def slice_derived(self,var,ind,time,**opts):
plot= opts.get('plot',False)
ax = opts.get('ax',None)
if not isinstance(ind,dict): # slicez,k
coords=opts.get('coords','x,y,t').split(',')
else: # slicell
coords=opts.get('coords','d,z,t').split(',')
out=Data()
out.msg=self.check_slice('u',t=time) # any time dependent var could be
# used here!
if out.msg: return out
if var in ('div','divergence','diverg'): var='hdiv'
if var in ('vort','vorticity','rel vort'): var='rvort'
if not isinstance(ind,dict): # horizontal slices, else, slicell
if var in ('speed','ke'):
outuv=self.sliceuv(ind,time,**opts)
if outuv.msg: return outuv
if var=='speed': res=phys.speed(*outuv.v)
elif var=='ke': res=phys.ke(*outuv.v)
out=outuv
out.v=res
out.info['v']['name']=var
if var=='speed': out.info['v']['units']='metre second-1'
elif var=='ke': out.info['v']['units']='metre2 second-2'
return out
elif var in ('okubo','hdiv','rvort'):
if ind>=0: slc=self.slicek
else: slc=self.slicez
if ind=='bar': uname,vname,ind='ubar','vbar',0
else: uname,vname='u','v'
outu=slc(uname,ind,time,**opts)
outv=slc(vname,ind,time,**opts)
if outu.msg: return outu
elif outv.msg: return outv
# coords at rho needed for okubo','hdiv','rvort,so:
if any([i in coords for i in 'xy']):
x,y,h,m=self.grid.vars(ruvp='r')
if 'x' in coords:
if self.grid.use('spherical') in (1,'T'):
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='Distance',units='km')
if 'y' in coords:
if self.grid.use('spherical') in (1,'T'):
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Distance',units='km')
if 't' in coords: out.t=self.time[time]
if 'z' in coords and self.hasz(uname):
out.z=self.s_levels(time,k=ind,ruvpw='r')
out.info['z']=dict(name='Depth',units='m')
if var=='okubo':
res=phys.okubo(outu.v,outv.v,self.grid.pm,self.grid.pn)
out.v=res
out.info['v']['name']=var
out.info['v']['units']='second-2'
elif var=='hdiv':
res=phys.hor_div(outu.v,outv.v,self.grid.pm,self.grid.pn)
out.v=res
out.info['v']['name']=var
out.info['v']['units']='second-1'
if not out.x is None: out.x=out.x[1:-1,1:-1]
if not out.y is None: out.y=out.y[1:-1,1:-1]
if not out.z is None: out.z=out.z[1:-1,1:-1]
elif var=='rvort':
res=phys.vorticity(outu.v,outv.v,self.grid.pm,self.grid.pn)
out.v=res
out.info['v']['name']=var
out.info['v']['units']='second-1'
out.coordsReq=','.join(sorted(coords))
return out
else: # slice ll:
print 'TODO !!!!'
return out
def slicez(self,varname,ind,time=0,**opts):
if not self.hasz(varname):
return self.slicek(varname,ind,time,**opts)
surf_nans=opts.get('surf_nans',True)
spline=opts.get('spline',True)
coords=opts.get('coords',self._default_coords('slicez')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time)
if out.msg: return out##None,au
v=self.use(varname,SEARCHtime=time)
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname)[0])
zeta=self.use('zeta',SEARCHtime=time)
zeta=rt.rho2uvp(zeta,varname)
out.v=rt.slicez(v,m,h,zeta,self.s_params,ind,surf_nans,spline)
out.info['v']['name']=varname
if calc.isarray(ind):
out.info['v']['slice']='z= array %.2f to %.2f'%(ind.min(),ind.max())
else:
out.info['v']['slice']='z=%d'%ind
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords:
if 'x' in coords:
if self.grid.is_spherical:
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='Distance',units='km')
if 'y' in coords:
if self.grid.is_spherical:
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Distance',units='km')
if 'z' in coords:
out.z=ind+np.zeros(out.v.shape)
out.info['z']=dict(name='Depth',units='m')
if 't' in coords and self.hast(varname): out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'x' in coords: out.extra[0].x=out.x
if 'y' in coords: out.extra[0].y=out.y
out.extra[0].v=h
if h.max()>1000: cvals=200.,1000.
elif h.max()>200: cvals=50.,100.,200.
else: cvals=3
out.extra[0].config['field.plot']='contour'
out.extra[0].config['field.cvals']=cvals
out.extra[0].config['field.linecolors']='k'
out.extra[0].alias='bathy'
out.coordsReq=','.join(sorted(coords))
return out
def slice_derived(self, var, ind, time, **opts):
plot = opts.get('plot', False)
ax = opts.get('ax', None)
if not isinstance(ind, dict): # slicez,k
coords = opts.get('coords', 'x,y,t').split(',')
else: # slicell
coords = opts.get('coords', 'd,z,t').split(',')
out = Data()
