def fill(self,data,tind='next',quiet=1):
'''
Fills model netcdf climatology file (data can be provided by
prognostic.data2roms
'''
nc=netcdf.Pync(self.filename,'w')
if tind=='next': tind=nc.dims['time']
if not quiet: print('filling clm file %s' % self.filename)
# about time:
try:
date=dts.parse_date(data['date'])
time=netcdf.date2num(date,self.tunits)
except:
time=data['date'] # date as number!
for i in nc.varnames:
if i.endswith('time'):
if not quiet: print(' -- %s tind=%d %f' % (i,tind,time))
nc.vars[i][tind]=time
names='temp','salt','u','v','ubar','vbar','zeta'
for i in names:
if not quiet: print(' %s' % i)
nc.vars[i][tind,...]=data[i]
nc.close()
def fill(self, data, tind='next', quiet=1):
'''
Fills model netcdf climatology file (data can be provided by
prognostic.data2roms
'''
nc = netcdf.Pync(self.filename, 'w')
if tind == 'next': tind = nc.dims['time']
if not quiet: print('filling clm file %s' % self.filename)
# about time:
try:
date = dts.parse_date(data['date'])
time = netcdf.date2num(date, self.tunits)
except:
time = data['date'] # date as number!
for i in nc.varnames:
if i.endswith('time'):
if not quiet: print(' -- %s tind=%d %f' % (i, tind, time))
nc.vars[i][tind] = time
names = 'temp', 'salt', 'u', 'v', 'ubar', 'vbar', 'zeta'
for i in names:
if not quiet: print(' %s' % i)
nc.vars[i][tind, ...] = data[i]
nc.close()
def fill_frc(fname, time, u, v):
nc = netcdf.Pync(fname, 'w')
tunits = netcdf.vatt(nc, 'wind_time', 'units')
time = netcdf.date2num(time, tunits)
tind = nc.dims['wind_time']
nc.vars['wind_time'][tind] = time
nc.vars['Uwind_ascat24'][tind, ...] = u
nc.vars['Vwind_ascat24'][tind, ...] = v
nc.close()
def fill_frc(fname,time,u,v): nc=netcdf.Pync(fname,'w') tunits=netcdf.vatt(nc,'wind_time','units') time=netcdf.date2num(time,tunits) tind=nc.dims['wind_time'] nc.vars['wind_time'][tind]=time nc.vars['Uwind_ascat24'][tind,...]=u nc.vars['Vwind_ascat24'][tind,...]=v nc.close()
def __init__(self, filename, grid, sparams, **kargs):
if not 'type' in kargs.keys(): kargs['type'] = 'ROMS Initial file'
if not 'title' in kargs.keys(): kargs['title'] = 'ROMS Initial file'
GenCommon.__init__(self, filename, grid, sparams, **kargs)
self.date = kargs.get('date', 0)
# about time:
try:
self.date = dts.parse_date(self.date)
self.time = netcdf.date2num(self.date, self.tunits)
except:
self.time = self.date # date as number!
def __init__(self,filename,grid,sparams,**kargs):
if not 'type' in kargs.keys(): kargs['type'] = 'ROMS Initial file'
if not 'title' in kargs.keys(): kargs['title'] = 'ROMS Initial file'
GenCommon.__init__(self,filename,grid,sparams,**kargs)
date = 0
if 'date' in kargs.keys(): date = kargs['date']
self.date = date
# about time:
try:
self.date=dts.parse_date(self.date)
self.time=netcdf.date2num(self.date,self.tunits)
except:
self.time=self.date # date as number!
def fill(self, data, quiet=1):
'''
Fills model netcdf river forcing file
The input data shoud have as keys the river names
(with river runoff, temp, salt, vshape, xi,eta and direction)
and time (datetime)
Example:
data['amazonas']=q,temp,salt,vshape,Xi,Eta,Dir
data['time']=np.arange(20)
'''
# convert time to tunits:
time = data['time']
for i in range(len(time)):
time[i] = netcdf.date2num(time[i], self.tunits)
nc = netcdf.Pync(self.fname, 'a')
if not quiet: print ' -- filling time...'
