def missing_interp(lon, lat, arr):
grid0 = create_grid(lon[0, :], lat[:, 0])
varri = MV2.asarray(arr)
varri = set_grid(varri, grid0)
tempf = fill2d(varri, method='carg')
lon = np.ma.masked_where(tempf == tempf.fill_value, lon)
lat = np.ma.masked_where(tempf == tempf.fill_value, lat)
arri = griddata(lon.compressed(),
lat.compressed(),
tempf.compressed(), (lon[0, :], lat[:, 0]),
method='nat',
ext=True,
sub=10)
return arri
from vcmq import P, N, MV2, code_file_name, os, add_grid, rotate_grid, set_grid, \
create_grid, rc, rcdefaults, plot2d
from vacumm.misc.grid.regridding import regrid2d
# Input grid and data
nxi = 20
nyi = 15
# - rect
xi = N.arange(nxi*1.)
yi = N.arange(nyi*1.)
gridri = create_grid(xi, yi)
xxri, yyri = N.meshgrid(xi, yi)
zzri = N.ma.array(yyri)
zzri[int(nyi*0.3):int(nyi*0.6), int(nxi*0.3):int(nxi*0.6)] = N.ma.masked
varri = MV2.asarray(zzri)
set_grid(varri, gridri)
# - curv
gridci = rotate_grid(gridri, 30)
xxci = gridci.getLongitude().getValue()
yyci = gridci.getLatitude().getValue()
zzci = N.ma.array(yyci)
zzci[int(nyi*0.3):int(nyi*0.6), int(nxi*0.3):int(nxi*0.6)] = N.ma.masked
varci = MV2.asarray(zzci)
set_grid(varci, gridci)
# Output positions
nxo = 25
nyo = 18
# - rect
dxi = xi[-1]-xi[0]
# Input grid and data nxi = 20 nyi = 15 nt = 5 # - rect xi = N.arange(nxi*1.) yi = N.arange(nyi*1.) ti = create_time((nt, ), 'years since 2000') gridri = create_grid(xi, yi) xxri, yyri = N.meshgrid(xi, yi) zzri = N.ma.resize(yyri, (nt, nyi, nxi)) zzri[:, int(nyi*0.3):int(nyi*0.6), int(nxi*0.3):int(nxi*0.6)] = N.ma.masked zzri[1] = N.ma.masked varri = MV2.asarray(zzri) varri.setAxis(0, ti) set_grid(varri, gridri) # - curv gridci = rotate_grid(gridri, 30) xxci = gridci.getLongitude().getValue() yyci = gridci.getLatitude().getValue() zzci = N.ma.resize(yyci, (nt, nyi, nxi)) zzci[:, int(nyi*0.3):int(nyi*0.6), int(nxi*0.3):int(nxi*0.6)] = N.ma.masked zzci[1] = N.ma.masked varci = MV2.asarray(zzci) varci.setAxis(0, ti) set_grid(varci, gridci) # Output positions nxo = 25
P.subplot(132, sharex=ax, sharey=ax)
P.pcolormesh(xbo, ybo, vol, **kw)
P.title('Linear')
P.subplot(133, sharex=ax, sharey=ax)
P.pcolormesh(xbo, ybo, voc, **kw)
P.ylim(ymin=min(ybi.min(), ybo.min()), ymax=max(ybi.max(), ybo.max()))
P.title('Cellave')
P.tight_layout()
P.savefig(figfile)
# 1d->1d
depi1d = create_dep(N.arange(-4500., 1, 500))
depo1d = create_dep(N.arange(-4000., 1, 333.33))
nzi = depi1d.shape[0]
vari = MV2.asarray(
N.ma.resize(depi1d[:], (nt, ny, nx, nzi)).transpose([0, 3, 1, 2]))
vari.setAxis(1, depi1d)
varol1 = regrid1d(vari, depo1d, method='linear')
varol2 = regrid1d(vari, depo1d, method='linear', iaxi=0, iaxo=0, axi=depi1d)
result.append(('assertEqual', [(varol1 - varol2).std(), 0]))
varoc = regrid1d(vari, depo1d, method='cellave')
myplot(vari, depi1d, varol1, varoc, depo1d, code_file_name(ext='_0.png'))
# 4d->1d
depi1d = N.arange(-4500., 1, 500)
nzi = depi1d.shape[0]
depi4d = N.resize(N.resize(depi1d, (nx, ny, nzi)).T, (nt, nzi, ny, nx))
depi4d += 500 * (N.random.random(depi4d.shape) - 0.5)
depo1d = create_dep(N.arange(-4000., 1, 333.33))
vari = MV2.array(depi4d, fill_value=1e20)
vari.getAxis(1).designateLevel()
P.subplot(132, sharex=ax, sharey=ax)
P.pcolormesh(xbo, ybo, vol, **kw)
P.title('Linear')
P.subplot(133, sharex=ax, sharey=ax)
P.pcolormesh(xbo, ybo, voc, **kw)
P.ylim(ymin=min(ybi.min(), ybo.min()), ymax=max(ybi.max(), ybo.max()))
P.title('Cellave')
P.tight_layout()
P.savefig(figfile)
# 1d->1d
depi1d = create_dep(N.arange(-4500., 1, 500))
depo1d = create_dep(N.arange(-4000., 1, 333.33))
nzi = depi1d.shape[0]
vari = MV2.asarray(N.ma.resize(depi1d[:], (nt, ny, nx, nzi)).transpose([0, 3, 1, 2]))
vari.setAxis(1, depi1d)
varol1 = regrid1d(vari, depo1d, method='linear')
varol2 = regrid1d(vari, depo1d, method='linear', iaxi=0, iaxo=0, axi=depi1d)
result.append(('assertEqual', [(varol1-varol2).std(), 0]))
varoc = regrid1d(vari, depo1d, method='cellave')
myplot(vari, depi1d, varol1, varoc, depo1d, code_file_name(ext='_0.png'))
# 4d->1d
depi1d = N.arange(-4500., 1, 500)
nzi = depi1d.shape[0]
depi4d = N.resize(N.resize(depi1d, (nx, ny, nzi)).T, (nt, nzi, ny, nx))
depi4d += 500*(N.random.random(depi4d.shape)-0.5)
depo1d = create_dep(N.arange(-4000., 1, 333.33))
vari = MV2.array(depi4d, fill_value=1e20)
