def geomerisfactor(self,
dataobj,
lat=None,
lon=None,
inc=None,
wvl=np.pi * 4.):
''' Write pi-factor from Li et al 2012 to a matrix / HDF5 object or a file directly. This is used when the latitude and longitude values are available for each radar pixel. Incidence angle can be a constant or a file name.
Bilinear Interpolation is used.
Args:
* dataobj (str or HDF5 or np.array): Final output. If str, output is written to file.
Kwargs:
* lat (str) : Path to the latitude file (np.float32).
* lon (str) : Path to the longitude file (np.float32).
* inc (str or np.float): Path to incidence angle file in degrees (str) or a constant float.
* wvl (np.float) : Wavelength in meters. Default output results in delay in meters.
.. note::
If dataobj is string, output is written to the file.
If np.array or HDF5 object, it should be of size (ny,nx).'''
assert lat is not None, 'PyAPS: Need a valid latitude file.'
assert lon is not None, 'PyAPS: Need a valid longitude file.'
if isinstance(inc, float) or isinstance(inc, np.float64) or isinstance(
inc, np.float32):
cinc = np.cos(inc * np.pi / 180.)
incFileFlag = False
else:
assert inc is not None, 'PyAPS: Need a valid incidence angle file or constant.'
incFileFlag = True
incin = open(inc, 'rb')
latin = open(lat, 'rb')
lonin = open(lon, 'rb')
minAltp = self.dict['minAltP']
# Compute the two integrals
WonT = self.Vi / self.Ti
WonT2 = WonT / self.Ti
S1 = intg.cumtrapz(WonT, x=self.hgt, axis=-1)
val = 2 * S1[:, -1] - S1[:, -2]
val = val[:, None]
S1 = np.concatenate((S1, val), axis=-1)
del WonT
S2 = intg.cumtrapz(WonT2, x=self.hgt, axis=-1)
val = 2 * S2[:, -1] - S2[:, -2]
val = val[:, None]
S2 = np.concatenate((S2, val), axis=-1)
del WonT2
Tm = S1 / S2
self.Tm = Tm
# Reading in the DEM
if self.verb:
print 'PROGRESS: READING DEM'
fin = open(self.hfile, 'rb')
if self.fmt in ('HGT'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=self.nx * self.ny).reshape(
self.ny, self.nx)
elif self.fmt in ('RMG'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=2 * self.nx * self.ny).reshape(
self.ny, 2 * self.nx)
dem = dem[:, self.nx:]
dem = np.round(dem).astype(np.int)
fin.close()
# check output, and open file if necessary
outFile = isinstance(dataobj, str)
if outFile:
fout = open(dataobj, 'wb')
dout = np.zeros((self.ny, self.nx))
else:
assert ((dataobj.shape[0] == self.ny) &
(dataobj.shape[1]
== self.nx)), 'PyAPS: Not a valid data object.'
dout = dataobj
# Create the 1d interpolator
if self.verb:
print 'PROGRESS: FINE INTERPOLATION OF HEIGHT LEVELS'
intp_1d = si.interp1d(self.hgt, Tm, kind='cubic', axis=1)
# Interpolate the Tm variable every meter
dem[dem < minAltp] = minAltp
minH = dem.min()
maxH = dem.max() + 1
kh = np.arange(minH, maxH)
Tm_1m = intp_1d(kh)
self.alti = kh
# Reshape Tm
Lonu = np.unique(self.lonlist)
Latu = np.unique(self.latlist)
nLon = len(Lonu)
nLat = len(Latu)
Tm_1m = np.reshape(Tm_1m.T, (len(kh), nLat, nLon))
self.Tm_1m = Tm_1m
# build the x array
xarr = np.arange(1., self.nx + 1.)
# Create the cube interpolator for the bilinear method
if self.verb:
print 'PROGRESS: CREATE THE BILINEAR INTERPOLATION FUNCTION'
bilicube = processor.Bilinear2DInterpolator(Lonu,
Latu,
Tm_1m,
cube=True)
# Get the values from the dictionnary
k1 = self.dict['k1']
k2 = self.dict['k2']
k3 = self.dict['k3']
mmO = self.dict['mmO']
mmH = self.dict['mmH']
mma = self.dict['mma']
w = (2 * mmH + mmO) / mma
Rv = self.dict['Rv']
Rho = self.dict['Rho']
# Loop on the lines
if self.verb:
toto = utils.ProgressBar(maxValue=self.ny)
print 'PROGRESS: MAPPING THE DELAY'
for m in xrange(self.ny):
if self.verb:
toto.update(m, every=5)
# Get Latitude and Longitude arrays
lati = np.fromfile(file=latin, dtype=np.float32, count=self.nx)
loni = np.fromfile(file=lonin, dtype=np.float32, count=self.nx)
loni[loni < 0.] += 360.
ii = np.where(np.isnan(lati))
jj = np.where(np.isnan(loni))
xx = np.union1d(ii, jj)
lati[xx] = 0.0
loni[xx] = 0.0
# Get incidence if file provided
if incFileFlag:
incz = np.fromfile(file=incin, dtype=np.float32, count=self.nx)
cinc = np.cos(incz * np.pi / 180.)
