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 if 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=vis.Data()
out.label='time_series'
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))
lon,lat,hr,mr=self.grid.vars(ruvp=self.vloc(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):
if 'z' in self.vaxes(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=rt.s_levels(h,zeta,self.s_params,rw=self.vloc(varname)[1])
z=np.squeeze(z)
# depth slice:
### if isDepth and self.hasz(varname):
if isDepth and 'z' in self.vaxes(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=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,
surface_masked=opts.get('surf_mask',True),
spline=opts.get('spline',True))[...,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 't' in coords and 't' in self.vaxes(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 'z' in coords and 'z' in self.vaxes(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.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.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 slicez(self,varname,ind,time=0,**opts):
surf_mask=opts.get('surf_mask',True)
spline=opts.get('spline',True)
coords=opts.get('coords',self._default_coords('slicez')).split(',')
out=vis.Data()
out.label='slicez'
out.msg=self.check_slice(varname,t=time)
if out.msg: return out
if not 'z' in self.vaxes(varname):
return self.slicek(varname,ind,time,**opts)
v=self.use(varname,SEARCHtime=time)
### x,y,h,m=self.grid.vars(ruvp=self.var_at(varname)[0])
x,y,h,m=self.grid.vars(ruvp=self.vloc(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_mask,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.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.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 't' in self.vaxes(varname): out.t=self.time[time]
if out.v.ndim==2:
out.extra=[vis.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.cmap']='k'
out.extra[0].label='bathy'
out.coordsReq=','.join(sorted(coords))
# about projection:
out.set_projection(self.grid.proj_info['basemap_opts'])
return out
def plot(self,coords='auto',proj='auto',labels=True,extras=True,isExtra=0,**kargs):
ax=kargs.pop('ax',None)
if ax: self.ax=ax
parent=kargs.pop('inherit',0)
if parent:
self.inherit(parent)
isExtra=1
if isExtra: labels=False
debug_lev=kargs.pop('debug_level',0)
self.set_param(**kargs)
# make vfield vars 2d to simplify the process:
if isinstance(self.v,tuple) and self.v[0].ndim==1:
self.x=self.x[:,np.newaxis]
self.y=self.y[:,np.newaxis]
self.v=self.v[0][:,np.newaxis],self.v[1][:,np.newaxis]
try:
if isinstance(self.v,tuple):
ndim=self.v[0].ndim
vshape=self.v[0].shape
else:
ndim=self.v.ndim
vshape=self.v.shape
except:
ndim=0
vshape=()
x,y,xname,yname=None,None,None,None
if coords=='auto':
if ndim==2:
if not self.x is None and (self.x.ndim==2 or self.x.size==vshape[1]): x,xname=self.x,'x'
elif not self.d is None and (self.d.ndim==2 or self.d.size==vshape[1]): x,xname=self.d,'d'
elif not self.t is None and (self.t.ndim==2 or self.t.size==vshape[1]): x,xname=self.t,'t'
elif not self.tnum is None and (self.tnum.ndim==2 or self.tnum.size==vshape[1]): x,xname=self.tnum,'tnum'
elif not self.y is None and (self.y.ndim==2 or self.y.size==vshape[1]): x,xname=self.y,'y'
if not self.y is None and (self.y.ndim==2 or self.y.size==vshape[0]): y,yname=self.y,'y'
elif not self.z is None and (self.z.ndim==2 or self.z.size==vshape[0]): y,yname=self.z,'z'
elif ndim==1:
y,yname=self.v,'v'
if not self.d is None and self.d.ndim==1: x,xname=self.d,'d'
elif not self.t is None and (calc.isarray(self.t) and self.t.ndim==1): x,xname=self.t,'t'
elif not self.x is None and self.x.ndim==1: x,xname=self.x,'x'
elif not self.y is None and self.y.ndim==1: x,xname=self.y,'y'
elif not self.z is None and self.z.ndim==1:
y,yname=self.z,'z'
x,xname=self.v,'v'
if ndim==2 and proj=='auto' and xname=='x' and yname=='y' and\
np.all(x>=-360) and np.all(x<=360) and np.all(y>=-90) and np.all(y<=90): proj=True
elif proj=='auto': proj=False
if hasattr(self,'fig') and pl.fignum_exists(self.fig.number):
if isExtra: pass
else:
if debug_lev==2: print ' -> will clear axes'
self.clear_axes()
else:
if hasattr(self,'ax') and pl.fignum_exists(self.ax.figure.number):
if debug_lev==2: print ' -> will use previous ax'
self.init_figure(ax=self.ax)
else:
if debug_lev==2: print ' -> will create new fig'
self.init_figure()
if proj and not isExtra:
