def _test_swan(self, testfile):
print("Reading %s" % testfile)
self.s = read_swan(testfile)
fileout = os.path.join(TMP_DIR, 'test.spec')
print("Writing %s" % fileout)
self.s.spec.to_swan(fileout)
print("Verifying %s" % fileout)
tmpspec = read_swan(fileout)
check_equal(self.s, tmpspec)
def test_swan(self):
for testfile in SWAN_TEST_FILES:
print("Reading %s" % testfile)
self.s = read_swan(testfile)
fileout = os.path.join(TMP_DIR,
os.path.basename(testfile) + '.json')
print("Writing %s" % fileout)
self.s.spec.to_json(fileout)
y = _infer_interval_breaks(y, check_monotonic=True)
else:
# we have to infer the intervals on both axes
y = _infer_interval_breaks(y, axis=1)
y = _infer_interval_breaks(y, axis=0)
primitive = ax.pcolormesh(x, y, z, **kwargs)
# by default, pcolormesh picks "round" values for bounds
# this results in ugly looking plots with lots of surrounding whitespace
if not hasattr(ax, "projection") and x.ndim == 1 and y.ndim == 1:
# not a cartopy geoaxis
ax.set_xlim(x[0], x[-1])
ax.set_ylim(y[0], y[-1])
if clean_radius:
ax.set_rticks([])
if clean_sector:
ax.set_xticks([])
return primitive
if __name__ == "__main__":
import matplotlib.pyplot as plt
from wavespectra import read_swan
dset = read_swan("../tests/sample_files/swanfile.spec", as_site=True)
dset.isel(site=0).efth.spec.plot(col="time", col_wrap=3)
plt.show()
"""
Spectrum as contourf
====================
Contourf type plot of wave spectrum
"""
import matplotlib.pyplot as plt
from wavespectra import read_swan
dset = read_swan("../_static/swanfile.spec", as_site=True)
ds = dset.isel(site=0, time=0)
fig = plt.figure(figsize=(6, 4))
p = ds.spec.plot.contourf()
def setup_class(self):
"""Read test spectra from file."""
here = os.path.dirname(os.path.abspath(__file__))
self.swanspec = read_swan(os.path.join(FILES_DIR, 'swanfile.spec'))
def test_swan_files(self):
for swanfile in SWAN_TEST_FILES:
print("Reading %s" % swanfile)
self.s = read_swan(swanfile)
self._test_netcdf(swanfile)
def setup_class(self):
"""Read test spectra and pre-calculated stats from file."""
self.control = pd.read_csv(os.path.join(FILES_DIR, "swanfile.txt"),
sep="\t")
self.swanspec = read_swan(os.path.join(FILES_DIR, "swanfile.spec"))
def setup_class(self):
"""Read test spectra and pre-calculated stats from file."""
self.swanspec = read_swan(os.path.join(FILES_DIR, "swanfile.spec"))
self.wshed = self.swanspec.spec.partition(self.swanspec.wspd,
self.swanspec.wdir,
self.swanspec.dpt)
def dset():
filename = os.path.join(FILES_DIR, "swanfile.spec")
_dset = read_swan(filename)
yield _dset
def load_specdataset():
"""Load SpecDset but skip test if matplotlib is not installed."""
pytest.importorskip("matplotlib")
dset = read_swan(os.path.join(FILES_DIR, "swanfile.spec"), as_site=True)
return dset