/
dalekSteps.py
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/
dalekSteps.py
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#The fitting steps for the dalek fitter
initialLum=[8.8,10]
initialVph=[6000,15000]
if __name__!='__main__':
from .launcher import multi_dist_launch
from .read import readModels
import read
import fit
import os,pickle
import numpy as np
import util,config,initialize,abund,param,fitelem
##### FOR DEBUG PURPOSES ONLY SHOULD NOT BE USE LATER ON
remoteBasePath='/priv/manana1/wkerzend/sn_rad_trans'
localBasePath='/Users/wkerzend/wdata'
##### FOR DEBUG PURPOSES ONLY SHOULD NOT BE USE LATER ON
use_machines=['miner','myriad','maggot','merino','minotaur','miami','munch']
#use_machines=['miner']
def getInitLumParams(runDirs,params,doPickle=True):
##### FOR DEBUG PURPOSES ONLY SHOULD NOT BE USE LATER ON
#params=pickle.load(file('params.pkl'))
#runDirs=pickle.load(file('rundirs.pkl'))
#runDirs=[item.replace(remoteBasePath,localBasePath) for item in runDirs]
##### FOR DEBUG PURPOSES ONLY SHOULD NOT BE USE LATER ON
modelGrid=read.modelGrid(runDirs,params)
if doPickle:
pickle.dump(modelGrid,file('mg.pkl','w'))
def checkElementBounds(intervals,bounds):
for element in intervals.keys():
boundCheck=zip(intervals[element],bounds[element])
checkedInterval=[np.max(boundCheck[0]),np.min(boundCheck[1])]
if checkedInterval!=intervals[element]:
print "%s interval out of Bounds. Changing from %s to %s"%(element,intervals[element],checkedInterval)
intervals[element]=checkedInterval
return intervals
def getNextElementParams(element,MG,initParam,bounds,sampleSize=3):
elementAbundance=MG[element]
curValue=initParam[element]
lineMerits,eweights,dweights=fitelem.getSetMerits(element,MG)
emask=np.all(eweights==0,axis=1)
eweights[emask]=1
dweights[emask]=1
merits=np.average(lineMerits,weights=dweights*eweights,axis=1)
merits[emask]=10.
paramSortID=np.argsort(np.abs(merits))
bestParam=paramSortID[:sampleSize]
m,t=np.polyfit(elementAbundance[bestParam],merits[bestParam],1)
bestValue=(1-t)/m
newValue=np.mean([bestValue,curValue])
newDev=np.abs(bestValue-curValue)
newInterval=[newValue-newDev,newValue+newDev]
boundCheck=zip(newInterval,bounds)
checkedInterval=[np.max(boundCheck[0]),np.min(boundCheck[1])]
steady=checkSteadiness(merits)
print "Element %s steadiness %s fraction %s"%(element,steady,newDev/newValue)
if steady>7 or newDev/newValue>0.1:
finished=False
else:
finished=True
return checkedInterval,finished
def checkSteadiness(merits):
dMerits=np.diff(merits)
steadParam=np.abs(np.sum(dMerits>0)-np.sum(dMerits<0))
return steadParam
def getNextLumInterval(params,sampleSize=3):
#lumMerits=read.getGridInt(params['divSpec'])
lumMerits=2.*read.getGridInt(params['subSpec'])/read.getGridInt(params['addSpec'])
paramSortID=np.argsort(np.abs(lumMerits))
bestParam=paramSortID[:sampleSize]
m,t=np.polyfit(params['lum'][bestParam],lumMerits[bestParam],1)
bestLum=(-t)/m
lumDev=min(np.abs(params['lum']-bestLum))
interval=[bestLum-lumDev,bestLum+lumDev]
minIntervalCheck=False
steadParam=checkSteadiness(lumMerits)
if steadParam<4:
print "Warning merits not steady suggestions might be problematic (steadParam=%s)"%steadParam
#WARNING. CHECK SAMPLES THIS WILL BE BAD LATER ON
