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')