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 |
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8 | class SignalGenerator(object):
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9 | """ Signal Generator
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10 | generates signals for testing several helper classes like:
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11 | * fir filters
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12 | * signal extractors
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13 | """
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14 |
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15 | def __init__(self, option_str = 'len 100 noise 3', name = 'SignalGenerator'):
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16 | """ initialize the generator
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17 | sets default signal to generate
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18 | """
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19 | self.__module__ = 'generator'
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20 | self.option_str = option_str.lower()
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21 | self.options = make_options_from_str(option_str)
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22 | self.parse_options()
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23 | self.name = name
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24 |
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25 | def parse_options(self):
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26 | o = self.options #shortcut
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27 | if 'len' in o:
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28 | self.npoints = int(o['len'][0])
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29 | else:
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30 | self.npoints = 100
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31 | if 'noise' in o:
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32 | self.sigma = float(o['noise'][0])
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33 | else:
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34 | self.sigma = 1
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35 | if 'bsl' in o:
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36 | self.bsl = float(o['bsl'][0])
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37 | else:
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38 | self.bsl = -0.5
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39 |
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40 | if 'step' in o:
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41 | self.step_height = float(o['step'][0])
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42 | self.step_start = int(o['step'][1])
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43 | self.step_stop = int(o['step'][2])
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44 |
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45 | if 'triangle' in o:
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46 | self.pulses = []
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47 | # append 1st pulse to list of pulses
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48 | self.pulses.append( ( float(o['triangle'][0]) , float(o['triangle'][1]), int(o['triangle'][2]), int(o['triangle'][3]) ) )
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49 | number_of_pulses_after_1st = (len(o['triangle'])-4)/2
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50 | for i in range(number_of_pulses_after_1st):
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51 | self.pulses.append( ( float(o['triangle'][2*i+4]) , float(o['triangle'][2*i+5]), int(o['triangle'][2]), int(o['triangle'][3]) ) )
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52 |
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53 | if 'spike' in o:
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54 | self.spikes = []
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55 | for i in range(len(o['spike'])/2):
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56 | self.spikes.append( ( int(o['spike'][2*i]), float(o['spike'][2*i+1]) ) )
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57 |
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58 | def __call__(self, option_str = ''):
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59 | if option_str:
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60 | self.option_str = option_str.lower()
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61 | self.options = make_options_from_str(self.option_str)
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62 | self.parse_options()
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63 |
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64 | signal = np.zeros(self.npoints)
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65 | signal += self.bsl
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66 | signal += np.random.randn(self.npoints) * self.sigma
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67 | if 'step' in self.options:
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68 | signal[self.step_start:self.step_stop] += self.step_height
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69 | if 'triangle' in self.options:
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70 | for pulse in self.pulses:
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71 | pos = pulse[0]
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72 | height = pulse[1]
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73 | rise = pulse[2]
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74 | fall = pulse[3]
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75 | start = pos - rise
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76 | stop = pos + fall
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77 | signal[start:pos] += np.linspace(0., height, rise)
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78 | signal[pos:stop] += np.linspace(height, 0. , fall)
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79 | if 'spike' in self.options:
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80 | for spike in self.spikes:
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81 | signal[spike[0]] += spike[1]
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82 | return signal
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83 |
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84 | def __str__(self):
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85 | s = self.name + '\n'
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86 | s += 'possible options and parameters\n'
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87 | s += ' * len: number of samples (100)\n'
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88 | s += ' * noise: sigma (1)\n'
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89 | s += ' * bsl: level (-0.5)\n'
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90 | s += ' * step: height, start, end\n'
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91 | s += ' * triangle: pos height risingedge, fallingedge [pos height ...]\n'
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92 | s += ' * spike: pos height [pos height ...]\n'
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93 |
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94 | s += 'current options are:\n'
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95 | for key in self.options.keys():
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96 | s += key + ':' + str(self.options[key]) + '\n'
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97 | return s
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98 |
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99 |
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100 | class SignalGeneratorCSV(object):
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101 |
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102 | def __init__(self, file_name, option_str = 'len 100 noise 3', name = 'SignalGenerator'):
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103 | time, maxprob, mean, median = np.loadtxt( file_name, delimiter=',', unpack=True)
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104 | csv_data = maxprob
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105 |
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106 | # csv data was downshifted, I shift it up here
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107 | self.csv_data = csv_data - csv_data.min()
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108 |
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109 |
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110 | self.__module__ = 'CSV generator'
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111 | self.option_str = option_str.lower()
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112 | self.options = make_options_from_str(option_str)
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113 | self.parse_options()
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114 | self.name = name
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115 |
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116 | def parse_options(self):
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117 | o = self.options #shortcut
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118 | if 'len' in o:
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119 | self.npoints = int(o['len'][0])
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120 | else:
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121 | self.npoints = 100
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122 | if 'noise' in o:
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123 | self.sigma = float(o['noise'][0])
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124 | else:
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125 | self.sigma = 1
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126 | if 'bsl' in o:
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127 | self.bsl = float(o['bsl'][0])
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128 | else:
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129 | self.bsl = -0.5
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130 |
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131 | if 'step' in o:
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132 | self.step_height = float(o['step'][0])
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133 | self.step_start = int(o['step'][1])
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134 | self.step_stop = int(o['step'][2])
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135 |
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136 | if 'triangle' in o:
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137 | self.pulses = []
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138 | # append 1st pulse to list of pulses
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139 | self.pulses.append( ( float(o['triangle'][0]) , float(o['triangle'][1]), int(o['triangle'][2]), int(o['triangle'][3]) ) )
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140 | number_of_pulses_after_1st = (len(o['triangle'])-4)/2
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141 | for i in range(number_of_pulses_after_1st):
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142 | self.pulses.append( ( float(o['triangle'][2*i+4]) , float(o['triangle'][2*i+5]), int(o['triangle'][2]), int(o['triangle'][3]) ) )
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143 |
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144 | if 'spike' in o:
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145 | self.spikes = []
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146 | for i in range(len(o['spike'])/2):
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147 | self.spikes.append( ( int(o['spike'][2*i]), float(o['spike'][2*i+1]) ) )
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148 |
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149 | if 'csv' in o:
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150 | self.csvs = []
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151 | for i in range(len(o['csv'])/2):
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152 | time = int( o['csv'][2*i] )
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153 | amplitude = float( o['csv'][2*i+1] )
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154 | self.csvs.append( (time, amplitude) )
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155 |
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156 | def __call__(self, option_str = ''):
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157 | if option_str:
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158 | self.option_str = option_str.lower()
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159 | self.options = make_options_from_str(self.option_str)
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160 | self.parse_options()
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161 |
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162 | signal = np.zeros(self.npoints)
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163 | signal += self.bsl
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164 |
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165 | if 'step' in self.options:
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166 | signal[self.step_start:self.step_stop] += self.step_height
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167 | if 'triangle' in self.options:
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168 | for pulse in self.pulses:
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169 | pos = pulse[0]
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170 | height = pulse[1]
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171 | rise = pulse[2]
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172 | fall = pulse[3]
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173 | start = pos - rise
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174 | stop = pos + fall
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175 | signal[start:pos] += np.linspace(0., height, rise)
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176 | signal[pos:stop] += np.linspace(height, 0. , fall)
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177 | if 'spike' in self.options:
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178 | for spike in self.spikes:
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179 | signal[spike[0]] += spike[1]
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180 | if 'csv' in self.options:
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181 | for csv in self.csvs:
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182 | amplitude = csv[1]
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183 | time = csv[0]
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184 | csv_data = self.csv_data.copy()
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185 | #scale
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186 | csv_data *= amplitude
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187 | # add shifted
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188 | print 'bumm', len(csv_data)
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189 | print csv_data.shape
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190 | print signal[time:time+len(csv_data)].shape
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191 | signal[time:time+len(csv_data)] += csv_data
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192 |
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193 | # add noise
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194 | signal += + np.random.normal(0.0,self.sigma, signal.shape)
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195 | return signal
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196 |
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197 | def __str__(self):
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198 | s = self.name + '\n'
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199 | s += 'possible options and parameters\n'
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200 | s += ' * len: number of samples (100)\n'
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201 | s += ' * noise: sigma (1)\n'
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202 | s += ' * bsl: level (-0.5)\n'
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203 | s += ' * step: height, start, end\n'
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204 | s += ' * triangle: pos height risingedge, fallingedge [pos height ...]\n'
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205 | s += ' * spike: pos height [pos height ...]\n'
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206 | s += ' * csv: pos height [pos height ...]\n'
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207 |
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208 | s += 'current options are:\n'
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209 | for key in self.options.keys():
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210 | s += key + ':' + str(self.options[key]) + '\n'
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211 | return s
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212 |
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213 |
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214 | # Helper function to parse signalname and create a dictionary
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215 | # dictionary layout :
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216 | # key : string
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217 | # value : [list of parameters]
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218 | def make_options_from_str(signalname):
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219 | options = {}
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220 | for word in (signalname.lower()).split():
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221 | if word.isalpha():
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222 | current_key = word
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223 | options[current_key] = []
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224 | # if word.isdigit():
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225 | else:
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226 | options[current_key].append(word)
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227 | # else:
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228 | # print '-nothing'
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229 | return options
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230 |
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231 | if __name__ == '__main__':
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232 | from plotters import Plotter
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233 | myGenerator = SignalGenerator('len 400 noise 0.3 bsl -2.5 triangle 50 10.2 10 100 65 10 150 20 spike 100 50. 20 50 21 49')
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234 | sig = myGenerator()
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235 | print myGenerator
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236 |
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237 | p = Plotter('generator test')
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238 | p(sig)
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239 |
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240 | anothergen = SignalGeneratorCSV('PulseTemplate_PointSet_0.csv',
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241 | 'len 1000 noise 0.4 bsl -2.0 csv 300 1 60 2 650 1 spike 110 50')
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242 | sig2 = anothergen()
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243 | print anothergen
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244 |
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245 | pp = Plotter('CSV Gen Test')
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246 | pp(sig2)
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247 |
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248 | raw_input('any key to quit')
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