Exemplo n.º 1
0
I = Natgrid(xi, yi, xr, yr)
I.ext = 1                                               # Changer
I.igr = 1                                               # les parametres
zzoc = I.rgrd(zi).T

# - Matplotlib / R. Kern
from matplotlib.delaunay import Triangulation
tri = Triangulation(xi,yi)
I = tri.nn_extrapolator(zi)                             # Tester les autres methodes
zzork = I(xxr,yyr)  # vers grille
zork = I(xo,yo) # vers points


# Avec VACUMM
from vacumm.misc.grid.regridding import GridData, griddata, xy2xy
zzov = griddata(xi, yi, zi, (xr, yr), method='nat', ext=True, sub=10)     
# -> Tester la methode "carg"
# -> Testez parametre sub=...
# -> Essayer avec GridData
zov2 = xy2xy(xi, yi, zi, xo, yo)

# Krigeage
from vacumm.misc.grid.kriging import krig
zzok = krig(xi, yi, zi, xxr.ravel(), yyr.ravel(), nproc=1).reshape(zzr.shape)
# -> Tester nproc et npmax


# Plots
from vcmq import meshbounds, P
xxrb, yyrb = meshbounds(xr, yr)
P.figure(figsize=(10, 8))
yr = N.arange(10.)
xxr, yyr = N.meshgrid(xr, yr)
xrb, yrb = meshbounds(xr, yr)
zzr = (N.sin(xxr*N.pi/6)*N.sin(yyr*N.pi/6) + \
    N.exp(-((xxr-7.)**2+(yyr-7.)**2)/4.**2))*100.
zzr -= zzr.min()
vminmax=dict(vmin=zzr.min(), vmax=zzr.max())

# On construit un echantillon irregulier a partir du regulier
ij = N.unique((N.random.rand(50)*zzr.size).astype('i'))
xi, yi, zi = xxr.flat[ij], yyr.flat[ij], zzr.flat[ij]

# Interpolation sur la grille reguliere
# - natgrid
from vacumm.misc.grid.regridding import griddata
zirn = griddata(xi, yi, zi, (xr, yr), method='nat', ext=True, sub=6)
# - krigeage
zirk = griddata(xi, yi, zi, (xr, yr), method='carg')

# Plot de verif
import pylab as P
from vacumm.misc.plot import savefigs
P.figure(1, figsize=(6, 8))
P.subplots_adjust(hspace=.3, bottom=.05, top=.95, left=.06)
# - regulier
P.subplot(311)
P.pcolor(xrb, yrb, zzr, **vminmax)
P.xlim(xrb.min(), xrb.max()) ; P.ylim(yrb.min(), yrb.max())
P.title('Original')
stdref = zzr.std()
# - irregulier via natgrid
Exemplo n.º 3
0
yr = N.arange(10.)
xxr, yyr = N.meshgrid(xr, yr)
xrb, yrb = meshbounds(xr, yr)
zzr = (N.sin(xxr*N.pi/6)*N.sin(yyr*N.pi/6) + \
    N.exp(-((xxr-7.)**2+(yyr-7.)**2)/4.**2))*100.
zzr -= zzr.min()
vminmax = dict(vmin=zzr.min(), vmax=zzr.max())

# On construit un echantillon irregulier a partir du regulier
ij = N.unique((N.random.rand(50) * zzr.size).astype('i'))
xi, yi, zi = xxr.flat[ij], yyr.flat[ij], zzr.flat[ij]

# Interpolation sur la grille reguliere
# - natgrid
from vacumm.misc.grid.regridding import griddata
zirn = griddata(xi, yi, zi, (xr, yr), method='nat', ext=True, sub=6)
# - krigeage
zirk = griddata(xi, yi, zi, (xr, yr), method='carg')

# Plot de verif
import pylab as P
from vacumm.misc.plot import savefigs
P.figure(1, figsize=(6, 8))
P.subplots_adjust(hspace=.3, bottom=.05, top=.95, left=.06)
# - regulier
P.subplot(311)
P.pcolor(xrb, yrb, zzr, **vminmax)
P.xlim(xrb.min(), xrb.max())
P.ylim(yrb.min(), yrb.max())
P.title('Original')
stdref = zzr.std()