def load_dims(self):
dms = netcdf.fdim(self.name)
for k in dms.keys():
if k in ("ocean_time", "time", "scrum_time"):
setattr(self, "TIME", dms[k])
else:
setattr(self, k.upper(), dms[k])
def load_dims(self):
dms=netcdf.fdim(self.name)
for k in dms.keys():
if k in ('ocean_time','time','scrum_time'):
setattr(self,'TIME',dms[k])
else:
setattr(self,k.upper(),dms[k])
def gen_frc(fname,grd,tag='_ccmp'):
nc=netcdf.Pync(fname,'t',version=3)
# dims:
grd_dims=netcdf.fdim(grd)
gdims='xi_rho','xi_u','xi_v','eta_rho','eta_u','eta_v'
for name in gdims: nc.add_dim(name,grd_dims[name])
# time dim:
nc.add_dim('wind_time',0)
v=nc.add_var('wind_time',np.dtype('d'),('wind_time',))
v.add_att('long_name','wind forcing time')
tunits='days since 1970-01-01'
v.add_att('units',tunits)
v=nc.add_var('Uwind'+tag,np.dtype('d'),('wind_time','eta_rho', 'xi_rho'))
v.add_att('long_name','u-wind')
v.add_att('units','metre second-1')
v.add_att('time','time')
v=nc.add_var('Vwind'+tag,np.dtype('d'),('wind_time','eta_rho', 'xi_rho'))
v.add_att('long_name','v-wind')
v.add_att('units','metre second-1')
v.add_att('time','time')
# Global Attributes:
nc.add_att('type','Wind forcing file')
nc.add_att('title','CCMP wind')
nc.add_att('grd_file',os.path.realpath(grd))
from time import ctime
nc.add_att('history','ROMS wind file, '+ctime())
nc.add_att('author',cb.username()[1]+', '+cb.machinename())
nc.close()
def load_dims(self):
dms=netcdf.fdim(self.nc)
for k in dms:
if k in ('ocean_time','time','scrum_time'):
setattr(self,'TIME',dms[k])
else:
setattr(self,k.upper(),dms[k])
def add_horiz_dims(self,nc):
'''
Adds horizontal dimensions to netcdf file
'''
grd_dims=netcdf.fdim(self.grid)
gdims='xi_rho','xi_u','xi_v','eta_rho','eta_u','eta_v'
for name in gdims: nc.add_dim(name,grd_dims[name])
def add_horiz_dims(self,nc):
'''
Adds horizontal dimensions to netcdf file
'''
grd_dims=netcdf.fdim(self.grid)
gdims='xi_rho','xi_u','xi_v','eta_rho','eta_u','eta_v'
for name in gdims: nc.add_dim(name,grd_dims[name])
def roms2clmbry(f0,clm,grd,sparams,**kargs):
'''
kargs:
bry, bry file to create (False by default, no bry is created)
times, all by default, but can be a range of times (inds or datetimes)
tunits, 'days since 1970-01-01'
ctitle, title for clm file (default used)
btitle, title for bry file (defaul used)
obc, bry open boundaries (defaul used)
quiet, False
other kargs of roms2roms:
grd0
sparams0
tunits0
quiet
Z, intermediate interpolation step depths, automatically
generated by default
ij, interpolations along *i or j
'''
bry = kargs.get('bry', False)
times = kargs.get('times', 'all')
tunits = kargs.get('tunits', 'days since 1970-01-01')
ctitle = kargs.get('ctitle', False)
btitle = kargs.get('btitle', False)
obc = kargs.get('obc', False)
quiet = kargs.get('quiet', False)
create=True
Cargs={}
if ctitle: Cargs['title'] = ctitle
Cargs['tunits'] = tunits
Cargs['create'] = create
Bargs={}
if btitle: Bargs['title'] = btitle
if obc: Bargs['obc'] = obc
Bargs['tunits'] = tunits
Bargs['create'] = create
if times=='all':
times=range(netcdf.fdim(f0,'ocean_time'))
for tind in times:
data,datab=roms2roms(f0,grd,sparams,tind,**kargs)
prognostic.make_clm(clm,data,grd,sparams,quiet=quiet,**Cargs)
if bry:
prognostic.make_bry(bry,datab,grd,sparams,quiet=quiet,**Bargs)
if create:
Cargs['create']=False
Bargs['create']=False
def make_blk_wrf(wrfpath, grd, bulk, date0=False, date1=False, **kargs):
"""
see make_blk_interim
"""
quiet = kargs.get("quiet", 0)
create = kargs.get("create", 1)
model = kargs.get("model", "roms") # or roms-agrif
wrffiles = kargs.get("wrffiles", "wrfout*")
dt = kargs.get("dt", 6)
data = load_blkdata_wrf(wrfpath, wrffiles, date0, date1, quiet)
if not len(data):
return
q = gennc.GenBlk(bulk, grd, **kargs)
if create:
# about original data, run data2romsblk once to test for x_original:
tmp = data2romsblk(data[data.keys()[0]], grd, **kargs)
if "x_original" in tmp.keys():
original = tmp["x_original"].shape
else:
original = False
q.create(model, original)
for d in data.keys():
# be sure time increases. Note that in load_blkdata_wrf
# we checked if time increases in the dataset... not if dates are higher
# then previous dates in file
ntimes = netcdf.fdim(bulk, "time")
if ntimes:
tin = netcdf.nctime(bulk, "time")
if tin.size and (d - tin[-1]) < datetime.timedelta(hours=dt - 0.1):
print "-> not including %s" % d.isoformat()
continue
if model == "roms":
if not quiet:
print " converting units:",
