def oceanmodel2ic(self,ncfile,\
convert2utm=True,setUV=False,seth=False,zmax=6000.,name='HYCOM'):
"""
Interpolate data from a downloaded netcdf file to the initial condition
"""
print 'Loading initial condition data from ocean model netcdf file:\n\t%s...'%ncfile
dt = timedelta(days=0.5)
trange = [self.time - dt, self.time + 3*dt]
# Get the temperature data and coordinate data
temp, nc = get_metocean_local(ncfile,'temp',name=name, trange=trange)
# Convert to utm
if nc.X.ndim==1:
X, Y = np.meshgrid(nc.X, nc.Y)
else:
X, Y = nc.X, nc.Y
ll = np.vstack([X.ravel(),Y.ravel()]).T
if convert2utm:
xy = ll2utm(ll,self.utmzone,north=self.isnorth)
else:
xy = ll
# Construct a 3D mask
mask3d = temp.mask
mask3d = mask3d[0,...]
mask3d = mask3d.reshape((nc.nz,xy.shape[0]))
# Ensure that the bottom cell of the ocean model is deeper than the suntans grid
nc.Z[-1] = zmax
# Construct the 4D interp class
F4d =\
Interp4D(xy[:,0],xy[:,1],nc.Z, nc.localtime,\
self.xv,self.yv,self.z_r,self.time,mask=mask3d,**self.interpdict)
tempnew = F4d(temp)
self.T[:] = tempnew
salt, nc = get_metocean_local(ncfile,'salt', name=name, trange=trange)
saltnew = F4d(salt)
self.S[:] = saltnew
if seth:
# Construct the 3D interp class for surface height
ssh, nc = get_metocean_local(ncfile,'ssh', name=name, trange=trange)
mask2d = ssh.mask
mask2d = mask2d[0,...].ravel()
F3d = Interp4D(xy[:,0],xy[:,1],None,nc.time,\
self.xv,self.yv,None,self.time,mask=mask2d,**self.interpdict)
sshnew = F3d(ssh)
self.h[:] = sshnew
def oceanmodel2bdy(self,ncfile,\
convert2utm=True,setUV=True,seth=True, zmax=6000., name='HYCOM'):
"""
Interpolate data from a downloaded netcdf file to the open boundaries
"""
print 'Loading boundary data from ocean model netcdf file:\n\t%s...'%ncfile
dt = timedelta(days=0.5)
trange = [self.time[0] - dt, self.time[-1] + dt]
# Load the temperature salinity data and coordinate data
temp, nc = get_metocean_local(ncfile,'temp', name=name, trange=trange)
salt, nc = get_metocean_local(ncfile,'salt', name=name, trange=trange)
if nc.X.ndim==1:
X, Y = np.meshgrid(nc.X, nc.Y)
else:
X, Y = nc.X, nc.Y
# Convert to utm
ll = np.vstack([X.ravel(),Y.ravel()]).T
if convert2utm:
xy = ll2utm(ll,self.utmzone,north=self.isnorth)
else:
xy = ll
# Construct a 3D mask
mask3d = temp.mask
mask3d = mask3d[0,...]
mask3d = mask3d.reshape((nc.nz,xy.shape[0]))
# Ensure that the bottom cell of the ocean model is deeper than the suntans grid
nc.Z[-1] = zmax
# Type 3 cells
if self.N3>0:
# Construct the 4D interp class
F4d =\
Interp4D(xy[:,0],xy[:,1],nc.Z,nc.localtime,\
self.xv,self.yv,self.z,self.time,mask=mask3d,**self.interpdict)
tempnew = F4d(temp)
self.T[:] = tempnew
saltnew = F4d(salt)
self.S[:] = saltnew
# Never do this for type-3
#if setUV:
# unew = F4d(u)
# self.u[:] += unew
# vnew = F4d(v)
# self.v[:] += vnew
if seth:
# Construct the 3D interp class for surface height
ssh, nc2d = get_metocean_local(ncfile,'ssh', name=name, trange=trange)
mask2d = ssh.mask
mask2d = mask2d[0,...].ravel()
F3d = Interp4D(xy[:,0],xy[:,1],None,nc2d.localtime,\
self.xv,self.yv,None,self.time,mask=mask2d,**self.interpdict)
sshnew = F3d(ssh)
self.h[:] += sshnew
# Type 2 cells : no free-surface
if self.N2>0:
# Construct the 4D interp class
F4d =\
Interp4D(xy[:,0], xy[:,1], nc.Z, nc.localtime,\
self.xe,self.ye,self.z,self.time,mask=mask3d,**self.interpdict)
tempnew = F4d(temp)
self.boundary_T[:] = tempnew
del temp
saltnew = F4d(salt)
self.boundary_S[:] = saltnew
del salt
if setUV:
u, nc = get_metocean_local(ncfile,'u', name=name, trange=trange)
unew = F4d(u)
self.boundary_u[:] += unew
del u
