def calc_runstats(datablob,sims, seas=None,siglevel=0.05):
"""
datablob: 'ctl','pert','diff' should be timeseries of regional means
sims: a tuple of sim names in the datablob. (prob unnecessary)
seas: 2 or 3 month seasons
return allstats: dictionary of 'tpvals', 'fpvals' for sim key and then sea key
"""
ctldt = datablob['ctl']
pertdt = datablob['pert']
diffdt = datablob['diff']
simspdt = con.get_simpairsdict()
if seas==None:
seasons=('SON','DJF','MAM','JJA')
else:
seasons=seas
allstats={}; alltpval={}; allfpval={}
for sim in sims:
ctlsim=ctldt[sim]
pertsim=pertdt[sim]
seatpval={}; seafpval={}
for sea in seasons:
thestats={}
print sim + ' ' + sea
ctl=ctlsim[sea]
pert=pertsim[sea]
(tstat,tpval,lstat,lpval) = cutl.calc_pvals(pert,ctl)
## print ' DIFF: ' + str(pert.mean()-ctl.mean()) + ', CTL mean: ' + str(ctl.mean()) + ', PERT mean: ' + str(pert.mean())
## tstat, tpval = sp.stats.ttest_ind(pert,ctl) # add autocorr @@
## print ' TSTAT: ' + str(tstat) + ' PVAL: ' + str(tpval)
## if tpval<=siglevel:
## print ' **The ensemble means are significantly different (' + str(1-siglevel) + ')'
## #thestats['tpval'] = pval
## #fstat, fpval = sp.stats.f_oneway(pert,ctl) # same as t statistic
## #print ' FSTAT: ' + str(fstat) + ' PVAL: ' + str(fpval)
## #if fpval<=siglevel:
## # print ' **The ensemble means are significantly different (' + str(1-siglevel) + ')'
## print ' CTL std: ' + str(ctl.std()) + ', PERT std: ' + str(pert.std())
## lstat, lpval = sp.stats.levene(pert,ctl)
## print ' LSTAT: ' + str(lstat) + ' PVAL: ' + str(lpval)
## if lpval<=siglevel:
## print ' **The ensemble variances are significantly different (' + str(1-siglevel) + ')'
seatpval[sea]=tpval
seafpval[sea]=lpval
alltpval[sim]=seatpval
allfpval[sim]=seafpval
allstats['tpval']=alltpval
allstats['fpval']=allfpval
return allstats
ax.plot(tpxx,tppdf_fitted,'r')
ax.set_xlabel(label)
ax.set_title('TOT')
ax.legend(('CTL','PERT'))
print label
print 'TOT CTL (mean,std): ' + str(tcnormed)
print 'TOT PERT (mean,std): ' + str(tpnormed)
if printtofile:
fig.savefig('histpdf_' + label + '_ANTTOTsbplt.pdf')
printtofile=False
plot_anttotanom_histpdf(allantr2,alltotr2,
label=(field2 + region2 + '_' + str(sea2)),printtofile=printtofile)
cutl.calc_pvals(allantr2,alltotr2)
print '-------------------------'
plot_anttotanom_histpdf(allantr1,alltotr1,
label=(field1 + region1 + '_' + str(sea1)),printtofile=printtofile)
cutl.calc_pvals(allantr1,alltotr1)
plot_anttotsbplt_histpdf((allantcr2,allantpr2),(alltotcr2,alltotpr2),
label=(field2 + region2 + '_' + str(sea2)),printtofile=printtofile)
print 'ANT: ' + field2, region2
cutl.calc_pvals(allantpr2,allantcr2)
print 'TOT: ' + field2, region2
cutl.calc_pvals(alltotpr2,alltotcr2)
plot_anttotsbplt_histpdf((allantcr1,allantpr1),(alltotcr1,alltotpr1),