conv_units(data[d], model, quiet)
D = data2romsblk(data[d], grd, **kargs)
D["date"] = d
if not quiet:
print " =>filling date=%s" % d.isoformat(" ")
q.fill(D, quiet=quiet)
def make_blk_wrf(wrfpath,grd,bulk,date0=False,date1=False,**kargs):
'''
see make_blk_interim
'''
quiet = kargs.get('quiet',0)
create = kargs.get('create',1)
model = kargs.get('model','roms') # or roms-agrif
wrffiles=kargs.get('wrffiles','wrfout*')
dt = kargs.get('dt',6)
proj = kargs.get('proj','auto')
data=load_blkdata_wrf(wrfpath,wrffiles,date0,date1,quiet)
if not len(data): return
g=roms.Grid(grd)
if proj=='auto': kargs['proj']=g.get_projection()
q=gennc.GenBlk(bulk,grd,**kargs)
if create:
# about original data, run data2romsblk once to test for x_original:
tmp=data2romsblk(data[list(data.keys())[0]],g,**kargs)
if 'x_original' in tmp: original=tmp['x_original'].shape
else: original=False
q.create(model,original)
for d in data:
# be sure time increases. Note that in load_blkdata_wrf
# we checked if time increases in the dataset... not if dates are higher
# then previous dates in file
ntimes=netcdf.fdim(bulk,'time')
if ntimes:
tin=netcdf.nctime(bulk,'time')
if tin.size and (d-tin[-1])<datetime.timedelta(hours=dt-0.1):
print('-> not including %s'%d.isoformat())
continue
if model=='roms':
if not quiet: print(' converting units:'),
conv_units(data[d],model,quiet)
D=data2romsblk(data[d],g,**kargs)
D['date']=d
if not quiet: print(' =>filling date=%s' % d.isoformat(' '))
q.fill(D,quiet=quiet)
def make_blk_wrf(wrfpath, grd, bulk, date0=False, date1=False, **kargs):
'''
see make_blk_interim
'''
quiet = kargs.get('quiet', 0)
create = kargs.get('create', 1)
model = kargs.get('model', 'roms') # or roms-agrif
wrffiles = kargs.get('wrffiles', 'wrfout*')
dt = kargs.get('dt', 6)
proj = kargs.get('proj', 'auto')
data = load_blkdata_wrf(wrfpath, wrffiles, date0, date1, quiet)
if not len(data): return
g = roms.Grid(grd)
if proj == 'auto': kargs['proj'] = g.get_projection()
q = gennc.GenBlk(bulk, grd, **kargs)
if create:
# about original data, run data2romsblk once to test for x_original:
tmp = data2romsblk(data[list(data.keys())[0]], g, **kargs)
if 'x_original' in tmp: original = tmp['x_original'].shape
else: original = False
q.create(model, original)
for d in data:
# be sure time increases. Note that in load_blkdata_wrf
# we checked if time increases in the dataset... not if dates are higher
# then previous dates in file
ntimes = netcdf.fdim(bulk, 'time')
if ntimes:
tin = netcdf.nctime(bulk, 'time')
if tin.size and (d - tin[-1]) < datetime.timedelta(hours=dt - 0.1):
print('-> not including %s' % d.isoformat())
continue
if model == 'roms':
if not quiet: print(' converting units:'),
conv_units(data[d], model, quiet)
D = data2romsblk(data[d], g, **kargs)
D['date'] = d
if not quiet: print(' =>filling date=%s' % d.isoformat(' '))
q.fill(D, quiet=quiet)
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 narr_file_data(fname, xlim=False, ylim=False, quiet=False):
'''
Returns bulk data from one NARR file
'''
out = {}
# loading grid:
if 0:
if not quiet: print ' reading lon,lat from file %s' % grd
nc = netcdf.ncopen(grd)
x = nc.vars['East_longitude_0-360'][0, ...] - 360.
y = nc.vars['Latitude_-90_to_+90'][0, ...] # time always 1 !!
nc.close()
else:
if not quiet: print ' reading lon,lat from file %s' % grdTxt
x, y = load_grid()
#x=x-360.
x = -x
ny, nx = x.shape
if (xlim, ylim) == (False, False): i0, i1, j0, j1 = 0, nx, 0, ny
else:
i0, i1, j0, j1 = calc.ij_limits(x, y, xlim, ylim, margin=0)
x = x[j0:j1, i0:i1]
y = y[j0:j1, i0:i1]
try:
nc = netcdf.ncopen(fname)
except:
return {}
xx = str(i0) + ':' + str(i1)
yy = str(j0) + ':' + str(j1)
tdim = netcdf.fdim(nc, 'time1')
if tdim != 1: print 'WARNING: tdim !=1 !!!!!!'
# T surface [K->C]
if not quiet: print ' --> T air'
tair = netcdf.use(nc, 'Temperature_surface', time1=0, x=xx, y=yy)
tair = tair - 273.15
out['tair'] = cb.Data(x, y, tair, 'C')
# R humidity [% -> 0--1]
if not quiet: print ' --> R humidity'
rhum = netcdf.use(nc, 'Relative_humidity', time1=0, x=xx, y=yy)
out['rhum'] = cb.Data(x, y, rhum / 100., '0--1')
# surface pressure [Pa]
if not quiet: print ' --> Surface pressure'
pres = netcdf.use(nc, 'Pressure_surface', time1=0, x=xx, y=yy)
out['pres'] = cb.Data(x, y, pres, 'Pa')
# P rate [kg m-2 s-1 -> cm/d]
if not quiet: print ' --> P rate'
prate = netcdf.use(nc, 'Precipitation_rate', time1=0, x=xx, y=yy)
prate = prate * 86400 * 100 / 1000.