for i in range(len(time)):
nc.vars['river_time'][i] = time[i]
# better sync here:
nc._nc.sync()
cont = -1
for k in data.keys():
if k == 'time': continue
cont += 1
q, temp, salt, vshape, Xi, Eta, Dir = data[k]
if not quiet: print ' -- filling river', cont
nc.vars['river'][cont] = cont
nc.vars['river_Xposition'][cont] = Xi
nc.vars['river_Eposition'][cont] = Eta
nc.vars['river_direction'][cont] = Dir
nc.vars['river_Vshape'][:, cont] = vshape
nc.vars['river_transport'][:, cont] = q
nc.vars['river_temp'][:, :, cont] = temp
nc.vars['river_salt'][:, :, cont] = salt
nc.close()
def fill(self, data, tind='next', quiet=1):
'''
Fills model netcdf boundary conditions (data can be provided by
prognostic.data2romsbry
'''
nc = netcdf.Pync(self.filename, 'w')
if tind == 'next': tind = nc.dims['time']
if not quiet: print('filling bry file %s' % self.filename)
# about time:
try:
date = dts.parse_date(data['date'])
time = netcdf.date2num(date, self.tunits)
except:
time = data['date'] # date as number!
for i in nc.varnames:
if i.endswith('time'):
if not quiet: print(' -- %s tind=%d %f' % (i, tind, time))
nc.vars[i][tind] = time
names = 'temp', 'salt', 'u', 'v', 'ubar', 'vbar', 'zeta'
if self.addxz:
names = list(names) + [
'dist', 'distu', 'distv', 'depth', 'depthu', 'depthv'
]
for i in names:
for j in 'north', 'south', 'east', 'west':
vname = i + '_' + j
if vname in nc.varnames:
if vname.startswith('dist'):
if tind == 0:
if not quiet: print(' %s' % vname)
nc.vars[vname][:] = data[
vname] # not time dependent
else:
if not quiet: print(' %s' % vname)
nc.vars[vname][tind, ...] = data[vname]
nc.close()
def fill(self,data,quiet=1):
'''
Fills model netcdf river forcing file
The input data shoud have as keys the river names
(with river runoff, temp, salt, vshape, xi,eta and direction)
and time (datetime)
Example:
data['amazonas']=q,temp,salt,vshape,Xi,Eta,Dir
data['time']=np.arange(20)
'''
# convert time to tunits:
time=data['time']
for i in range(len(time)): time[i]=netcdf.date2num(time[i],self.tunits)
nc=netcdf.Pync(self.fname,'a')
if not quiet: print(' -- filling time...')
for i in range(len(time)): nc.vars['river_time'][i]=time[i]
# better sync here:
nc._nc.sync()
cont=-1
for k in data.keys():
if k=='time': continue
cont+=1
q,temp,salt,vshape,Xi,Eta,Dir=data[k]
if not quiet: print(' -- filling river',cont)
nc.vars['river'][cont] = cont
nc.vars['river_Xposition'][cont] = Xi
nc.vars['river_Eposition'][cont] = Eta
nc.vars['river_direction'][cont] = Dir
nc.vars['river_Vshape'][:,cont] = vshape
nc.vars['river_transport'][:,cont] = q
nc.vars['river_temp'][:,:,cont] = temp
nc.vars['river_salt'][:,:,cont] = salt
nc.close()
def fill(self,data,tind='next',quiet=1):
'''
Fills model netcdf boundary conditions (data can be provided by
prognostic.data2romsbry
'''
nc=netcdf.Pync(self.filename,'w')
if tind=='next': tind=nc.dims['time']
if not quiet: print('filling bry file %s' % self.filename)
# about time:
try:
date=dts.parse_date(data['date'])
time=netcdf.date2num(date,self.tunits)
except:
time=data['date'] # date as number!