minInterval=0.02
if 2*lumDev<minInterval:
minIntervalCheck=True
print "Interval too small"
intervalIDs=[0,1]
i=2
while True:
intervalPoints=params['lum'][paramSortID][intervalIDs]
minIntervalPoint,maxIntervalPoint=min(intervalPoints),max(intervalPoints)
if np.abs(minIntervalPoint-maxIntervalPoint)>minInterval:
interval=[minIntervalPoint,maxIntervalPoint]
break
if len(intervalIDs)>len(lumMerits)-3:
interval=[bestLum-2*lumDev,bestLum+2*lumDev]
break
intervalIDs.append(i)
i+=1
evalDic={'suggestValue':bestLum,
'bestFitID':bestParam[0],
'merit':abs(lumMerits[bestParam[0]]),
'merits':lumMerits,
'interval':interval,
'dev':lumDev,
'sortedModelIDX':paramSortID,
'fitKey':'lum',
'mininterval':minIntervalCheck,
'steady':steadParam}
return evalDic
return bestLum,bestParam[0],abs(lumMerits[bestParam[0]]),[bestLum-lumDev,bestLum+lumDev]
def getNextVphInterval(params,sampleSize=4):
contin=[item.smoothg(75) for item in params['subspec']]
#contin=[item.fitContinuum(func='poly1') for item in params['subspec']]
vphMerits=read.getGridSlope(params['subspec'])
curVph=initialize.getCurVph()
#vphMerits=vphMerits[(params['vph']>curVph-4000.)*(params['vph']<curVph+4000.)]
paramSortID=np.argsort(np.abs(vphMerits))
bestParam=paramSortID[:sampleSize]
m,t=np.polyfit(params['vph'][bestParam],vphMerits[bestParam],1)
bestVph=-t/m
vphDev=min(np.abs(params['vph']-bestVph))
minIntervalCheck=False
minInterval=100
interval=[bestVph-vphDev,bestVph+vphDev]
steadParam=checkSteadiness(vphMerits)
if 2*vphDev<minInterval:
print "Interval too small"
minIntervalCheck=True
intervalIDs=[0,1]
i=2
while True:
intervalPoints=params['vph'][paramSortID][intervalIDs]
minIntervalPoint,maxIntervalPoint=min(intervalPoints),max(intervalPoints)
if np.abs(minIntervalPoint-maxIntervalPoint)>minInterval:
interval=[minIntervalPoint,maxIntervalPoint]
break
if len(intervalIDs)>len(vphMerits)-3:
interval=[bestVph-2*vphDev,bestVph+2*vphDev]
break
intervalIDs.append(i)
i+=1
evalDic={'suggestValue':bestVph,
'bestFitID':bestParam[0],
'merit':abs(vphMerits[bestParam[0]]),
'merits':vphMerits,
'dev':vphDev,
'interval':interval,
'sortedModelIDX':paramSortID,
'fitKey':'vph',
'mininterval':minIntervalCheck,
'steady':steadParam}
return evalDic
return bestVph,bestParam[0],abs(vphMerits[bestParam[0]]),[bestVph-vphDev,bestVph+vphDev]
def getNextIGEInterval(params,IGEElement,sampleSize=3):
IGEMeritsOptical=read.getGridOptical(params['subspec'])
IGEMeritsUV=read.getGridUV(params['subspec'])
#VERY IMPORTANT NEED TO CHANGE WEIGHTS. THIS IS ONLY TESTING ATM
IGEMerits=IGEMeritsUV-IGEMeritsOptical
#IGEMerits=read.getGridUV(params['subSpec'])/read.getGridUV(params.origSpec)
paramSortID=np.argsort(np.abs(IGEMerits))
bestParam=paramSortID[:sampleSize]
m,t=np.polyfit(params[IGEElement][bestParam],IGEMerits[bestParam],1)
bestIGE=-t/m
IGEDev=min(np.abs(params[IGEElement]-bestIGE))
minInterval=1e-8
interval=[bestIGE-IGEDev,bestIGE+IGEDev]
steadParam=checkSteadiness(IGEMerits)
minIntervalCheck=False
if 2*IGEDev<minInterval:
print "Interval too small"
minIntervalCheck=True
intervalIDs=[0,1]
i=2
while True:
intervalPoints=params[IGEElement][intervalIDs]
minIntervalPoint,maxIntervalPoint=min(intervalPoints),max(intervalPoints)
