def test_Bearing(self):
"""Test conversion from bearing to theta and back again"""
for th in self.theta:
bearing = maputils.theta2bearing(th)
result = maputils.bearing2theta(bearing)
if th < 0.0:
self.assertAlmostEqual(th + 2. * pi, result)
else:
self.assertAlmostEqual(th, result)
def test_Bearing(self):
"""Test conversion from bearing to theta and back again"""
for th in self.theta:
bearing = maputils.theta2bearing(th)
result = maputils.bearing2theta(bearing)
if th < 0.0:
self.assertAlmostEqual(th + 2.0 * pi, result)
else:
self.assertAlmostEqual(th, result)
def localWindField(self, i):
"""
Calculate the local wind field at time `i` around the
tropical cyclone.
:type i: int
:param i: the time.
"""
lat = self.track.Latitude[i]
lon = self.track.Longitude[i]
beta = self.track.beta[i]
eP = convert(self.track.EnvPressure[i], 'hPa', 'Pa')
cP = convert(self.track.CentralPressure[i], 'hPa', 'Pa')
rMax = self.track.rMax[i]*1000
vFm = convert(self.track.Speed[i], 'kph', 'mps')
thetaFm = bearing2theta(self.track.Bearing[i] * np.pi/180.)
thetaMax = self.thetaMax
beta = self.track.beta[i]
#FIXME: temporary way to do this
cls = windmodels.profile(self.profileType)
params = windmodels.profileParams(self.profileType)
values = [getattr(self, p) for p in params if hasattr(self, p)]
profile = cls(lat, lon, eP, cP, rMax, beta, *values)
R, theta = self.polarGridAroundEye(i)
P = self.pressureProfile(i, R)
#FIXME: temporary way to do this
cls = windmodels.field(self.windFieldType)
params = windmodels.fieldParams(self.windFieldType)
values = [getattr(self, p) for p in params if hasattr(self, p)]
windfield = cls(profile, *values)
Ux, Vy = windfield.field(R * 1000, theta, vFm, thetaFm, thetaMax)
log.debug("UU: {0}, VV: {1}".format(Ux.max(), Vy.max()))
return (Ux, Vy, P)
def calculateWindField(lon, lat, pEnv, pCentre, rMax, vFm, thetaFm, beta,
profileType='powell', windFieldType='kepert'):
pCentre = metutils.convert(pCentre, 'hPa', 'Pa')
pEnv = metutils.convert(pEnv, 'hPa', 'Pa')
vFm = metutils.convert(vFm, 'kmh', 'mps')
thetaFm = bearing2theta(np.pi * thetaFm / 180.)
thetaMax = 70.
rmax = metutils.convert(rMax, 'km', 'm')
cls = windmodels.profile(profileType)
if profileType=="holland":
profile = cls(lat, lon, pEnv, pCentre, rmax, beta)
else:
profile = cls(lat, lon, pEnv, pCentre, rmax)
R, theta = polarGridAroundEye(lon, lat, 5.)
gradV = profile.velocity(R*1000)
cls = windmodels.field(windFieldType)
windfield = cls(profile)
Ux, Vy = windfield.field(R*1000, theta, vFm, thetaFm, thetaMax)
surfV = np.sqrt(Ux*Ux+Vy*Vy)*1.268 # Gust conversion factor
return gradV, surfV
log.addHandler(logging.NullHandler())
TRACKFILE_COLS = ('CycloneNumber', 'Datetime', 'TimeElapsed', 'Longitude',
'Latitude', 'Speed', 'Bearing', 'CentralPressure',
'EnvPressure', 'rMax')
TRACKFILE_UNIT = ('', '%Y-%m-%d %H:%M:%S', 'hr', 'degree', 'degree', 'kph', 'degrees',
'hPa', 'hPa', 'km')
TRACKFILE_FMTS = ('i', datetime, 'f', 'f', 'f', 'f', 'f', 'f', 'f', 'f')
TRACKFILE_CNVT = {
0: lambda s: int(float(s.strip() or 0)),
1: lambda s: datetime.strptime(s.strip(), TRACKFILE_UNIT[1]),
5: lambda s: convert(float(s.strip() or 0), TRACKFILE_UNIT[5], 'mps'),
6: lambda s: bearing2theta(float(s.strip() or 0) * np.pi / 180.),
7: lambda s: convert(float(s.strip() or 0), TRACKFILE_UNIT[7], 'hPa'),
8: lambda s: convert(float(s.strip() or 0), TRACKFILE_UNIT[8], 'hPa'),
}
def readTrackData(trackfile):
"""
Read a track .csv file into a numpy.ndarray.
The track format and converters are specified with the global variables
TRACKFILE_COLS -- The column names
TRACKFILE_FMTS -- The entry formats
TRACKFILE_CNVT -- The column converters
:param str trackfile: the track data filename.
# Define format for TCRM output track files:
ISO_FORMAT = "%Y-%m-%d %H:%M:%S"
TCRM_COLS = ('CycloneNumber', 'Datetime', 'TimeElapsed', 'Longitude',
'Latitude', 'Speed', 'Bearing', 'CentralPressure', 'EnvPressure',
'rMax')
TCRM_UNIT = ('', '', 'hr', 'degree', 'degree', 'kph', 'degrees', 'hPa', 'hPa',
'km')
TCRM_FMTS = ('i', 'object', 'f', 'f8', 'f8', 'f8', 'f8', 'f8', 'f8', 'f8')
TCRM_CNVT = {
0: lambda s: int(float(s.strip() or 0)),
1: lambda s: datetime.strptime(s.strip(), ISO_FORMAT),
5: lambda s: convert(float(s.strip() or 0), TCRM_UNIT[5], 'mps'),
6: lambda s: bearing2theta(float(s.strip() or 0) * np.pi / 180.),
7: lambda s: convert(float(s.strip() or 0), TCRM_UNIT[7], 'Pa'),
8: lambda s: convert(float(s.strip() or 0), TCRM_UNIT[8], 'Pa'),
}
TRACK_DT_ERR = "Track data does not have required \
attributes to convert to datetime object"
TRACK_EMPTY_GROUP = """No track groups in this netcdf file: {0}"""
def ncReadTrackData(trackfile):
"""
Read a netcdf-format track file into a collection of
:class:`Track` objects. The returned :class:`Track` objects *must*
have all attributes accessed by the `__getattr__` method.