1 | #!/usr/bin/python -tt
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2 | #
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3 | # Dominik Neise, Werner Lustermann
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4 | # TU Dortmund, ETH Zurich
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5 | #
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6 | import numpy as np
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7 | from generator import *
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8 | from fir_filter import *
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9 |
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10 | class GlobalMaxFinder(object):
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11 | """ Pulse Extractor
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12 | Finds the global maximum in the given window.
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13 | (Best used with filtered data)
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14 | """
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15 |
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16 | def __init__(self, min=30, max=250 , name = 'GlobalMaxFinder'):
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17 | """ initialize search Window
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18 |
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19 | """
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20 | self.__module__="extractor"
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21 | self.min = min
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22 | self.max = max
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23 | self.name = name
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24 |
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25 | def __call__(self, data):
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26 | if data.ndim > 1:
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27 | time = np.argmax( data[ : , self.min:self.max ], 1)
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28 | amplitude = np.max( data[ : , self.min:self.max], 1)
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29 | else:
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30 | time = np.argmax( data[self.min:self.max])
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31 | amplitude = np.max( data[self.min:self.max])
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32 | return amplitude, time+self.min
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33 |
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34 | def __str__(self):
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35 | s = self.name + '\n'
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36 | s += 'window:\n'
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37 | s += '(min,max) = (' + str(self.min) + ',' + str(self.max) + ')'
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38 | return s
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39 |
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40 | def test(self):
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41 | pass
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42 |
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43 |
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44 | class WindowIntegrator(object):
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45 | """ Integrates in a given intergration window around the given position
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46 | """
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47 |
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48 | def __init__(self, min=13, max=23 , name = 'WindowIntegrator'):
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49 | """ initialize integration Window
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50 | """
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51 | self.__module__="extractor"
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52 | self.min = min
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53 | self.max = max
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54 | self.name = name
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55 |
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56 | def __call__(self, data, pos):
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57 | integral = np.empty( data.shape[0] )
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58 | for pixel in range( data.shape[0] ):
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59 | integral[pixel] = data[pixel, (pos[pixel]-self.min):(pos[pixel]+self.max)].sum()
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60 | return integral
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61 |
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62 | def __str__(self):
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63 | s = self.name + '\n'
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64 | s += 'window:\n'
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65 | s += '(min,max) = (' + str(self.min) + ',' + str(self.max) + ')'
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66 | return s
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67 |
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68 | class FixedWindowIntegrator(object):
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69 | """ Integrates in a given intergration window
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70 | """
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71 |
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72 | def __init__(self, min=55, max=105 , name = 'FixedWindowIntegrator'):
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73 | """ initialize integration Window
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74 | """
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75 | self.__module__="extractor"
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76 | self.min = min
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77 | self.max = max
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78 | self.name = name
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79 |
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80 | def __call__(self, data):
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81 | integral = np.empty( data.shape[0] )
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82 | for pixel in range( data.shape[0] ):
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83 | integral[pixel] = data[pixel, self.min:self.max].sum()
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84 | return integral
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85 |
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86 | def __str__(self):
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87 | s = self.name + '\n'
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88 | s += 'window:\n'
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89 | s += '(min,max) = (' + str(self.min) + ',' + str(self.max) + ')'
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90 | return s
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91 |
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92 | class ZeroXing(object):
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93 | """ Finds zero crossings in given data
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94 | (should be used on CFD output for peak finding)
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95 | returns list of lists of time_of_zero_crossing
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96 | """
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97 | def __init__(self, slope=1, name = 'ZeroXing'):
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98 | self.__module__="extractor"
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99 | if (slope >= 0):
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100 | self.slope = 1 # search for rising edge crossing
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101 | elif (slope < 0):
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102 | self.slope = -1 # search for falling edge crossing
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103 | self.name = name
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104 |