out.msg = self.check_slice('u',
t=time) # any time dependent var could be
# used here!
if out.msg: return out
if var in ('div', 'divergence', 'diverg'): var = 'hdiv'
if var in ('vort', 'vorticity', 'rel vort'): var = 'rvort'
if not isinstance(ind, dict): # horizontal slices, else, slicell
if var in ('speed', 'ke'):
outuv = self.sliceuv(ind, time, **opts)
if outuv.msg: return outuv
if var == 'speed': res = phys.speed(*outuv.v)
elif var == 'ke': res = phys.ke(*outuv.v)
out = outuv
out.v = res
out.info['v']['name'] = var
if var == 'speed': out.info['v']['units'] = 'metre second-1'
elif var == 'ke': out.info['v']['units'] = 'metre2 second-2'
return out
elif var in ('okubo', 'hdiv', 'rvort'):
if ind >= 0: slc = self.slicek
else: slc = self.slicez
if ind == 'bar': uname, vname, ind = 'ubar', 'vbar', 0
else: uname, vname = 'u', 'v'
outu = slc(uname, ind, time, **opts)
outv = slc(vname, ind, time, **opts)
if outu.msg: return outu
elif outv.msg: return outv
# coords at rho needed for okubo','hdiv','rvort,so:
if any([i in coords for i in 'xy']):
x, y, h, m = self.grid.vars(ruvp='r')
if 'x' in coords:
if self.grid.use('spherical') in (1, 'T'):
out.x = x
out.info['x'] = dict(name='Longitude', units=r'$\^o$E')
else:
out.x = x / 1000.
out.info['x'] = dict(name='Distance', units='km')
if 'y' in coords:
if self.grid.use('spherical') in (1, 'T'):
out.y = y
out.info['y'] = dict(name='Latitude', units=r'$\^o$N')
else:
out.y = y / 1000.
out.info['y'] = dict(name='Distance', units='km')
if 't' in coords: out.t = self.time[time]
if 'z' in coords and self.hasz(uname):
out.z = self.s_levels(time, k=ind, ruvpw='r')
out.info['z'] = dict(name='Depth', units='m')
if var == 'okubo':
res = phys.okubo(outu.v, outv.v, self.grid.pm,
self.grid.pn)
out.v = res
out.info['v']['name'] = var
out.info['v']['units'] = 'second-2'
elif var == 'hdiv':
res = phys.hor_div(outu.v, outv.v, self.grid.pm,
self.grid.pn)
out.v = res
out.info['v']['name'] = var
out.info['v']['units'] = 'second-1'
if not out.x is None: out.x = out.x[1:-1, 1:-1]
if not out.y is None: out.y = out.y[1:-1, 1:-1]
if not out.z is None: out.z = out.z[1:-1, 1:-1]
elif var == 'rvort':
res = phys.vorticity(outu.v, outv.v, self.grid.pm,
self.grid.pn)
out.v = res
out.info['v']['name'] = var
out.info['v']['units'] = 'second-1'
out.coordsReq = ','.join(sorted(coords))
return out
else: # slice ll:
print 'TODO !!!!'
return out
def slicej(self,varname,ind,time=0,**opts):
coords=opts.get('coords',self._default_coords('slicej')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time,j=ind)
if out.msg: return out
v=self.use(varname,SEARCHtime=time,eta_SEARCH=ind)
# add mask if not masked:
if not np.ma.isMA(v):
m=self.grid.vars(ruvp=self.var_at(varname)[0],j=ind)[-1]
if v.ndim==2: m=np.tile(m,(v.shape[0],1))
v=np.ma.masked_where(m==0,v)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='j=%d'%ind
try: out.info['v']['units']=netcdf.vatt(self.name,varname,'units')
except: pass
# coords:
if 'z' in coords and v.ndim==2:
###### out.z=self.s_levels(time=time,ruvpw=self.var_at(varname),j=ind)
out.z=self.s_levels(time=time,loc=self.var_at(varname),j=ind)
out.info['z']=dict(name='Depth',units='m')
if any([i in coords for i in 'xyd']):
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname)[0],j=ind)
if 'd' in coords:
d=calc.distance(x,y)
if d[-1]-d[0]>1e4:
d=d/1000.
dunits='km'
else: dunits='m'
if v.ndim==2: d=np.tile(d,(v.shape[0],1))
out.d=d
out.info['d']=dict(name='Distance',units=dunits)
if 'x' in coords:
if v.ndim==2: x=np.tile(x,(v.shape[0],1))
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
if 'y' in coords:
if v.ndim==2: y=np.tile(y,(v.shape[0],1))
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
if 't' in coords and self.hast(varname): out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'd' in coords: out.extra[0].x=out.d[0]
if 'x' in coords: out.extra[0].y=out.x[0]
if 'y' in coords: out.extra[0].x=out.y[0]
out.extra[0].v=-h
out.extra[0].config['d1.plot']='fill_between'
out.extra[0].config['d1.y0']=-h.max()-(h.max()-h.min())/20.