for i in nc.varnames:
if i.endswith('time'):
if not quiet: print(' -- %s tind=%d %f' % (i,tind,time))
nc.vars[i][tind]=time
names='temp','salt','u','v','ubar','vbar','zeta'
if self.addxz:
names=list(names)+['dist','distu','distv','depth','depthu','depthv']
for i in names:
for j in 'north','south','east','west':
vname=i+'_'+j
if vname in nc.varnames:
if vname.startswith('dist'):
if tind==0:
if not quiet: print(' %s' % vname)
nc.vars[vname][:]=data[vname] # not time dependent
else:
if not quiet: print(' %s' % vname)
nc.vars[vname][tind,...]=data[vname]
nc.close()
def fill(self,data,tind='next',quiet=1):
'''
Fills model netcdf bulk forcing file
'''
nc=netcdf.Pync(self.filename,'w')
if tind=='next': tind=nc.dims['time']
if not quiet: print('filling blk file %s' % self.filename)
# about time:
try:
date=dts.parse_date(data['date'])
time=netcdf.date2num(date,self.tunits)
except:
time=data['date'] # date as number!
for i in nc.varnames:
if i.endswith('time'):
if not quiet: print(' -- %s tind=%d %f' % (i,tind,time))
nc.vars[i][tind]=time
if 'Tair' in nc.varnames: # roms
names=('Tair','tair'),('Pair','pres'),('Qair','rhum'),('rain','prate'),\
('swrad','radsw'),('lwrad','radlw'),('Uwind','uwnd'),('Vwind','vwnd'),\
'sustr','svstr','wspd','cloud',('lwrad_down','dlwrf')
if not 'tair' in data.keys(): # assuming data has roms (not agrif) varnames:
names='Tair','Pair','Qair','rain','swrad','lwrad','Uwind','Vwind','sustr','svstr','wspd','cloud','lwrad_down'
elif 'tair' in nc.varnames: # roms-agrif
names='tair','pres','rhum','prate','radlw','radsw','dlwrf','uwnd',\
'vwnd','wspd','sustr','svstr',\
'cloud' # not used, but add it anyway
for i in names:
if isinstance(i,basestring): filev,datav=i,i
else: filev,datav=i
if datav not in data.keys():
if not quiet: print(' Warning: data key %s not present' % datav)
else:
if not quiet: print(' %s (%s) min=%8.3f max=%8.3f' % (filev.ljust(7),datav.ljust(7),
data[datav].min(),data[datav].max()))
nc.vars[filev][tind,...]=data[datav]
# fill original data:
orig=datav+'_original'
if orig in data.keys() and not orig in nc.varnames:
if not quiet: print(' Warning: original data will not be written %s' % orig)
elif not orig in data.keys() and orig in nc.varnames:
if not quiet: print(' Warning: original data not present %s' % orig)
elif orig in data.keys() and orig in nc.varnames:
if not quiet: print(' %s min=%8.3f max=%8.3f' % (orig.ljust(7+9),
data[orig].min(),data[orig].max()))
nc.vars[orig][tind,...]=data[orig]
# fill original x,y:
if tind==0 and 'x_original' in data.keys() and 'x_original' in nc.varnames:
if not quiet: print(' filling x,y original')
nc.vars['x_original'][:]=data['x_original']
nc.vars['y_original'][:]=data['y_original']
