# Lecture de la température
f =cdms2.open(data_sample('mars3d.tsigyx.nc'))
data_in = f('TEMP', time=slice(0,2)) # T-YX (- = level)
# Détermination des profondeurs d'après les sigma
sigma_converter = NcSigma.factory(f) # détection auto et initialisation du convertisseur
# -> VERIFIER QUE sigma_class EST BIEN SigmaGeneralized
depths_in = sigma_converter.sigma_to_depths(selector=dict(time=slice(0,2))).filled() # lecture eta, etc + conversion
# (Equivalent à depths_in = sigma_converter(selector=dict(time=slice(0,2))).filled())
f.close()
# Creation de l'axe des profondeurs cibles
depths = N.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
depth_out = create_depth(depths)
# Interpolation
data_out = regrid1d(data_in, depth_out, axi=depths_in, axis=1, method='linear', extrap=1)
# Plot
kw = dict(vmin=10, vmax=14, xhide='auto', add_grid=True, ymax=0, fill='contourf') # FILL=PCOLOR ?
section2(data_in[0, :, 10], yaxis=depths_in[0, :, 10], subplot=211, title='Sigma', show=False, **kw)
s = section2(data_out[0, :, 10], subplot=212, title='Z', show=False, savefig=__file__, **kw)
# Imports
from vcmq import N, MV2, cdms2, create_dep, rc, section2, code_file_name, os
# Init data with z 1D
nz = 8
nd = 10
var = N.dot(N.hanning(nz).reshape(nz, 1), N.hanning(nd).reshape(1, nd))
var = MV2.array(var)
d = cdms2.createAxis(N.arange(nd))
d.units = 'km'
d.long_name = 'Distance'
z1d = create_dep((-nz + 1, 1.))
var.setAxis(0, z1d)
var.setAxis(1, d)
z2d = N.resize(z1d[:].reshape(1, nz), (nd, nz)).T
z2d *= N.arange(1., nd + 1) / nd
# Plot with z 1D
rc('font', size=8)
kw = dict(show=False, bgcolor='0.5')
section2(var, subplot=211, **kw)
# Plot with z 2D
figfile = code_file_name(ext='png')
if os.path.exists(figfile): os.remove(figfile)
section2(var, yaxis=z2d, subplot=212, savefig=figfile, close=True, **kw)
# Result
result = dict(files=figfile)
# Imports
from vcmq import create_lon, N, MV2, create_dep, os, code_file_name, section2
from vacumm.misc.phys.units import deg2m
# Init data with z 1D
nz = 11
nx = 11
x = create_lon(N.arange(nx))
xm = deg2m(x[:],lat=45.) # meters
dx = xm[:].ptp()
z = create_dep((-nz+1, 1.), units='m', long_name='Depth')
dz = z[:].ptp()
scale = dz/dx
u = MV2.ones((nz,nx)) # 1 m/s
w = u*scale # 1 m/s * scale
for var in u,w:
var.setAxis(0, z)
var.setAxis(1, x)
var.units = 'm/s'
# Plot
figfile = code_file_name(ext='png')
if os.path.exists(figfile): os.remove(figfile)
s = section2((u,w), quiver_norm=1, fill=False, show=False,
savefig=figfile, close=False, axes_aspect=1)
# Result
result = dict(files=figfile)
from vcmq import N, MV2, cdms2, create_dep, rc, section2, code_file_name, os
# Init data with z 1D
nz = 8
nd = 10
var = N.dot(N.hanning(nz).reshape(nz, 1), N.hanning(nd).reshape(1, nd))
var = MV2.array(var)
d = cdms2.createAxis(N.arange(nd))
d.units='km'
d.long_name='Distance'
z1d = create_dep((-nz+1, 1.))
