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1 | 1 | { |
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2 | 2 | "metadata": { |
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3 | 3 | "name": "Animations_and_Progress" |
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4 | 4 | }, |
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5 | 5 | "nbformat": 3, |
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6 | 6 | "nbformat_minor": 0, |
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7 | 7 | "worksheets": [ |
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8 | 8 | { |
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9 | 9 | "cells": [ |
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10 | 10 | { |
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11 | 11 | "cell_type": "heading", |
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12 | 12 | "level": 1, |
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13 | 13 | "metadata": {}, |
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14 | 14 | "source": [ |
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15 | 15 | "Simple animations, progress bars, and clearing output" |
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16 | 16 | ] |
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17 | 17 | }, |
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18 | 18 | { |
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19 | 19 | "cell_type": "markdown", |
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20 | 20 | "metadata": {}, |
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21 | 21 | "source": [ |
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22 | 22 | "Sometimes you want to print progress in-place, but don't want\n", |
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23 | 23 | "to keep growing the output area. In terminals, there is the carriage-return\n", |
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24 | 24 | "(`'\\r'`) for overwriting a single line, but the notebook frontend does not support this\n", |
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25 | 25 | "behavior (yet).\n", |
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26 | 26 | "\n", |
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27 | 27 | "What the notebook *does* support is explicit `clear_output`, and you can use this to replace previous\n", |
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28 | 28 | "output (specifying stdout/stderr or the special IPython display outputs)." |
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29 | 29 | ] |
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30 | 30 | }, |
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31 | 31 | { |
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32 | 32 | "cell_type": "markdown", |
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33 | 33 | "metadata": {}, |
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34 | 34 | "source": [ |
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35 | 35 | "A simple example printing our progress iterating through a list:" |
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36 | 36 | ] |
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37 | 37 | }, |
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38 | 38 | { |
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39 | 39 | "cell_type": "code", |
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40 | 40 | "collapsed": true, |
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41 | 41 | "input": [ |
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42 | 42 | "import sys\n", |
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43 | 43 | "import time" |
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44 | 44 | ], |
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45 | 45 | "language": "python", |
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46 | 46 | "metadata": {}, |
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47 | 47 | "outputs": [] |
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48 | 48 | }, |
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49 | 49 | { |
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50 | 50 | "cell_type": "code", |
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51 | 51 | "collapsed": false, |
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52 | 52 | "input": [ |
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53 | 53 | "from IPython.display import clear_output\n", |
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54 | 54 | "for i in range(10):\n", |
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55 | 55 | " time.sleep(0.25)\n", |
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56 | 56 | " clear_output()\n", |
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57 | 57 | " print i\n", |
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58 | 58 | " sys.stdout.flush()" |
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59 | 59 | ], |
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60 | 60 | "language": "python", |
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61 | 61 | "metadata": {}, |
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62 | 62 | "outputs": [] |
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63 | 63 | }, |
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64 | 64 | { |
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65 | 65 | "cell_type": "markdown", |
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66 | 66 | "metadata": {}, |
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67 | 67 | "source": [ |
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68 | 68 | "The AsyncResult object has a special `wait_interactive()` method, which prints its progress interactively,\n", |
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69 | 69 | "so you can watch as your parallel computation completes.\n", |
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70 | 70 | "\n", |
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71 | 71 | "**This example assumes you have an IPython cluster running, which you can start from the [cluster panel](/#tab2)**" |
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72 | 72 | ] |
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73 | 73 | }, |
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74 | 74 | { |
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75 | 75 | "cell_type": "code", |
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76 | 76 | "collapsed": false, |
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77 | 77 | "input": [ |
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78 | 78 | "from IPython import parallel\n", |
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79 | 79 | "rc = parallel.Client()\n", |
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80 | 80 | "view = rc.load_balanced_view()\n", |
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81 | 81 | "\n", |
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82 | 82 | "amr = view.map_async(time.sleep, [0.5]*100)\n", |
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83 | 83 | "\n", |
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84 | 84 | "amr.wait_interactive()" |
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85 | 85 | ], |
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86 | 86 | "language": "python", |
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87 | 87 | "metadata": {}, |
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88 | 88 | "outputs": [] |
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89 | 89 | }, |
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90 | 90 | { |
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91 | 91 | "cell_type": "markdown", |
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92 | 92 | "metadata": {}, |
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93 | 93 | "source": [ |
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94 | 94 | "You can also use `clear_output()` to clear figures and plots.\n", |
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95 | 95 | "\n", |