nc.close()
def frc2gnome(fname, frc, grd, xylim=False, dates=False, ij=(1, 1), **kargs):
'''
Creates GNOME wind file
kargs:
t[u,v]var
t[u,v]dim
x[y,ang]var
Ex:
.frc2gnome(out,frc,grd,ij=(10,10),dates=dates,**{'tdim':'Time'})
'''
deta, dxi = ij
tvar = 'time'
uvar = 'Uwind'
vvar = 'Vwind'
#tvar='bulk_time'
#uvar='uwnd'
#vvar='vwnd'
tdim = 'time'
#tdim='bulk_time'
xdim = 'xi_rho'
ydim = 'eta_rho'
xvar = 'lon_rho'
yvar = 'lat_rho'
angvar = 'angle'
if 'tvar' in kargs.keys(): tvar = kargs['tvar']
if 'uvar' in kargs.keys(): uvar = kargs['uvar']
if 'vvar' in kargs.keys(): vvar = kargs['vvar']
if 'tdim' in kargs.keys(): tdim = kargs['tdim']
if 'xdim' in kargs.keys(): xdim = kargs['xdim']
if 'ydim' in kargs.keys(): ydim = kargs['ydim']
if 'xvar' in kargs.keys(): xvar = kargs['xvar']
if 'yvar' in kargs.keys(): yvar = kargs['yvar']
if 'angvar' in kargs.keys(): angvar = kargs['angvar']
dims = netcdf.fdim(grd)
xi, eta = dims[xdim], dims[ydim]
xi0, eta0 = xi, eta
ncg = netcdf.ncopen(grd)
nc0 = netcdf.ncopen(frc)
try:
t = netcdf.nctime(nc0, tvar)
except:
t = netcdf.use(nc0, tvar)
t = netcdf.num2date(t, 'days since %d-01-01' % year0)
time = netcdf.date2num(t, tunits)
x0 = netcdf.use(grd, xvar)
y0 = netcdf.use(grd, yvar)
if x0.ndim == 1: x0, y0 = np.meshgrid(x0, y0)
if angvar:
ang = netcdf.use(grd, angvar)
if not xylim is False:
xlim = xylim[:2]
ylim = xylim[2:]
i1, i2, j1, j2 = calc.ij_limits(x0, y0, xlim, ylim)
xi = i2 - i1
eta = j2 - j1
else:
i1, i2 = 0, xi
j1, j2 = 0, eta
XI = '%d:%d:%d' % (i1, i2, dxi)
ETA = '%d:%d:%d' % (j1, j2, deta)
xi = len(range(i1, i2, dxi))
eta = len(range(j1, j2, deta))
# create file:
create_wind(fname, xi, eta)
nc = netcdf.ncopen(fname, 'a')
x = x0[j1:j2:deta, i1:i2:dxi]
y = y0[j1:j2:deta, i1:i2:dxi]
nc.vars['lon'][:] = x
nc.vars['lat'][:] = y
if angvar: ang = ang[j1:j2:deta, i1:i2:dxi]
n = -1
for it in range(len(time)):
if not dates is False:
d0, d1 = dates
if t[it] < d0 or t[it] >= d1: continue
n += 1
u = netcdf.use(nc0, uvar, **{xdim: XI, ydim: ETA, tdim: it})
v = netcdf.use(nc0, vvar, **{xdim: XI, ydim: ETA, tdim: it})
# rotate uv:
if angvar:
print('rotating ...')
u, v = calc.rot2d(u, v, -ang)
nc.vars['time'][n] = time[it]
print('filling uv', n, t[it])
nc.vars['air_u'][n, ...] = u
nc.vars['air_v'][n, ...] = v
nc.close()
nc0.close()
ncg.close()
def his2gnome(fname,
his,
grd=False,
nomask=False,
gshhsMask=True,
xylim=False,
dates=False,
ij=(1, 1)):
'''
Creates GNOME wind file
Ex:
his2gnome(out,his,grd,dates=dates,ij=(2,2))
if gshhsMask, the high res mask file mask_gshhs.npy will be created at 1st usage.
Mask is based on high (h) resolution gshhs data which must be available (env variable
GSHHS_MASK must be set).