# Make the Bilinear interpolation
D = dem[m, :] - minH
val = bilicube(loni, lati, D)
val = 0.000001 * Rho * Rv * (k3 / val + k2 -
w * k1) * np.pi * 4.0 / (cinc * wvl)
val[xx] = np.nan
if outFile:
resy = val.astype(np.float32)
resy.tofile(fout)
else:
dataobj[m, :] = val
if self.verb:
toto.close()
latin.close()
lonin.close()
if incFileFlag:
incin.close()
if outFile:
fout.close()
def merisfactor(self, dataobj, inc=0.0, wvl=np.pi * 4.):
''' Write pi-factor from Li et al 2012 to a matrix / HDF5 object or a file directly. This is used when no lat/lon file is known.
Bilinear Interpolation is used.
Args:
* dataobj (str or HDF5 or np.array): Final output. If str, output is written to file.
Kwargs:
* inc (np.float) : Incidence angle in degrees.
* wvl (np.float) : Wavelength in meters. Default output results in delay in meters.
.. note::
If dataobj is string, output is written to the file.
If np.array or HDF5 object, it should be of size (ny,nx).'''
minAltp = self.dict['minAltP']
# Incidence
cinc = np.cos(inc * np.pi / 180.0)
# Compute the two integrals
WonT = self.Vi / self.Ti
WonT2 = WonT / self.Ti
S1 = intg.cumtrapz(WonT, x=self.hgt, axis=-1)
val = 2 * S1[:, -1] - S1[:, -2]
val = val[:, None]
S1 = np.concatenate((S1, val), axis=-1)
del WonT
S2 = intg.cumtrapz(WonT2, x=self.hgt, axis=-1)
val = 2 * S2[:, -1] - S2[:, -2]
val = val[:, None]
S2 = np.concatenate((S2, val), axis=-1)
del WonT2
Tm = S1 / S2
self.Tm = Tm
# Reading in the DEM
if self.verb:
print 'PROGRESS: READING DEM'
fin = open(self.hfile, 'rb')
if self.fmt in ('HGT'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=self.nx * self.ny).reshape(
self.ny, self.nx)
elif self.fmt in ('RMG'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=2 * self.nx * self.ny).reshape(
self.ny, 2 * self.nx)
dem = dem[:, self.nx:]
dem = np.round(dem).astype(np.int)
fin.close()
# check output, and open file if necessary
outFile = isinstance(dataobj, str)
if outFile:
fout = open(dataobj, 'wb')
dout = np.zeros((self.ny, self.nx))
else:
assert ((dataobj.shape[0] == self.ny) &
(dataobj.shape[1]
== self.nx)), 'PyAPS: Not a valid data object.'
dout = dataobj
# Create the 1d interpolator
if self.verb:
print 'PROGRESS: FINE INTERPOLATION OF HEIGHT LEVELS'
intp_1d = si.interp1d(self.hgt, Tm, kind='cubic', axis=1)
# Interpolate the Tm variable every meter
dem[dem < minAltp] = minAltp
minH = dem.min()
maxH = dem.max() + 1
kh = np.arange(minH, maxH)
Tm_1m = intp_1d(kh)
self.alti = kh
# Reshape Tm
Lonu = np.unique(self.lonlist)
Latu = np.unique(self.latlist)
nLon = len(Lonu)
nLat = len(Latu)
Tm_1m = np.reshape(Tm_1m.T, (len(kh), nLat, nLon))
self.Tm_1m = Tm_1m
# build the x array
xarr = np.arange(1., self.nx + 1.)