out['prate'] = cb.Data(x, y, prate, 'cm/d')
# Net shortwave flux [ W m-2]
if not quiet: print ' --> Net shortwave flux'
if not quiet: print ' SW down'
sw_down = netcdf.use(nc,
'Downward_shortwave_radiation_flux',
time1=0,
x=xx,
y=yy)
if not quiet: print ' SW up'
sw_up = netcdf.use(nc,
'Upward_short_wave_radiation_flux_surface',
time1=0,
x=xx,
y=yy)
sw_net = sw_down - sw_up
out['radsw'] = cb.Data(x, y, sw_net, 'W m-2', info='positive downward')
# Net longwave flux [W/m^2]
if not quiet: print ' --> Net longwave flux'
if not quiet: print ' LW down'
lw_down = netcdf.use(nc,
'Downward_longwave_radiation_flux',
time1=0,
x=xx,
y=yy)
if not quiet: print ' LW up'
lw_up = netcdf.use(nc,
'Upward_long_wave_radiation_flux_surface',
time1=0,
x=xx,
y=yy)
lw_net = lw_down - lw_up
out['radlw'] = cb.Data(x, y, -lw_net, 'W m-2', info='positive upward')
# downward lw:
out['dlwrf'] = cb.Data(x,
y,
-lw_down,
'W m-2',
info='negative... downward')
# U and V wind speed 10m
if not quiet: print ' --> U and V wind'
# vertical dim is height_above_ground1: 10 and 30 m
uwnd = netcdf.use(nc,
'u_wind_height_above_ground',
height_above_ground1=0,
time1=0,
x=xx,
y=yy)
vwnd = netcdf.use(nc,
'v_wind_height_above_ground',
height_above_ground1=0,
time1=0,
x=xx,
y=yy)
if not quiet: print ' --> calc wind speed and stress'
speed = np.sqrt(uwnd**2 + vwnd**2)
taux, tauy = air_sea.wind_stress(uwnd, vwnd)
out['wspd'] = cb.Data(x, y, speed, 'm s-1')
out['uwnd'] = cb.Data(x, y, uwnd, 'm s-1')
out['vwnd'] = cb.Data(x, y, vwnd, 'm s-1')
out['sustr'] = cb.Data(x, y, taux, 'Pa')
out['svstr'] = cb.Data(x, y, tauy, 'Pa')
# Cloud cover [0--100 --> 0--1]:
if not quiet: print ' --> Cloud cover'
clouds = netcdf.use(nc, 'Total_cloud_cover', time1=0, x=xx, y=yy)
out['cloud'] = cb.Data(x, y, clouds / 100., 'fraction (0--1)')
nc.close()
return out
def load_data(f, quiet=0, **kargs):
'''
Loads prognostic variables (temp,salt,u,v,ubar,vbar,zeta) from
netcdf file or opendap server. Also loads lon,lat, depth, and time.
If f is a file, it must include the 1d variables lon,lat and depth;
the 2d variable ssh (zeta) and the 3d variables temp, salt, u and v;
ie, each file must contain data for a simgle time. The file must also
contain the variable time.
If f is a opendap address, it must contain also all these variables
or the ones defined in the input karg settings (DataAccess object)
To deal with the case of variables in different files/opendap addresses,
f can also be a dictionary with keys the variables and values the files
or opendap addresses. In this case, the keys must be:
- temp
- salt
- u
- v
- ssh
- misc, for lon, lat, depth, time and dimensions
or xy for lon,lat and x,ydim; z for depth and zdim, time for time
The output data (dict) is suitable to be used by data2roms, which
interpolates the data to ROMS 3d grid.
Also outputs an error/status string.
kargs:
inds, dict with dimension names/values (where time dim can be integer
or datetime)
settings, DataAccess object
extra, extra misc vars to load [(outKey0,fileVar0),...]
t_units, units of variable time, by default the att units is used
'''
sett = DataAccess()
inds = {}
extra = []
t_units = []
if 'settings' in kargs.keys(): sett = kargs['settings']
if 'inds' in kargs.keys(): inds = kargs['inds']
if 'extra' in kargs.keys(): extra = kargs['extra']
if 't_units' in kargs.keys(): t_units = kargs['t_units']
res = {}
msg = ''
if not isinstance(f, dict) and not f.startswith('http') and not isfile(f):
msg = 'file not found %s' % f
if not quiet: print msg
return res, msg
# load nc files:
if not isinstance(f, dict):
f = {'temp': f, 'salt': f, 'u': f, 'v': f, 'ssh': f, 'misc': f}
if not f.has_key('xy'): f['xy'] = f['misc']
if not f.has_key('z'): f['z'] = f['misc']
if not f.has_key('time'): f['time'] = f['misc']
filesUsed = []
ncUsed = []
for i in f.keys():
if not quiet: print '(%s) loading from %s' % (i.ljust(5), f[i])
if i == 'temp':
if f[i] in filesUsed: ncTemp = ncUsed[filesUsed.index(f[i])]
else:
ncTemp = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncTemp]
elif i == 'salt':
if f[i] in filesUsed: ncSalt = ncUsed[filesUsed.index(f[i])]
else:
ncSalt = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncSalt]
elif i == 'u':
if f[i] in filesUsed: ncU = ncUsed[filesUsed.index(f[i])]
else:
ncU = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncU]
elif i == 'v':
if f[i] in filesUsed: ncV = ncUsed[filesUsed.index(f[i])]
else:
ncV = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncV]
elif i == 'ssh':
if f[i] in filesUsed: ncSsh = ncUsed[filesUsed.index(f[i])]
else:
ncSsh = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncSsh]
elif i == 'xy':
if f[i] in filesUsed: ncXy = ncUsed[filesUsed.index(f[i])]
else:
ncXy = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncXy]
elif i == 'z':
if f[i] in filesUsed: ncZ = ncUsed[filesUsed.index(f[i])]
else:
ncZ = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncZ]
elif i == 'time':
if f[i] in filesUsed: ncTime = ncUsed[filesUsed.index(f[i])]
else:
ncTime = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncTime]
elif i == 'misc':
if f[i] in filesUsed: ncMisc = ncUsed[filesUsed.index(f[i])]
else:
ncMisc = netcdf.ncopen(f[i])
filesUsed += [f[i]]
ncUsed += [ncMisc]
# load dims:
if not quiet: print ' loading dims...'
dimsXy = netcdf.fdim(ncXy)
dimsZ = netcdf.fdim(ncZ)
res['NX'] = dimsXy[sett.xdim]
res['NY'] = dimsXy[sett.ydim]
###if sett.z_name:
if sett.zdim:
res['NZ'] = dimsZ[sett.zdim]
else:
res['NZ'] = 1
# about horizontal inds:
if inds.has_key(
sett.xdim) and len(inds[sett.xdim]) == 2 and not isinstance(
inds[sett.xdim], basestring):
if not quiet: print ' calc horizontal inds...'
