t = TL.Timelist[k]
inputfile = INPUTDIR + t.strftime("%Y%m%d") + "_d-OC_CNR-L4-CHL-MedOC4_SAM_7KM-MED-REP-v02.nc"
CHL = Sat.readfromfile(inputfile, "lchlm")
SAT_3D[iFrame, :, :] = CHL
Sat2d = Sat.averager(SAT_3D)
masknan = TheMask.mask_at_level(0)
Sat2d[~masknan] = np.NaN
var = "SATchl"
layer = Layer(0, 10)
fig, ax = mapplot(
{"varname": var, "clim": [0, 0.4], "layer": layer, "data": Sat2d, "date": "annual"},
fig=None,
ax=None,
mask=TheMask,
coastline_lon=clon,
coastline_lat=clat,
)
ax.set_xlim([-5, 36])
ax.set_ylim([30, 46])
ax.set_xlabel("Lon").set_fontsize(12)
ax.set_ylabel("Lat").set_fontsize(12)
ax.ticklabel_format(fontsize=10)
ax.text(
-4, 44.5, var + " [mg /m^3]", horizontalalignment="left", verticalalignment="center", fontsize=14, color="black"
)
ax.text(
-4, 32, "Ave:" + layer.string(), horizontalalignment="left", verticalalignment="center", fontsize=13, color="black"
)
outfile = OUTPUTDIR + "Map_" + var + "_" + req_label + "_Ave" + layer.longname() + ".png"
if args.optype=='integral':
integrated = MapBuilder.get_layer_integral(De, layer)
else:
integrated = MapBuilder.get_layer_average(De, layer)
integrated=integrated * VARCONV
# mask200=TheMask.mask_at_level(200)
mask200=TheMask.mask_at_level(LIMIT_PER_MASK[il])
# clim = [M3d[TheMask.mask].min(), M3d[TheMask.mask].max()]
clim=CLIM_DICT[var]
integrated200=integrated*mask200 # taglio il costiero
integrated200[integrated200==0]=np.nan # sostituisco gli 0 con i NAN
#pl.set_cmap('gray_r') #changes the colormap
fig,ax = mapplot({'varname':var, 'clim':clim, 'layer':layer, 'data':integrated200, 'date':''},fig=None,ax=None,mask=TheMask,coastline_lon=clon,coastline_lat=clat)
ax.set_xlim([-5,36])
ax.set_ylim([30,46])
ax.set_xlabel('Lon').set_fontsize(12)
ax.set_ylabel('Lat').set_fontsize(12)
ax.ticklabel_format(fontsize=10)
ax.text(-4,44.5,var + ' [' + UNITS_DICT[var] + ']',horizontalalignment='left',verticalalignment='center',fontsize=14, color='black')
if args.optype=='integral':
ax.text(-4,32,'Int:' + layer.string() ,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
outfile = OUTPUTDIR + "Map_" + var + "_" + req_label + "_Int" + layer.longname() + ".png"
else:
ax.text(-4,32,'Ave:' + layer.string() ,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
outfile = OUTPUTDIR + "Map_" + var + "_" + req_label + "_Ave" + layer.longname() + ".png"
ax.xaxis.set_ticks(np.arange(-2,36,6))
ax.yaxis.set_ticks(np.arange(30,46,4))
ax.text(-4,30.5,req_label,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
for iFrame, k in enumerate(indexes):
t = TL.Timelist[k]
inputfile = INPUTDIR + t.strftime("%Y%m") + "_d-OC_CNR-L4-CHL-MedOC4_SAM_7KM-MED-REP-v02.nc"
CHL = Sat.readfromfile(inputfile,'lchlm')
SAT_3D[iFrame,:,:] = CHL
Sat2d=Sat.averager(SAT_3D)
mask=TheMask.mask_at_level(0)
Sat2d[~mask] = np.NaN
var = 'SATchl'
#layer = Layer(0,10)
#fig,ax = mapplot({'varname':var, 'clim':[0,0.4], 'layer':layer, 'data':Sat2d, 'date':'annual'},fig=None,ax=None,mask=TheMask,coastline_lon=clon,coastline_lat=clat)
fig,ax = mapplot({'clim':[0,0.4], 'data':Sat2d},fig=None,ax=None,mask=TheMask,coastline_lon=clon,coastline_lat=clat)
ax.set_xlim([-5,36])
ax.set_ylim([30,46])
ax.set_xlabel('Lon').set_fontsize(12)
ax.set_ylabel('Lat').set_fontsize(12)
ax.ticklabel_format(fontsize=10)
ax.text(-4,44.5,var + ' [mg /m^3]',horizontalalignment='left',verticalalignment='center',fontsize=14, color='black')
#ax.text(-4,32,'Ave:' + layer.string() ,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
outfile = OUTPUTDIR + "Map_" + var + "_" + req_label + ".png"
ax.xaxis.set_ticks(np.arange(-2,36,6))
ax.yaxis.set_ticks(np.arange(30,46,4))
