def testYears(self):
f = cdms2.open(
os.path.join(cdat_info.get_sampledata_path(), 'th_yr.nc'))
th = f('th', time=slice(-3, None, 1))
t = th.getTime()
cdutil.setTimeBoundsYearly(t)
self.assertEqual(th.shape, (3, 64, 128))
self.assertTrue(
numpy.equal(th.getTime().getBounds()[0], [1997., 1998.]).all())
dep = cdutil.YEAR.departures(th, statusbar=None)
self.assertEqual(dep.shape, (3, 64, 128))
def setTimeBounds( self, var ):
time_axis = var.getTime()
if time_axis._bounds_ == None:
try:
time_unit = time_axis.units.split(' since ')[0].strip()
if time_unit == 'hours':
values = time_axis.getValue()
freq = 24/( values[1]-values[0] )
cdutil.setTimeBoundsDaily( time_axis, freq )
elif time_unit == 'days':
cdutil.setTimeBoundsDaily( time_axis )
elif time_unit == 'months':
cdutil.setTimeBoundsMonthly( time_axis )
elif time_unit == 'years':
cdutil.setTimeBoundsYearly( time_axis )
except Exception, err:
wpsLog.debug( "Exception in setTimeBounds:\n " + traceback.format_exc() )
#!/usr/bin/env python
# Adapted for numpy/ma/cdms2 by convertcdms.py
import cdms2,cdutil,sys,os,numpy
cdms2.setAutoBounds('on')
f = cdms2.open(os.path.join(sys.prefix,'sample_data','th_yr.nc'))
th=f('th',time=slice(-3,None,1))
t=th.getTime()
cdutil.setTimeBoundsYearly(t)
assert(th.shape==(3,64,128))
assert(numpy.equal(th.getTime().getBounds()[0],[1997.,1998.]).all())
dep=cdutil.YEAR.departures(th,statusbar=None)
assert(dep.shape==(3, 64, 128))
#!/usr/bin/env python
# Adapted for numpy/ma/cdms2 by convertcdms.py
import cdms2,cdutil,sys,os,numpy,cdat_info
cdms2.setAutoBounds('on')
f = cdms2.open(os.path.join(cdat_info.get_sampledata_path(),'th_yr.nc'))
th=f('th',time=slice(-3,None,1))
t=th.getTime()
cdutil.setTimeBoundsYearly(t)
assert(th.shape==(3,64,128))
assert(numpy.equal(th.getTime().getBounds()[0],[1997.,1998.]).all())
dep=cdutil.YEAR.departures(th,statusbar=None)
assert(dep.shape==(3, 64, 128))
def pdsi_time_series(D,start_time,stop_time,SM=None,best_fit=True,aerosols=False,use_tree=True):
""" plot time series of PDSI data between start_time and stop_time"""
if aerosols:
aerosol_start = cdtime.comptime(1950,1,1)
aerosol_stop = cdtime.comptime(1975,12,31)
cru_p=D.ALL.project_cru_on_solver(start=start_time,solver=truncated_solver(D,aerosol_start,aerosol_stop,include_cru=True))
dai_p=D.ALL.project_dai_on_solver(start=start_time,solver=truncated_solver(D,aerosol_start,aerosol_stop,include_dai=True))
cdutil.setTimeBoundsYearly(dai_p)
tree_p=D.ALL.get_tree_ring_projection(solver=truncated_solver(D,aerosol_start,aerosol_stop))
else:
cru_p=D.ALL.project_cru_on_solver(start=start_time)
dai_p=D.ALL.project_dai_on_solver(start=start_time)
cdutil.setTimeBoundsYearly(dai_p)
tree_p=D.ALL.projection
x=np.arange(start_time.year,stop_time.year+1)
if use_tree:
cdutil.setTimeBoundsYearly(tree_p)
ytree=tree_p(time=(start_time,stop_time,"oob")).anom()
Plotting.time_plot(ytree,color=get_dataset_color("tree"),label="Tree ring reconstructions",lw=1)
xtree=x[:len(ytree)]
if best_fit:
p=np.polyfit(xtree,ytree.asma(),1)
plt.plot(xtree,np.polyval(p,xtree),"--",color=get_dataset_color("tree"),lw=1)
cdutil.setTimeBoundsYearly(cru_p)
if start_time.year>=1900:
ycru=cru_p(time=(start_time,stop_time,"oob")).anom()
Plotting.time_plot(ycru,color=get_dataset_color("cru"),label ="CRU",lw=1)
xcru=x[:len(ycru)]
if best_fit:
p=np.polyfit(xcru,ycru.asma(),1)
print "CRU slope is"+str(p[0]*10.)
plt.plot(xcru,np.polyval(p,xcru),"--",color=get_dataset_color("cru"),lw=1)
ydai=dai_p(time=(start_time,stop_time,"oob")).anom()
Plotting.time_plot(ydai,color=get_dataset_color("dai"),label="Dai",lw=1)
xdai=x[:len(ydai)]
if best_fit:
p=np.polyfit(xdai,ydai.asma(),1)
print "DAI slope is"+str(p[0]*10.)
plt.plot(xdai,np.polyval(p,xdai),"--",color=get_dataset_color("dai"),lw=1)
#Plotting.time_plot(dai_p(time=(start_time,stop_time)).anom())
plt.xlabel("Time")
plt.ylabel("Projection")
if SM is not None:
SM.project_soilmoisture("MERRA2")
SM.project_soilmoisture("GLEAM")
for depth in ["30cm","2m"]:
for dataset in ["GLEAM","MERRA2"]:
ymoist=SM.OBS_PROJECTIONS[dataset][depth](time=(start_time,stop_time))
xmoist=x[:len(ymoist)]
Plotting.time_plot(ymoist,color=get_dataset_color(dataset,depth),lw=1,label=dataset+": "+sm_label(depth))
if best_fit:
p=np.polyfit(xmoist,ymoist.asma(),1)
plt.plot(xmoist,np.polyval(p,xmoist),"--",color=get_dataset_color(dataset,depth),lw=1)
if aerosols:
return ytree,ycru,ydai