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105 |
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106 | def __call__(self, data):
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107 | all_hits = []
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108 | for pix_data in data:
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109 | hits = []
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110 | for i in range( data.shape[1]-1 ):
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111 | if ( self.slope > 0 ):
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112 | if ( pix_data[i] > 0 ):
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113 | continue
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114 | else:
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115 | if ( pix_data[i] < 0):
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116 | continue
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117 | if ( pix_data[i] * pix_data[i+1] <= 0 ):
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118 | # interpolate time of zero crossing with
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119 | # linear polynomial: y = ax + b
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120 | a = (pix_data[i+1] - pix_data[i]) / ((i+1) - i)
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121 | time = -1.0/a * pix_data[i] + i
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122 | hits.append(time)
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123 | all_hits.append(hits)
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124 | return all_hits
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125 |
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126 | def __str__(self):
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127 | s = self.name + '\n'
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128 | if (self.slope == 1):
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129 | s += 'search for rising edge crossing.\n'
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130 | else:
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131 | s += 'search for falling edge crossing.\n'
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132 | return s
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133 |
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134 |
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135 |
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136 | def _test_GlobalMaxFinder():
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137 | gmf = GlobalMaxFinder(30,250)
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138 | print gmf
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139 | amplitude, time = gmf(event)
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140 | if abs(amplitude.mean() - 10) < 0.5:
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141 | print "Test 1: OK GlobalMaxFinder found amplitude correctly", amplitude.mean()
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142 | if abs(time.mean() - 65) < 2:
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143 | print "Test 1: OK GlobalMaxFinder found time correctly", time.mean()
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144 | else:
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145 | print "BAD: time mean:", time.mean()
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146 |
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147 | def _test_FixedWindowIntegrator():
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148 | fwi = FixedWindowIntegrator(50,200)
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149 | print fwi
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150 | integral = fwi(event)
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151 | #value of integral should be: 150*bsl + 8*10/2 + 100*10/2 = 465
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152 | if abs( integral.mean() - 465) < 2:
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153 | print "Test 2: OK FixedWindowIntegrator found integral correctly", integral.mean()
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154 | else:
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155 | print "Test 2: X FixedWindowIntegrator integral.mean failed:", integral.mean()
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156 |
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157 | def _test_ZeroXing():
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158 | cfd = CFD()
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159 | sa = SlidingAverage(8)
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160 | print sa
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161 | cfd_out = sa(event)
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162 | cfd_out = cfd(cfd_out )
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163 | cfd_out = sa(cfd_out)
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164 | zx = ZeroXing()
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165 | print zx
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166 | list_of_list_of_times = zx(cfd_out)
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167 | times = []
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168 | for list_of_times in list_of_list_of_times:
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169 | times.extend(list_of_times)
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170 | times = np.array(times)
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171 |
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172 | hist,bins = np.histogram(times,3000,(0,300))
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173 | most_probable_time = np.argmax(hist)
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174 | print 'most probable time of zero-crossing', most_probable_time/10.
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175 | print 'this includes filter delays ... for average filter setting 8 this turns out to be 78.8 most of the time'
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176 |
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177 | if __name__ == '__main__':
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178 | import matplotlib.pyplot as plt
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179 | """ test the extractors """
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180 |
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181 | # Generate a fake event, with a triangular pulse at slice 65
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182 | sg = SignalGenerator()
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183 | pulse_str = 'len 300 bsl -0.5 noise 0.5 triangle 65 10 8 100'
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184 | pulse = sg(pulse_str)
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185 | event = []
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186 | for i in range(1440):
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187 | event.append(sg(pulse_str))
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188 | event = np.array(event)
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189 | print 'test event with 1000 pixel generated, like this:'
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190 | print pulse_str
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191 | print
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192 |
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193 | print '_test_GlobalMaxFinder()'
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194 | _test_GlobalMaxFinder()
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195 | print
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196 | print
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197 | print '_test_FixedWindowIntegrator()'
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198 | _test_FixedWindowIntegrator()
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199 | print
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200 | print
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201 | print '_test_ZeroXing()'
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202 | _test_ZeroXing()
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203 | print
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