dimsv = ('time', 'scen', anames[i] + '_index')
for j in range(nvars):
avev = f.createVariable(ivars[j] + '_' + anames[i], 'f4', dimsv, fill_value = 1e20, zlib = True, complevel = 9)
avev.units = vunits[j]
avev.long_name = 'average ' + anames[i] + ' ' + ivars[j]
slicer = [slice(0, n) for n in var[j].shape]
dimslist = list(dims[j])
dimslist.remove('scen')
timeidx, latidx, lonidx = dimslist.index('time'), dimslist.index('lat'), dimslist.index('lon')
for k in range(len(scensel)):
slicer[dims[j].index('scen')] = k
data = var[j][slicer].transpose((timeidx, latidx, lonidx))
if yieldvar:
yld = yieldv[slicer].transpose((timeidx, latidx, lonidx))
yldmask = getyieldmask(yld, yieldthr1, yieldthr2)
else:
yldmask = None
data = avobj.av(data, adata[i], lats, weights, calcarea = calcarea, mask = yldmask, numchunks = numchunks)
if leaddim == 'scen':
avev[k, :, :] = data.transpose((1, 0))
else:
avev[:, k, :] = data.transpose((1, 0))
f.close()
dimsv = ('time', 'scen', anames[i] + '_index')
for j in range(nvars):
avev = f.createVariable(ivars[j] + '_' + anames[i], 'f4', dimsv, fill_value = 1e20, zlib = True, complevel = 9)
avev.units = vunits[j]
avev.long_name = 'average ' + anames[i] + ' ' + ivars[j]
slicer = [slice(0, n) for n in var[j].shape]
dimslist = list(dims[j])
dimslist.remove('scen')
timeidx, latidx, lonidx = dimslist.index('time'), dimslist.index('lat'), dimslist.index('lon')
for k in range(len(scensel)):
slicer[dims[j].index('scen')] = k
data = var[j][slicer].transpose((timeidx, latidx, lonidx))
if yieldvar:
yld = yieldv[slicer].transpose((timeidx, latidx, lonidx))
yldmask = getyieldmask(yld, yieldthr1, yieldthr2)
else:
yldmask = None
data = avobj.av(data, adata[i], lats, weights, calcarea = calcarea, mask = yldmask, numchunks = numchunks)
if leaddim == 'scen':
avev[k, :, :] = data.transpose((1, 0))
else:
avev[:, k, :] = data.transpose((1, 0))
f.close()
var[i] = v[:]
var[i] = masked_where(isnan(var[i]), var[i]) # mask out NaNs
var[i].mask = resize(var[i].mask,
var[i].shape) # resize mask if necessary
vunits[i] = v.units if 'units' in v.ncattrs() else ''
createAggFile(options.output, time, tunits, audata, anames, aunits, alongnames)
f = nc(options.output, 'a') # open file for appending
if options.type == 'mean': # averager instance
avobj = MeanAverager()
else:
avobj = SumAverager()
for i in range(nmasks):
dims = (anames[i] + '_index', 'time')
for j in range(nvars):
avev = f.createVariable(ivars[j] + '_' + anames[i],
'f4',
dims,
fill_value=1e20,
zlib=True,
complevel=9)
avev[:] = avobj.av(var[j],
adata[i],
lats,
weights,
calcarea=options.calcarea)
avev.units = vunits[j]
avev.long_name = ' '.join([options.type, anames[i], ivars[j]])
f.close()
ivars = [v.strip() for v in ivars.split(',')]
nvars = len(ivars)
var = [0] * nvars; vunits = [0] * nvars
with nc(ifile) as f:
lats = f.variables['lat'][:]
t = f.variables['time']
time = t[:]
tunits = t.units if 'units' in t.ncattrs() else ''
for i in range(nvars):
v = f.variables[ivars[i]]
var[i] = v[:]
var[i] = masked_where(isnan(var[i]), var[i]) # mask out NaNs
var[i].mask = resize(var[i].mask, var[i].shape) # resize mask if necessary
vunits[i] = v.units if 'units' in v.ncattrs() else ''
createAggFile(options.output, time, tunits, audata, anames, aunits, alongnames)
f = nc(options.output, 'a') # open file for appending
if options.type == 'mean': # averager instance
avobj = MeanAverager()
else:
avobj = SumAverager()
for i in range(nmasks):
dims = (anames[i] + '_index', 'time')
for j in range(nvars):
avev = f.createVariable(ivars[j] + '_' + anames[i], 'f4', dims, fill_value = 1e20, zlib = True, complevel = 9)
avev[:] = avobj.av(var[j], adata[i], lats, weights, calcarea = options.calcarea)
avev.units = vunits[j]
avev.long_name = ' '.join([options.type, anames[i], ivars[j]])
f.close()