xlim = inds[sett.xdim]
ylim = inds[sett.ydim]
inds.pop(sett.xdim)
inds.pop(sett.ydim)
lon = netcdf.use(ncXy, sett.x_name, **inds)
if np.any(lon > 360): lon = np.mod(lon, 360.)
lat = netcdf.use(ncXy, sett.y_name, **inds)
i0, i1, j0, j1 = calc.ij_limits(lon, lat, xlim, ylim, margin=3)
inds[sett.xdim] = '%d:%d' % (i0, i1)
inds[sett.ydim] = '%d:%d' % (j0, j1)
if not quiet: print ' loading lon, lat, depth...'
res['lon'] = netcdf.use(ncXy, sett.x_name, **inds)
if np.any(res['lon'] > 360): res['lon'] = np.mod(res['lon'], 360.)
res['lat'] = netcdf.use(ncXy, sett.y_name, **inds)
if sett.z_name:
res['depth'] = -netcdf.use(ncZ, sett.z_name, **inds)
else:
res['depth'] = False
if res['lon'].size != res['lat'].size:
res['lon'], res['lat'] = np.meshgrid(res['lon'], res['lat'])
# needed for griddata, later
# update nx,ny:
if inds.has_key(sett.xdim):
res['NY'], res['NX'] = res['lon'].shape
# extra misc vars:
if len(extra):
for outKey, fileVar in extra:
if not quiet:
print ' loading extra misc... %s %s' % (outKey, fileVar)
res[outKey] = netcdf.use(ncMisc, fileVar, **inds)
# time:
# file may have one or several times. If several, time dim must be given
# with kargs inds!
# but file may also have no time dim or time name !
if sett.time_name:
if not quiet: print ' loading time...'
if t_units:
times = netcdf.use(ncTime, sett.time_name)
times = netcdf.num2date(times, t_units)
else:
times = netcdf.nctime(ncTime, sett.time_name)
if inds.has_key(sett.tdim):
try:
tind = dts.parse_date(inds[sett.tdim])
except:
tind = inds[sett.tdim] # is an integer, for instance
if isinstance(tind, datetime.datetime):
tind, = np.where(times == tind)
if tind.size:
tind = tind[0]
inds[sett.
tdim] = tind # update inds to extract other variables
else:
Msg = 'date not found'
msg += '\n' + Msg
return res, msg + ' ERROR'
date = times[tind]
try:
len(date)
ndates = True
except:
ndates = False
if ndates:
if not quiet:
print ' tind, date= len=%d: %d to %d, %s to %s' % (
len(date), tind[0], tind[-1], date[0].isoformat(' '),
date[-1].isoformat(' '))
else:
if not quiet:
print ' tind, date= %d %s' % (tind, date.isoformat(' '))
elif times.size == 1:
date = times[0]
if not quiet: print ' date= %s' % date.isoformat(' ')
else: # must provide tind as input!!
Msg = 'several dates in file... provice tind!'
msg += '\n' + Msg
return res, msg + ' ERROR'
res['date'] = date
else:
if not quiet: print ' warning: not using time !!'
res['date'] = 0
empty3d = np.zeros([res['NZ'], res['NY'], res['NX']])
empty2d = np.zeros([res['NY'], res['NX']])
if 'temp' in f.keys():
if not quiet: print ' loading temp...'
if sett.temp_name in ncTemp.varnames:
res['temp'] = netcdf.use(ncTemp, sett.temp_name, **inds)
else:
Msg = 'var %s not found' % 'temp'
msg += '\n' + Msg
if not quiet: print Msg
res['temp'] = empty3d
if 'salt' in f.keys():
if not quiet: print ' loading salt...'
if sett.salt_name in ncSalt.varnames:
res['salt'] = netcdf.use(ncSalt, sett.salt_name, **inds)
else:
Msg = 'var %s not found' % 'salt'
msg += '\n' + Msg
if not quiet: print Msg
res['salt'] = empty3d
if 'u' in f.keys():
if not quiet: print ' loading u...'
if sett.u_name in ncU.varnames:
res['u'] = netcdf.use(ncU, sett.u_name, **inds)
else:
Msg = 'var %s not found' % 'u'
msg += '\n' + Msg
if not quiet: print Msg
res['u'] = empty3d
if 'v' in f.keys():
if not quiet: print ' loading v...'
if sett.v_name in ncV.varnames:
res['v'] = netcdf.use(ncV, sett.v_name, **inds)
else:
Msg = 'var %s not found' % 'v'
msg += '\n' + Msg
if not quiet: print Msg
res['v'] = empty3d
if 'ssh' in f.keys():
if not quiet: print ' loading ssh...'
if sett.ssh_name in ncSsh.varnames:
res['ssh'] = netcdf.use(ncSsh, sett.ssh_name, **inds)
else:
Msg = 'var %s not found' % 'ssh'
msg += '\n' + Msg
if not quiet: print Msg
res['ssh'] = empty2d
for nc in ncUsed:
try:
nc.close()
except:
pass
return res, msg
def narr_file_data(fname,xlim=False,ylim=False,quiet=False):
'''
Returns bulk data from one NARR file
'''
out={}
# loading grid:
if 0:
if not quiet: print(' reading lon,lat from file %s' % grd)
nc=netcdf.ncopen(grd)
x=nc.vars['East_longitude_0-360'][0,...]-360.
y=nc.vars['Latitude_-90_to_+90'][0,...] # time always 1 !!
nc.close()
else:
if not quiet: print(' reading lon,lat from file %s' % grdTxt)
x,y=load_grid()
#x=x-360.
x=-x
ny,nx=x.shape
if (xlim,ylim)==(False,False):i0,i1,j0,j1=0,nx,0,ny
else:
i0,i1,j0,j1=calc.ij_limits(x, y, xlim, ylim, margin=0)
x=x[j0:j1,i0:i1]
y=y[j0:j1,i0:i1]
try:
nc=netcdf.ncopen(fname)
except:
return {}
xx=str(i0)+':'+str(i1)
yy=str(j0)+':'+str(j1)
tdim=netcdf.fdim(nc,'time1')
if tdim!=1: print('WARNING: tdim !=1 !!!!!!')