'''
if not grd: grd = his
deta, dxi = ij
dims = netcdf.fdim(his)
xi, eta = dims['xi_rho'], dims['eta_rho']
xi0, eta0 = xi, eta
nc0 = netcdf.ncopen(his)
time = netcdf.nctime(nc0, 'ocean_time')
# for roms agrif:
#t=netcdf.use(nc0,'scrum_time')
#time=netcdf.num2date(t,'seconds since %d-01-01' % year0)
x0 = netcdf.use(grd, 'lon_rho')
y0 = netcdf.use(grd, 'lat_rho')
ang = netcdf.use(grd, 'angle')
if not xylim is False:
xlim = xylim[:2]
ylim = xylim[2:]
i1, i2, j1, j2 = calc.ij_limits(x0, y0, xlim, ylim)
print(i1, i2, j1, j2)
xi = i2 - i1
eta = j2 - j1
else:
i1, i2 = 0, xi
j1, j2 = 0, eta
XI = '%d:%d:%d' % (i1, i2, dxi)
ETA = '%d:%d:%d' % (j1, j2, deta)
xi = len(range(i1, i2, dxi))
eta = len(range(j1, j2, deta))
# create file:
create_uv(fname, xi, eta)
nc = netcdf.ncopen(fname, 'a')
for v0, v in ('lon_rho', 'lon'), ('lat_rho', 'lat'), ('mask_rho',
'mask'), ('h',
'depth'):
print('filling %s with %s' % (v, v0))
nc.vars[v][:] = netcdf.use(grd, v0, xi_rho=XI, eta_rho=ETA)
if nomask:
print('NO MASK !!!')
nc.vars['mask'][:] = 1
if gshhsMask:
try:
mask = np.load('mask_gshhs.npy')
except:
mask = 1 + 0 * netcdf.use(nc0, 'mask_rho', xi_rho=XI, eta_rho=ETA)
mask = mask.astype('bool')
x = netcdf.use(grd, 'lon_rho', xi_rho=XI, eta_rho=ETA)
y = netcdf.use(grd, 'lat_rho', xi_rho=XI, eta_rho=ETA)
from okean import gshhs
axis = x.min(), x.max(), y.min(), y.max()
g = gshhs.gshhs(axis,
resolution='h',
area_thresh=0.,
max_level=2,
clip=True)
for lon, lat, level in zip(g.lon, g.lat, g.level):
if level == 1: # land
print('mask ', lon.shape)
i = calc.inpolygon(x, y, lon, lat)
mask = mask & ~i
mask.dump('mask_gshhs.npy')
nc.vars['mask'][:] = mask
x = x0[j1:j2:deta, i1:i2:dxi]
y = y0[j1:j2:deta, i1:i2:dxi]
ang = ang[j1:j2:deta, i1:i2:dxi]
n = -1
for it in range(len(time)):
if not dates is False:
d0, d1 = dates
if time[it] < d0 or time[it] >= d1: continue
n += 1
U = np.zeros((eta0, xi0), 'f')
V = np.zeros((eta0, xi0), 'f')
nc.vars['time'][n] = netcdf.date2num(time[it], tunits)
# for roms agrif:
#u=netcdf.use(nc0,'u',time=it,s_rho=-1)
#v=netcdf.use(nc0,'v',time=it,s_rho=-1)
u = netcdf.use(nc0, 'u', ocean_time=it, s_rho=-1)
v = netcdf.use(nc0, 'v', ocean_time=it, s_rho=-1)
# mask extrap:
print('mask extrap...')
u = calc.mask_extrap(x0, y0, np.ma.masked_where(u == 0, u))
v = calc.mask_extrap(x0, y0, np.ma.masked_where(v == 0, v))
U[:, 1:-1] = 0.5 * (u[:, :-1] + u[:, 1:])
U[:, 0] = u[:, 0]
U[:, -1] = u[:, -1]
V[1:-1, :] = 0.5 * (v[:-1.:] + v[1:, :])
V[0, :] = v[0, :]
V[-1, :] = v[-1, :]
U = U[j1:j2, i1:i2]
V = V[j1:j2, i1:i2]
U = U[j1:j2:deta, i1:i2:dxi]
V = V[j1:j2:deta, i1:i2:dxi]
# rotate uv:
print('rotating ...')