out.extra[0].alias='bottom'
out.coordsReq=','.join(sorted(coords))
return out
def slicek(self,varname,ind,time=0,**opts):
coords=opts.get('coords',self._default_coords('slicek')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time,k=ind)
if out.msg: out
v=self.use(varname,SEARCHtime=time,s_SEARCH=ind)
# add mask if not masked:
if not np.ma.isMA(v):
m=self.grid.vars(ruvp=self.var_at(varname)[0])[-1]
v=np.ma.masked_where(m==0,v)
out.v=v
out.info['v']['name']=varname
if self.hasz(varname): out.info['v']['slice']='k=%d'%ind
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords:
if 'z' in coords and self.hasz(varname):
##### out.z=self.s_levels(time,k=ind,ruvpw=self.var_at(varname))
out.z=self.s_levels(time,k=ind,loc=self.var_at(varname))
out.info['z']=dict(name='Depth',units='m')
if any([i in coords for i in 'xy']):
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname)[0])
if 'x' in coords:
if self.grid.is_spherical:
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='Distance',units='km')
if 'y' in coords:
if self.grid.is_spherical:
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Distance',units='km')
if 't' in coords and self.hast(varname): out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'x' in coords: out.extra[0].x=out.x
if 'y' in coords: out.extra[0].y=out.y
out.extra[0].v=h
if h.max()>1000: cvals=200.,1000.
elif h.max()>200: cvals=50.,100.,200.
else: cvals=3
out.extra[0].config['field.plot']='contour'
out.extra[0].config['field.cvals']=cvals
out.extra[0].config['field.linecolors']='k'
out.extra[0].alias='bathy'
out.coordsReq=','.join(sorted(coords))
return out
def sliceiso(self,varname,iso,time,**opts):
'''
Depths where variable, increasing/dec with depth, has some value.
Output is masked where surface is higher/lower than value or where all
water column is lower/higher than value.
'''
coords=opts.get('coords',self._default_coords('sliceiso')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time)
if out.msg: return out
if not self.hasz(varname):
out.msg='a depth dependent variable is needed for sliceiso!'
return out
v=self.use(varname,SEARCHtime=time)
#### z=self.s_levels(time=time,ruvpw=self.var_at(varname))
z=self.s_levels(time=time,loc=self.var_at(varname))
v=rt.depthof(v,z,iso)
out.v=v
#out.info['v']['name']=varname
out.info['v']['name']='depth'
if isinstance(iso,np.ndarray) and iso.ndim==2: siso='2d'
else: siso=str(iso)
try:
out.info['v']['slice']='%s (%s) iso=%s'%(varname,netcdf.vatt(self.nc,varname,'units'),siso)
except:
out.info['v']['slice']='%s iso=%s'%(varname,siso)
out.info['v']['units']='metre'
# coords:
if any([i in coords for i in 'xy']):
x,y,h=self.grid.vars(ruvp=self.var_at(varname))[:3]
if 'x' in coords:
if self.grid.is_spherical:
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='Distance',units='km')
if 'y' in coords:
if self.grid.is_spherical:
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Distance',units='km')
if 'z' in coords:
# makes no sense... v is the depth!
coords.remove('z')
if 't' in coords and self.hast(varname): out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'x' in coords: out.extra[0].x=out.x
if 'y' in coords: out.extra[0].y=out.y
out.extra[0].v=h
if h.max()>1000: cvals=200.,1000.
elif h.max()>200: cvals=50.,100.,200.
else: cvals=3
out.extra[0].config['field.plot']='contour'
out.extra[0].config['field.cvals']=cvals
out.extra[0].config['field.linecolors']='k'
out.extra[0].alias='bathy'
out.coordsReq=','.join(sorted(coords))
return out
def time_series(self,varname,x,y,times=None,depth=None,**opts):
coords=opts.get('coords',self._default_coords('time_series')).split(',')
if times is None: times=range(0,self.time.size)
# depth or s_level: check is is float or if is negative!
isDepth=False
if not depth is None:
if calc.isiterable(depth): depth=np.asarray(depth)
if calc.isarray(depth):
isDepth=np.any(depth<0) or depth.kind!='i'
else: isDepth=depth<0 or np.asarray(depth).dtype.kind!='i'
out=Data()
if not depth is None and not isDepth:
out.msg=self.check_slice(varname,t=np.max(times),k=depth)
else:
out.msg=self.check_slice(varname,t=np.max(times))
if out.msg: return out
# find nearest point:
lon,lat,hr,mr=self.grid.vars(ruvp=self.var_at(varname))
dist=(lon-x)**2+(lat-y)**2
i,j=np.where(dist==dist.min())
i,j=i[0],j[0]
if not depth is None and not isDepth: arg={'s_SEARCH':depth}
else: arg={}
v=self.use(varname,xiSEARCH=j,etaSEARCH=i,SEARCHtime=times,**arg).T
# calculate depths:
if self.hasz(varname):
h=self.grid.h[i,j]
zeta=self.use('zeta',xiSEARCH=j,etaSEARCH=i,SEARCHtime=times)
h=h+0*zeta
#### z=rt.s_levels(h,zeta,self.s_params,rw=varname)
z=rt.s_levels(h,zeta,self.s_params,rw=self.var_at(varname)[1])
z=np.squeeze(z)
# depth slice:
if isDepth and self.hasz(varname):
if v.ndim==2:
# could use calc.griddata, but better use slicez cos data at
# different times may be independent!
if 0:
from matplotlib.dates import date2num
t=np.tile(date2num(self.time[times]),(v.shape[0],1))
v=calc.griddata(t,z,v,t[0],depth+np.zeros(t[0].shape),
extrap=opts.get('extrap',False),norm_xy=opts.get('norm_xy',False))
# norm_xy True may be needed!
# extrap also may be needed cos the 1st and last value may be masked!
else:
nt=len(times)
land_mask=np.ones((nt,1),dtype=v.dtype) # needed for slicez... not used here!
