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240 | f9daq | 1 | { |
2 | "cells": [ |
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3 | { |
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4 | "cell_type": "markdown", |
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5 | "metadata": { |
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6 | "deletable": true, |
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7 | "editable": true |
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8 | }, |
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9 | "source": [ |
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10 | "# On trigger signal acquisition\n", |
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11 | "\n", |
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12 | "## Description\n", |
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13 | "\n", |
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14 | "This example shows how to acquire 16k samples of signal on fast analog inputs.\n", |
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15 | "Signal will be acquired when the internal trigger condition is meet.\n", |
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16 | "Time length of the acquired signal depends on the time scale of a buffer\n", |
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17 | "that can be set with a decimation factor.\n", |
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18 | "\n", |
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19 | "TODO: describe some calculations\n", |
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20 | "\n", |
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21 | "## Required hardware\n", |
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22 | "\n", |
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23 | "- Red Pitaya\n", |
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24 | "- Signal (function) generator\n", |
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25 | "\n", |
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26 | "![wiring diagram](img/generate_continous_signal_on_fast_analog_output.png)" |
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27 | ] |
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28 | }, |
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29 | { |
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30 | "cell_type": "markdown", |
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31 | "metadata": { |
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32 | "deletable": true, |
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33 | "editable": true |
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34 | }, |
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35 | "source": [ |
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36 | "The `rp` object is an instance of the `redpitaya` class.\n", |
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37 | "When the object is initialized, the FPGA bitstream is loaded and\n", |
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38 | "memory mapped FPGA registers are mapped into software.\n", |
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39 | "Repeating FPGA bitstream loading will cause all registers to reset,\n", |
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40 | "while mapping the memory space multiple times will cause segmentation faults.\n", |
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41 | "So untill this issues are handled by the driver\n", |
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42 | "a `redpitaya` instance should be created only once." |
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43 | ] |
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44 | }, |
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45 | { |
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46 | "cell_type": "code", |
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47 | "execution_count": null, |
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48 | "metadata": { |
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49 | "collapsed": false, |
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50 | "deletable": true, |
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51 | "editable": true |
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52 | }, |
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53 | "outputs": [], |
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54 | "source": [ |
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55 | "from redpitaya import redpitaya\n", |
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56 | "rp = redpitaya()" |
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57 | ] |
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58 | }, |
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59 | { |
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60 | "cell_type": "code", |
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61 | "execution_count": null, |
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62 | "metadata": { |
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63 | "collapsed": false, |
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64 | "deletable": true, |
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65 | "editable": true |
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66 | }, |
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67 | "outputs": [], |
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68 | "source": [ |
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69 | "# generator configuration\n", |
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70 | "#rp.GenReset()\n", |
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71 | "#rp.GenFreq(0, 100000.0)\n", |
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72 | "#rp.GenAmp(0, 1.0)\n", |
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73 | "#rp.GenWaveform(0, rp.WAVEFORM_SINE)\n", |
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74 | "#rp.GenOutEnable(0)" |
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75 | ] |
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76 | }, |
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77 | { |
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78 | "cell_type": "code", |
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79 | "execution_count": null, |
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80 | "metadata": { |
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81 | "collapsed": false, |
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82 | "deletable": true, |
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83 | "editable": true |
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84 | }, |
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85 | "outputs": [], |
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86 | "source": [ |
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87 | "# acquisition configuration\n", |
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88 | "size = rp.AcqGetBufSize()\n", |
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89 | "print(size)\n", |
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90 | "rp.AcqReset()\n", |
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91 | "rp.AcqSetDecimationFactor(1)\n", |
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92 | "rp.AcqSetTriggerLevel(0, -0.05)\n", |
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93 | "#rp.AcqSetPostTriggerDelay(size//2) # place trigger in the middle of the buffer\n", |
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94 | "#rp.AcqSetPostTriggerDelay(size//2)\n", |
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95 | "rp.AcqSetPostTriggerDelay(0)\n", |