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96 | 96 | "This time, we need to make sure we are using inline pylab (**requires matplotlib**)" |
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97 | 97 | ] |
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98 | 98 | }, |
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99 | 99 | { |
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100 | 100 | "cell_type": "code", |
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101 | 101 | "collapsed": false, |
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102 | 102 | "input": [ |
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103 | 103 | "%pylab inline" |
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104 | 104 | ], |
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105 | 105 | "language": "python", |
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106 | 106 | "metadata": {}, |
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107 | 107 | "outputs": [] |
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108 | 108 | }, |
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109 | 109 | { |
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110 | 110 | "cell_type": "code", |
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111 | 111 | "collapsed": false, |
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112 | 112 | "input": [ |
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113 | 113 | "from scipy.special import jn\n", |
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114 | 114 | "x = np.linspace(0,5)\n", |
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115 | 115 | "f, ax = plt.subplots()\n", |
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116 | 116 | "ax.set_title(\"Bessel functions\")\n", |
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117 | 117 | "\n", |
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118 | 118 | "for n in range(1,10):\n", |
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119 | 119 | " time.sleep(1)\n", |
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120 | 120 | " ax.plot(x, jn(x,n))\n", |
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121 | 121 | " clear_output()\n", |
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122 | 122 | " display(f)\n", |
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123 | 123 | "\n", |
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124 | 124 | "# close the figure at the end, so we don't get a duplicate\n", |
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125 | 125 | "# of the last plot\n", |
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126 | 126 | "plt.close()" |
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127 | 127 | ], |
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128 | 128 | "language": "python", |
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129 | 129 | "metadata": {}, |
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130 | 130 | "outputs": [] |
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131 | 131 | }, |
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132 | 132 | { |
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133 | 133 | "cell_type": "heading", |
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134 | 134 | "level": 2, |
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135 | 135 | "metadata": {}, |
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136 | 136 | "source": [ |
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137 | 137 | "A Javascript Progress Bar" |
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138 | 138 | ] |
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139 | 139 | }, |
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140 | 140 | { |
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141 | 141 | "cell_type": "markdown", |
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142 | 142 | "metadata": {}, |
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143 | 143 | "source": [ |
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144 | 144 | "`clear_output()` is still something of a hack, and if you want to do a progress bar in the notebook\n", |
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145 | 145 | "it is better to just use Javascript/HTML if you can.\n", |
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146 | 146 | "\n", |
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147 | 147 | "Here is a simple progress bar using HTML/Javascript:" |
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148 | 148 | ] |
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149 | 149 | }, |
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150 | 150 | { |
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151 | 151 | "cell_type": "code", |
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152 | 152 | "collapsed": false, |
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153 | 153 | "input": [ |
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154 | 154 | "import uuid\n", |
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155 | 155 | "from IPython.display import HTML, Javascript, display\n", |
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156 | 156 | "\n", |
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157 | 157 | "divid = str(uuid.uuid4())\n", |
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158 | 158 | "\n", |
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159 | 159 | "pb = HTML(\n", |
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160 | 160 | "\"\"\"\n", |
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161 | 161 | "<div style=\"border: 1px solid black; width:500px\">\n", |
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162 | 162 | " <div id=\"%s\" style=\"background-color:blue; width:0%%\"> </div>\n", |
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163 | 163 | "</div> \n", |
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164 | 164 | "\"\"\" % divid)\n", |
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165 | 165 | "display(pb)\n", |
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166 | 166 | "for i in range(1,101):\n", |
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167 | 167 | " time.sleep(0.1)\n", |
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168 | 168 | " \n", |
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169 | 169 | " display(Javascript(\"$('div#%s').width('%i%%')\" % (divid, i)))" |
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170 | 170 | ], |
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171 | 171 | "language": "python", |
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172 | 172 | "metadata": {}, |
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173 | 173 | "outputs": [] |
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174 | 174 | }, |
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175 | 175 | { |
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176 | 176 | "cell_type": "markdown", |
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177 | 177 | "metadata": {}, |
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178 | 178 | "source": [ |
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179 | 179 | "The above simply makes a div that is a box, and a blue div inside it with a unique ID \n", |
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180 | 180 | "(so that the javascript won't collide with other similar progress bars on the same page). \n", |
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181 | 181 | "\n", |
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182 | 182 | "Then, at every progress point, we run a simple jQuery call to resize the blue box to\n", |
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183 | 183 | "the appropriate fraction of the width of its containing box, and voil\u00e0 a nice\n", |
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184 | 184 | "HTML/Javascript progress bar!" |
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185 | 185 | ] |
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186 | 186 | }, |
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187 | 187 | { |