# T surface [K->C]
if not quiet: print(' --> T air')
tair=netcdf.use(nc,'Temperature_surface',time1=0,x=xx,y=yy)
tair=tair-273.15
out['tair']=cb.Data(x,y,tair,'C')
# R humidity [% -> 0--1]
if not quiet: print(' --> R humidity')
rhum=netcdf.use(nc,'Relative_humidity',time1=0,x=xx,y=yy)
out['rhum']=cb.Data(x,y,rhum/100.,'0--1')
# surface pressure [Pa]
if not quiet: print(' --> Surface pressure')
pres=netcdf.use(nc,'Pressure_surface',time1=0,x=xx,y=yy)
out['pres']=cb.Data(x,y,pres,'Pa')
# P rate [kg m-2 s-1 -> cm/d]
if not quiet: print(' --> P rate')
prate=netcdf.use(nc,'Precipitation_rate',time1=0,x=xx,y=yy)
prate=prate*86400*100/1000.
out['prate']=cb.Data(x,y,prate,'cm/d')
# Net shortwave flux [ W m-2]
if not quiet: print(' --> Net shortwave flux')
if not quiet: print(' SW down')
sw_down=netcdf.use(nc,'Downward_shortwave_radiation_flux',time1=0,x=xx,y=yy)
if not quiet: print(' SW up')
sw_up=netcdf.use(nc,'Upward_short_wave_radiation_flux_surface',time1=0,x=xx,y=yy)
sw_net=sw_down-sw_up
out['radsw']=cb.Data(x,y,sw_net,'W m-2',info='positive downward')
# Net longwave flux [W/m^2]
if not quiet: print(' --> Net longwave flux')
if not quiet: print(' LW down')
lw_down=netcdf.use(nc,'Downward_longwave_radiation_flux',time1=0,x=xx,y=yy)
if not quiet: print(' LW up')
lw_up=netcdf.use(nc,'Upward_long_wave_radiation_flux_surface',time1=0,x=xx,y=yy)
lw_net=lw_down-lw_up
out['radlw']=cb.Data(x,y,-lw_net,'W m-2',info='positive upward')
# downward lw:
out['dlwrf']=cb.Data(x,y,-lw_down,'W m-2',info='negative... downward')
# U and V wind speed 10m
if not quiet: print(' --> U and V wind')
# vertical dim is height_above_ground1: 10 and 30 m
uwnd=netcdf.use(nc,'u_wind_height_above_ground',height_above_ground1=0,time1=0,x=xx,y=yy)
vwnd=netcdf.use(nc,'v_wind_height_above_ground',height_above_ground1=0,time1=0,x=xx,y=yy)
if not quiet: print(' --> calc wind speed and stress')
speed = np.sqrt(uwnd**2+vwnd**2)
taux,tauy=air_sea.wind_stress(uwnd,vwnd)
out['wspd']=cb.Data(x,y,speed,'m s-1')
out['uwnd']=cb.Data(x,y,uwnd,'m s-1')
out['vwnd']=cb.Data(x,y,vwnd,'m s-1')
out['sustr']=cb.Data(x,y,taux,'Pa')
out['svstr']=cb.Data(x,y,tauy,'Pa')
# Cloud cover [0--100 --> 0--1]:
if not quiet: print(' --> Cloud cover')
clouds=netcdf.use(nc,'Total_cloud_cover',time1=0,x=xx,y=yy)
out['cloud']=cb.Data(x,y,clouds/100.,'fraction (0--1)')
nc.close()
return out
def create(self):
'''
Creates model netcdf river forcing file
'''
nc=netcdf.Pync(self.fname,self.perm,version=self.ncversion)
nx=netcdf.fdim(self.grid,'xi_rho')
ny=netcdf.fdim(self.grid,'eta_rho')
# Dimensions:
nc.add_dim('s_rho',self.nz)
nc.add_dim('river',self.nrivers)
nc.add_dim('river_time',0)
# Variables:
v=nc.add_var('river',np.dtype('d'),('river',))
v.add_att('long_name','river runoff identification number')
v=nc.add_var('river_Xposition',np.dtype('d'),('river',))
v.add_att('long_name','river XI-position at RHO-points')
v.add_att('valid_min',1)
v.add_att('valid_max',nx-1)
v=nc.add_var('river_Eposition',np.dtype('d'),('river',))
v.add_att('long_name','river ETA-position at RHO-points')
v.add_att('valid_min',1)
v.add_att('valid_max',ny-1)
v=nc.add_var('river_direction',np.dtype('d'),('river',))
v.add_att('long_name','river runoff direction')
v=nc.add_var('river_Vshape',np.dtype('d'),('s_rho','river'))
v.add_att('long_name','river runoff mass transport vertical profile')
v=nc.add_var('river_time',np.dtype('d'),('river_time',))
v.add_att('long_name','river runoff time')
v.add_att('units',self.tunits)
v.add_att('add_offset',0)
v=nc.add_var('river_transport',np.dtype('d'),('river_time','river'))
v.add_att('long_name','river runoff vertically integrated mass transport')
v.add_att('units','metre3 second-1')
v.add_att('time','river_time')
v=nc.add_var('river_temp',np.dtype('d'),('river_time','s_rho','river'))
v.add_att('long_name','river runoff potential temperature')
v.add_att('units','Celsius')
v.add_att('time','river_time')
v=nc.add_var('river_salt',np.dtype('d'),('river_time','s_rho','river'))
v.add_att('long_name','river runoff salinity')
v.add_att('units','Celsius')
v.add_att('time','river_time')
# Global Attributes:
nc.add_att('type',self.type)
nc.add_att('title',self.title)
nc.add_att('grd_file',os.path.realpath(self.grid))
nc.add_att('date',dts.currday().isoformat(' '))
nc.add_att('author',cb.username()[1]+', '+cb.username()[0]+'@'+cb.machinename())
# extra attrs:
for i in self.attr.keys(): nc.add_att(i,self.attr[i])
nc.close()
def roms2swan_wind(frc,date0,date1,fname='swan_wind.dat',**kargs):
tname='wind_time'
uname='Uwind'
vname='Vwind'
grd=False # needed if wind is 1d
dt=1 # hours
path=''
if 'tname' in kargs.keys(): tname=kargs['tname']
if 'uname' in kargs.keys(): uname=kargs['uname']
if 'vname' in kargs.keys(): vname=kargs['vname']
if 'grd' in kargs.keys(): grd =kargs['grd']
if 'dt' in kargs.keys(): dt =kargs['dt']
if 'path' in kargs.keys(): path =kargs['path']
print 'wind: loading time ...'