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96 | "\n", |
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97 | "size = 1024\n", |
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98 | "channels = (0,1)\n", |
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99 | "\n", |
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100 | "# start acquisition process\n", |
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101 | "rp.AcqStart()\n", |
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102 | "# set trigger source to start acquisition\n", |
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103 | "rp.AcqSetTriggerSrc(rp.TRIG_SRC_CHA_PE)\n", |
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104 | "# wait in a loop for trigger state to chage from TRIG_STATE_WAITING\n", |
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105 | "while rp.AcqGetTriggerSrc():\n", |
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106 | " pass\n", |
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107 | "print('triggered')\n", |
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108 | "\n", |
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109 | "# read data from FPGA FIFO into memory and display it\n", |
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110 | "buff = [rp.AcqGetOldestDataV(ch, size) for ch in channels];" |
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111 | ] |
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112 | }, |
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113 | { |
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114 | "cell_type": "code", |
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115 | "execution_count": null, |
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116 | "metadata": { |
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117 | "collapsed": false, |
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118 | "deletable": true, |
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119 | "editable": true |
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120 | }, |
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121 | "outputs": [], |
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122 | "source": [ |
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123 | "import time\n", |
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124 | "import numpy as np\n", |
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125 | "\n", |
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126 | "from bokeh.io import push_notebook, show, output_notebook\n", |
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127 | "from bokeh.models import HoverTool, Range1d\n", |
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128 | "from bokeh.plotting import figure\n", |
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129 | "from bokeh.plotting import show, output_file, vplot\n", |
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130 | "from bokeh.resources import INLINE \n", |
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131 | "from bokeh.models import Column\n", |
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132 | "output_notebook(resources=INLINE)" |
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133 | ] |
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134 | }, |
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135 | { |
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136 | "cell_type": "code", |
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137 | "execution_count": null, |
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138 | "metadata": { |
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139 | "collapsed": false, |
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140 | "deletable": true, |
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141 | "editable": true |
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142 | }, |
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143 | "outputs": [], |
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144 | "source": [ |
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145 | "def hfill(histogram, datum, weight=1):\n", |
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146 | " for idx, b in enumerate(histogram[1]):\n", |
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147 | " if idx > 0:\n", |
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148 | " if (datum < b and datum >= histogram[1][0]) or (datum <= b and idx == len(histogram[1]) - 1):\n", |
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149 | " histogram[0][idx - 1] += int(weight)\n", |
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150 | " break\n", |
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151 | " \n", |
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152 | "def h1d(title, titlex, titley, nbins, xmin,xmax):\n", |
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153 | " h = np.histogram([], bins=nbins, range= (xmin,xmax))\n", |
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154 | " p = figure(title=title,tools=\"save\", background_fill_color=\"#E8DDCB\")\n", |
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155 | " p.quad(top=h[0], bottom=0, left=h[1][:-1], right=h[1][1:])\n", |
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156 | " p.xaxis.axis_label = 'p.h.(ADC)'\n", |
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157 | " p.yaxis.axis_label = 'N'\n", |
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158 | " return [h,p]" |
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159 | ] |
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160 | }, |
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161 | { |
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162 | "cell_type": "code", |
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163 | "execution_count": null, |
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164 | "metadata": { |
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165 | "collapsed": false, |
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166 | "deletable": true, |
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167 | "editable": true, |
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168 | "scrolled": false |
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169 | }, |
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170 | "outputs": [], |
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171 | "source": [ |
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172 | "hadc = np.histogram([], bins=40, range= (0,0.5))\n", |
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173 | "p1 = figure(title=\"ADC distribution\",tools=\"save\", background_fill_color=\"#E8DDCB\")\n", |
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174 | "p1.quad(top=hadc[0], bottom=0, left=hadc[1][:-1], right=hadc[1][1:], fill_color=\"#036564\", line_color=\"#033649\")\n", |
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175 | "p1.xaxis.axis_label = 'p.h.(ADC)'\n", |
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176 | "p1.yaxis.axis_label = 'N'\n", |
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177 | "\n", |
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178 | "\n", |
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179 | "htdc = np.histogram([], bins=100, range= (0,size))\n", |
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180 | "p2 = figure(title=\"TDC distribution\",tools=\"save\", background_fill_color=\"#E8DDCB\")\n", |
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181 | "p2.quad(top=htdc[0], bottom=0, left=htdc[1][:-1], right=htdc[1][1:], fill_color=\"#036564\", line_color=\"#033649\")\n", |
