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1 | { | |
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2 | "metadata": { | |
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3 | "name": "Parallel Magics" | |
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4 | }, | |
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5 | "nbformat": 3, | |
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6 | "worksheets": [ | |
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7 | { | |
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8 | "cells": [ | |
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9 | { | |
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10 | "cell_type": "heading", | |
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11 | "level": 1, | |
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12 | "source": [ | |
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13 | "Using Parallel Magics" | |
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14 | ] | |
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15 | }, | |
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16 | { | |
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17 | "cell_type": "markdown", | |
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18 | "source": [ | |
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19 | "IPython has a few magics for working with your engines.", | |
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20 | "", | |
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21 | "This assumes you have started an IPython cluster, either with the notebook interface,", | |
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22 | "or the `ipcluster/controller/engine` commands." | |
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23 | ] | |
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24 | }, | |
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25 | { | |
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26 | "cell_type": "code", | |
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27 | "collapsed": false, | |
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28 | "input": [ | |
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29 | "from IPython import parallel", | |
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30 | "rc = parallel.Client()", | |
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31 | "dv = rc[:]", | |
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32 | "dv.block = True", | |
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33 | "dv" | |
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34 | ], | |
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35 | "language": "python", | |
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36 | "outputs": [] | |
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37 | }, | |
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38 | { | |
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39 | "cell_type": "markdown", | |
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40 | "source": [ | |
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41 | "The parallel magics come from the `parallelmagics` IPython extension.", | |
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42 | "The magics are set to work with a particular View object,", | |
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43 | "so to activate them, you call the `activate()` method on a particular view:" | |
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44 | ] | |
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45 | }, | |
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46 | { | |
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47 | "cell_type": "code", | |
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48 | "collapsed": true, | |
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49 | "input": [ | |
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50 | "dv.activate()" | |
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51 | ], | |
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52 | "language": "python", | |
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53 | "outputs": [] | |
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54 | }, | |
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55 | { | |
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56 | "cell_type": "markdown", | |
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57 | "source": [ | |
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58 | "Now we can execute code remotely with `%px`:" | |
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59 | ] | |
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60 | }, | |
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61 | { | |
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62 | "cell_type": "code", | |
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63 | "collapsed": false, | |
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64 | "input": [ | |
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65 | "%px a=5" | |
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66 | ], | |
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67 | "language": "python", | |
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68 | "outputs": [] | |
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69 | }, | |
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70 | { | |
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71 | "cell_type": "code", | |
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72 | "collapsed": false, | |
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73 | "input": [ | |
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74 | "%px print a" | |
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75 | ], | |
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76 | "language": "python", | |
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77 | "outputs": [] | |
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78 | }, | |
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79 | { | |
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80 | "cell_type": "code", | |
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81 | "collapsed": false, | |
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82 | "input": [ | |
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83 | "%px a" | |
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84 | ], | |
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85 | "language": "python", | |
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86 | "outputs": [] | |
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87 | }, | |
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88 | { | |
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89 | "cell_type": "markdown", | |
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90 | "source": [ | |
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91 | "You don't have to wait for results:" | |
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92 | ] | |
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93 | }, | |
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94 | { | |
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95 | "cell_type": "code", | |
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96 | "collapsed": true, | |
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97 | "input": [ | |
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98 | "dv.block = False" | |
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99 | ], | |
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100 | "language": "python", | |
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101 | "outputs": [] | |
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102 | }, | |
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103 | { | |
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104 | "cell_type": "code", | |
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105 | "collapsed": false, | |
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106 | "input": [ | |
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107 | "%px import time", | |
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108 | "%px time.sleep(5)", | |
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109 | "%px time.time()" | |
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110 | ], | |
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111 | "language": "python", | |
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112 | "outputs": [] | |
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113 | }, | |
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114 | { | |
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115 | "cell_type": "markdown", | |
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116 | "source": [ | |
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117 | "But you will notice that this didn't output the result of the last command.", | |