v,vm=rt.slicez(v[...,np.newaxis],land_mask,
self.grid.h[i,j]*np.ones((nt,1),dtype=v.dtype), # bottom depth
zeta[:,np.newaxis],self.s_params,depth,spline=opts.get('spline',True))
v=np.ma.masked_where(vm,v)
v=v[...,0]
else: # one time only
v=np.interp(depth,z,v,left=np.nan,right=np.nan)
v=np.ma.masked_where(np.isnan(v),v)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='time series'
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords
if 't' in coords and self.hast(varname):
if v.ndim==2:
out.t=np.tile(self.time[times],(v.shape[0],1))
from matplotlib.dates import date2num
out.tnum=np.tile(date2num(self.time[times]),(v.shape[0],1))
else: out.t=self.time[times]
out.info['t']['name']='Time'
out.info['tnum']=dict(name='Time',units=self.var_as['time']['units'])
if 'z' in coords and self.hasz(varname):
if not depth is None:
if not isDepth: out.z=z[depth,...]
else: out.z=depth+0*v
else: out.z=z
out.info['z']=dict(name='Depth',units='m')
if 'x' in coords:
out.x=lon[i,j]
if self.grid.is_spherical:
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='X-position',units='km')
if 'y' in coords:
out.y=lat[i,j]
if self.grid.is_spherical:
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Y-position',units='km')
out.coordsReq=','.join(sorted(coords))
return out
def slicell(self,varname,X,Y,time=0,**opts):
# x,y,z,v,m=[[]]*5
######## plot= opts.get('plot',False)
######### ax = opts.get('ax',None)
coords=opts.get('coords',self._default_coords('slicell')).split(',')
data = opts.get('data',False)
# dist = opts.get('dist',False)
extrap = opts.get('extrap',False)
# varOnly = opts.get('retv',False)
maskLimit = opts.get('lmask',0.5) # points where interpolated mask are above
# this value are considered as mask!
# Most strict value is 0
out=Data()
out.msg=self.check_slice(varname,t=time)
if out.msg: return out#None,aux
X=np.asarray(X)
Y=np.asarray(Y)
if X.ndim>1: X=np.squeeze(X)
if Y.ndim>1: Y=np.squeeze(X)
# if varname not in netcdf.varnames(self.name):
# print ':: variable %s not found' % varname
# return x,y,z,v,m
#
# if time>=self.TIME:
# print 't = %d exceeds TIME dimension (%d)' % (time,self.TIME)
# return x,y,z,v,m
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname))
if True: # extrat only portion of data needed:
## print 'start', x.shape,y.shape,X.shape
i0,i1,j0,j1=calc.ij_limits(x, y, (X.min(),X.max()),(Y.min(),Y.max()), margin=1)
## print 'end'
xi='%d:%d'%(i0,i1)
eta='%d:%d'%(j0,j1)
if data is False: V=self.use(varname,SEARCHtime=time,xi_SEARCH=xi,eta_SEARCH=eta)
else: v=data[...,j0:j1,i0:i1]
x=x[j0:j1,i0:i1]
y=y[j0:j1,i0:i1]
h=h[j0:j1,i0:i1]
m=m[j0:j1,i0:i1]
else:
if data is False: V=self.use(varname,SEARCHtime=time)
else: v=data
if V.ndim==3:
v=calc.griddata(x,y,V,X,Y,extrap=extrap,mask2d=m==0, keepMaskVal=maskLimit)
elif V.ndim==2:
v=calc.griddata(x,y,np.ma.masked_where(m==0,V),X,Y,extrap=extrap, keepMaskVal=maskLimit)
# coords:
if 'z' in coords and V.ndim==3:
out.z=self.path_s_levels(time,X,Y,rw=varname[0])
if 'd' in coords:
d=calc.distance(X,Y)
if v.ndim==2: d=np.tile(d,(v.shape[0],1))
out.d=d
if 'x' in coords:
if v.ndim==2: X=np.tile(X,(v.shape[0],1))
out.x=X
if 'y' in coords:
if v.ndim==2: Y=np.tile(Y,(v.shape[0],1))
out.y=Y
if 't' in coords: out.t=self.time[time]
# # X, Y, dist:
# if dist:
# Dist=calc.distance(X,Y)
# if v.ndim==3:
# Dist=np.tile(Dist,(v.shape[0],1))
# else:
# if v.ndim==3:
# X=np.tile(X,(v.shape[0],1))
# Y=np.tile(Y,(v.shape[0],1))
#
# if dist:
# return Dist,Z,V
# else:
# return X,Y,Z,V
#
# if plot:
# if not ax: ax=pl.gca()
# if v.ndim==2:
# if 'x' in coords:
# p=ax.pcolormesh(out.x,out.z,v)
### ax.plot(aux.x[0],-h)
# elif 'y' in coords:
# p=ax.pcolormesh(out.y,out.z,v)
### ax.plot(aux.y[0],-h)
# else:
# p=ax.pcolormesh(out.d,out.z,v)
#### ax.plot(aux.d[0],-h)
##
# pl.colorbar(p,shrink=.7)
## elif v.ndim==1:
# if 'x' in coords:
# ax.plot(out.x,v)
# elif 'y' in coords:
# ax.plot(out.y,v)
# else:
# ax.plot(out.d,v)
#
out.v=v
out.coordsReq=','.join(sorted(coords))
return out###v,aux
def slicell(self,varname,X,Y,time=0,**opts):
coords=opts.get('coords',self._default_coords('slicell')).split(',')
data = opts.get('data',False)
extrap = opts.get('extrap',False)