if not hasattr(self,'map') or self.map_info_get()!=self.map_info_current:
# make a new projection:
if not self.config['axes.axis'] and not x is None: self.config['axes.axis']=x.min(),x.max(),y.min(),y.max()
if debug_lev==2: print ' -> new projection needed'
self.init_projection(debug_level=debug_lev)
### useProj=1
# set labels:
xlab=ylab=vlab=''
if not xname is None:
xunits=self.info[xname]['units']
if xunits in (None,'Unk'): xlab = '%s'%self.info[xname]['name']
else: xlab = '%s (%s)'%(self.info[xname]['name'],xunits)
if not yname is None:
yunits=self.info[yname]['units']
if yunits in (None,'Unk'): ylab = '%s'%self.info[yname]['name']
else: ylab = '%s (%s)'%(self.info[yname]['name'],yunits)
vunits=self.info['v']['units']
if vunits in (None,'Unk'): vlab = '%s'%self.info['v']['name']
else: vlab = '%s (%s)'%(self.info['v']['name'],vunits)
# vifield, 1d or 2d
if isinstance(self.v,tuple):
if debug_lev==2: print ' -> will draw vfield'
self.draw_vector_field(x,y,self.v[0],self.v[1])
# sclar:
else:
if ndim==2:
if debug_lev==2: print ' -> will draw 2d'
self.draw_scalar_field(x,y,self.v)
if not isExtra: self.draw_colorbar()
elif ndim==1:
if debug_lev==2: print ' -> will draw 1d'
self.draw_1d(x,y)
# add labels:
if labels:
if ndim==2:
tit=vlab
if not self.t is None:
if isinstance(self.t,datetime.datetime):
tit+=' $\\bullet$ %s'%self.t.strftime('%Y-%m-%d %H:%M')
else:
tit+=' $\\bullet$ %s to %s'%(self.t[0,0].strftime('%Y-%m-%d %H:%M'),self.t[0,-1].strftime('%Y-%m-%d %H:%M'))
if not self.info['v']['slice'] in (None,'Unk'):
tit+=' $\\bullet$ %s'%self.info['v']['slice']
if not tit=='Unk': self.draw_label('title',tit)
if not proj:###not useProj:
if not xlab=='Unk': self.draw_label('xlabel',xlab)
if not ylab=='Unk': self.draw_label('ylabel',ylab)
elif ndim==1:
if not xlab=='Unk': self.draw_label('xlabel',xlab)
if yname=='v':
if not vlab=='Unk': self.draw_label('title',vlab)
else:
if not ylab=='Unk': self.draw_label('ylabel',ylab)
if proj and not isExtra:
if debug_lev==2: print ' -> will draw projection', self.info['v']
self.draw_projection()
if self.extra and extras:
for e in self.extra:
e.inherit(self)
if debug_lev==2: print ' -> will plot extras'
e.plot(isExtra=1,debug_level=debug_lev)
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 if 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=vis.Data()
out.label='time_series'
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))
lon,lat,hr,mr=self.grid.vars(ruvp=self.vloc(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):
if 'z' in self.vaxes(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=rt.s_levels(h,zeta,self.s_params,rw=self.vloc(varname)[1])
z=np.squeeze(z)
# depth slice:
### if isDepth and self.hasz(varname):
if isDepth and 'z' in self.vaxes(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=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,
surface_masked=opts.get('surf_mask',True),
spline=opts.get('spline',True))[...,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 't' in coords and 't' in self.vaxes(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 'z' in coords and 'z' in self.vaxes(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.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.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 slicez(self,varname,ind,time=0,**opts):
surf_mask=opts.get('surf_mask',True)
spline=opts.get('spline',True)
coords=opts.get('coords',self._default_coords('slicez')).split(',')
out=vis.Data()
out.label='slicez'
out.msg=self.check_slice(varname,t=time)
if out.msg: return out
if not 'z' in self.vaxes(varname):
return self.slicek(varname,ind,time,**opts)
v=self.use(varname,SEARCHtime=time)
### x,y,h,m=self.grid.vars(ruvp=self.var_at(varname)[0])
x,y,h,m=self.grid.vars(ruvp=self.vloc(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_mask,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.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.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 't' in self.vaxes(varname): out.t=self.time[time]
if out.v.ndim==2:
out.extra=[vis.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.cmap']='k'
out.extra[0].label='bathy'
out.coordsReq=','.join(sorted(coords))
# about projection:
out.set_projection(self.grid.proj_info['basemap_opts'])
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
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(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