def evalbreaks(shuf):
breaklist = {}
yearlist = {}
yearseglist={}
# analysis=r[:-2]
for bs in shuf.keys():
with open(shuf[bs][0]+'.shuffle', 'w') as outf:
b=shuffler(shuf[bs][0])
for line in shuf[bs]:
print >>outf, line
#bs=str(shuf.data().breaks())
print >>outf,bs
if not bs in breaklist:
breaklist[bs]=0
breaklist[bs] += 1
bse=eval(bs)
for bry in bse:
if not bry in yearlist:
yearlist[bry] = 0
yearlist[bry] += 1
for i in range(1,len(bs) -1):
ysl=str(bse[i-1:i+2])
if not ysl in yearseglist:
yearseglist[ysl] =0
yearseglist[ysl] += 1
for i in range(1,len(b.data().breaks())-1):
for offset in [-2,-1,0,1,2]:
st=b.shuffle(i,offset=offset)
print >>outf,i, b.data().breaks()[i], offset,st[3:],
histog=[(st[2][j], st[1][j]) for j in range(len(st[1]))]
print >>outf, histog
for i in range(1,len(b.data().breaks())-1):
xs,ys,yrs=b.spanned(i)
pcb=convergent_breaks.resample_break(np.array(ys), np.array(yrs), N=100,withmode=True)
print >>outf,"C",pcb#, detrend=False)
print >>outf,"S",b.shuffle(i, span=0)[-2]
for i in range(1,len(bs) -1):
ysl=str(bse[i-1:i+2])
if not ysl in yearseglist:
yearseglist[ysl] =0
yearseglist[ysl] += 1
for i in range(1,len(b.data().breaks())-1):
for offset in [-2,-1,0,1,2]:
st=b.shuffle(i,offset=offset)
print >>outf,i, b.data().breaks()[i], offset,st[3:],
histog=[(st[2][j], st[1][j]) for j in range(len(st[1]))]
print >>outf, histog
for i in range(1,len(b.data().breaks())-1):
xs,ys,yrs=b.spanned(i)
pcb=convergent_breaks.resample_break(np.array(ys), np.array(yrs), N=100,withmode=True)
print >>outf,"C",pcb#, detrend=False)
print >>outf,"S",b.shuffle(i, span=0)[-2]
# with open(b.filename()+'.shuffle', 'r') as inf:
# lines =inf.readlines()
# for line in lines:
# print line[:-1]
outf=open(finalname,"w")
print finalname
for brl in breaklist:
bre=eval(brl)
for Y in range(len(bre[1:-1])):
bre=eval(brl)
for Y in range(len(bre[1:-1])):
Year=bre[1:-1][Y]
if Y==0:
lowyr= list(b.data().years()).index(bre[Y])
else:
lowyr= list(b.data().years()).index(bre[Y])+1
highyr=list(b.data().years()).index(bre[Y+2])+1
midyr=list(b.data().years()).index(bre[Y+1])+1
print >>outf, '"'+str(brl)+'"', saveddata["breaklist"][brl], Year, bre[Y], bre[Y+2], saveddata["yearseglist"][str(bre[Y:Y+3])],
#print '"'+str(brl)+'"', saveddata["breaklist"][brl], Year, bre[Y], bre[Y+2], saveddata["yearseglist"][str(bre[Y:Y+3])],
segstr=str((lowyr,highyr))
if not segstr in saveddata["segs"]:
saveddata["segs"][segstr]=convergent_breaks.resample_break(b.data().ys()[lowyr:highyr],b.data().years()[lowyr:highyr], N=100,withmode=True)
pcb=saveddata["segs"][segstr]
print >>outf,pcb[1][0], pcb[2][0], saveddata["yearlist"][Year], pcb[3][0][0], pcb[3][0][1],
if pcb[3][1] == None:
print >>outf,0, 0,
else:
print >>outf,pcb[3][1][0], pcb[3][1][1],
betaseg, alphaseg=regress.regress(b.data().ys()[lowyr:highyr],b.data().years()[lowyr:highyr])
