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)