maskLimit = opts.get('lmask',0.5) # points where interpolated mask are above
# this value are considered as mask!
# Most strict value is 0
out=Data()
out.msg=self.check_slice(varname,t=time)
if out.msg: return out#None,aux
X=np.asarray(X)
Y=np.asarray(Y)
if X.ndim>1: X=np.squeeze(X)
if Y.ndim>1: Y=np.squeeze(X)
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname)[0])
if True: # extrat only portion of data needed:
i0,i1,j0,j1=calc.ij_limits(x, y, (X.min(),X.max()),(Y.min(),Y.max()), margin=1)
xi='%d:%d'%(i0,i1)
eta='%d:%d'%(j0,j1)
if data is False: V=self.use(varname,SEARCHtime=time,xi_SEARCH=xi,eta_SEARCH=eta)
else: v=data[...,j0:j1,i0:i1]
x=x[j0:j1,i0:i1]
y=y[j0:j1,i0:i1]
#h=h[j0:j1,i0:i1] # not used
m=m[j0:j1,i0:i1]
else:
if data is False: V=self.use(varname,SEARCHtime=time)
else: v=data
if V.ndim==3:
v=calc.griddata(x,y,V,X,Y,extrap=extrap,mask2d=m==0, keepMaskVal=maskLimit)
elif V.ndim==2:
v=calc.griddata(x,y,np.ma.masked_where(m==0,V),X,Y,extrap=extrap, keepMaskVal=maskLimit)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='path npts=%d'%X.size
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords:
if 'z' in coords and V.ndim==3:
inds=dict(xi=(i0,i1),eta=(j0,j1))
######### out.z=self.path_s_levels(time,X,Y,rw=varname[0],inds=inds)
out.z=self.path_s_levels(time,X,Y,rw=self.var_at(varname)[1],inds=inds)
if 'd' in coords:
d=calc.distance(X,Y)
if v.ndim==2: d=np.tile(d,(v.shape[0],1))
out.d=d
if 'x' in coords:
if v.ndim==2: X=np.tile(X,(v.shape[0],1))
out.x=X
if 'y' in coords:
if v.ndim==2: Y=np.tile(Y,(v.shape[0],1))
out.y=Y
if 't' in coords and self.hast(varname): out.t=self.time[time]
out.coordsReq=','.join(sorted(coords))
return out
def slicek(self,varname,ind,time=0,**opts):
coords=opts.get('coords',self._default_coords('slicek')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time,k=ind)
if out.msg: out
v=self.use(varname,SEARCHtime=time,s_SEARCH=ind)
# add mask if not masked:
if not np.ma.isMA(v):
m=self.grid.vars(ruvp=self.var_at(varname))[-1]
v=np.ma.masked_where(m==0,v)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='k=%d'%ind
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords:
if 'z' in coords and self.hasz(varname):
out.z=self.s_levels(time,k=ind,ruvpw=self.var_at(varname))
out.info['z']=dict(name='Depth',units='m')
if any([i in coords for i in 'xy']):
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname))
if 'x' in coords:
if self.grid.is_spherical:
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='Distance',units='km')
if 'y' in coords:
if self.grid.is_spherical:
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Distance',units='km')
if 't' in coords: out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'x' in coords: out.extra[0].x=out.x
if 'y' in coords: out.extra[0].y=out.y
out.extra[0].v=h
if h.max()>1000: cvals=200.,1000.
elif h.max()>200: cvals=50.,100.,200.
else: cvals=3
out.extra[0].config['field.plot']='contour'
out.extra[0].config['field.cvals']=cvals
out.extra[0].config['field.linecolors']='k'
out.extra[0].alias='bathy'
out.coordsReq=','.join(sorted(coords))
return out
def slicez(self,varname,ind,time=0,**opts):
if not self.hasz(varname):
return self.slicek(varname,ind,time,**opts)
surf_nans=opts.get('surf_nans',True)
spline=opts.get('spline',True)
coords=opts.get('coords',self._default_coords('slicez')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time)
if out.msg: return out##None,au
v=self.use(varname,SEARCHtime=time)
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname))
zeta=self.use('zeta',SEARCHtime=time)
zeta=rt.rho2uvp(zeta,varname)
v,mask=rt.slicez(v,m,h,zeta,self.s_params,ind,surf_nans,spline)
v=np.ma.masked_where(mask,v)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='z=%d'%ind
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords:
if 'x' in coords:
if self.grid.is_spherical:
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='Distance',units='km')
if 'y' in coords:
if self.grid.is_spherical:
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Distance',units='km')
if 'z' in coords:
out.z=ind+np.zeros(v.shape)
out.info['z']=dict(name='Depth',units='m')
if 't' in coords: out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'x' in coords: out.extra[0].x=out.x
if 'y' in coords: out.extra[0].y=out.y
out.extra[0].v=h
if h.max()>1000: cvals=200.,1000.
