def roms2z(var, grd, grdz, Cpos='rho', irange=None, jrange=None, \
spval=1e37, mode='linear'):
"""
varz = roms2z(var, grd, grdz)
optional switch:
- Cpos='rho', 'u' 'v' or 'w' specify the C-grid position where
the variable rely
- irange specify grid sub-sample for i direction
- jrange specify grid sub-sample for j direction
- spval=1e37 define spval value
- mode='linear' or 'spline' specify the type of interpolation
Interpolate the variable from ROMS grid grd to z vertical grid grdz
"""
var = var.copy()
assert len(var.shape) == 3, 'var must be 3D'
if mode == 'linear':
imode = 0
elif mode == 'spline':
imode = 1
else:
imode = 0
raise Warning('%s not supported, defaulting to linear' % mode)
if Cpos is 'rho':
z = grd.vgrid.z_r[0, :]
depth = grdz.vgrid.z
mask = grd.hgrid.mask_rho
elif Cpos is 'u':
z = 0.5 * (grd.vgrid.z_r[0, :, :, :-1] + grd.vgrid.z_r[0, :, :, 1:])
depth = 0.5 * (grdz.vgrid.z[:, :, :-1] + grdz.vgrid.z[:, :, 1:])
mask = grd.hgrid.mask_u
elif Cpos is 'v':
z = 0.5 * (grd.vgrid.z_r[0, :, :-1, :] + grd.vgrid.z_r[0, :, 1:, :])
depth = 0.5 * (grdz.vgrid.z[:, :-1, :] + grdz.vgrid.z[:, 1:, :])
mask = grd.hgrid.mask_v
elif Cpos is 'w':
z = grd.vgrid.z_w[0, :]
depth = grdz.vgrid.z
mask = grd.hgrid.mask_rho
else:
raise Warning('%s unknown position. Cpos must be rho, u, v or w.' %
Cpos)
Nm, Mm, Lm = var.shape
nlev = grdz.vgrid.N
var = np.concatenate((var, var[-2:-1, :, :]), 0)
z = np.concatenate((z, 100 * np.ones((1, z.shape[1], z.shape[2]))), 0)
if irange is None:
irange = (0, Lm)
else:
assert var.shape[2] == irange[1]-irange[0], \
'var shape and irange must agree'
if jrange is None:
jrange = (0, Mm)
else:
assert var.shape[1] == jrange[1]-jrange[0], \
'var shape and jrange must agree'
varz = np.zeros((nlev, jrange[1] - jrange[0], irange[1] - irange[0]))
for k in range(nlev):
varz[k,:,:] = _interp.xhslice(var, \
z[:,jrange[0]:jrange[1], irange[0]:irange[1]], \
depth[k,jrange[0]:jrange[1], irange[0]:irange[1]], \
mask[jrange[0]:jrange[1], irange[0]:irange[1]], \
imode, spval)
#mask
idx = np.where(abs((varz - spval) / spval) <= 1e-5)
varz[idx] = spval
#varz = np.ma.masked_values(varz, spval, rtol=1e-5)
return varz
def z2roms(varz, grdz, grd, Cpos='rho', irange=None, jrange=None, \
spval=1e37, flood=True, dmax=0, cdepth=0, kk=0, \
mode='linear'):
"""
var = z2roms(var, grdz, grd)
optional switch:
- Cpos='rho', 'u' or 'v' specify the C-grid position where
the variable rely
- irange specify grid sub-sample for i direction
- jrange specify grid sub-sample for j direction
- spval=1e37 define spval value
- dmax=0 if dmax>0, maximum horizontal
flooding distance
- cdepth=0 critical depth for flooding
if depth<cdepth => no flooding
- kk
- mode='linear' or 'spline' specify the type of interpolation
Interpolate the variable from z vertical grid grdz to ROMS grid grd
"""
varz = varz.copy()
assert len(varz.shape) == 3, 'var must be 3D'
if mode=='linear':
imode=0
elif mode=='spline':
imode=1
else:
raise Warning, '%s not supported, defaulting to linear' % mode
if Cpos is 'rho':
z = grdz.vgrid.z[:]
depth = grd.vgrid.z_r[0,:]
mask = grd.hgrid.mask_rho
elif Cpos is 'u':
z = 0.5 * (grdz.vgrid.z[:,:,:-1] + grdz.vgrid.z[:,:,1:])