v, nc = get_metocean_local(ncfile,'v', name=name, trange=trange)
vnew = F4d(v)
self.boundary_v[:] += vnew
del v
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
# Check if the input file is not a list
T = type(self.infile)
if T != list:
self.multifile = False
# Parse the data file into two vectors
print "Reading data from: %s..." % self.infile
if self.infile[-3:] == ".gz":
LL, self.Zin = read_xyz_gz(self.infile)
elif self.infile[-3:] == "txt":
LL, self.Zin = read_xyz(self.infile)
elif self.infile[-3:] == "shp":
LL, self.Zin = readShpBathy(self.infile)
elif self.infile[-3:] == "dem":
LL, self.Zin = readDEM(self.infile, True)
elif self.infile[-3:] == ".nc":
self.loadnc(fv=2)
LL = self._returnXY()
self.Zin = np.ravel(self.Zin)
elif self.infile[-3:] in [".h5", "hdf"]:
LL, self.Zin = self.load_hdf(self.infile, self.h5groups)
# rescale the data
self.Zin = self.scale * self.Zin
# Convert the coordinates
self.npt = len(self.Zin)
if self.convert2utm:
if self.bbox == None:
# Work out the domain limits from the input file
self.bbox = [LL[:, 0].min(), LL[:, 0].max(), LL[:, 1].min(), LL[:, 1].max()]
# else:
# # Clip the points outside of the domain
# print 'Clipping points outside of the bounding box...'
# LL=self.clipPoints(LL)
# Convert the coordinates
print "Transforming the coordinates to UTM..."
self.XY = ll2utm(LL, self.utmzone, self.CS, self.isnorth)
else:
self.XY = LL
else: # Multiple files
self.multifile = True
# Print out some details before processing
print 72 * "#"
print "Grid bounds: "
print "\tX: ", self.bbox[0:2]
print "\tY: ", self.bbox[2:4]
print "Data bounds:"
print "X min = %f, X max = %f" % (self.XY[:, 0].min(), self.XY[:, 0].max())
print "Y min = %f, Y max = %f" % (self.XY[:, 1].min(), self.XY[:, 1].max())
print 72 * "#"
# Create the grid object
self.grd = Grid(
self.bbox,
self.dx,
self.dx,
utmzone=self.utmzone,
CS=self.CS,
isnorth=self.isnorth,
convert2utm=self.convert2utm,
)
def build(self):
tic = time.clock()
if self.multifile == False:
if self.interptype == "nn":
print "Building DEM with Nearest Neighbour interpolation..."
self.nearestNeighbour()
elif self.interptype == "blockavg":
print "Building DEM with Block Averaging..."
self.blockAvg()
elif self.interptype == "idw":
print "Building DEM with Inverse Distance Weighted Interpolation..."
self.invdistweight()
elif self.interptype == "kriging":
print "Building DEM with Kriging Interpolation..."
self.krig()
elif self.interptype == "griddata":
print "Building DEM using griddata..."
self.griddata()
elif self.interptype == "curvmin":
print "Building DEM using curvmin..."
self.curvmin()
else:
print "Error - Unknown interpolation type: %s." % self.interptype
else: # Multiple file interpolation
print 'Multiple input files detected - setting "interptype" to "blockavg".'
self.interptype = "blockavg"
self.Z = np.zeros((self.grd.ny, self.grd.nx))
self.N = np.zeros((self.grd.ny, self.grd.nx))
ctr = 0
for f in self.infile:
ctr += 1
# Read in the array
print "Reading data file (%d of %d): %s..." % (ctr, len(self.infile), f)
if f[-3:] == ".gz":
LL, self.Zin = read_xyz_gz(f)
if f[-3:] == "txt":
LL, self.Zin = read_xyz(f)
elif f[-3:] == "shp":
LL, self.Zin = readShpBathy(f)
elif f[-3:] == "dem":
LL, self.Zin = readDEM(f, True)
self.npt = len(self.Zin)
if self.convert2utm:
# Clip the points outside of the domain
# print 'Clipping points outside of the bounding box...'
# LL=self.clipPoints(LL)
# Convert the coordinates
print "Transforming the coordinates to UTM..."
self.XY = ll2utm(LL, self.utmzone, self.CS, self.isnorth)
else:
self.XY = LL
del LL
# Interpolate
print "Building DEM with Block Averaging..."