elif h.max()>200: cvals=50.,100.,200.
else: cvals=3
out.extra[0].config['field.plot']='contour'
out.extra[0].config['field.cvals']=cvals
out.extra[0].config['field.linecolors']='k'
out.extra[0].alias='bathy'
out.coordsReq=','.join(sorted(coords))
return out
def slicej(self,varname,ind,time=0,**opts):
coords=opts.get('coords',self._default_coords('slicej')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time,j=ind)
if out.msg: return out
v=self.use(varname,SEARCHtime=time,eta_SEARCH=ind)
# add mask if not masked:
if not np.ma.isMA(v):
m=self.grid.vars(ruvp=self.var_at(varname),j=ind)[-1]
if v.ndim==2: m=np.tile(m,(v.shape[0],1))
v=np.ma.masked_where(m==0,v)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='j=%d'%ind
try: out.info['v']['units']=netcdf.vatt(self.name,varname,'units')
except: pass
# coords:
if 'z' in coords and v.ndim==2:
out.z=self.s_levels(time=time,ruvpw=self.var_at(varname),j=ind)
out.info['z']=dict(name='Depth',units='m')
if any([i in coords for i in 'xyd']):
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname),j=ind)
if 'd' in coords:
d=calc.distance(x,y)
if d[-1]-d[0]>1e4:
d=d/1000.
dunits='km'
else: dunits='m'
if v.ndim==2: d=np.tile(d,(v.shape[0],1))
out.d=d
out.info['d']=dict(name='Distance',units=dunits)
if 'x' in coords:
if v.ndim==2: x=np.tile(x,(v.shape[0],1))
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
if 'y' in coords:
if v.ndim==2: y=np.tile(y,(v.shape[0],1))
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
if 't' in coords: out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'd' in coords: out.extra[0].x=out.d[0]
if 'x' in coords: out.extra[0].y=out.x[0]
if 'y' in coords: out.extra[0].x=out.y[0]
out.extra[0].v=-h
out.extra[0].config['1d.plot']='fill_between'
out.extra[0].config['1d.y0']=-h.max()-(h.max()-h.min())/20.
out.extra[0].alias='bottom'
out.coordsReq=','.join(sorted(coords))
return out
def time_series(self,varname,x,y,times=None,depth=None,**opts):
######## plot= opts.get('plot',False)
######## ax = opts.get('ax',None)
coords=opts.get('coords',self._default_coords('sliceiso')).split(',')
if times is None: times=range(0,self.time.size)
out=Data()
out.msg=self.check_slice(varname,t=np.max(times),k=depth)
if out.msg: return out###None,aux
## t,z,v=[[]]*3
#
# RetVarOnly=False
# savename=False
# retMsg=False
# nearest=True # UNIQUE case Currently
# plot=False
#
# if 'retvar' in opts.keys(): RetVarOnly = opts['retvar']
# if 'savename' in opts.keys(): savename = opts['savename']
# if 'msg' in opts.keys(): retMsg = opts['msg']
# if 'nearest' in opts.keys(): nearest = opts['msg']
# if 'plot' in opts.keys(): plot = opts['msg']
#
#
# if varname not in netcdf.varnames(self.name):
# msg=':: variable %s not found' % varname
# if retMsg: return t,z,v,msg
# else:
# print msg
# return t,z,v
#
# isW=varname=='w'
# hasZ=self.hasz(varname)
#
# if not depth is False and hasZ :
# if isW and depth >= self.S_W:
# msg='k = %d exceeds S_W dimension (%d)' % (depth,self.S_W)
# if retMsg: return t,z,v,msg
# else:
# print msg
# return t,z,v
#
# elif depth >= self.S_RHO:
# msg='k = %d exceeds S_RHO dimension (%d)' % (depth,self.S_RHO)
# if retMsg: return t,z,v,msg
# else:
# print msg
# return t,z,v
#
# if times is False:
# times=0,len(self.tdays)
#
# if self.hast(varname) and times[-1]>self.TIME:
# msg='t = %d exceeds TIME dimension (%d)' % (times[-1],self.TIME)
# if retMsg: return t,z,v,msg
# else:
# print msg
# return t,z,v
#
# find nearest point:
lon,lat,hr,mr=self.grid.vars(ruvp=self.var_at(varname))
dist=(lon-x)**2+(lat-y)**2
i,j=np.where(dist==dist.min())
i,j=i[0],j[0]
if depth>=0: arg={'s_SEARCH':depth}
else: arg={}
v=self.use(varname,xiSEARCH=j,etaSEARCH=i,SEARCHtime=times,**arg).T
# calculate depths:
if self.hasz(varname):
h=self.grid.h[i,j]
zeta=self.use('zeta',xiSEARCH=j,etaSEARCH=i,SEARCHtime=times)
h=h+0*zeta
z=rt.s_levels(h,zeta,self.s_params,rw=varname)
z=np.squeeze(z)
# depth slice:
if not depth is None and self.hasz(varname) and depth<0:
if v.ndim==2:
from matplotlib.dates import date2num
t=np.tile(date2num(self.time[times]),(v.shape[0],1))
v=calc.griddata(t,z,v,t[0],depth+np.zeros(t[0].shape),
extrap=opts.get('extrap',False),norm_xy=opts.get('norm_xy',False))