U, V = calc.rot2d(U, V, -ang)
print('filling uv', n, time[it])
nc.vars['u'][n, ...] = U
nc.vars['v'][n, ...] = V
nc.close()
nc0.close()
def fill(self, data, tind='next', quiet=1):
'''
Fills model netcdf bulk forcing file
'''
nc = netcdf.Pync(self.filename, 'w')
if tind == 'next': tind = nc.dims['time']
if not quiet: print('filling blk file %s' % self.filename)
# about time:
try:
date = dts.parse_date(data['date'])
time = netcdf.date2num(date, self.tunits)
except:
time = data['date'] # date as number!
for i in nc.varnames:
if i.endswith('time'):
if not quiet: print(' -- %s tind=%d %f' % (i, tind, time))
nc.vars[i][tind] = time
if 'Tair' in nc.varnames: # roms
names=('Tair','tair'),('Pair','pres'),('Qair','rhum'),('rain','prate'),\
('swrad','radsw'),('lwrad','radlw'),('Uwind','uwnd'),('Vwind','vwnd'),\
'sustr','svstr','wspd','cloud',('lwrad_down','dlwrf')
if not 'tair' in data.keys(
): # assuming data has roms (not agrif) varnames:
names = 'Tair', 'Pair', 'Qair', 'rain', 'swrad', 'lwrad', 'Uwind', 'Vwind', 'sustr', 'svstr', 'wspd', 'cloud', 'lwrad_down'
elif 'tair' in nc.varnames: # roms-agrif
names='tair','pres','rhum','prate','radlw','radsw','dlwrf','uwnd',\
'vwnd','wspd','sustr','svstr',\
'cloud' # not used, but add it anyway
for i in names:
if isinstance(i, basestring): filev, datav = i, i
else: filev, datav = i
if datav not in data.keys():
if not quiet:
print(' Warning: data key %s not present' % datav)
else:
if not quiet:
print(' %s (%s) min=%8.3f max=%8.3f' %
(filev.ljust(7), datav.ljust(7), data[datav].min(),
data[datav].max()))
nc.vars[filev][tind, ...] = data[datav]
# fill original data:
orig = datav + '_original'
if orig in data.keys() and not orig in nc.varnames:
if not quiet:
print(' Warning: original data will not be written %s' %
orig)
elif not orig in data.keys() and orig in nc.varnames:
if not quiet:
print(' Warning: original data not present %s' % orig)
elif orig in data.keys() and orig in nc.varnames:
if not quiet:
print(' %s min=%8.3f max=%8.3f' %
(orig.ljust(7 + 9), data[orig].min(),
data[orig].max()))
nc.vars[orig][tind, ...] = data[orig]
# fill original x,y:
if tind == 0 and 'x_original' in data.keys(
) and 'x_original' in nc.varnames:
if not quiet: print(' filling x,y original')
nc.vars['x_original'][:] = data['x_original']
nc.vars['y_original'][:] = data['y_original']
nc.close()
def frc2gnome(fname,frc,grd,xylim=False,dates=False,ij=(1,1),**kargs):