depth = 0.5 * (grd.vgrid.z_r[0,:,:,:-1] + grd.vgrid.z_r[0,:,:,1:])
mask = grd.hgrid.mask_u
elif Cpos is 'v':
z = 0.5 * (grdz.vgrid.z[:,:-1,:] + grdz.vgrid.z[:,1:,:])
depth = 0.5 * (grd.vgrid.z_r[0,:,:-1,:] + grd.vgrid.z_r[0,:,1:,:])
mask = grd.hgrid.mask_v
elif Cpos is 'w':
z = grdz.vgrid.z[:]
depth = grd.vgrid.z_w[0,:]
mask = grd.hgrid.mask_rho
else:
raise Warning, '%s bad position. Use depth at Arakawa-C \
rho points instead.' % Cpos
nlev, Mm, Lm = varz.shape
Nm = depth.shape[0]
if irange is None:
irange = (0,Lm)
else:
assert varz.shape[2] == irange[1]-irange[0], \
'var shape and irange must agreed'
if jrange is None:
jrange = (0,Mm)
else:
assert varz.shape[1] == jrange[1]-jrange[0], \
'var shape and jrange must agreed'
# flood varz if requested
if flood is True:
varz = pyroms.remapping.flood(varz, grdz, Cpos=Cpos, \
irange=irange, jrange=jrange, spval=spval, \
dmax=dmax, cdepth=cdepth, kk=kk)
varz = np.concatenate((varz[0:1,:,:], varz, varz[-1:,:,:]), 0)
z = np.concatenate((-9999*np.ones((1,z.shape[1], z.shape[2])), \
z, \
100*np.ones((1,z.shape[1], z.shape[2]))), 0)
var = np.ma.zeros((Nm, Mm, Lm))
for k in range(Nm):
var[k,:,:] = _interp.xhslice(varz, \
z[:,jrange[0]:jrange[1], irange[0]:irange[1]], \
depth[k,jrange[0]:jrange[1], irange[0]:irange[1]], \
mask[jrange[0]:jrange[1], irange[0]:irange[1]], \
imode, spval)
#mask
var = np.ma.masked_values(var, spval, rtol=1e-5)
#var[k,:,:] = np.ma.masked_where(mask == 0, var[k,:,:])
return var
def roms2z(var, grd, grdz, Cpos='rho', irange=None, jrange=None, \
spval=1e37, mode='linear'):
"""
varz = roms2z(var, grd, grdz)
optional switch:
- Cpos='rho', 'u' 'v' or 'w' specify the C-grid position where
the variable rely
- irange specify grid sub-sample for i direction
- jrange specify grid sub-sample for j direction
- spval=1e37 define spval value
- mode='linear' or 'spline' specify the type of interpolation
Interpolate the variable from ROMS grid grd to z vertical grid grdz
"""
var = var.copy()
assert len(var.shape) == 3, 'var must be 3D'
if mode=='linear':
imode=0
elif mode=='spline':
imode=1
else:
imode=0
raise Warning, '%s not supported, defaulting to linear' % mode
if Cpos is 'rho':
z = grd.vgrid.z_r[0,:]
depth = grdz.vgrid.z
mask = grd.hgrid.mask_rho
elif Cpos is 'u':
z = 0.5 * (grd.vgrid.z_r[0,:,:,:-1] + grd.vgrid.z_r[0,:,:,1:])
depth = 0.5 * (grdz.vgrid.z[:,:,:-1] + grdz.vgrid.z[:,:,1:])
mask = grd.hgrid.mask_u
elif Cpos is 'v':
z = 0.5 * (grd.vgrid.z_r[0,:,:-1,:] + grd.vgrid.z_r[0,:,1:,:])
depth = 0.5 * (grdz.vgrid.z[:,:-1,:] + grdz.vgrid.z[:,1:,:])
mask = grd.hgrid.mask_v
elif Cpos is 'w':
z = grd.vgrid.z_w[0,:]
depth = grdz.vgrid.z
mask = grd.hgrid.mask_rho
else:
raise Warning, '%s unknown position. Cpos must be rho, u, v or w.' % Cpos
Nm, Mm, Lm = var.shape
nlev = grdz.vgrid.N
var = np.concatenate((var, var[-2:-1,:,:]), 0)
z = np.concatenate((z, 100*np.ones((1,z.shape[1], z.shape[2]))), 0)
if irange is None:
irange = (0,Lm)
else:
assert var.shape[2] == irange[1]-irange[0], \
'var shape and irange must agreed'
if jrange is None:
jrange = (0,Mm)
else:
assert var.shape[1] == jrange[1]-jrange[0], \
'var shape and jrange must agreed'
varz = np.zeros((nlev, jrange[1]-jrange[0], irange[1]-irange[0]))