betalow, alphalow=regress.regress(b.data().ys()[lowyr:midyr],b.data().years()[lowyr:midyr])
betahigh, alphahigh=regress.regress(b.data().ys()[midyr:highyr],b.data().years()[midyr:highyr])
print >>outf,betaseg, betalow, betahigh,
#now do a diagnostic on 15 year enclosed
low15 = max(0, midyr-8)
hi15=midyr+8
def Warming(self, mode='Anomaly', baseincludes=[1975, 2004]):
if mode == 'Anomaly':
lo=self.__Years.tolist().index(baseincludes[0])
hi=self.__Years.tolist().index(baseincludes[1])+1
mean=self.__Temperature[lo:hi].mean()
return self.__Temperature-mean
elif mode== 'Kelvin' and self.__Temperature[0] < 200:
return self.__Temperatures + 273.15
elif mode=='Celcius' and self.__Temperature[0] > 200:
return self.__Temperatures - 273.15
elif not mode in self.TempConversion:
raise CMIP3Exception('Conversion mode must be in '+str(self.TempConversion))
else:
return self.__Temperature
if __name__ == "__main__":
fn='C:\\\Users\\s4493222\\Documents\\ReferenceData\\CSIRO_Model_Set\\gwFiles\\csiro_mk3_0.sresa1b.run1.monthly.tas_A1_1871-2100_gw.txt'
fn='C:\\\Users\\s4493222\\Documents\\ReferenceData\\CSIRO_Model_Set\\gwFiles\\csiro_mk3_5.sresa1b.run1.monthly.tas_A1_1871-2100_gw.txt'
c3=CMIP3gw(fn)
for i in range(c3.count()):
print c3.Years()[i], c3.Temperature()[i], c3.Warming()[i]
import ConvergentBreaks as convergent_breaks
import random
ys = c3.Warming()
xs = np.array([random.random() for y in ys])
Years= c3.Years()
convergent_breaks.TraceFile=""
cb=convergent_breaks.convergentBreaks(ys, xs, Years, 'GWAnom', shallow=False, mode="control", guide="Stability",screenpr=0.05, pr=0.01, trace=True)
print cb
if __name__ == "__main__":
prewhiten=False
outf=open("SHUFFLE.txt", "w")
print >>outf, datetime.datetime.now()
data=np.genfromtxt(STARS.fn,delimiter=",",names=True,filling_values =np.NaN) #fill with NaNs so must use their bounds
for d in ["A4"]:#data.dtype.fields.keys():
ys = data[d]
if prewhiten:
ys=whitening.prewhiten(ys,STARS.AlphaEst(ys, 15, option="optIPN4", returnmsgs=False))
Years=data['Year']
xs= np.array([random.random() for i in ys])
for i in range(len(ys)):
print >>outf, Years[i],xs[i], ys[i]
cb=convergent_breaks.convergentBreaks(ys, xs, Years, d, screenpr=0.01, pr=0.01, trace=False)
breaks=[0]
for b in cb[2]:
#print b
breaks.extend([list(Years[:]).index(round(b[0][0])) +1])
breaks.append(len(Years))
#print "BREAKS",breaks
for b in range(len(breaks))[1:-1]:
sc=shuffle_cut(xs[breaks[b-1]:breaks[b+1]], ys[breaks[b-1]:breaks[b+1]], Years[breaks[b-1]:breaks[b+1]], breaks[b]-breaks[b-1])
#jk=jack_knife(xs[breaks[b-1]:breaks[b+1]], ys[breaks[b-1]:breaks[b+1]], Years[breaks[b-1]:breaks[b+1]], breaks[b]-breaks[b-1])
print >>outf, "CUT",d, b, breaks[b], cb[2][b-1][0], sc
outf.close()
#an experiment which simply quantifies the effect of a break at half trend of 0.5, 1.0, 1.5 2.0, 2.5 3.0 Std
std=stats.tstd(xs)