# norm_xy True may be needed!
# extrap also may be needed cos the 1st and last value may be masked!
else: # one time only
v=np.interp(depth,z,v,left=np.nan,right=np.nan)
v=np.ma.masked_where(np.isnan(v),v)
# coords
if 't' in coords:
if v.ndim==2:
out.t=np.tile(self.time[times],(v.shape[0],1))
from matplotlib.dates import date2num
out.tnum=np.tile(date2num(self.time[times]),(v.shape[0],1))
else: out.t=self.time[times]
if 'z' in coords and self.hasz(varname):
if not depth is None:
if depth>=0: out.z=z[depth,...]
else: out.z=depth+0*v
else: out.z=z
if 'x' in coords: out.x=lon[i,j]
if 'y' in coords: out.y=lat[i,j]
## if plot and v.ndim:
## if not ax:
## ax=pl.gca()
## opts['ax']=ax
##
## if v.ndim==2:
## p=ax.pcolormesh(out.tnum,out.z,v)
## #ax.xaxis_date()
## pl.colorbar(p,shrink=.7)
## elif v.size>1:
## if out.t.size>1: # time series:
## ax.plot(out.t,v)
## else: # vertical profile:
## ax.plot(v,out.z)
out.v=v
out.coordsReq=','.join(sorted(coords))
return out##v,aux
def sliceiso(self,varname,iso,time,**opts):
'''
Depths where variable, increasing/dec with depth, has some value.
Output is masked where surface is higher/lower than value or where all
water column is lower/higher than value.
'''
coords=opts.get('coords',self._default_coords('sliceiso')).split(',')
out=Data()
out.msg=self.check_slice(varname,t=time)
if out.msg: return out
if not self.hasz(varname):
out.msg='a depth dependent variable is needed for sliceiso!'
return out
v=self.use(varname,SEARCHtime=time)
z=self.s_levels(time=time,ruvpw=self.var_at(varname))
v=rt.depthof(v,z,iso)
out.v=v
out.info['v']['name']=varname
if isinstance(iso,np.ndarray) and iso.ndim==2: siso='2d'
else: siso=str(iso)
out.info['v']['slice']='iso=%s'%siso
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords:
if any([i in coords for i in 'xy']):
x,y,h=self.grid.vars(ruvp=self.var_at(varname))[:3]
if 'x' in coords:
if self.grid.is_spherical:
out.x=x
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x/1000.
out.info['x']=dict(name='Distance',units='km')
if 'y' in coords:
if self.grid.is_spherical:
out.y=y
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y/1000.
out.info['y']=dict(name='Distance',units='km')
if 'z' in coords:
# makes no sense... v is the depth!
coords.remove('z')
if 't' in coords: out.t=self.time[time]
if v.ndim==2:
out.extra=[Data()]
if 'x' in coords: out.extra[0].x=out.x
if 'y' in coords: out.extra[0].y=out.y
out.extra[0].v=h
if h.max()>1000: cvals=200.,1000.
elif h.max()>200: cvals=50.,100.,200.
else: cvals=3
out.extra[0].config['field.plot']='contour'
out.extra[0].config['field.cvals']=cvals
out.extra[0].config['field.linecolors']='k'
out.extra[0].alias='bathy'
out.coordsReq=','.join(sorted(coords))
return out
def time_series(self,varname,x,y,times=None,depth=None,**opts):
coords=opts.get('coords',self._default_coords('time_series')).split(',')
if times is None: times=range(0,self.time.size)
# depth or s_level: check is is float or if is negative!
isDepth=False
if not depth is None:
if calc.isiterable(depth): depth=np.asarray(depth)
if calc.isarray(depth):
isDepth=np.any(depth<0) or depth.kind!='i'
else: isDepth=depth<0 or np.asarray(depth).dtype.kind!='i'
out=Data()
if not depth is None and not isDepth:
out.msg=self.check_slice(varname,t=np.max(times),k=depth)
else:
out.msg=self.check_slice(varname,t=np.max(times))
if out.msg: return out
# find nearest point:
lon,lat,hr,mr=self.grid.vars(ruvp=self.var_at(varname))
dist=(lon-x)**2+(lat-y)**2
i,j=np.where(dist==dist.min())
i,j=i[0],j[0]
if not depth is None and not isDepth: arg={'s_SEARCH':depth}
else: arg={}
v=self.use(varname,xiSEARCH=j,etaSEARCH=i,SEARCHtime=times,**arg).T
# calculate depths:
if self.hasz(varname):
h=self.grid.h[i,j]
zeta=self.use('zeta',xiSEARCH=j,etaSEARCH=i,SEARCHtime=times)
h=h+0*zeta
#### z=rt.s_levels(h,zeta,self.s_params,rw=varname)
z=rt.s_levels(h,zeta,self.s_params,rw=self.var_at(varname)[1])
z=np.squeeze(z)
# depth slice:
if isDepth and self.hasz(varname):
if v.ndim==2:
# could use calc.griddata, but better use slicez cos data at
# different times may be independent!
if 0:
from matplotlib.dates import date2num
t=np.tile(date2num(self.time[times]),(v.shape[0],1))
v=calc.griddata(t,z,v,t[0],depth+np.zeros(t[0].shape),
extrap=opts.get('extrap',False),norm_xy=opts.get('norm_xy',False))
# norm_xy True may be needed!
# extrap also may be needed cos the 1st and last value may be masked!
else:
nt=len(times)
land_mask=np.ones((nt,1),dtype=v.dtype) # needed for slicez... not used here!