'''
Creates GNOME wind file
kargs:
t[u,v]var
t[u,v]dim
x[y,ang]var
Ex:
.frc2gnome(out,frc,grd,ij=(10,10),dates=dates,**{'tdim':'Time'})
'''
deta,dxi=ij
tvar='time'
uvar='Uwind'
vvar='Vwind'
#tvar='bulk_time'
#uvar='uwnd'
#vvar='vwnd'
tdim='time'
#tdim='bulk_time'
xdim='xi_rho'
ydim='eta_rho'
xvar='lon_rho'
yvar='lat_rho'
angvar='angle'
if 'tvar' in kargs.keys(): tvar=kargs['tvar']
if 'uvar' in kargs.keys(): uvar=kargs['uvar']
if 'vvar' in kargs.keys(): vvar=kargs['vvar']
if 'tdim' in kargs.keys(): tdim=kargs['tdim']
if 'xdim' in kargs.keys(): xdim=kargs['xdim']
if 'ydim' in kargs.keys(): ydim=kargs['ydim']
if 'xvar' in kargs.keys(): xvar=kargs['xvar']
if 'yvar' in kargs.keys(): yvar=kargs['yvar']
if 'angvar' in kargs.keys(): angvar=kargs['angvar']
dims=netcdf.fdim(grd)
xi,eta=dims[xdim],dims[ydim]
xi0,eta0=xi,eta
ncg=netcdf.ncopen(grd)
nc0=netcdf.ncopen(frc)
try:
t=netcdf.nctime(nc0,tvar)
except:
t=netcdf.use(nc0,tvar)
t=netcdf.num2date(t,'days since %d-01-01' % year0)
time=netcdf.date2num(t,tunits)
x0=netcdf.use(grd,xvar)
y0=netcdf.use(grd,yvar)
if x0.ndim==1: x0,y0=np.meshgrid(x0,y0)
if angvar:
ang=netcdf.use(grd,angvar)
if not xylim is False:
xlim=xylim[:2]
ylim=xylim[2:]
i1,i2,j1,j2=calc.ij_limits(x0,y0,xlim,ylim)
xi=i2-i1
eta=j2-j1
else:
i1,i2=0,xi
j1,j2=0,eta
XI ='%d:%d:%d' %(i1,i2,dxi)
ETA ='%d:%d:%d' %(j1,j2,deta)
xi=len(range(i1,i2,dxi))
eta=len(range(j1,j2,deta))
# create file:
create_wind(fname,xi,eta)
nc=netcdf.ncopen(fname,'a')
x=x0[j1:j2:deta,i1:i2:dxi]
y=y0[j1:j2:deta,i1:i2:dxi]
nc.vars['lon'][:]=x
nc.vars['lat'][:]=y
if angvar: ang=ang[j1:j2:deta,i1:i2:dxi]
n=-1
for it in range(len(time)):
if not dates is False:
d0,d1=dates
if t[it]<d0 or t[it]>=d1: continue
n+=1
u=netcdf.use(nc0,uvar,**{xdim:XI,ydim:ETA,tdim:it})
v=netcdf.use(nc0,vvar,**{xdim:XI,ydim:ETA,tdim:it})
# rotate uv:
if angvar:
print 'rotating ...'
u,v=calc.rot2d(u,v,-ang)
nc.vars['time'][n]=time[it]
print 'filling uv',n,t[it]
nc.vars['air_u'][n,...]=u
nc.vars['air_v'][n,...]=v
nc.close()
nc0.close()
ncg.close()
def his2gnome(fname,his,grd=False,nomask=False,gshhsMask=True,xylim=False,dates=False,ij=(1,1)):
'''
Creates GNOME wind file
Ex:
his2gnome(out,his,grd,dates=dates,ij=(2,2))
if gshhsMask, the high res mask file mask_gshhs.npy will be created at 1st usage.
Mask is based on high (h) resolution gshhs data which must be available (env variable
GSHHS_MASK must be set).