time=netcdf.nctime(frc,tname)
#time=np.load('tfile')
#cond=(time>=date0)&(time<=date1)
cond=(time>=date0)&(time<=date1+datetime.timedelta(days=1)) # add one day at the end, just to avoid the "repeating last"
time=time[cond]
d=np.diff(pl.date2num(time))
print 'current max and min dt = %6.2f %6.2f hrs = %6.2f %6.2f mins'%(d.max()*24, d.min()*24, d.max()*24*60, d.min()*24*60)
# time=time[::dt]
# d=np.diff(pl.date2num(time))
# print ' final max and min dt = %6.2f %6.2f hrs = %6.2f %6.2f mins'%(d.max()*24, d.min()*24, d.max()*24*60, d.min()*24*60)
print 'wind: loading u ...'
u,nc=netcdf.var(frc,uname)
print 'wind: loading v ...'
v,nc=netcdf.var(nc,uname)
# u=u[cond,...][::dt,...]
# v=v[cond,...][::dt,...]
u=u[cond,...]
v=v[cond,...]
nc.close()
if u.ndim==1:
if not grd:
print 'must provide grd karg!'
return
nt=u.size
eta=netcdf.fdim(grd)['eta_rho']
xi=netcdf.fdim(grd)['xi_rho']
else:
nt,eta,xi=u.shape
# array may be too big, so do this later (for each it)
#
# u=np.tile(u[:,np.newaxis,np.newaxis],(1,eta,xi))
# v=np.tile(v[:,np.newaxis,np.newaxis],(1,eta,xi))
i=open(fname,'w')
times=[]
time0=time[0]-datetime.timedelta(hours=dt)
ITs=[]
for it in range(nt):
time0=time0+datetime.timedelta(hours=dt)
if time0>date1: break
if time0>time[-1]:
print 'Warning : repeating last ...', it
times+=[time0]
d=np.abs(time-time0)
it=np.where(d==d.min())[0][0]
ITs+=[it]
if it%100==0: print 'saving u %s %s'%(fname,time[it].isoformat(' '))
if u[it,...].ndim==0:
U=np.tile(u[it,...],(eta,xi)).flatten()
else:
U=u[it,...].flatten()
[i.write('%8.4f\n'%uu) for uu in U]
for it in ITs:
if it%100==0: print 'saving v %s %s'%(fname,time[it].isoformat(' '))
if v[it,...].ndim==0:
V=np.tile(v[it,...],(eta,xi)).flatten()
else:
V=v[it,...].flatten()
[i.write('%8.4f\n'%vv) for vv in V]
times=np.asarray(times)
t0iso=times[0].strftime('%Y%m%d.%H%M%S')
t1iso=times[-1].strftime('%Y%m%d.%H%M%S')
dt=times[1]-times[0]
dth=dt.days*24. + dt.seconds/60.**2
print ' -- created swan wind file %s\n'%fname
# add to swan INPUT:
print '\n'
print 'INPGRID WIND CURVILINEAR 0 0 %d %d EXC 9.999000e+003 &'%(xi-1,eta-1)
print ' NONSTATIONARY %s %.2f HR %s'%(t0iso,dth,t1iso)
print 'READINP WIND 1 \'%s\' 4 0 FREE '%(os.path.join(path,fname))
print '\n'
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 roms2swan_wind(frc, date0, date1, fname='swan_wind.dat', **kargs):
tname = 'wind_time'
uname = 'Uwind'
vname = 'Vwind'
grd = False # needed if wind is 1d
dt = 1 # hours
path = ''
if 'tname' in kargs.keys(): tname = kargs['tname']
if 'uname' in kargs.keys(): uname = kargs['uname']
if 'vname' in kargs.keys(): vname = kargs['vname']
if 'grd' in kargs.keys(): grd = kargs['grd']
if 'dt' in kargs.keys(): dt = kargs['dt']
if 'path' in kargs.keys(): path = kargs['path']
print 'wind: loading time ...'
time = netcdf.nctime(frc, tname)
#time=np.load('tfile')
#cond=(time>=date0)&(time<=date1)
cond = (time >= date0) & (
time <= date1 + datetime.timedelta(days=1)
) # add one day at the end, just to avoid the "repeating last"
time = time[cond]
d = np.diff(pl.date2num(time))
print 'current max and min dt = %6.2f %6.2f hrs = %6.2f %6.2f mins' % (
d.max() * 24, d.min() * 24, d.max() * 24 * 60, d.min() * 24 * 60)
# time=time[::dt]
# d=np.diff(pl.date2num(time))
# print ' final max and min dt = %6.2f %6.2f hrs = %6.2f %6.2f mins'%(d.max()*24, d.min()*24, d.max()*24*60, d.min()*24*60)
print 'wind: loading u ...'
nc = netcdf.ncopen(frc)
u = netcdf.var(nc, uname)
print 'wind: loading v ...'
v = netcdf.var(nc, uname)
# u=u[cond,...][::dt,...]
# v=v[cond,...][::dt,...]
u = u[cond, ...]
v = v[cond, ...]
nc.close()
if u.ndim == 1:
if not grd:
print 'must provide grd karg!'