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118 | "For this, we have `%result`, which displays the output of the latest request:" | |
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119 | ] | |
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120 | }, | |
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121 | { | |
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122 | "cell_type": "code", | |
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123 | "collapsed": false, | |
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124 | "input": [ | |
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125 | "%result" | |
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126 | ], | |
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127 | "language": "python", | |
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128 | "outputs": [] | |
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129 | }, | |
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130 | { | |
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131 | "cell_type": "markdown", | |
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132 | "source": [ | |
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133 | "Remember, an IPython engine is IPython, so you can do magics remotely as well!" | |
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134 | ] | |
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135 | }, | |
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136 | { | |
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137 | "cell_type": "code", | |
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138 | "collapsed": false, | |
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139 | "input": [ | |
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140 | "dv.block = True", | |
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141 | "%px %pylab inline" | |
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142 | ], | |
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143 | "language": "python", | |
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144 | "outputs": [] | |
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145 | }, | |
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146 | { | |
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147 | "cell_type": "markdown", | |
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148 | "source": [ | |
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149 | "`%%px` can also be used as a cell magic, for submitting whole blocks.", | |
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150 | "This one acceps `--block` and `--noblock` flags to specify", | |
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151 | "the blocking behavior, though the default is unchanged.", | |
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152 | "" | |
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153 | ] | |
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154 | }, | |
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155 | { | |
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156 | "cell_type": "code", | |
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157 | "collapsed": true, | |
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158 | "input": [ | |
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159 | "dv.scatter('id', dv.targets, flatten=True)", | |
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160 | "dv['stride'] = len(dv)" | |
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161 | ], | |
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162 | "language": "python", | |
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163 | "outputs": [] | |
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164 | }, | |
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165 | { | |
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166 | "cell_type": "code", | |
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167 | "collapsed": false, | |
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168 | "input": [ | |
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169 | "%%px --noblock", | |
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170 | "x = linspace(0,pi,1000)", | |
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171 | "for n in range(id,12, stride):", | |
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172 | " print n", | |
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173 | " plt.plot(x,sin(n*x))", | |
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174 | "plt.title(\"Plot %i\" % id)" | |
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175 | ], | |
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176 | "language": "python", | |
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177 | "outputs": [] | |
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178 | }, | |
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179 | { | |
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180 | "cell_type": "code", | |
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181 | "collapsed": false, | |
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182 | "input": [ | |
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183 | "%result" | |
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184 | ], | |
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185 | "language": "python", | |
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186 | "outputs": [] | |
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187 | }, | |
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188 | { | |
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189 | "cell_type": "markdown", | |
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190 | "source": [ | |
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191 | "It also lets you choose some amount of the grouping of the outputs with `--group-outputs`:", | |
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192 | "", | |
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193 | "The choices are:", | |
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194 | "", | |
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195 | "* `engine` - all of an engine's output is collected together", | |
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196 | "* `type` - where stdout of each engine is grouped, etc. (the default)", | |
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197 | "* `order` - same as `type`, but individual displaypub outputs are interleaved.", | |
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198 | " That is, it will output the first plot from each engine, then the second from each,", | |
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199 | " etc." | |
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200 | ] | |
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201 | }, | |
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202 | { | |
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203 | "cell_type": "code", | |
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204 | "collapsed": false, | |
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205 | "input": [ | |
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206 | "%%px --group-outputs=engine", | |
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207 | "x = linspace(0,pi,1000)", | |
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208 | "for n in range(id,12, stride):", | |
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209 | " print n", | |
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210 | " plt.plot(x,sin(n*x))", | |
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211 | "plt.title(\"Plot %i\" % id)" | |
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212 | ], | |
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213 | "language": "python", | |
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214 | "outputs": [] | |
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215 | }, | |
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216 | { | |
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217 | "cell_type": "code", | |
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218 | "collapsed": true, | |
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219 | "input": [ | |
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220 | "" | |
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221 | ], | |
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222 | "language": "python", | |
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223 | "outputs": [] | |
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224 | } | |
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225 | ] | |
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226 | } | |
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227 | ] | |
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228 | } No newline at end of file |
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