'''
if not grd: grd=his
deta,dxi=ij
dims=netcdf.fdim(his)
xi,eta=dims['xi_rho'],dims['eta_rho']
xi0,eta0=xi,eta
nc0=netcdf.ncopen(his)
time=netcdf.nctime(nc0,'ocean_time')
# for roms agrif:
#t=netcdf.use(nc0,'scrum_time')
#time=netcdf.num2date(t,'seconds since %d-01-01' % year0)
x0=netcdf.use(grd,'lon_rho')
y0=netcdf.use(grd,'lat_rho')
ang=netcdf.use(grd,'angle')
if not xylim is False:
xlim=xylim[:2]
ylim=xylim[2:]
i1,i2,j1,j2=calc.ij_limits(x0,y0,xlim,ylim)
print i1,i2,j1,j2
xi=i2-i1
eta=j2-j1
else:
i1,i2=0,xi
j1,j2=0,eta
XI ='%d:%d:%d' %(i1,i2,dxi)
ETA ='%d:%d:%d' %(j1,j2,deta)
xi=len(range(i1,i2,dxi))
eta=len(range(j1,j2,deta))
# create file:
create_uv(fname,xi,eta)
nc=netcdf.ncopen(fname,'a')
for v0,v in ('lon_rho','lon'),('lat_rho','lat'),('mask_rho','mask'),('h','depth'):
print 'filling %s with %s' % (v,v0)
nc.vars[v][:]=netcdf.use(grd,v0,xi_rho=XI,eta_rho=ETA)
if nomask:
print 'NO MASK !!!'
nc.vars['mask'][:]=1
if gshhsMask:
try:
mask=np.load('mask_gshhs.npy')
except:
mask=1+0*netcdf.use(nc0,'mask_rho',xi_rho=XI,eta_rho=ETA)
mask=mask.astype('bool')
x=netcdf.use(grd,'lon_rho',xi_rho=XI,eta_rho=ETA)
y=netcdf.use(grd,'lat_rho',xi_rho=XI,eta_rho=ETA)
from okean import gshhs
axis=x.min(),x.max(),y.min(),y.max()
g=gshhs.gshhs(axis, resolution='h',area_thresh=0., max_level=2,clip=True)
for lon, lat, level in zip(g.lon, g.lat, g.level):
if level == 1: # land
print 'mask ',lon.shape
i=calc.inpolygon(x,y,lon,lat)
mask=mask & ~i
mask.dump('mask_gshhs.npy')
nc.vars['mask'][:]=mask
x=x0[j1:j2:deta,i1:i2:dxi]
y=y0[j1:j2:deta,i1:i2:dxi]
ang=ang[j1:j2:deta,i1:i2:dxi]
n=-1
for it in range(len(time)):
if not dates is False:
d0,d1=dates
if time[it]<d0 or time[it]>=d1: continue
n+=1
U=np.zeros((eta0,xi0),'f')
V=np.zeros((eta0,xi0),'f')
nc.vars['time'][n]=netcdf.date2num(time[it],tunits)
# for roms agrif:
#u=netcdf.use(nc0,'u',time=it,s_rho=-1)
#v=netcdf.use(nc0,'v',time=it,s_rho=-1)
u=netcdf.use(nc0,'u',ocean_time=it,s_rho=-1)
v=netcdf.use(nc0,'v',ocean_time=it,s_rho=-1)
# mask extrap:
print 'mask extrap...'
u=calc.mask_extrap(x0,y0,np.ma.masked_where(u==0,u))
v=calc.mask_extrap(x0,y0,np.ma.masked_where(v==0,v))
U[:,1:-1]=0.5*(u[:,:-1]+u[:,1:])
U[:,0]=u[:,0]
U[:,-1]=u[:,-1]
V[1:-1,:]=0.5*(v[:-1.:]+v[1:,:])
V[0,:]=v[0,:]
V[-1,:]=v[-1,:]
U=U[j1:j2,i1:i2]
V=V[j1:j2,i1:i2]
U=U[j1:j2:deta,i1:i2:dxi]
V=V[j1:j2:deta,i1:i2:dxi]
# rotate uv:
print 'rotating ...'
U,V=calc.rot2d(U,V,-ang)
print 'filling uv', n, time[it]
nc.vars['u'][n,...]=U
nc.vars['v'][n,...]=V
nc.close()
nc0.close()
