def load_vars(self,vars):
var,nc=netcdf.var(self.name)
varnames=var.keys()
for i in vars:
if not self.quiet: print(':: loading var ', i)
if isinstance(i,dict):
iname, iopts = i.items()[0]
elif isinstance(i,basestring):
iname=i
iopts=i
elif isinstance(i,tuple):
iname=False
iopts=i
if not isinstance(iopts,tuple):
iopts=(iopts,)
found=0
if not hasattr(self,'var_as'): self.var_as={}
for j in iopts:
if not iname: iname=j
if j in varnames:
setattr(self,iname,var[j][:])
found=1
if not self.quiet: print(' - found %s as %s' % (iname,j))
# store original name and other info, like units
try: units=var[j].atts['units'].value
except: units=''
self.var_as[iname]={'name':j,'units':units}
break
if not found and not self.quiet: print(':: %s not found in %s' % (str(iopts),self.name))
nc.close()
def load_vars(self,vars):
var=netcdf.var(self.nc)
for i in vars:
if not self.quiet: print(':: loading var %s'%i)
if isinstance(i,dict):
iname, iopts = list(i.items())[0]
elif cb.isstr(i):
iname=i
if iname.startswith('@'): iopts=iname[1:]
else: iopts=iname
if not isinstance(iopts,tuple):
iopts=(iopts,)
found=0
if not hasattr(self,'var_as'): self.var_as={}
for j in iopts:
if j in var:
if iname.startswith('@'): # variable will be loaded only when needed!
iname=iname[1:]
# can't use self._get inside lambda function... j is always the last element!
# so, instead of:
# setattr(self.__class__, iname, property(fget=lambda self: self._get(j)))
# a propVar variable is used, storing the riht j value:
ob=propVar(j)
setattr(self.__class__,iname,property(fget=ob.get))##lambda self: self.getx(vv)))
else:
setattr(self,iname,var[j][:])
found=1
if not self.quiet: print(' - found %s as %s'%(iname,j))
# store original name and other info, like units
try: units=var[j].atts['units'].value
except: units=''
self.var_as[iname]={'name':j,'units':units}
break
if not found and not self.quiet: print(':: %s not found in %s'%(str(iopts),self.name))
def load_vars(self,vars):
var=netcdf.var(self.nc)
for i in vars:
if not self.quiet: print(':: loading var %s'%i)
if isinstance(i,dict):
iname, iopts = list(i.items())[0]
elif cb.isstr(i):
iname=i
if iname.startswith('@'): iopts=iname[1:]
else: iopts=iname
if not isinstance(iopts,tuple):
iopts=(iopts,)
found=0
if not hasattr(self,'var_as'): self.var_as={}
for j in iopts:
if j in var:
if iname.startswith('@'): # variable will be loaded only when needed!
iname=iname[1:]
# can't use self._get inside lambda function... j is always the last element!
# so, instead of:
# setattr(self.__class__, iname, property(fget=lambda self: self._get(j)))
# a propVar variable is used, storing the riht j value:
ob=propVar(j)
setattr(self.__class__,iname,property(fget=ob.get))##lambda self: self.getx(vv)))
else:
setattr(self,iname,var[j][:])
found=1
if not self.quiet: print(' - found %s as %s'%(iname,j))
# store original name and other info, like units
try: units=var[j].atts['units'].value
except: units=''
self.var_as[iname]={'name':j,'units':units}
break
if not found and not self.quiet: print(':: %s not found in %s'%(str(iopts),self.name))
def load_vars(self, vars):
var, nc = netcdf.var(self.name)
varnames = var.keys()
for i in vars:
if not self.quiet: print(':: loading var ', i)
if isinstance(i, dict):
iname, iopts = i.items()[0]
elif isinstance(i, basestring):
iname = i
iopts = i
elif isinstance(i, tuple):
iname = False
iopts = i
if not isinstance(iopts, tuple):
iopts = (iopts, )
found = 0
if not hasattr(self, 'var_as'): self.var_as = {}
for j in iopts:
if not iname: iname = j
if j in varnames:
setattr(self, iname, var[j][:])
found = 1
if not self.quiet: print(' - found %s as %s' % (iname, j))
# store original name and other info, like units
try:
units = var[j].atts['units'].value
except:
units = ''
self.var_as[iname] = {'name': j, 'units': units}
break
if not found and not self.quiet:
print(':: %s not found in %s' % (str(iopts), self.name))
nc.close()
def load_vars(self,vars):
#self.quiet=0
var=netcdf.var(self.nc)
varnames=var.keys()
for i in vars:
if not self.quiet: print ':: loading var ', i
if isinstance(i,dict):
iname, iopts = i.items()[0]
elif isinstance(i,basestring):
iname=i
if iname.startswith('@'): iopts=iname[1:]
else: iopts=iname
if not isinstance(iopts,tuple):
iopts=(iopts,)
found=0
if not hasattr(self,'var_as'): self.var_as={}
for j in iopts:
if j in varnames:
if iname.startswith('@'):
iname=iname[1:]
setattr(Common, iname, property(fget=lambda self: self.use(j)))
# not working as expected! self.use is executed in the end, for last variable only!
# check later...
else:
setattr(self,iname,var[j][:])
found=1
if not self.quiet: print ' - found %s as %s' % (iname,j)
# store original name and other info, like units
try: units=var[j].atts['units'].value
except: units=''
self.var_as[iname]={'name':j,'units':units}
break
if not found and not self.quiet: print ':: %s not found in %s' % (str(iopts),self.name)
def load_vars(self,vars):
#self.quiet=0
var=netcdf.var(self.nc)
varnames=var.keys()
for i in vars:
if not self.quiet: print ':: loading var ', i
if isinstance(i,dict):
iname, iopts = i.items()[0]
elif isinstance(i,basestring):
iname=i
if iname.startswith('@'): iopts=iname[1:]
else: iopts=iname
if not isinstance(iopts,tuple):
iopts=(iopts,)
found=0
if not hasattr(self,'var_as'): self.var_as={}
for j in iopts:
if j in varnames:
if iname.startswith('@'):
iname=iname[1:]
setattr(Common, iname, property(fget=lambda self: self.use(j)))
# not working as expected! self.use is executed in the end, for last variable only!
# check later...
else:
setattr(self,iname,var[j][:])
found=1
if not self.quiet: print ' - found %s as %s' % (iname,j)
# store original name and other info, like units
try: units=var[j].atts['units'].value
except: units=''
self.var_as[iname]={'name':j,'units':units}
break
if not found and not self.quiet: print ':: %s not found in %s' % (str(iopts),self.name)
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 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'
