for j in range(nv):
# load variable
varfile = findfile(files, scen_irr, variables[j])
if not len(varfile): continue
with nc(indir + sep + varfile) as f:
var = f.variables[variables[j] + '_' + crop]
if not i: vunits[j] = var.units if 'units' in var.ncattrs() else ''
var = var[:]
var[isnan(var)] = 0. # change NaNs to zero
var = shiftdata(var, pd, hd, yearthr) # shift data
var = var[yrsinrange] # restrict to overlapping years
# aggregate
averages[j, :, :, sidx,
iidx] = avobj.sum(var, adata, lats, weights[iidx], calcarea,
ymsk)
averages[j, :, :, sidx, iidx] /= areas[:, :, sidx, iidx]
# sum areas
area1, area2 = areas[:, :, :, 0], areas[:, :, :, 1]
area1[logical_and(area1.mask, ~area2.mask)] = 0.
area2[logical_and(area2.mask, ~area1.mask)] = 0.
areas[:, :, :, 2] = area1 + area2
# create output file
fout = AggregationFile(outfile, time, tunits, scens, audata, aname, aunits,
alongname)
# add area
fout.append('area_' + aname, areas, (aname, 'time', 'scen', 'irr'), 'hectares',
aname + ' harvested area')
for j in range(nvariables):
varfile = findfile(files, variables[j])
print "Reading %s" % varfile
if not varfile:
continue
with Dataset(varfile) as f:
var = f.variables[variables[j] + '_' + crop]
if not i:
vunits[j] = var.units if 'units' in var.ncattrs() else ''
var = var[:]
var[isnan(var)] = 0. # change NaNs to zero
var = shiftdata(var, planting_date, harvest_date, yearthr) # shift data
var = var[yrsinrange] # restrict to overlapping years
# aggregate
print "sum is %s" % avobj.sum(var, adata, lats, weights[iidx], calc_area, ymsk)
averages[j, :, :, iidx] = avobj.sum(var, adata, lats, weights[iidx], calc_area, ymsk)
averages[j, :, :, iidx] /= areas[:, :, iidx]
# sum areas
area1, area2 = areas[:, :, 0], areas[:, :, 1]
area1[logical_and(area1.mask, ~area2.mask)] = 0.
area2[logical_and(area2.mask, ~area1.mask)] = 0.
areas[:, :, 2] = area1 + area2
# create output file
for iidx in range(nirrs):
print "Writing %s" % outfiles[iidx]
fout = AggregationFile(outfiles[iidx], time, tunits, audata, aname, aunits, alongname)
# add area
areas[:, :, sidx, iidx] = avobj.areas(yvar, adata, lats, weights[iidx], calcarea)
for j in range(nv):
# load variable
varfile = findfile(files, scen_irr, variables[j])
if not len(varfile): continue
with nc(indir + sep + varfile) as f:
var = f.variables[variables[j] + '_' + crop]
if not i: vunits[j] = var.units if 'units' in var.ncattrs() else ''
var = var[:]
var[isnan(var)] = 0. # change NaNs to zero
var = shiftdata(var, pd, hd, yearthr) # shift data
var = var[yrsinrange] # restrict to overlapping years
# aggregate
averages[j, :, :, sidx, iidx] = avobj.sum(var, adata, lats, weights[iidx], calcarea, ymsk)
averages[j, :, :, sidx, iidx] /= areas[:, :, sidx, iidx]
# sum areas
area1, area2 = areas[:, :, :, 0], areas[:, :, :, 1]
area1[logical_and(area1.mask, ~area2.mask)] = 0.
area2[logical_and(area2.mask, ~area1.mask)] = 0.
areas[:, :, :, 2] = area1 + area2
# create output file
fout = AggregationFile(outfile, time, tunits, scens, audata, aname, aunits, alongname)
# add area
fout.append('area_' + aname, areas, (aname, 'time', 'scen', 'irr'), 'hectares', aname + ' harvested area')
# add variables