var.setAxis(0, z1d)
var.setAxis(1, d)
z2d = N.resize(z1d[:].reshape(1, nz), (nd, nz)).T
z2d *= N.arange(1., nd+1)/nd
# Plot with z 1D
rc('font', size=8)
kw = dict(show=False, bgcolor='0.5')
section2(var, subplot=211, **kw)
# Plot with z 2D
figfile = code_file_name(ext='png')
if os.path.exists(figfile): os.remove(figfile)
section2(var, yaxis=z2d, subplot=212, savefig=figfile, close=True, **kw)
# Result
result = dict(files=figfile)
# Imports
from vcmq import create_lon, N, MV2, create_dep, os, code_file_name, section2
from vacumm.misc.phys.units import deg2m
# Init data with z 1D
nz = 11
nx = 11
x = create_lon(N.arange(nx))
xm = deg2m(x[:], lat=45.) # meters
dx = xm[:].ptp()
z = create_dep((-nz + 1, 1.), units='m', long_name='Depth')
dz = z[:].ptp()
scale = dz / dx
u = MV2.ones((nz, nx)) # 1 m/s
w = u * scale # 1 m/s * scale
for var in u, w:
var.setAxis(0, z)
var.setAxis(1, x)
var.units = 'm/s'
# Plot
figfile = code_file_name(ext='png')
if os.path.exists(figfile): os.remove(figfile)
s = section2((u, w),
quiver_norm=1,
fill=False,
show=False,
savefig=figfile,
close=True,
axes_aspect=1)
tlons,
tlats,
getcoords=True,
outaxis='dist')
xdepth = transect(depth, tlons, tlats)
xmld = transect(mld, tlons, tlats)
xmld[:] *= -1
# Plot temperature
s = section2(
xtemp,
yaxis=xdepth,
ymin=-800,
fill='contourf',
nmax=20,
contour_linewidths=0.7,
bgcolor='0.5',
figsize=(7, 4),
cmap='thermal',
# cmap='vacumm_rnb2_hymex',
title='%(long_name)s (dens) along temp transect',
show=False)
# Plot MLD
curve2(xmld, 'w-', linewidth=2, show=False)
# Add a small map to show the transect positions
add_map_lines(temp[-1],
xlons,
xlats,
map_zoom=0.7,
depths = -depths[::-1] # croissantes et négatives
depth_out = create_depth(depths)
# Interpolation
data_out = regrid1d(data_in,
depth_out,
axi=depths_in,
axis=1,
method='linear',
extrap=1)
# Plot
kw = dict(vmin=10,
vmax=14,
xhide='auto',
add_grid=True,
ymax=0,
fill='contourf') # FILL=PCOLOR ?
section2(data_in[0, :, 10],
yaxis=depths_in[0, :, 10],
subplot=211,
title='Sigma',
show=False,
**kw)
s = section2(data_out[0, :, 10],
subplot=212,
title='Z',
show=False,
savefig=__file__,
**kw)
mld = mixed_layer_depth(dens, depth=depth, mode='deltadens', format_axes=True)
del dens
# Compute transect
tlons = (lon0,lon1)
tlats = (lat0,lat1)
tlons = N.concatenate([N.linspace(lon0,lon1,100.),N.linspace(lon1,lon1,100.)])
tlats = N.concatenate([N.linspace(lat0,lat1,100.),N.linspace(lat1,lat0,100.)])
xtemp, xlons, xlats = transect(temp, tlons, tlats, getcoords=True, outaxis='dist')
xdepth = transect(depth, tlons, tlats)
xmld = transect(mld, tlons, tlats)
xmld[:]*=-1
# Plot temperature
s = section2(xtemp, yaxis=xdepth, ymin=-800, fill='contourf', nmax=20,
contour_linewidths=0.7, bgcolor='0.5', figsize=(7,4),
cmap='vacumm_rnb2_hymex',
title='%(long_name)s (dens) along temp transect', show=False)
# Plot MLD
curve2(xmld, 'w-', linewidth=2, show=False)
# Add a small map to show the transect positions
add_map_lines(temp[-1], xlons, xlats, map_zoom=0.7, color='k')
# Save
figfile = code_file_name(ext='png')
if os.path.exists(figfile): os.remove(figfile)
s.savefig(figfile, pdf=True)