v,vm=rt.slicez(v[...,np.newaxis],land_mask,
self.grid.h[i,j]*np.ones((nt,1),dtype=v.dtype), # bottom depth
zeta[:,np.newaxis],self.s_params,depth,spline=opts.get('spline',True))
v=np.ma.masked_where(vm,v)
v=v[...,0]
else: # one time only
v=np.interp(depth,z,v,left=np.nan,right=np.nan)
v=np.ma.masked_where(np.isnan(v),v)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='time series'
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords
if 't' in coords and self.hast(varname):
if v.ndim==2:
out.t=np.tile(self.time[times],(v.shape[0],1))
from matplotlib.dates import date2num
out.tnum=np.tile(date2num(self.time[times]),(v.shape[0],1))
else: out.t=self.time[times]
out.info['t']['name']='Time'
out.info['tnum']=dict(name='Time',units=self.var_as['time']['units'])
if 'z' in coords and self.hasz(varname):
if not depth is None:
if not isDepth: out.z=z[depth,...]
else: out.z=depth+0*v
else: out.z=z
out.info['z']=dict(name='Depth',units='m')
if 'x' in coords:
out.x=lon[i,j]
if self.grid.is_spherical:
out.info['x']=dict(name='Longitude',units=r'$\^o$E')
else:
out.x=x#/1000.
out.info['x']=dict(name='X-position',units='m')
if 'y' in coords:
out.y=lat[i,j]
if self.grid.is_spherical:
out.info['y']=dict(name='Latitude',units=r'$\^o$N')
else:
out.y=y#/1000.
out.info['y']=dict(name='Y-position',units='m')
out.coordsReq=','.join(sorted(coords))
return out
def slicell(self,varname,X,Y,time=0,**opts):
coords=opts.get('coords',self._default_coords('slicell')).split(',')
data = opts.get('data',False)
extrap = opts.get('extrap',False)
maskLimit = opts.get('lmask',0.5) # points where interpolated mask are above
# this value are considered as mask!
# Most strict value is 0
out=Data()
out.msg=self.check_slice(varname,t=time)
if out.msg: return out#None,aux
X=np.asarray(X)
Y=np.asarray(Y)
if X.ndim>1: X=np.squeeze(X)
if Y.ndim>1: Y=np.squeeze(X)
x,y,h,m=self.grid.vars(ruvp=self.var_at(varname)[0])
if True: # extrat only portion of data needed:
i0,i1,j0,j1=calc.ij_limits(x, y, (X.min(),X.max()),(Y.min(),Y.max()), margin=1)
xi='%d:%d'%(i0,i1)
eta='%d:%d'%(j0,j1)
if data is False: V=self.use(varname,SEARCHtime=time,xi_SEARCH=xi,eta_SEARCH=eta)
else: v=data[...,j0:j1,i0:i1]
x=x[j0:j1,i0:i1]
y=y[j0:j1,i0:i1]
#h=h[j0:j1,i0:i1] # not used
m=m[j0:j1,i0:i1]
else:
if data is False: V=self.use(varname,SEARCHtime=time)
else: v=data
if V.ndim==3:
v=calc.griddata(x,y,V,X,Y,extrap=extrap,mask2d=m==0, keepMaskVal=maskLimit)
elif V.ndim==2:
v=calc.griddata(x,y,np.ma.masked_where(m==0,V),X,Y,extrap=extrap, keepMaskVal=maskLimit)
out.v=v
out.info['v']['name']=varname
out.info['v']['slice']='path npts=%d'%X.size
try: out.info['v']['units']=netcdf.vatt(self.nc,varname,'units')
except: pass
# coords:
if 'z' in coords and V.ndim==3:
inds=dict(xi=(i0,i1),eta=(j0,j1))
######### out.z=self.path_s_levels(time,X,Y,rw=varname[0],inds=inds)
out.z=self.path_s_levels(time,X,Y,rw=self.var_at(varname)[1],inds=inds)
if 'd' in coords:
d=calc.distance(X,Y)
if v.ndim==2: d=np.tile(d,(v.shape[0],1))
out.d=d
if 'x' in coords:
if v.ndim==2: X=np.tile(X,(v.shape[0],1))
out.x=X
if 'y' in coords:
if v.ndim==2: Y=np.tile(Y,(v.shape[0],1))
out.y=Y
if 't' in coords and self.hast(varname): out.t=self.time[time]
out.coordsReq=','.join(sorted(coords))
return out