def getExample1Data(conditionData, conditions, shockTubeEffectiveHeatingTimes, smilesInExperiments):
"""
Parses the simulation's data to make generic data objects to compare with shock tube data taken from figure 1 of
#Y. Hiadka, K. Sato, H. Hoshikawa, T. Nishimori, H. Tanaka, K. Inami, N. Ito. Combust. Flame, 120 3 (2000), pp. 245-264
"""
#First get the time points close to
allResults=[]
for T, timepoint in shockTubeEffectiveHeatingTimes.iteritems():
for smiles in smilesInExperiments:
temperatureResults=GenericData(label=label='Temperature',
data = []
units = 'K')
for conIndex, data in conditionData:
if conditions[conIndex].T0==T:
#index1 is the index of time from the simulation closest to timepoint
#data is organized as (timeArray, rest of data)
index1=findNearest(data[0], timepoint)
for speciesData in data[1]:
if smiles==speciesData.species:
if smiles not in exptCompDict1: exptCompDict1[smiles]=[]
#need to multiply by 20, in the experiment, they don't seem to count the Ar in the mole fraction
exptCompDict1[smiles].append(resultsDictionary[T][1][index1][index2+1]*20)
(index1, timepoint2)=rt.getNearestTime(timepoint1, resultsDictionary[T][2])
for index2, smiles in enumerate(majorSpecies[0:4]):
if smiles not in exptCompDict2: exptCompDict2[smiles]=[]
exptCompDict2[smiles].append(resultsDictionary[T][3][index1][index2+1]*20)
# Plot the results if matplotlib is installed.
# See http://ma tplotlib.org/ to get it.
if '--plot' in sys.argv[1:]:
import matplotlib.pyplot as plt
#first test
# plt.semilogy(times1, data1[:,1], 'r', label="sim1")
# plt.semilogy(times2, data2[:,1], label='sim2')
# plt.legend()
# plt.show()
exptCompDict1={}
exptCompDict2={}
#Plot vs experiment
for T, timepoint1 in shockTubeEffectiveHeatingTimes.iteritems():
(index1,timepoint2)=rt.getNearestTime(timepoint1, resultsDictionary[T][0])
for index2, smiles in enumerate(majorSpecies[0:4]):
if smiles not in exptCompDict1: exptCompDict1[smiles]=[]
#need to multiply by 20, in the experiment, they don't seem to count the Ar in the mole fraction
exptCompDict1[smiles].append(resultsDictionary[T][1][index1][index2+1]*20)
(index1, timepoint2)=rt.getNearestTime(timepoint1, resultsDictionary[T][2])
for index2, smiles in enumerate(majorSpecies[0:4]):
if smiles not in exptCompDict2: exptCompDict2[smiles]=[]
exptCompDict2[smiles].append(resultsDictionary[T][3][index1][index2+1]*20)
x=1
plt.clf()
plt.subplot(2, 2, 1)
plt.plot(C2H6molfrac.keys(), C2H6molfrac.values(), 'o', label="Expt")
plt.plot(shockTubeEffectiveHeatingTimes.keys(),exptCompDict1['CC'], 'r', label='Trusted')
