tmin = var.min(axis=0),
tmax = var.max(axis=0),
savail = 1.*(~var2d.mask).sum(axis=1)/var2d.shape[1],
smean = var2d.mean(axis=1),
sstd = var2d.std(axis=1),
smin = var2d.min(axis=1),
smax = var2d.max(axis=1),
)
dstats['thist'] = N.ma.zeros((nbins-1, ny, nx), 'l')
dstats['shist'] = N.ma.zeros((nt, nbins-1), 'l')
for ibin in xrange(nbins-1):
valid = (varm>=bins[ibin])&(varm<bins[ibin+1])
dstats['thist'][ibin] = valid.filled(False).sum(axis=0)
dstats['shist'][:, ibin] = valid.filled(False).reshape((nt, -1)).sum(axis=1)
dstats['thist'][:, maskyx] = N.ma.masked
dstats['shist'][:, maskt] = N.ma.masked
# Indirect using StatAccum
sa = StatAccum(tall=True, sall=True, bins=bins)
sa += var[:7]
sa += var[7:]
istats = sa.get_stats()
# Unitest
result = []
for key in sorted(dstats.keys()):
value = N.ma.allclose(dstats[key], istats[key])
result.append(('assertTrue', value))
# print key, value
)
dstats['thist'] = N.ma.zeros((nbins - 1, ny, nx), 'l'), N.ma.zeros(
(nbins - 1, ny, nx), 'l')
dstats['shist'] = N.ma.zeros((nt, nbins - 1), 'l'), N.ma.zeros((nt, nbins - 1),
'l')
for ivar, varm in enumerate([varm1, varm2]):
for ibin in xrange(nbins - 1):
valid = (varm >= bins[ibin]) & (varm < bins[ibin + 1])
dstats['thist'][ivar][ibin] = valid.filled(False).sum(axis=0)
dstats['shist'][ivar][:, ibin] = valid.filled(False).reshape(
(nt, -1)).sum(axis=1)
dstats['thist'][ivar][:, maskyx] = N.ma.masked
dstats['shist'][ivar][maskt, :] = N.ma.masked
# Indirect using StatAccum
sa = StatAccum(tall=True, sall=True, bins=bins)
sa += var1[:7], var2[:7]
sa += var1[7:], var2[7:]
istats = sa.get_stats()
# Unitest
result = []
for key in sorted(dstats.keys()):
if isinstance(dstats[key], tuple):
for i in 0, 1:
value = N.ma.allclose(dstats[key][i], istats[key][i])
result.append(('assertTrue', value))
else:
value = N.ma.allclose(dstats[key], istats[key])
result.append(('assertTrue', value))
var1.id = 'ssh' var2 = var1.clone() var2[:] += N.ma.sin(var1)*100 var1[3:13, 5:9, 3:7] = MV2.masked var2[5:15, 7:12, 1:5] = MV2.masked var2.long_name = 'Sea level' var2.id = 'sla' mask = var1.mask|var2.mask # common mask vmax = var2.max() bins = N.linspace(-0.1*vmax, 0.9*vmax, 14) nbins = len(bins) restart_file = code_file_name(ext='nc') print restart_file # Normal sa0 = StatAccum(tall=True, sall=True, bins=bins) sa0 += var1[:7], var2[:7] # Dump sa0.dump(restart_file) # Load from scratach sa1 = StatAccum(restart=True, restart_file=restart_file) ## Intermediate load #sa1 = StatAccum(tall=True, sall=True, bins=bins) #sa1 += var1[:5], var2[:5] #sa1.load(restart_file) # # Finish stats sa0 += var1[7:], var2[7:]
