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msu_checktimes.py
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msu_checktimes.py
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#!/env python
# Check times, branches, etc. for MSU data.
import cdms2, os, glob, cdtime
inputroot = '/Users/painter1/data/MSU_Data/'
#models = ['CCSM4', 'CNRM-CM5', 'CSIRO-Mk3-6-0', 'CanESM2', 'GFDL-CM3', 'GFDL-ESM2G', 'GFDL-ESM2M', 'GISS-E2-R',\
# 'HadGEM2-CC', 'IPSL-CM5A-LR', 'MIROC-ESM', 'MIROC5', 'MRI-CGCM3', 'inmcm4' ]
models = ['GISS-E2-H','GISS-E2-R']
ensembles_piControl = { 'ACCESS1-0':['r1i1p1'], 'bcc-csm1-1-m':['r1i1p1'], 'CCSM4':['r1i1p1'],\
'CESM1-BGC':['r1i1p1'], 'CESM1-WACCM':['r2i1p1'],\
'CMCC-CESM':['r1i1p1'], 'CMCC-CMS':['r1i1p1'], 'CNRM-CM5':['r2i1p1'],\
'CSIRO-Mk3-6-0':['r1i1p1'], 'CanESM2':['r1i1p1'], \
'GFDL-CM3':['r1i1p1'], 'GFDL-ESM2G':['r1i1p1'], 'GFDL-ESM2M':['r1i1p1'],\
'GISS-E2-R':['r1i1p1','r1i1p2','r1i1p3'],\
'HadGEM2-AO':['r1i1p1'], 'HadGEM2-CC':['r1i1p1'], 'HadGEM2-ES':['r1i1p1'],\
'IPSL-CM5A-LR':['r1i1p1'], 'IPSL-CM5A-MR':['r1i1p1'], 'IPSL-CM5B-LR':['r1i1p1'],\
'MIROC-ESM':['r1i1p1'], 'MIROC-ESM-CHEM':['r1i1p1'], 'MIROC5':['r1i1p1'],\
'MPI-ESM-MR':['r1i1p1'], 'MRI-CGCM3':['r2i1p1'], 'NorESM1-ME':['r1i1p1'],\
'inmcm4':['r1i1p1'] }
ensembles_historical = { 'ACCESS1-0':['r1i1p1'], 'bcc-csm1-1-m':['r1i1p1'], 'CCSM4':['r1i1p1','r2i1p1','r3i1p1'],\
'CESM1-BGC':['r1i1p1'],\
'CESM1-WACCM':['r2i1p1'], 'CMCC-CESM':['r1i1p1'], 'CMCC-CMS':['r1i1p1'],\
'CNRM-CM5':['r1i1p1','r2i1p1','r4i1p1'], 'CSIRO-Mk3-6-0':['r1i1p1','r10i1p1'],\
'CanESM2':['r1i1p1','r2i1p1','r3i1p1','r4i1p1','r5i1p1'],\
'GFDL-CM3':['r1i1p1'], 'GFDL-ESM2G':['r1i1p1'], 'GFDL-ESM2M':['r1i1p1'],\
'GISS-E2-H':['r1i1p3','r6i1p1'],\
'GISS-E2-R':['r1i1p1','r1i1p2','r1i1p3','r4i1p3'],\
'HadGEM2-AO':['r1i1p1'], \
'HadGEM2-CC':['r1i1p1','r2i1p1','r3i1p1'], 'HadGEM2-ES':['r1i1p1','r2i1p1'],\
'IPSL-CM5A-LR':['r1i1p1','r2i1p1'], 'IPSL-CM5A-MR':['r1i1p1'], 'IPSL-CM5B-LR':['r1i1p1'],\
'MIROC-ESM':['r1i1p1'], 'MIROC-ESM-CHEM':['r1i1p1'], 'MIROC5':['r1i1p1'],\
'MPI-ESM-MR':['r1i1p1'], 'MRI-CGCM3':['r1i1p1'], 'NorESM1-ME':['r1i1p1'],\
'inmcm4':['r1i1p1'] }
ensembles_historicalExt = { 'GISS-E2-H':['r1i1p3','r6i1p1'],\
'GISS-E2-R':['r1i1p1','r1i1p2','r1i1p3','r4i1p3'] }
def print_times_branch( inputroot, model, experiment, ensemble, piControl_units=None, historical_units=None ):
pspath = inputroot+experiment+'/'+model+'/'+ensemble+'/atmos/mon/ps/'
tspath = inputroot+experiment+'/'+model+'/'+ensemble+'/atmos/mon/ts/'
tapath = inputroot+experiment+'/'+model+'/'+ensemble+'/atmos/mon/ta/'
lsps = glob.glob(pspath+'ps_*')
lsps.sort()
lsts = glob.glob(tspath+'ts_*')
lsts.sort()
lsta = glob.glob(tapath+'ta_*')
lsta.sort()
if len(lsts)==0:
print 'files',tspath+'ts_*','not found'
return
f=cdms2.open(lsts[0])
ts0=f['ts']
t0=ts0.getTime()
g=cdms2.open(lsts[-1])
ts1=g['ts']
t1=ts1.getTime()
calstr = t0.calendar
cal=cdtime.StandardCalendar
# For calendar attribute meanings, cf CF Conventions 4.4.1.
# For cdtime calendars, c.f. http://esg.llnl.gov/cdat/cdms_html/cdms-3.htm
# I assume that an experiment and its parent have the same calendar, as do all data of the same experiment.
if calstr=="365_day": cal=cdtime.NoLeapCalendar
elif calstr=="noleap": cal=cdtime.NoLeapCalendar
elif calstr=="gregorian": cal=cdtime.MixedCalendar # not cdtime.Gregorian calendar!