self.blockAvgMulti()
# Memory cleanup
del self.XY
del self.Zin
# Compute the block average for all of the files
self.Z = np.divide(self.Z, self.N)
toc = time.clock()
print "Elapsed time %10.3f seconds." % (toc - tic)
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
# Check if the input file is not a list
T = type(self.infile)
if T != list:
self.multifile = False
# Parse the data file into two vectors
print('Reading data from: %s...' % self.infile)
if self.infile[-3:] == '.gz':
LL, self.Zin = read_xyz_gz(self.infile)
elif self.infile[-3:] == 'txt':
LL, self.Zin = read_xyz(self.infile)
elif self.infile[-3:] == 'shp':
LL, self.Zin = readShpBathy(self.infile)
elif self.infile[-3:] == 'dem':
LL, self.Zin = readDEM(self.infile, True)
elif self.infile[-3:] == '.nc':
self.loadnc(fv=2)
LL = self._returnXY()
self.Zin = np.ravel(self.Zin)
elif self.infile[-3:] in ['.h5', 'hdf']:
LL, self.Zin = self.load_hdf(self.infile, self.h5groups)
# rescale the data
self.Zin = self.scale * self.Zin
# Convert the coordinates
self.npt = len(self.Zin)
if self.convert2utm:
if self.bbox == None:
# Work out the domain limits from the input file
self.bbox = [
LL[:, 0].min(), LL[:, 0].max(), LL[:, 1].min(),
LL[:, 1].max()
]
#else:
# # Clip the points outside of the domain
# print 'Clipping points outside of the bounding box...'
# LL=self.clipPoints(LL)
# Convert the coordinates
print('Transforming the coordinates to UTM...')
self.XY = ll2utm(LL, self.utmzone, self.CS, self.isnorth)
else:
self.XY = LL
else: # Multiple files
self.multifile = True
# Print out some details before processing
print(72 * '#')
print('Grid bounds: ')
print('\tX: ', self.bbox[0:2])
print('\tY: ', self.bbox[2:4])
print('Data bounds:')
print('X min = %f, X max = %f' %
(self.XY[:, 0].min(), self.XY[:, 0].max()))
print('Y min = %f, Y max = %f' %
(self.XY[:, 1].min(), self.XY[:, 1].max()))
print(72 * '#')
# Create the grid object
self.grd = Grid(self.bbox,self.dx,self.dx,\
utmzone=self.utmzone,\
CS=self.CS,\
isnorth=self.isnorth,
convert2utm= self.convert2utm)
def build(self):
tic = time.clock()
if self.multifile == False:
if self.interptype == 'nn':
print('Building DEM with Nearest Neighbour interpolation...')
self.nearestNeighbour()
elif self.interptype == 'blockavg':
print('Building DEM with Block Averaging...')
self.blockAvg()
elif self.interptype == 'idw':
print(
'Building DEM with Inverse Distance Weighted Interpolation...'
)
self.invdistweight()
elif self.interptype == 'kriging':
print('Building DEM with Kriging Interpolation...')
self.krig()
elif self.interptype == 'griddata':
print('Building DEM using griddata...')
self.griddata()
elif self.interptype == 'curvmin':
print('Building DEM using curvmin...')
self.curvmin()
else:
print('Error - Unknown interpolation type: %s.' %
self.interptype)
else: # Multiple file interpolation
print(
'Multiple input files detected - setting "interptype" to "blockavg".'
)
self.interptype = 'blockavg'
self.Z = np.zeros((self.grd.ny, self.grd.nx))
self.N = np.zeros((self.grd.ny, self.grd.nx))
ctr = 0
for f in self.infile:
ctr += 1
# Read in the array
print('Reading data file (%d of %d): %s...' %
(ctr, len(self.infile), f))
if f[-3:] == '.gz':
LL, self.Zin = read_xyz_gz(f)
if f[-3:] == 'txt':
LL, self.Zin = read_xyz(f)
elif f[-3:] == 'shp':
LL, self.Zin = readShpBathy(f)
elif f[-3:] == 'dem':
LL, self.Zin = readDEM(f, True)
self.npt = len(self.Zin)
if self.convert2utm:
# Clip the points outside of the domain
#print 'Clipping points outside of the bounding box...'
#LL=self.clipPoints(LL)
# Convert the coordinates
print('Transforming the coordinates to UTM...')
self.XY = ll2utm(LL, self.utmzone, self.CS, self.isnorth)
else:
self.XY = LL
del LL
# Interpolate
print('Building DEM with Block Averaging...')
self.blockAvgMulti()
# Memory cleanup
del self.XY
del self.Zin
# Compute the block average for all of the files
self.Z = np.divide(self.Z, self.N)
toc = time.clock()
print('Elapsed time %10.3f seconds.' % (toc - tic))
