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 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 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 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 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 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