ax.text(-4,30.5,req_label,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
ax.grid()
title = "%s %s" % ('annual', var)
fig.suptitle(title)
fig.savefig(outfile)
if args.optype=='integral':
integrated = MapBuilder.get_layer_integral(De, layer)
else:
integrated = MapBuilder.get_layer_average(De, layer)
integrated=integrated * VARCONV
mask=TheMask.mask_at_level(LF[il]['mapdepthfilter'])
# clim = [M3d[TheMask.mask].min(), M3d[TheMask.mask].max()]
clim=CLIM_DICT[var]
integrated_masked=integrated*mask # taglio il costiero
integrated_masked[integrated_masked==0]=np.nan # sostituisco gli 0 con i NAN
#pl.set_cmap('gray_r') #changes the colormap
#fig,ax = mapplot({'varname':var, 'clim':clim, 'layer':layer, 'data':integrated_masked, 'date':'annual'},fig=None,ax=None,mask=TheMask,coastline_lon=clon,coastline_lat=clat)
fig,ax = mapplot({'clim':clim, 'data':integrated_masked, },fig=None,ax=None,mask=TheMask,coastline_lon=clon,coastline_lat=clat)
ax.set_xlim([-5,36])
ax.set_ylim([30,46])
ax.set_xlabel('Lon').set_fontsize(11)
ax.set_ylabel('Lat').set_fontsize(12)
ax.ticklabel_format(fontsize=10)
ax.text(-4,44.5,var + ' [' + UNITS_DICT[var] + ']',horizontalalignment='left',verticalalignment='center',fontsize=14, color='black')
if args.optype=='integral':
#ax.text(-4,32,'Int:' + layer.string() ,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
outfile = OUTPUTDIR + "Map_" + var + "_" + req_label + "_Int" + layer.longname() + ".png"
else:
#ax.text(-4,32,'Ave:' + layer.string() ,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
outfile = OUTPUTDIR + "Map_" + var + "_" + req_label + "_Ave" + layer.longname() + ".png"
ax.xaxis.set_ticks(np.arange(-2,36,6))
ax.yaxis.set_ticks(np.arange(30,46,4))
#ax.text(-4,30.5,req_label,horizontalalignment='left',verticalalignment='center',fontsize=13, color='black')
else:
integrated = MapBuilder.get_layer_average(De, layer)
integrated = integrated * VARCONV
# mask200=TheMask.mask_at_level(200)
mask = TheMask.mask_at_level(args.mapdepthfilter)
# clim = [M3d[TheMask.mask].min(), M3d[TheMask.mask].max()]
clim = CLIM_DICT[var]
integrated_masked = integrated * mask # taglio il costiero
integrated_masked[integrated_masked == 0] = np.nan # sostituisco gli 0 con i NAN
# pl.set_cmap('gray_r') #changes the colormap
fig, ax = mapplot(
{"varname": var, "clim": clim, "layer": layer, "data": integrated_masked, "date": "annual"},
fig=None,
ax=None,
mask=TheMask,
coastline_lon=clon,
coastline_lat=clat,
)
ax.set_xlim([-5, 36])
ax.set_ylim([30, 46])
ax.set_xlabel("Lon").set_fontsize(12)
ax.set_ylabel("Lat").set_fontsize(12)
ax.ticklabel_format(fontsize=10)
ax.text(
-4,
44.5,
var + " [" + UNITS_DICT[var] + "]",
horizontalalignment="left",
verticalalignment="center",
fontsize=14,
"_d-OC_CNR-L4-CHL-MedOC4_SAM_7KM-MED-REP-v02.nc"
print inputfile
CHL = Sat.readfromfile(inputfile,'lchlm')
SAT_3D[iFrame,:,:] = CHL
iFrame +=1
Sat2d=Sat.averager(SAT_3D)
masknan=TheMask.mask_at_level(0)
Sat2d[~masknan] = np.NaN
var = 'SATchl'
layer = Layer(0,10)
fig,ax = mapplot({'varname':var, 'clim':[0,0.4], \
'layer':layer, 'data':Sat2d, 'date':'annual'}, \
fig=None,ax=None, \
mask=TheMask, \
coastline_lon=clon, \
coastline_lat=clat)
ax.set_xlim([-5,36])
ax.set_ylim([30,46])
ax.set_xlabel('Lon').set_fontsize(12)
ax.set_ylabel('Lat').set_fontsize(12)
ax.ticklabel_format(fontsize=10)
ax.text(-4,44.5,var + ' [mg /m^3]', \
horizontalalignment='left', \
verticalalignment='center', \
fontsize=14, color='black')
ax.text(-4,32,'Ave:' + layer.string() , \
horizontalalignment='left', \
verticalalignment='center', \
fontsize=13, color='black')