if np.abs(minIntervalPoint-maxIntervalPoint)>minInterval:
interval=[minIntervalPoint,maxIntervalPoint]
break
if len(intervalIDs)>len(IGEMerits)-3:
interval=[bestIGE-2*IGEDev,bestIGE+2*IGEDev]
break
intervalIDs.append(i)
i+=1
evalDic={'suggestValue':bestIGE,
'bestFitID':bestParam[0],
'merit':abs(IGEMerits[bestParam[0]]),
'merits':IGEMerits,
'interval':interval,
'dev':IGEDev,
'sortedModelIDX':paramSortID,
'fitKey':IGEElement,
'mininterval':minIntervalCheck,
'steady':steadParam}
return evalDic
return bestIGE,bestParam[0],abs(IGEMerits[bestParam[0]]),[bestIGE-IGEDev,bestIGE+IGEDev]
def readTriModel(params,runDirs,doPickle=True):
lumModelGrid=read.modelGrid(runDirs[0],params[0])
vphModelGrid=read.modelGrid(runDirs[1],params[1])
IGEModelGrid=read.modelGrid(runDirs[2],params[2])
if doPickle:
pickle.dump(lumModelGrid,file('lmg.pkl','w'))
pickle.dump(vphModelGrid,file('vmg.pkl','w'))
pickle.dump(IGEModelGrid,file('img.pkl','w'))
return lumModelGrid,vphModelGrid,IGEModelGrid
def getLumScale(params,noForFit=2):
lums=params['lum']
lumMerits=read.getGridInt(params['divSpec'])
selLumMerits=np.argsort(lumMerits)[:noForFit]
return np.polyfit(lums[selLumMerits],lumMerits[selLumMerits],1)
def getNextLumGuess(params,noForFit=2):
lums=params['lum']
lumMerits=read.getGridInt(params['subspec'])
selLumMerits=np.argsort(lumMerits)[:noForFit]
print lums[selLumMerits],lumMerits[selLumMerits]
return np.polyfit(lums[selLumMerits],lumMerits[selLumMerits],1)
def initLumVphGrid(step=1,gridSize=10,doPickle=True):
t=config.getTimeFromExplosion()
vph=initialize.time2vph(t)
mainConfigDir=config.getMainConfigDir()
modelW7=initialize.readW7Data(os.path.join(mainConfigDir,'w7.combined.dat'))
initDica=config.getVanillaDica()
initDica['t']=t
#Preparing the normalization
initComp=config.getVanillaComp()
initComp.update(initialize.getW7Comp(modelW7,t))
initComp=abund.setNiDecay(initComp,t)
initComp=abund.setCONe(initComp)
initComp=abund.normAbundances(initComp)
initRunDir='init_lumvph_run/'
initialVph=[0.6*vph,1.4*vph]
return lumVphGrid(initialLum,initialVph,1,initRunDir,initComp=initComp,initDica=initDica,gridSize=gridSize,doPickle=doPickle)
def singleElement(element,abundances,step,runDir,initDica=None,initComp=None):
comps=[]
dicas=[{}]*len(abundances)
#Creating the dicas and comps
for abund in abundances:
comps.append({element:abund})
#Launching with different properties
multi_dist_launch(dicas,comps,use_machines,runDir,init_dica=initDica,init_comp=initComp)
return readModels(runDir)
def lumVphGrid(lumLimits,vphLimits,step,runDir,gridSize=10,initDica={},initComp={},doPickle=True):
lums,vphs=util.makeGrid(lumLimits,vphLimits,gridSize)
print "Doing grid: Lum: %s vph: %s"%(lumLimits,vphLimits)
dicas=[]
for lum,vph in zip(lums,vphs):
tmpDica=initDica.copy()
tmpDica.update({'log_lbol':lum,'v_ph':vph})
#print lum,vph
#print tmpDica
dicas.append(tmpDica.copy())
comps=[initComp]*len(dicas)
print "Using Machines %s"%use_machines
#Launching with different properties
multi_dist_launch(dicas,comps,use_machines,runDir,init_dica=initDica,init_comp=initComp)
#Reading model
if doPickle:
pickle.dump(readModels(runDir),file('tmp.pkl','w'))
else:
return readModels(runDir)
#def checkLu