#return Convolve(AvgIRF, Exp(Time, Amp, LifeTime))+Convolve(AvgIRF, Exp(Time+12.5, Amp, LifeTime)) + 1.0*AvgIRF*ScatterAmp
#FuncToFit = partial(FitFunc, AvgIRF)
FitData = AlignedRaw['Channel_1']
Results = FitFunc(Time, FitData, FitRaw, LastIndex=argmax(Time > 10.0), VarGuesses = [max(FitData), 4.0, FitData[0], 2.0*10.0**8.0])
#print FitExp(Time, AlignedRaw[Sum], GateIndex=argmax(Time > 0.1), LastIndex=argmax(Time > 9.0))
print Results
"""
# AlignedRaw.ChangeColName("Channel_4", "Fit_{Sum}")
# AlignedRaw = AlignedRaw.DeleteCol('Channel_1')
# AlignedRaw = AlignedRaw.DeleteCol('Channel_2')
# AlignedRaw["Fit_{Sum}"] = FitRaw(Time, Results[0], Results[1], Results[2], Results[3])
Data._SetItems()
Data = Data.ViewAsType(Dtype)
from Common.Helpers import Smooth
Normed = ChannelizedArray(Length, 2, Dtype)
for Index in Data.keys():
Nonzero = Norm[Index].nonzero()
Normed[Index][Nonzero] = Data[Index][Nonzero] / Norm[Index][Nonzero]
Normed[Index] = roll(Normed[Index],
(Shift + DataShift - argmax(Normed[Index])))
#Normed[Index] = Smooth(Normed[Index],100, 101)
Normed[Index] = Normed[Index] / sum(Normed[Index])
for g in file_handle.walk_groups():
if g == file_handle.root:
continue
Result = search('(.*(mg water).*) \(Group\)', str(g))
if Result == None or Result.group(1) == '':
continue
if g.TAC_Gain.read() == 3 and g.ChannelCount.read() == 2:
if g._DataType.read() == "ADCData":
Data.append(ADCData(PyTablesGroup=g))
ChannelCount += g.ChannelCount.read()
from DataContainer.StorageArray import ChannelizedArray
TotalNormInt = ChannelizedArray(len(Data[0].ADC_Intervals), 2, 'uint64')
TotalNormInt._Data = file_handle.get_node('/TotalNorm')._RawBinned.read()
TotalNormInt._SetItems()
TotalNorm = ChannelizedArray(len(Data[0].ADC_Intervals), 2, 'float64')
"""
Scatter Data:
(Removed) /2013-08-28 exp 4 mg water 150 degree light
(Removed) /2013-08-28 exp 5 mg water 150 degree light again last time objective dried out
(Removed) /2013-08-28 exp 6 mg water 150 degree light again
/2013-09-05 exp 4 mg water 150 pol
/2013-09-05 exp 5 mg water 240 pol
/2013-09-05 exp 6 mg water 200 pol
/2013-09-05 exp 7 mg water cp
"""
Data = array(Data[3:])
from numpy import sum, roll, argmax, diff
BufferExps = [
'/2013-09-02 exp 10 buffer 150 pol', '/2013-09-02 exp 11 buffer 240 pol',
'/2013-09-02 exp 12 buffer 200 pol', '/2013-09-02 exp 13 buffer cp'
]
from TTSPCfromBH.DataCalc import ADCData
Data = list()
for Exp in BufferExps:
group = file_handle.get_node(Exp)
Data.append(ADCData(PyTablesGroup=group))
from DataContainer.StorageArray import ChannelizedArray
TotalNormInt = ChannelizedArray(len(Data[0].ADC_Intervals), 2, 'uint64')
TotalNormInt._Data = file_handle.get_node('/TotalNorm')._RawBinned.read()
TotalNormInt._SetItems()
TotalNorm = ChannelizedArray(len(Data[0].ADC_Intervals), 2, 'float64')
file_handle.close()
from numpy import sum, roll, argmax
SummedBuffer = ChannelizedArray(len(Data[0].ADC_Intervals), 2, 'float64')
NoTAC_Norm_SummedBuffer = ChannelizedArray(len(Data[0].ADC_Intervals), 2,
'float64')
for D in Data:
Temp = ChannelizedArray(len(Data[0].ADC_Intervals), 2, 'float64')
for Index in NoTAC_Norm_SummedBuffer.keys():
Nonzero = D._RawBinned[Index].nonzero()
Temp[Index][Nonzero] = (1.0 * D._RawBinned[Index][Nonzero])
Temp[Index] = roll(Temp[Index], (Shift - argmax(Temp[Index])))