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188 | 188 | "cell_type": "heading", |
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189 | 189 | "level": 2, |
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190 | 190 | "metadata": {}, |
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191 | 191 | "source": [ |
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192 | 192 | "ProgressBar class" |
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193 | 193 | ] |
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194 | 194 | }, |
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195 | 195 | { |
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196 | 196 | "cell_type": "markdown", |
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197 | 197 | "metadata": {}, |
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198 | 198 | "source": [ |
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199 | 199 | "And finally, here is a progress bar *class* extracted from [PyMC](http://code.google.com/p/pymc/), which will work in regular Python as well as in the IPython Notebook" |
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200 | 200 | ] |
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201 | 201 | }, |
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202 | 202 | { |
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203 | 203 | "cell_type": "code", |
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204 | 204 | "collapsed": true, |
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205 | 205 | "input": [ |
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206 | 206 | "import sys, time\n", |
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207 | "try:\n", | |
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208 | " from IPython.display import clear_output\n", | |
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209 | " have_ipython = True\n", | |
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210 | "except ImportError:\n", | |
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211 | " have_ipython = False\n", | |
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212 | 207 | "\n", |
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213 | 208 | "class ProgressBar:\n", |
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214 | 209 | " def __init__(self, iterations):\n", |
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215 | 210 | " self.iterations = iterations\n", |
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216 | 211 | " self.prog_bar = '[]'\n", |
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217 | 212 | " self.fill_char = '*'\n", |
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218 |
" self.width = |
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213 | " self.width = 50\n", | |
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219 | 214 | " self.__update_amount(0)\n", |
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220 | " if have_ipython:\n", | |
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221 | " self.animate = self.animate_ipython\n", | |
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222 | " else:\n", | |
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223 | " self.animate = self.animate_noipython\n", | |
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224 | 215 | "\n", |
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225 |
" def animate |
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216 | " def animate(self, iter):\n", | |
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226 | 217 | " print '\\r', self,\n", |
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227 | 218 | " sys.stdout.flush()\n", |
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228 | 219 | " self.update_iteration(iter + 1)\n", |
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229 | 220 | "\n", |
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230 | 221 | " def update_iteration(self, elapsed_iter):\n", |
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231 | 222 | " self.__update_amount((elapsed_iter / float(self.iterations)) * 100.0)\n", |
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232 | 223 | " self.prog_bar += ' %d of %s complete' % (elapsed_iter, self.iterations)\n", |
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233 | 224 | "\n", |
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234 | 225 | " def __update_amount(self, new_amount):\n", |
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235 | 226 | " percent_done = int(round((new_amount / 100.0) * 100.0))\n", |
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236 | 227 | " all_full = self.width - 2\n", |
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237 | 228 | " num_hashes = int(round((percent_done / 100.0) * all_full))\n", |
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238 | 229 | " self.prog_bar = '[' + self.fill_char * num_hashes + ' ' * (all_full - num_hashes) + ']'\n", |
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239 | 230 | " pct_place = (len(self.prog_bar) // 2) - len(str(percent_done))\n", |
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240 | 231 | " pct_string = '%d%%' % percent_done\n", |
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241 | 232 | " self.prog_bar = self.prog_bar[0:pct_place] + \\\n", |
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242 | 233 | " (pct_string + self.prog_bar[pct_place + len(pct_string):])\n", |
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243 | 234 | "\n", |
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244 | 235 | " def __str__(self):\n", |
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245 | 236 | " return str(self.prog_bar)" |
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246 | 237 | ], |
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247 | 238 | "language": "python", |
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248 | 239 | "metadata": {}, |
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249 | 240 | "outputs": [] |
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250 | 241 | }, |
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251 | 242 | { |
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252 | 243 | "cell_type": "code", |
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253 | 244 | "collapsed": false, |
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254 | 245 | "input": [ |
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255 | 246 | "p = ProgressBar(1000)\n", |
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256 | 247 | "for i in range(1001):\n", |
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248 | " time.sleep(0.002)\n", | |
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257 | 249 | " p.animate(i)" |
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258 | 250 | ], |
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259 | 251 | "language": "python", |
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260 | 252 | "metadata": {}, |
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261 | 253 | "outputs": [] |
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262 | }, | |
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263 | { | |
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264 | "cell_type": "code", | |
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265 | "collapsed": false, | |
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266 | "input": [], | |
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267 | "language": "python", | |
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268 | "metadata": {}, | |
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269 | "outputs": [] | |
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270 | 254 | } |
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271 | 255 | ], |
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272 | 256 | "metadata": {} |
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273 | 257 | } |
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274 | 258 | ] |
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275 | 259 | } No newline at end of file |
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