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The statistics for the total Layer 0-1000m are calculated as the MEAN VALUES #85

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The statistics for the total Layer 0-1000m are calculated as the MEAN VALUES #85

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39 changes: 28 additions & 11 deletions src/bitsea/validation/deliverables/static_clim_validation_OpenSea.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ def argument():
import xarray as xr

#List consistent with /g100_work/OGS_test2528/Observations/TIME_RAW_DATA/STATIC/MedBGCins/Clim_Annual_Ref
LayerList = [Layer(0,10), Layer(10,30), Layer(30,60), Layer(60,100), Layer(100,150), Layer(150,300), Layer(300,600), Layer(600,1000)]
LayerList = [Layer(0,10), Layer(10,30), Layer(30,60), Layer(60,100), Layer(100,150), Layer(150,300), Layer(300,600), Layer(600,1000), Layer(0,1000)]

INPUTDIR=addsep(args.inputdir)
OUTDIR = addsep(args.outdir)
Expand Down Expand Up @@ -136,24 +136,41 @@ def Layers_Mean(Pres,Values,LayerList):
STATS = np.zeros((nLayers,3),np.float32)*np.nan
STATS_STD = np.zeros((nLayers,7),np.float32)*np.nan
for ilayer, layer in enumerate(LayerList):

refsubs = CLIM_REF_static[:,ilayer]
modsubs = CLIM_MODEL[:,ilayer]
bad = np.isnan(refsubs) | np.isnan(modsubs)
good = ~bad

m = matchup(modsubs[good], refsubs[good])

STATS[ilayer,0] = m.bias()
STATS[ilayer,1] = m.RMSE()
STATS[ilayer,2] = m.correlation()
# SET THE METRICS OF THE TOTAL LAYER 0-1000 AS THE MEAN VALUES OF THE LAYERS ABOVE
if (layer == Layer(0,1000) ):

STATS[ilayer,0] = np.mean(STATS[:-1,0])
STATS[ilayer,1] = np.mean(STATS[:-1,1])
STATS[ilayer,2] = np.mean(STATS[:-1,2])

STATS_STD[ilayer,0] = np.mean(STATS_STD[:-1,0])
STATS_STD[ilayer,1] = np.mean(STATS_STD[:-1,1])
STATS_STD[ilayer,2] = np.mean(STATS_STD[:-1,2])
STATS_STD[ilayer,3] = np.mean(STATS_STD[:-1,3])
STATS_STD[ilayer,4] = np.mean(STATS_STD[:-1,4])
STATS_STD[ilayer,5] = np.mean(STATS_STD[:-1,5])
STATS_STD[ilayer,6] = np.mean(STATS_STD[:-1,6])

else:
STATS[ilayer,0] = m.bias()
STATS[ilayer,1] = m.RMSE()
STATS[ilayer,2] = m.correlation()

STATS_STD[ilayer,0] = m.bias()
STATS_STD[ilayer,1] = m.RMSE()
STATS_STD[ilayer,2] = m.correlation()
STATS_STD[ilayer,3] = np.mean(modsubs[good])
STATS_STD[ilayer,4] = np.mean(refsubs[good])
STATS_STD[ilayer,5] = np.std(modsubs[good])
STATS_STD[ilayer,6] = np.std(refsubs[good])
STATS_STD[ilayer,0] = m.bias()
STATS_STD[ilayer,1] = m.RMSE()
STATS_STD[ilayer,2] = m.correlation()
STATS_STD[ilayer,3] = np.mean(modsubs[good])
STATS_STD[ilayer,4] = np.mean(refsubs[good])
STATS_STD[ilayer,5] = np.std(modsubs[good])
STATS_STD[ilayer,6] = np.std(refsubs[good])
writetable(OUTDIR + var + "-LAYER-Y-CLASS4-CLIM.txt", STATS,rows_names,column_names)
writetable(OUTDIR + var + "-LAYER-Y-CLASS4-CLIM_STD.txt", STATS_STD,rows_names,column_names_STD)

Expand Down