def runElementCycle(initParam,elements=['C','Ca','Mg','Si','S','Ti','Ni0','Fe0'],samples=10,scaling='lin'):
#initParam.autoRelAbund='O'
intervals,initParam=initElementCycle(initParam,elements,samples,scaling)
#print "Dumping initial run in initElemCycle.pkl"
#pickle.dump(elementMG,file('initElemCycle.pkl','w'))
bounds=initialize.getElementsBounds(initParam.comp)
intervalHistory={'Si':[],'S':[],'Mg':[],'C':[]}
i=1
while True:
converged=[]
for element in ['Si','S','Mg','C']:
if scaling=='log':
elementRange=np.logspace(*np.log10(intervals[element]),**dict(num=samples))
elif scaling=='lin':
elementRange=np.linspace(*intervals[element],**dict(num=samples))
elementMG=launcherSteps.launchElementCycle({element:elementRange},initParam=initParam)
plot.plotElementModelGrid(element,elementMG[0],suffix=str(i))
intervals[element],finished=dalekSteps.getNextElementParams(element,elementMG[0],initParam,bounds[element])
converged.append(finished)
intervalHistory[element].append(intervals[element])
print "New Interval for %s: %s "%(element,intervals[element])
initParam[element]=np.mean(intervals[element])
bounds=initialize.getElementsBounds(initParam.comp)
intervals=dalekSteps.checkElementBounds(intervals,bounds)
print "Convergence status %s"%converged
if all(converged): break
print "Looking for stop.txt in %s"%os.getcwd()
if os.path.exists('stop.txt'): break
i+=1
return intervalHistory
def initElementCycle(initParam,elements,samples,scaling):
bounds=initialize.getElementsBounds(initParam.comp)
divIntervals={'Si':[5e-3,5],
'S':[1e-3,1],
'Ca':[0.5e-3,0.5],
'Mg':[0.5e-3,2],
'C':[0.5e-3,0.5],
'Fe0':[1e-3,1]}
intervals=copy.deepcopy(bounds)
initParam.lockIGE=False
initParam.lockIGEwNi=False
initParam.lockIGEwoNi=True
ranges={}
#intervalHistory={}
for element in intervals.keys():
if scaling=='log':
ranges[element]=np.logspace(*np.log10(intervals[element]),**dict(num=samples))
elif scaling=='lin':
ranges[element]=np.linspace(*intervals[element],**dict(num=samples))
else:
raise Exception('Unknown scaling option %s. Please use lin or log.'%scaling)
finished=False
for element in ['Si','S','Mg','C']:
if scaling=='log':
elementRange=np.logspace(*np.log10(intervals[element]),**dict(num=samples))
elif scaling=='lin':
elementRange=np.linspace(*intervals[element],**dict(num=samples))
elementMG=launcherSteps.launchElementCycle({element:elementRange},initParam=initParam)
plot.plotElementModelGrid(element,elementMG[0])
newInterval,finished=dalekSteps.getNextElementParams(element,elementMG[0],initParam,bounds[element])
if not finished: intervals[element]=newInterval
print "New Interval for %s: %s "%(element,intervals[element])
initParam[element]=np.mean(intervals[element])
bounds=initialize.getElementsBounds(initParam.comp)
intervals=dalekSteps.checkElementBounds(intervals,bounds)
#pdb.set_trace()
#allMG=launcherSteps.launchElementCycle(ranges,initParam=initParam)
#elementMG=dict(zip(ranges.keys(),allMG[:-1]))%debug
#curParamMG=allMG[-1]
return intervals,initParam