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182 | "p2.xaxis.axis_label = 'p.h.(ADC)'\n", |
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183 | "p2.yaxis.axis_label = 'N'\n", |
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184 | "\n", |
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185 | "#print(hist)\n", |
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186 | "#for event in [ 1,2,3,4,4,5,6,32,4,10]:\n", |
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187 | "# hfill(hist,event)\n", |
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188 | "\n", |
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189 | "#adcplot = show(p1, notebook_handle=True)\n", |
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190 | "N = size\n", |
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191 | "x = np.arange(N) / rp.FS\n", |
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192 | "\n", |
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193 | "colors = ('red', 'blue')\n", |
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194 | "hover = HoverTool(mode = 'vline', tooltips=[(\"T\", \"@x\"), (\"V\", \"@y\")])\n", |
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195 | "tools = \"pan,wheel_zoom,box_zoom,reset,crosshair,save\"\n", |
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196 | "p = figure(plot_height=500, plot_width=900, title=\"oscilloscope\", toolbar_location=\"above\", tools=(tools, hover))\n", |
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197 | "p.xaxis.axis_label='time [s]'\n", |
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198 | "p.yaxis.axis_label='voltage [V]'\n", |
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199 | "p.y_range=Range1d(-0.1, 0.1)\n", |
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200 | "r = [p.line(x, buff[i], line_width=1, line_alpha=0.7, color=colors[i]) for i in channels]\n", |
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201 | "\n", |
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202 | "target = show( Column(p, p1, p2), notebook_handle=True)" |
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203 | ] |
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204 | }, |
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205 | { |
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206 | "cell_type": "code", |
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207 | "execution_count": null, |
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208 | "metadata": { |
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209 | "collapsed": false, |
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210 | "deletable": true, |
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211 | "editable": true |
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212 | }, |
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213 | "outputs": [], |
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214 | "source": [ |
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215 | "size = 1024\n", |
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216 | "channels = (0,1)\n", |
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217 | "\n", |
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218 | "rp.AcqReset()\n", |
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219 | "rp.AcqSetDecimationFactor(1)\n", |
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220 | "threshold = -0.05\n", |
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221 | "rp.AcqSetTriggerLevel(0, threshold)\n", |
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222 | "rp.AcqSetPostTriggerDelay(size-80)\n", |
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223 | "\n", |
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224 | "neve = 0\n", |
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225 | "while True:\n", |
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226 | " rp.AcqStart()\n", |
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227 | " rp.AcqSetTriggerSrc(rp.TRIG_SRC_CHA_NE) \n", |
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228 | " while (rp.AcqSetTriggerSrc(rp.TRIG_SRC_CHA_NE)): pass\n", |
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229 | " buff = [rp.AcqGetLatestDataV(ch, size) for ch in channels];\n", |
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230 | "\n", |
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231 | " adcdata = np.absolute(np.amin(buff[0]))\n", |
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232 | " signal = np.array(buff[0])\n", |
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233 | " tdcdata = np.where(signal < threshold)[0] # get item\n", |
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234 | "# print (adcdata, tdcdata)\n", |
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235 | " hfill(hadc,adcdata)\n", |
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236 | " \n", |
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237 | " for a in tdcdata:\n", |
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238 | " if a - tdcdata[0] > 5:\n", |
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239 | " hfill(htdc,a-tdcdata[0])\n", |
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240 | " break \n", |
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241 | " neve+=1\n", |
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242 | " for i in channels:\n", |
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243 | " r[i].data_source.data['y'] = buff[i]\n", |
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244 | "# push updates to the plot continuously using the handle (intererrupt the notebook kernel to stop)\n", |
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245 | " if (neve%10 == 0):\n", |
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246 | " push_notebook(handle=target)\n", |
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247 | "# time.sleep(0.05)" |
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248 | ] |
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249 | } |
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250 | ], |
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251 | "metadata": { |
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252 | "kernelspec": { |
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253 | "display_name": "Python 3", |
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254 | "language": "python", |
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255 | "name": "python3" |
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256 | }, |
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257 | "language_info": { |
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258 | "codemirror_mode": { |
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259 | "name": "ipython", |
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260 | "version": 3 |
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261 | }, |
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262 | "file_extension": ".py", |
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263 | "mimetype": "text/x-python", |
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264 | "name": "python", |
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265 | "nbconvert_exporter": "python", |
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266 | "pygments_lexer": "ipython3", |
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267 | "version": "3.5.2" |
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268 | } |
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269 | }, |
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270 | "nbformat": 4, |
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271 | "nbformat_minor": 2 |
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272 | } |