test spectra from file."""
self.dset = read_ww3(os.path.join(FILES_DIR, "ww3file.nc"))
if method is None:
kwargs.update({"exact": True})
# Providing station coordinates is a lot more efficient for chunked datasets
if dset_lons is None:
dset_lons = self.dset[attrs.LONNAME].values
if dset_lats is None:
dset_lats = self.dset[attrs.LATNAME].values
dsout = func(
dset=self.dset,
lons=lons,
lats=lats,
tolerance=tolerance,
dset_lons=dset_lons,
dset_lats=dset_lats,
**kwargs
)
return dsout
if __name__ == "__main__":
from wavespectra import read_ww3
here = os.path.dirname(os.path.abspath(__file__))
# filename = os.path.join(here, "../tests/sample_files/swanfile.spec")
filename = os.path.join(here, "../tests/sample_files/spec20170101T00_spec.nc")
dset = read_ww3(filename)
lons = [283.5, 284, 284.4974365234375]
lats = [-53.500091552734375, -53.500091552734375, -53.500091552734375]
ds = dset.spec.sel(lons, lats, method="nearest", tolerance=2.0)
def dset2():
_ds = read_ww3(str(FILES_DIR / 'ww3file.nc'))
yield _ds
Copied as a function so it can be used in a generic context.
Args:
- spec (ndarray): wave spectrum array
- freqs (darray): wave frequency array
- dirs (darray): wave direction array
- tail (bool): if True fit high-frequency tail before integrating spectra
"""
df = abs(freqs[1:] - freqs[:-1])
if len(dirs) > 1:
ddir = abs(dirs[1] - dirs[0])
E = ddir * spec.sum(1)
else:
E = np.squeeze(spec)
Etot = 0.5 * sum(df * (E[1:] + E[:-1]))
if tail and freqs[-1] > 0.333:
Etot += 0.25 * E[-1] * freqs[-1]
return 4.0 * np.sqrt(Etot)
if __name__ == "__main__":
from wavespectra import read_ww3
dset = read_ww3("/wave/socean/spec20120101T00_spec.nc",
chunks={"station": 1})
ds = dset.isel(site=2000)
ret = dset.spec.dspr()
# part = ds.spec.partition(ds.wspd, ds.wdir, ds.dpt)
# print(part.isel(time=0).spec.hs().values)