# Create the cube interpolator for the bilinear method
if self.verb:
print 'PROGRESS: CREATE THE BILINEAR INTERPOLATION FUNCTION'
bilicube = processor.Bilinear2DInterpolator(Lonu,
Latu,
Tm_1m,
cube=True)
# Get the values from the dictionnary
k1 = self.dict['k1']
k2 = self.dict['k2']
k3 = self.dict['k3']
mmO = self.dict['mmO']
mmH = self.dict['mmH']
mma = self.dict['mma']
w = (2 * mmH + mmO) / mma
Rv = self.dict['Rv']
Rho = self.dict['Rho']
# Loop on the lines
if self.verb:
toto = utils.ProgressBar(maxValue=self.ny)
print 'PROGRESS: MAPPING THE DELAY'
for m in xrange(self.ny):
if self.verb:
toto.update(m, every=5)
# Transfert (range,azimuth) to (lon,lat)
yarr = (m + 1) * np.ones((xarr.shape))
[loni, lati] = utils.rdr2glob(self.nx, self.ny, self.lat, self.lon,
xarr, yarr)
# Make the bilinear interpolation
D = dem[m, :] - minH
val = bilicube(loni, lati, D)
val = 0.000001 * Rho * Rv * (k3 / val + k2 -
w * k1) * np.pi * 4.0 / (cinc * wvl)
if outFile:
resy = val.astype(np.float32)
resy.tofile(fout)
else:
dataobj[m, :] = val
if self.verb:
toto.close()
# Close if outfile
if outFile:
fout.close()
def getdelay(self, dataobj, inc=0.0, wvl=4 * np.pi):
'''Write delay to a matrix / HDF5 object or a file directly. Bilinear interpolation at each elevation level is used.
Args:
* dataobj (str or HDF5 or np.array): Final output. If str, output is written to file.
Kwargs:
* inc (np.float): Incidence angle in degrees. Default is vertical.
* wvl (np.float): Wavelength in meters. Default output results in delay in meters.
.. note::
If dataobj is string, output is written to the file.
If np.array or HDF5 object, it should be of size (ny,nx).'''
minAltp = self.dict['minAltP']
# Reading in the DEM
if self.verb:
print 'PROGRESS: READING DEM'
fin = open(self.hfile, 'rb')
if self.fmt in ('HGT'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=self.nx * self.ny).reshape(
self.ny, self.nx)
elif self.fmt in ('RMG'):
dem = np.fromfile(file=fin,
dtype=self.demtype,
count=2 * self.nx * self.ny).reshape(
self.ny, 2 * self.nx)
dem = dem[:, self.nx:]
dem = np.round(dem).astype(np.int)
fin.close()
# check output, and open file if necessary
outFile = isinstance(dataobj, str)
if outFile:
fout = open(dataobj, 'wb')
dout = np.zeros((self.ny, self.nx))
else:
assert ((dataobj.shape[0] == self.ny) &
(dataobj.shape[1]
== self.nx)), 'PyAPS: Not a valid data object.'
dout = dataobj
# Incidence
cinc = np.cos(inc * np.pi / 180.0)
# Create the 1d interpolator
if self.verb:
print 'PROGRESS: FINE INTERPOLATION OF HEIGHT LEVELS'
intp_1d = si.interp1d(self.hgt, self.Delfn, kind='cubic', axis=-1)
# Interpolate the delay function every meter
dem[dem < minAltp] = minAltp
minH = dem.min()
maxH = dem.max() + 1
kh = np.arange(minH, maxH)
Delfn_1m = intp_1d(kh)
self.Delfn_interp = Delfn_1m.copy()
self.alti = kh
# Reshape Delfn
Lonu = np.unique(self.lonlist)
Latu = np.unique(self.latlist)
nLon = len(Lonu)
nLat = len(Latu)
Delfn_1m = np.reshape(Delfn_1m.T, (len(kh), nLat, nLon))
self.Delfn_1m = Delfn_1m
# build the x array
xarr = np.arange(1., self.nx + 1.)
# Create the cube interpolator for the bilinear method
if self.verb:
print 'PROGRESS: CREATE THE BILINEAR INTERPOLATION FUNCTION'
bilicube = processor.Bilinear2DInterpolator(Lonu,
Latu,
Delfn_1m,
cube=True)
# Loop on the lines
if self.verb:
toto = utils.ProgressBar(maxValue=self.ny)
print 'PROGRESS: MAPPING THE DELAY'
for m in xrange(self.ny):
if self.verb:
toto.update(m, every=5)
# Transfert (range,azimuth) to (lon,lat)
yarr = (m + 1) * np.ones((xarr.shape))
[loni, lati] = utils.rdr2glob(self.nx, self.ny, self.lat, self.lon,
xarr, yarr)
# Make the bilinear interpolation
D = dem[m, :] - minH
val = bilicube(loni, lati, D) * np.pi * 4.0 / (cinc * wvl)
if outFile:
resy = val.astype(np.float32)
resy.tofile(fout)
else:
dataobj[m, :] = val
if self.verb:
toto.close()
# Close if outfile
if outFile:
fout.close()