Changeset 14198


Ignore:
Timestamp:
06/21/12 15:43:11 (12 years ago)
Author:
neise
Message:
playing
File:
1 edited

Legend:

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  • fact/tools/pyscripts/sandbox/dneise/mc_pulses_for_sabrina/gen_TH1D.py

    r13468 r14198  
    77import sys
    88from ROOT import *
     9from scipy import interpolate
     10
     11#from plotters import Plotter
     12import matplotlib.pyplot as plt
    913
    1014class SignalGenerator(object):
     
    105109        time, maxprob, mean, median = np.loadtxt( file_name, delimiter=',', unpack=True)
    106110        csv_data = maxprob
     111       
     112        # shift the input data such, that the left baseline is equal to zero
     113        csv_data = csv_data - csv_data[:50].mean()
     114       
     115        # I want the data to be longer than they are, so I add 1000 slices left and right
     116        self.csv_data = np.zeros(2000 + len(csv_data))
     117       
     118        for i in range(len(csv_data)):
     119            self.csv_data[1000+i] = csv_data[i]
     120        for i in range(1000):
     121            self.csv_data[i] = csv_data[:50].mean()
     122            self.csv_data[-1*i] = csv_data[-50:].mean()
     123       
     124        # fermi dirac distribution for weighting the input data.
     125        # we do not believe the right tail is really higher than zero, so we make it go to zero.
     126        weight_function = lambda x : 1. / (1 + np.exp((x - 1200.)/25.))
     127        x = np.arange(0,len(self.csv_data),1)
     128        weights = map(weight_function, x)
     129       
     130        bla = self.csv_data.copy()
     131       
     132        self.csv_data = weights * self.csv_data
     133       
     134        tck = interpolate.splrep(x, self.csv_data ,s=50)
     135        tck2 = interpolate.splrep(x, bla ,s=50)
     136       
     137        xnew = np.arange(0,len(self.csv_data), 0.1)
     138        ynew = interpolate.splev(xnew,tck,der=0)
     139        ynew2 = interpolate.splev(xnew,tck2,der=0)
     140
     141        plt.figure()
     142        plt.plot(x,self.csv_data,'.:k',xnew,ynew,'b',x, weights, '.:r', x,bla,'.:g',xnew,ynew2,'m')
     143        plt.show()
     144        raw_input('stop')
    107145       
    108146        # csv data was downshifted, I shift it up here
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