示例#1
0
import cdms2
from vacumm.config import data_sample
from vacumm.diag.thermdyn import mixed_layer_depth
from vacumm.misc.plot import map2
from vacumm.data.misc.sigma import NcSigma
from vacumm.misc.grid import curv2rect

# Read temperature
print 'Read'
ncfile = data_sample(ncfile)
f = cdms2.open(ncfile)
temp = curv2rect(f('TEMP'))(lon=lon,  lat=lat,  squeeze=1)

# Compute depth
print 'depth'
s = NcSigma.factory(f)
depth = curv2rect(s())(lon=lon,  lat=lat, squeeze=1)
f.close()

# Compute MLD
print 'mld'
print temp.shape, depth.shape
mld = mixed_layer_depth(temp, depth, mode='deltatemp', deltatemp=0.1)

# Plot
print 'plot'
map2(mld, proj='merc', figsize=(6, 4), autoresize=0,
    fill='pcolormesh',  contour=False, show=False,
    colorbar_shrink=0.7, right=1, savefigs=__file__)

示例#2
0
import cdms2
from vacumm.config import data_sample
from vacumm.diag.thermdyn import mixed_layer_depth
from vacumm.misc.plot import map2
from vacumm.data.misc.sigma import NcSigma
from vacumm.misc.grid import curv2rect

# Read temperature
print 'Read'
ncfile = data_sample(ncfile)
f = cdms2.open(ncfile)
temp = curv2rect(f('TEMP'))(lon=lon,  lat=lat,  squeeze=1)

# Compute depth
print 'depth'
s = NcSigma.factory(f)
depth = curv2rect(s())(lon=lon,  lat=lat, squeeze=1)
f.close()

# Compute MLD
print 'mld'
print temp.shape, depth.shape
mld = mixed_layer_depth(temp, depth, mode='deltatemp', deltatemp=0.1)

# Plot
print 'plot'
map2(mld, proj='merc', figsize=(6, 4), autoresize=0,
    fill='pcolormesh',  contour=False, show=False,
    colorbar_shrink=0.7, right=1, savefigs=__file__, close=True)

示例#3
0
time_format = "%Y%m%d"
date = strftime(time_format)
print "Begin : " + strftime(print_time_format)

# Profondeurs sur lesquelles nous souhaitons interpoler (en m)
depths = np.array([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,
    22,24,26,28,30,32,34,36,38,40,45,50,55,60,65,70,75,80,85,90,95,100,120,140,160])
depths = -depths[::-1] # croissantes et négatives

# Lecture de la température
f = cdms2.open(data_sample('mars3d.tsigyx.nc'))
data_in = f('TEMP') # T-YX (- = level)

# Détermination des profondeurs d'après les sigma
# - détection auto de la classe de sigma d'après fichier
sigma_class = NcSigma.factory(f)
# - initialisation du convertisseur
sigma_converter = sigma_class(copyaxes=True)
# - lecture de eta (sans sélection de domaine) et calcul des profondeurs
depths_in = sigma_converter().filled()
f.close()

# Creation de l'axe des profondeurs cibles
depth_out = create_depth(depths)

# Interpolation
xmap = (0, 2, 3) # la profondeur varie en T/Y/X
xmapper = np.rollaxis(depths_in, 1, 4) # profondeur = dernier axe
data_out = regrid1d(data_in, depth_out, axi=depths_in, axis=1, method='linear', extrap=1)

# Plot
示例#4
0
time_format = "%Y%m%d"
date = strftime(time_format)
print "Begin : " + strftime(print_time_format)

# Profondeurs sur lesquelles nous souhaitons interpoler (en m)
depths = np.array([0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,
    22,24,26,28,30,32,34,36,38,40,45,50,55,60,65,70,75,80,85,90,95,100,120,140,160])
depths = -depths[::-1] # croissantes et négatives

# Lecture de la température
f = cdms2.open(data_sample('mars3d.tsigyx.nc'))
data_in = f('TEMP') # T-YX (- = level)

# Détermination des profondeurs d'après les sigma
# - détection auto de la classe de sigma d'après fichier
sigma_class = NcSigma.factory(f)
# - initialisation du convertisseur
sigma_converter = sigma_class(copyaxes=True)
# - lecture de eta (sans sélection de domaine) et calcul des profondeurs
depths_in = sigma_converter().filled()
f.close()

# Creation de l'axe des profondeurs cibles
depth_out = create_depth(depths)

# Interpolation
xmap = (0, 2, 3) # la profondeur varie en T/Y/X
xmapper = np.rollaxis(depths_in, 1, 4) # profondeur = dernier axe
data_out = regrid1d(data_in, depth_out, axi=depths_in, axis=1, method='linear', extrap=1)

# Plot