for k in range(nlev):
varz[k,:,:] = _interp.xhslice(var, \
z[:,jrange[0]:jrange[1], irange[0]:irange[1]], \
depth[k,jrange[0]:jrange[1], irange[0]:irange[1]], \
mask[jrange[0]:jrange[1], irange[0]:irange[1]], \
imode, spval)
#mask
idx = np.where(abs((varz-spval)/spval)<=1e-5)
varz[idx] = spval
#varz = np.ma.masked_values(varz, spval, rtol=1e-5)
return varz
def sta2z(var, grd, grdz, Cpos='rho', srange=None, \
spval=1e37, mode='linear'):
"""
varz = roms2z(var, grd, grdz)
optional switch:
- Cpos specify vertical grid type
- srange specify grid sub-sample of stations
- spval=1e37 define spval value
- mode='linear' or 'spline' specify the type of interpolation
Interpolate the variable from stations grid grd to z vertical grid grdz
"""
var = var.copy()
assert len(var.shape) == 2, 'var must be 2D'
if mode == 'linear':
imode = 0
elif mode == 'spline':
imode = 1
else:
imode = 0
raise Warning, '%s not supported, defaulting to linear' % mode
if Cpos is 'rho':
z = grd.vgrid.z_r[0, :]
depth = grdz.vgrid.z
elif Cpos is 'w':
z = grd.vgrid.z_w[0, :]
depth = grdz.vgrid.z
else:
raise Warning, '%s unknown position. Cpos must be rho or w.' % Cpos
var = var.T
Nm, Sm = var.shape
nlev = grdz.vgrid.N
# putting in a fake i dimension
var = np.dstack(var).T
z = np.dstack(z).T
depth = np.dstack(depth).T
mask = np.ones((Sm, 1))
# copy surface value to high in the sky
var = np.concatenate((var, var[-2:-1, :, :]), 0)
z = np.concatenate((z, 100 * np.ones((1, z.shape[1], z.shape[2]))), 0)
# print 'nlev', nlev, 'var.shape', var.shape, srange
# print 'z.shape', z.shape
# print 'mask.shape', mask.shape
# print 'depth.shape', depth.shape
if srange is None:
srange = (0, Sm)
else:
assert var.shape[1] == srange[1]-srange[0], \
'var shape and srange must agree'
varz = np.zeros((nlev, srange[1] - srange[0], 1))
for k in range(nlev):
varz[k,:] = _interp.xhslice(var, \
z[:, srange[0]:srange[1], :], \
depth[k, srange[0]:srange[1], :], \
mask[srange[0]:srange[1], :], \
imode, spval)
# pdb.set_trace()
#mask
idx = np.where(abs((varz - spval) / spval) <= 1e-5)
varz[idx] = spval
#varz = np.ma.masked_values(varz, spval, rtol=1e-5)
return varz
def sta2z(var, grd, grdz, Cpos='rho', srange=None, \
spval=1e37, mode='linear'):
"""
varz = roms2z(var, grd, grdz)
optional switch:
- Cpos specify vertical grid type
- srange specify grid sub-sample of stations
- spval=1e37 define spval value
- mode='linear' or 'spline' specify the type of interpolation
Interpolate the variable from stations grid grd to z vertical grid grdz
"""
var = var.copy()
assert len(var.shape) == 2, 'var must be 2D'
if mode=='linear':
imode=0
elif mode=='spline':
imode=1
else:
imode=0
raise Warning, '%s not supported, defaulting to linear' % mode
if Cpos is 'rho':
z = grd.vgrid.z_r[0,:]
depth = grdz.vgrid.z
elif Cpos is 'w':
z = grd.vgrid.z_w[0,:]
depth = grdz.vgrid.z
else:
raise Warning, '%s unknown position. Cpos must be rho or w.' % Cpos
var = var.T
Nm, Sm = var.shape
nlev = grdz.vgrid.N
# putting in a fake i dimension
var = np.dstack(var).T
z = np.dstack(z).T
depth = np.dstack(depth).T
mask = np.ones((Sm, 1))
# copy surface value to high in the sky
var = np.concatenate((var, var[-2:-1,:,:]), 0)
