corca=vdic['ORCA'], lkcont=False, cfignm=path_fig+'dS_annual_'+cdepth+'_'+CONFEXP+'_-_'+CC,
cbunit='PSU', cfig_type=fig_type,
ctitle='Salinity diff. to "'+cname_obs+'" at '+cdepth_true+', '+CONFEXP+' ('+cy1+'-'+cy2+')',
lforce_lim=True)
del Sobs_JFM, Sobs_JAS
if l_do_monthly_3d: del Tnemo_JFM, Tnemo_JAS, Snemo_JFM, Snemo_JAS, Tobs_JFM, Tobs_JAS
# Temperature and salinity for vertical sections
if lfig2 and i_do_sect==1 and (l_do_monthly_3d or l_3df_are_annual):
vdico = bt.check_env_var(sys.argv[0], {'TS_SECTION_FILE'})
vboxes, vlon1, vlat1, vlon2, vlat2, vTmin, vTmax, vSmin, vSmax = bt.read_coor(vdico['TS_SECTION_FILE'], ctype='float', lTS_bounds=True)
js = 0
for csname in vboxes:
[ i1, i2, j1, j2 ] = bo.transect_zon_or_med(vlon1[js], vlon2[js], vlat1[js], vlat2[js], xlon, xlat)
if i2>i1 and i2 < ni0-1: i2 = i2+1
if j2>j1 and j2 < nj0-1: j2 = j2+1
print '\n *** Section: '+csname+':'
print ' lon1, lon2, lat1, lat2 =', vlon1[js], vlon2[js], vlat1[js], vlat2[js]
print ' => i1, i2, j1, j2 =', i1, i2, j1, j2
#print ' xlon[j1,i1], xlon[j1,i2] =', xlon[j1,i1]-360., xlon[j1,i2]
print ''
if i1 > i2: print 'ERROR (temp_sal.py) => i1 > i2 !'; sys.exit(0)
cf_mm = sys.argv[2]
# Opening mesh_mask:
f_mm = Dataset(cf_mm)
Xlon = f_mm.variables['glamt'][0, :, :]
Xlat = f_mm.variables['gphit'][0, :, :]
mask = f_mm.variables['tmask'][0, 0, :, :]
f_mm.close()
(nj, ni) = nmp.shape(Xlon)
nmask = nmp.zeros((nj, ni))
# Getting sections:
vboxes, vlon1, vlat1, vlon2, vlat2 = bt.read_coor(cf_tf,
ctype='float',
lTS_bounds=False)
js = -1
for csname in vboxes:
js = js + 1
print '\n *** ' + sys.argv[0] + ': treating section ' + csname
nmask[:, :] = mask[:, :]
(i1, i2, j1, j2) = bo.transect_zon_or_med(vlon1[js], vlon2[js], vlat1[js],
vlat2[js], Xlon, Xlat)
print 'Nt, nk, nj, ni =', Nt, nk, nj, ni
# Masking:
for jt in range(Nt):
XT[jt, :, :, :] = rmsk[:, :, :] * XT[jt, :, :, :] + (
1. - rmsk[:, :, :]) * -9999.
XS[jt, :, :, :] = rmsk[:, :, :] * XS[jt, :, :, :] + (
1. - rmsk[:, :, :]) * -9999.
vtime = nmp.zeros(Nt)
for jt in range(Nt):
vtime[jt] = float(jyear) + (float(jt) + 0.5) / float(Nt)
# Getting sections:
vboxes, vlon1, vlat1, vlon2, vlat2 = bt.read_coor(f_sections,
ctype='float',
lTS_bounds=False)
js = -1
for csname in vboxes:
js = js + 1
print '\n *** ' + sys.argv[0] + ': treating section ' + csname
(i1, i2, j1, j2) = bo.transect_zon_or_med(vlon1[js], vlon2[js], vlat1[js],
vlat2[js], xlon, xlat)
print csname + ' :'
print '(lon1, lon2, lat1, lat2) =', vlon1[js], vlon2[js], vlat1[js], vlat2[
js]
cyear = sys.argv[2] ; jyear = int(cyear); cyear = '%4.4i'%jyear
print 'Current year is '+cyear+' !\n'
# Vector containing the different z_crit:
vMLD_crit = []
vv = vdic['MLD_CRIT'].split(',')
for cv in vv: vMLD_crit.append(float(cv))
print "\n All the z_crit to use:", vMLD_crit[:]
# First will read name and coordinates of rectangular boxes to treat into file FILE_DMV_BOXES
##############################################################################################
vboxes, vi1, vj1, vi2, vj2 = bt.read_coor(vdic['FILE_DMV_BOXES'])
nbb = len(vboxes)
print ''
bt.chck4f(vdic['MM_FILE'])
id_mm = Dataset(vdic['MM_FILE'])
zmask_orca = id_mm.variables['tmask'][0,0,:,:]
ze1t_orca = id_mm.variables['e1t'] [0,:,:]
ze2t_orca = id_mm.variables['e2t'] [0,:,:]
id_mm.close()
bt.chck4f(cf_in)
id_in = Dataset(cf_in)
Xmld_orca = id_in.variables[vdic['NN_MLD']][:,:,:]
print 'nt, nj, ni =', nt, nj, ni
vtime = nmp.zeros(nt)
for jt in range(nt): vtime[jt] = float(jyear) + (float(jt) + 0.5)/float(nt)
# First will read name and coordinates of rectangular boxes to treat into file 'FILE_DEF_BOXE'
##############################################################################################
vboxes, vi1, vj1, vi2, vj2 = bt.read_coor(vdic['FILE_DEF_BOXE'])
nbb = len(vboxes)
print ''
rmean_sst = nmp.zeros((nt,nbb))
rmean_sss = nmp.zeros((nt,nbb))
for jb in range(nbb):
cbox = vboxes[jb] ; print '\n *** Focus on '+cbox+' box'
i1 = vi1[jb]
j1 = vj1[jb]
i2 = vi2[jb]+1
j2 = vj2[jb]+1