return
nt = u.size
eta = netcdf.fdim(grd)['eta_rho']
xi = netcdf.fdim(grd)['xi_rho']
else:
nt, eta, xi = u.shape
# array may be too big, so do this later (for each it)
#
# u=np.tile(u[:,np.newaxis,np.newaxis],(1,eta,xi))
# v=np.tile(v[:,np.newaxis,np.newaxis],(1,eta,xi))
i = open(fname, 'w')
times = []
time0 = time[0] - datetime.timedelta(hours=dt)
ITs = []
for it in range(nt):
time0 = time0 + datetime.timedelta(hours=dt)
if time0 > date1: break
if time0 > time[-1]:
print 'Warning : repeating last ...', it
times += [time0]
d = np.abs(time - time0)
it = np.where(d == d.min())[0][0]
ITs += [it]
if it % 100 == 0:
print 'saving u %s %s' % (fname, time[it].isoformat(' '))
if u[it, ...].ndim == 0:
U = np.tile(u[it, ...], (eta, xi)).flatten()
else:
U = u[it, ...].flatten()
[i.write('%8.4f\n' % uu) for uu in U]
for it in ITs:
if it % 100 == 0:
print 'saving v %s %s' % (fname, time[it].isoformat(' '))
if v[it, ...].ndim == 0:
V = np.tile(v[it, ...], (eta, xi)).flatten()
else:
V = v[it, ...].flatten()
[i.write('%8.4f\n' % vv) for vv in V]
times = np.asarray(times)
t0iso = times[0].strftime('%Y%m%d.%H%M%S')
t1iso = times[-1].strftime('%Y%m%d.%H%M%S')
dt = times[1] - times[0]
dth = dt.days * 24. + dt.seconds / 60.**2
print ' -- created swan wind file %s\n' % fname
# add to swan INPUT:
print '\n'
print 'INPGRID WIND CURVILINEAR 0 0 %d %d EXC 9.999000e+003 &' % (xi - 1,
eta - 1)
print ' NONSTATIONARY %s %.2f HR %s' % (t0iso, dth, t1iso)
print 'READINP WIND 1 \'%s\' 4 0 FREE ' % (os.path.join(path, fname))
print '\n'
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 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 roms2clmbry(f0,clm,grd,sparams,**kargs):
'''
kargs:
bry, bry file to create (False by default, no bry is created)
times, all by default, but can be a range of times (inds or datetimes)
tunits, 'days since 1970-01-01'
ctitle, title for clm file (default used)
btitle, title for bry file (defaul used)
obc, bry open boundaries (defaul used)
quiet, False
other kargs of roms2roms:
grd0
sparams0
tunits0
'''
bry = False
times = 'all'
tunits = 'days since 1970-01-01'
ctitle = False
btitle = False
obc = False
quiet = False
if 'bry' in kargs.keys(): bry = kargs['bry']
if 'times' in kargs.keys(): times = kargs['times']
if 'tunits' in kargs.keys(): tunits = kargs['tunits']
if 'ctitle' in kargs.keys(): ctitle = kargs['ctitle']
if 'btitle' in kargs.keys(): btitle = kargs['btitle']
if 'obc' in kargs.keys(): obc = kargs['obc']
if 'quiet' in kargs.keys(): quiet = kargs['quiet']
create=True
Cargs={}
if ctitle: Cargs['title'] = ctitle
Cargs['tunits'] = tunits
Cargs['create'] = create
Bargs={}
if btitle: Bargs['title'] = btitle
if obc: Bargs['obc'] = obc
Bargs['tunits'] = tunits
Bargs['create'] = create
if times=='all':
times=range(netcdf.fdim(f0,'ocean_time'))
for tind in times:
data,datab=roms2roms(f0,grd,sparams,tind,**kargs)
prognostic.make_clm(clm,data,grd,sparams,quiet=quiet,**Cargs)
if bry:
prognostic.make_bry(bry,datab,grd,sparams,quiet=quiet,**Bargs)
if create:
Cargs['create']=False
Bargs['create']=False
def load_data(f,quiet=0,**kargs):
'''
Loads prognostic variables (temp,salt,u,v,ubar,vbar,zeta) from
netcdf file or opendap server. Also loads lon,lat, depth, and time.
If f is a file, it must include the 1d variables lon,lat and depth;
the 2d variable ssh (zeta) and the 3d variables temp, salt, u and v;
ie, each file must contain data for a simgle time. The file must also
contain the variable time.
If f is a opendap address, it must contain also all these variables
or the ones defined in the input karg settings (DataAccess object)
To deal with the case of variables in different files/opendap addresses,
f can also be a dictionary with keys the variables and values the files
or opendap addresses. In this case, the keys must be:
- temp
- salt
- u
- v
- ssh
- misc, for lon, lat, depth, time and dimensions
or xy for lon,lat and x,ydim; z for depth and zdim, time for time
The output data (dict) is suitable to be used by data2roms, which
interpolates the data to ROMS 3d grid.
Also outputs an error/status string.
kargs:
inds, dict with dimension names/values (where time dim can be integer
or datetime)
settings, DataAccess object
extra, extra misc vars to load [(outKey0,fileVar0),...]
t_units, units of variable time, by default the att units is used
'''
sett=DataAccess()
inds={}
extra=[]
t_units=[]
if 'settings' in kargs.keys(): sett = kargs['settings']
if 'inds' in kargs.keys(): inds = kargs['inds']
if 'extra' in kargs.keys(): extra = kargs['extra']
if 't_units' in kargs.keys(): t_units = kargs['t_units']
res={}
msg=''
if not isinstance(f,dict) and not f.startswith('http') and not isfile(f):
msg='file not found %s' % f
if not quiet: print msg
return res, msg
# load nc files:
if not isinstance(f,dict):
f={'temp':f,'salt':f,'u':f,'v':f,'ssh':f,'misc':f}
if not f.has_key('xy'): f['xy'] = f['misc']
if not f.has_key('z'): f['z'] = f['misc']
if not f.has_key('time'): f['time'] = f['misc']
filesUsed=[]
ncUsed=[]
for i in f.keys():
if not quiet: print '(%s) loading from %s' % (i.ljust(5),f[i])
if i=='temp':
if f[i] in filesUsed: ncTemp=ncUsed[filesUsed.index(f[i])]
else:
ncTemp=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncTemp]
elif i=='salt':
if f[i] in filesUsed: ncSalt=ncUsed[filesUsed.index(f[i])]
else:
ncSalt=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncSalt]
elif i=='u':
if f[i] in filesUsed: ncU=ncUsed[filesUsed.index(f[i])]
else:
ncU=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncU]
elif i=='v':
if f[i] in filesUsed: ncV=ncUsed[filesUsed.index(f[i])]
else:
ncV=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncV]
elif i=='ssh':
if f[i] in filesUsed: ncSsh=ncUsed[filesUsed.index(f[i])]
else:
ncSsh=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncSsh]
elif i=='xy':
if f[i] in filesUsed: ncXy=ncUsed[filesUsed.index(f[i])]
else:
ncXy=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncXy]
elif i=='z':
if f[i] in filesUsed: ncZ=ncUsed[filesUsed.index(f[i])]
else:
ncZ=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncZ]
elif i=='time':
if f[i] in filesUsed: ncTime=ncUsed[filesUsed.index(f[i])]
else:
ncTime=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncTime]
elif i=='misc':
if f[i] in filesUsed: ncMisc=ncUsed[filesUsed.index(f[i])]
else:
ncMisc=netcdf.ncopen(f[i])
filesUsed+=[f[i]]
ncUsed+=[ncMisc]
# load dims:
if not quiet: print ' loading dims...'