z = np.concatenate((z, 100*np.ones((1,z.shape[1], z.shape[2]))), 0)
# print 'nlev', nlev, 'var.shape', var.shape, srange
# print 'z.shape', z.shape
# print 'mask.shape', mask.shape
# print 'depth.shape', depth.shape
if srange is None:
srange = (0,Sm)
else:
assert var.shape[1] == srange[1]-srange[0], \
'var shape and srange must agree'
varz = np.zeros((nlev, srange[1]-srange[0], 1))
for k in range(nlev):
varz[k,:] = _interp.xhslice(var, \
z[:, srange[0]:srange[1], :], \
depth[k, srange[0]:srange[1], :], \
mask[srange[0]:srange[1], :], \
imode, spval)
# pdb.set_trace()
#mask
idx = np.where(abs((varz-spval)/spval)<=1e-5)
varz[idx] = spval
#varz = np.ma.masked_values(varz, spval, rtol=1e-5)
return varz
def z2roms(varz, grdz, grd, Cpos='rho', irange=None, jrange=None, \
spval=1e37, flood=True, dmax=0, cdepth=0, kk=0, \
mode='linear'):
"""
var = z2roms(var, grdz, grd)
optional switch:
- Cpos='rho', 'u' or 'v' specify the C-grid position where
the variable rely
- irange specify grid sub-sample for i direction
- jrange specify grid sub-sample for j direction
- spval=1e37 define spval value
- dmax=0 if dmax>0, maximum horizontal
flooding distance
- cdepth=0 critical depth for flooding
if depth<cdepth => no flooding
- kk
- mode='linear' or 'spline' specify the type of interpolation
Interpolate the variable from z vertical grid grdz to ROMS grid grd
"""
varz = varz.copy()
assert len(varz.shape) == 3, 'var must be 3D'
if mode=='linear':
imode=0
elif mode=='spline':
imode=1
else:
raise Warning, '%s not supported, defaulting to linear' % mode
if Cpos is 'rho':
z = grdz.vgrid.z[:]
depth = grd.vgrid.z_r[0,:]
mask = grd.hgrid.mask_rho
elif Cpos is 'u':
z = 0.5 * (grdz.vgrid.z[:,:,:-1] + grdz.vgrid.z[:,:,1:])
depth = 0.5 * (grd.vgrid.z_r[0,:,:,:-1] + grd.vgrid.z_r[0,:,:,1:])
mask = grd.hgrid.mask_u
elif Cpos is 'v':
z = 0.5 * (grdz.vgrid.z[:,:-1,:] + grdz.vgrid.z[:,1:,:])
depth = 0.5 * (grd.vgrid.z_r[0,:,:-1,:] + grd.vgrid.z_r[0,:,1:,:])
mask = grd.hgrid.mask_v
elif Cpos is 'w':
z = grdz.vgrid.z[:]
depth = grd.vgrid.z_w[0,:]
mask = grd.hgrid.mask_rho
else:
raise Warning, '%s bad position. Use depth at Arakawa-C \
rho points instead.' % Cpos
nlev, Mm, Lm = varz.shape
Nm = depth.shape[0]
if irange is None:
irange = (0,Lm)
else:
assert varz.shape[2] == irange[1]-irange[0], \
'var shape and irange must agree'
if jrange is None:
jrange = (0,Mm)
else:
assert varz.shape[1] == jrange[1]-jrange[0], \
'var shape and jrange must agree'
# flood varz if requested
if flood is True:
varz = pyroms.remapping.flood(varz, grdz, Cpos=Cpos, \
irange=irange, jrange=jrange, spval=spval, \
dmax=dmax, cdepth=cdepth, kk=kk)
varz = np.concatenate((varz[0:1,:,:], varz, varz[-1:,:,:]), 0)
z = np.concatenate((-9999*np.ones((1,z.shape[1], z.shape[2])), \
z, \
100*np.ones((1,z.shape[1], z.shape[2]))), 0)
var = np.ma.zeros((Nm, Mm, Lm))
for k in range(Nm):
var[k,:,:] = _interp.xhslice(varz, \
z[:,jrange[0]:jrange[1], irange[0]:irange[1]], \
depth[k,jrange[0]:jrange[1], irange[0]:irange[1]], \
mask[jrange[0]:jrange[1], irange[0]:irange[1]], \
imode, spval)
#mask
var = np.ma.masked_values(var, spval, rtol=1e-5)
#var[k,:,:] = np.ma.masked_where(mask == 0, var[k,:,:])
return var