elif calstr=="standard": cal=cdtime.StandardCalendar
elif calstr=="proleptic_gregorian": cal=cdtime.GregorianCalendar
elif calstr=="360_day": cal=cdtime.Calendar360
elif calstr=="julian": cal=cdtime.JulianCalendar
else: print "don't understand calendar",calstr
tmin=t0[:].min()
tmax=t1[:].max()
tb0 = f[ t0.bounds ]
tb1 = g[ t1.bounds ]
tbmin = tb0[0,0]
tbmax = tb1[-1,1]
units = t0.units
# Convert final time and time bound to same units as initial times
tmax = cdtime.reltime( tmax, t1.units ).tocomp(cal).torel(units,cal).value
tbmax = cdtime.reltime( tbmax, t1.units ).tocomp(cal).torel(units,cal).value
if f.parent_experiment_id=='piControl' and piControl_units:
parent_units = piControl_units
elif f.parent_experiment_id=='historical' and historical_units:
parent_units = historical_units
else:
parent_units = ''
if len(lsts)==1:
print "In",tspath,',\n ',lsts[0],\
"\nhas time centers running from",tmin,"to",tmax,\
"and time bounds from",tbmin,"to",tbmax,units,'(',calstr,')'
else:
print "In",tspath,',\n ',lsts[0],"...\n...",lsts[-1],\
"\nhave time running from",tmin,"to",tmax,\
"and time bounds from",tbmin,"to",tbmax,units,'(',calstr,')'
tminrel = cdtime.reltime( tmin, units )
tmincomp = tminrel.tocomp(cal)
tbminrel = cdtime.reltime( tbmin, units )
tbmincomp = tbminrel.tocomp(cal)
print "i.e.,",tmincomp, 'to', cdtime.reltime(tmax,units).tocomp(cal)," and ",\
tbmincomp,"to",cdtime.reltime(tbmax,units).tocomp(cal)
if f.parent_experiment_id==None or f.parent_experiment_id=='N/A':
print "and there is no parent."
else:
print "and branch(es) from ",f.parent_experiment_id,\
getattr(f,'parent_experiment_rip','(rip not available)')," at parent time",f.branch_time,\
parent_units
if len(parent_units)>0:
tprel = cdtime.reltime(float(f.branch_time),parent_units)
tpcomp = tprel.tocomp(cal)
# The branch time is in the parent's units and should be the same moment of time as the
# initial time for this experiment. If it isn't, the difference is the "offset" which
# needs to be applied to times (of this experiment or its parent) to make their data
# strictly comparable.
tmrp = tbmincomp.torel(parent_units,cal)
u = parent_units.split(' ')[0] # usually 'days'
print "i.e.,",tpcomp," so the offset is", tmrp.value-tprel.value,u
print '\n'
f.close()
g.close()
return units
def print_ts_centering( inputroot, model, experiment, ensemble, piControl_units=None, historical_units=None ):
tspath = inputroot+experiment+'/'+model+'/'+ensemble+'/atmos/mon/ts/'
lsts = glob.glob(tspath+'ts_*')
lsts.sort()
if len(lsts)==0:
print 'files',tspath+'ts_*','not found'
return
f=cdms2.open(lsts[0])
ts = f['ts']
t = ts.getTime()
time_bnds = f['time_bnds']
print "cell_methods=",ts.cell_methods," t[0]=",t[0]," in bounds",time_bnds[0,:]
# Note we see that cell_methods contains "time: mean" and bounds is [0. 31.] for January (The
# first month for Hadley is November so bounds is [0. 30.]). Many models also provide the
# sampling interval used in computing this mean. CF CF Conventions section 7.3 and 7.3.2.
# To print information on time range and branch times:
for model in models:
print '\n',model,'----------------\n'
if model in ensembles_piControl.keys():
for ensemble in ensembles_piControl[model]:
piControl_units = print_times_branch( inputroot, model, 'piControl', ensemble )
if model.find("IPSL")==0 or model=="GISS-E2-R" or model=="GISS-E2-H" or model=="CCSM4":
# IPSL, GISS, and CCSM4 follow special standards :-)
piControl_units = "years since 0" # used for branch time, not internally in piControl
else:
piControl_units = None
if model in ensembles_historical.keys():
for ensemble in ensembles_historical[model]:
historical_units = print_times_branch( inputroot, model, 'historical', ensemble, piControl_units )
if model.find("IPSL")==0 or model=="GISS-E2-R" or model=="GISS-E2-H" or model=="CCSM4":
# IPSL, GISS, and CCSM4 follow special standards :-)
historical_units = "years since 0" # used for branch time, not internally in piControl
#print_times_branch( inputroot, model, 'rcp85', ensemble, piControl_units, historical_units )
print_times_branch( inputroot, model, 'historicalExt', ensemble, piControl_units, historical_units )
# To print information on time centering and averaging:
for model in models:
print '\n',model,'----------------\n'
for ensemble in ensembles_historical[model]:
print_ts_centering( inputroot, model, 'historical', ensemble )