dimsXy=netcdf.fdim(ncXy)
dimsZ =netcdf.fdim(ncZ)
res['NX']=dimsXy[sett.xdim]
res['NY']=dimsXy[sett.ydim]
###if sett.z_name:
if sett.zdim:
res['NZ']=dimsZ[sett.zdim]
else:
res['NZ']=1
# about horizontal inds:
if inds.has_key(sett.xdim) and len(inds[sett.xdim])==2 and not isinstance(inds[sett.xdim],basestring):
if not quiet: print ' calc horizontal inds...'
xlim=inds[sett.xdim]
ylim=inds[sett.ydim]
inds.pop(sett.xdim)
inds.pop(sett.ydim)
lon=netcdf.use(ncXy,sett.x_name,**inds)
if np.any(lon>360): lon=np.mod(lon,360.)
lat=netcdf.use(ncXy,sett.y_name,**inds)
i0,i1,j0,j1=calc.ij_limits(lon,lat,xlim,ylim,margin=3)
inds[sett.xdim]='%d:%d' % (i0,i1)
inds[sett.ydim]='%d:%d' % (j0,j1)
if not quiet: print ' loading lon, lat, depth...'
res['lon'] = netcdf.use(ncXy,sett.x_name,**inds)
if np.any(res['lon']>360): res['lon']=np.mod(res['lon'],360.)
res['lat'] = netcdf.use(ncXy,sett.y_name,**inds)
if sett.z_name:
res['depth'] = -netcdf.use(ncZ,sett.z_name,**inds)
else: res['depth']=False
if res['lon'].size!=res['lat'].size:
res['lon'],res['lat']=np.meshgrid(res['lon'],res['lat'])
# needed for griddata, later
# update nx,ny:
if inds.has_key(sett.xdim):
res['NY'],res['NX']=res['lon'].shape
# extra misc vars:
if len(extra):
for outKey,fileVar in extra:
if not quiet: print ' loading extra misc... %s %s' % (outKey,fileVar)
res[outKey]=netcdf.use(ncMisc,fileVar,**inds)
# time:
# file may have one or several times. If several, time dim must be given
# with kargs inds!
if not quiet: print ' loading time...'
if t_units:
times=netcdf.use(ncTime,sett.time_name)
times=netcdftime.num2date(times,t_units)
else:
times=netcdf.nctime(ncTime,sett.time_name)
if inds.has_key(sett.tdim):
try: tind=dts.parse_date(inds[sett.tdim])
except: tind=inds[sett.tdim] # is an integer, for instance
if isinstance(tind,datetime.datetime):
tind,=np.where(times==tind)
if tind.size:
tind=tind[0]
inds[sett.tdim]=tind # update inds to extract other variables
else:
Msg='date not found'
msg+='\n'+Msg
return res,msg+' ERROR'
date=times[tind]
if not quiet: print ' tind, date= %d %s' % (tind,date.isoformat(' '))
elif times.size==1:
date=times[0]
if not quiet: print ' date= %s' % date.isoformat(' ')
else: # must provide tind as input!!
Msg='several dates in file... provice tind!'
msg+='\n'+Msg
return res,msg+' ERROR'
res['date'] = date
empty3d=np.zeros([res['NZ'],res['NY'],res['NX']])
empty2d=np.zeros([res['NY'],res['NX']])
if 'temp' in f.keys():
if not quiet: print ' loading temp...'
if sett.temp_name in ncTemp.varnames: res['temp'] = netcdf.use(ncTemp,sett.temp_name,**inds)
else:
Msg='var %s not found' % 'temp'
msg+='\n'+Msg
if not quiet: print Msg
res['temp']=empty3d
if 'salt' in f.keys():
if not quiet: print ' loading salt...'
if sett.salt_name in ncSalt.varnames: res['salt'] = netcdf.use(ncSalt,sett.salt_name,**inds)
else:
Msg='var %s not found' % 'salt'
msg+='\n'+Msg
if not quiet: print Msg
res['salt']=empty3d
if 'u' in f.keys():
if not quiet: print ' loading u...'
if sett.u_name in ncU.varnames: res['u'] = netcdf.use(ncU,sett.u_name,**inds)
else:
Msg='var %s not found' % 'u'
msg+='\n'+Msg
if not quiet: print Msg
res['u']=empty3d
if 'v' in f.keys():
if not quiet: print ' loading v...'
if sett.v_name in ncV.varnames: res['v'] = netcdf.use(ncV,sett.v_name,**inds)
else:
Msg='var %s not found' % 'v'
msg+='\n'+Msg
if not quiet: print Msg
res['v']=empty3d
if 'ssh' in f.keys():
if not quiet: print ' loading ssh...'
if sett.ssh_name in ncSsh.varnames: res['ssh'] = netcdf.use(ncSsh,sett.ssh_name,**inds)
else:
Msg='var %s not found' % 'ssh'
msg+='\n'+Msg
if not quiet: print Msg
res['ssh']=empty2d
for nc in ncUsed:
try: nc.close()
except: pass
return res, msg