1 | function NeuronDrawer(contextName, width, height) { |
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2 | this._canvasWidth = width; |
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3 | this._canvasHeight = height; |
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4 | this._containerContextName = contextName; |
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5 | this._unknown_symbol=[1,4, 25,25, 75,25, 75,75, 25,75, 25,25]; |
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6 | this._neuron_symbol=[1,4, 75,50, 25,0, 25,99, 75,50, 100,50]; |
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7 | this._inputonly_symbol=[1,5, 25,40, 35,40, 45,50, 35,60, 25,60, 25,40]; |
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8 | this._outputonly_symbol=[1,7, 75,50, 75,60, 55,60, 65,50, 55,40, 75,40, 75,50, 100,50]; |
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9 | this._neurons = undefined; |
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10 | this._SCALE = 150; |
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11 | this._scale = 1; |
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12 | this._min_scale = 0.1; |
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13 | //Kinetic.js |
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14 | this._stage = undefined; |
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15 | this._layer = undefined; |
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16 | } |
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17 | |
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18 | NeuronDrawer.prototype.initializeNewCanvas = function () { |
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19 | |
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20 | this._stage = new Kinetic.Stage({ |
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21 | container: this._containerContextName, |
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22 | width: this._canvasWidth, |
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23 | height: this._canvasHeight, |
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24 | draggable: true |
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25 | }); |
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26 | |
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27 | this._layer = new Kinetic.Layer(); |
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28 | |
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29 | this._addZoom(); |
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30 | } |
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31 | |
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32 | NeuronDrawer.prototype._addZoom = function(){ |
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33 | var self = this; |
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34 | |
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35 | var isFirefox = (/Firefox/i.test(navigator.userAgent)) ? true : false; |
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36 | |
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37 | var mousewheelevt= isFirefox ? "DOMMouseScroll" : "mousewheel" //FF doesn't recognize mousewheel as of FF3.x |
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38 | |
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39 | document.getElementById(this._containerContextName).addEventListener(mousewheelevt,function(e){ |
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40 | e.preventDefault(); |
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41 | |
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42 | var zoomAmount = 0; |
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43 | if(!isFirefox) |
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44 | zoomAmount = e.wheelDelta * 0.001; |
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45 | else |
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46 | zoomAmount = e.detail * -0.12; |
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47 | |
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48 | var newScale = self._stage.scale(); |
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49 | newScale.x += zoomAmount; |
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50 | newScale.y += zoomAmount; |
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51 | |
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52 | self._stage.scale(newScale) |
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53 | self._stage.draw(); |
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54 | }); |
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55 | } |
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56 | |
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57 | NeuronDrawer.prototype.drawNeuralNetwork = function (neurons, connections, layouts, classes) { |
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58 | |
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59 | this._neurons = []; |
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60 | var offsetFactor = 0; |
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61 | |
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62 | for (var i = 0; i < layouts.length; i++) { |
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63 | var scheme = undefined; |
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64 | scheme = this._chooseSchema(i,neurons, connections, classes); |
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65 | |
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66 | var neuronData = this._getSize(scheme); |
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67 | neuronData.scheme = scheme; |
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68 | neuronData.x += layouts[i].x * this._SCALE; |
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69 | neuronData.y += -layouts[i].y * this._SCALE; |
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70 | |
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71 | this._neurons.push(neuronData); |
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72 | this.drawNeuron(layouts[i].x * this._SCALE, -layouts[i].y * this._SCALE, scheme); |
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73 | |
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74 | offsetFactor = Math.min(offsetFactor, layouts[i].x); |
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75 | } |
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76 | |
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77 | this._layer.offsetX(offsetFactor * this._SCALE); |
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78 | |
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79 | for (var i = 0; i < connections.length; i++) |
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80 | this.drawConnection(i, neurons, connections, einfos); |
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81 | } |
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82 | |
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83 | NeuronDrawer.prototype.drawNeuron = function (x, y, scheme) { |
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84 | var points = []; |
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85 | |
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86 | var position = 0; |
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87 | var noOfBlocks = scheme[position++];//number of "blocks" to draw |
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88 | var noOfLines = 0;//number of line to draw |
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89 | for (var i = 0; i < noOfBlocks; i++) { |
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90 | noOfLines = scheme[position++]; |
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91 | |
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92 | for (var j = 0; j < noOfLines; j++) { |
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93 | points.push(scheme[position++]+x); |
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94 | points.push(scheme[position++]+y); |
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95 | } |
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96 | |
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97 | points.push(scheme[position++]+x); |
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98 | points.push(scheme[position++]+y); |
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99 | |
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100 | var symbol = new Kinetic.Line({ |
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101 | points: points, |
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102 | stroke: 'black', |
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103 | strokeWidth: 1 |
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104 | }); |
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105 | |
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106 | symbol.move({x:0, y: 0}); |
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107 | var self = this; |
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108 | symbol.on('mousemove', function(){ |
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109 | var mousePos = self._stage.getPointerPosition(); |
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110 | var x = mousePos.x; |
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111 | var y = mousePos.y; |
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112 | console.log(x,y); |
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113 | }); |
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114 | |
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115 | this._layer.add(symbol); |
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116 | points = []; |
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117 | } |
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118 | } |
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119 | |
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120 | NeuronDrawer.prototype._getConnection = function(connections, id, number){ |
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121 | |
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122 | var counter = 0; |
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123 | for(var i = 0; i < connections.length; i++) |
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124 | { |
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125 | if(connections[i].getDestination() == id) |
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126 | { |
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127 | if(counter == number) |
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128 | return connections[i].getSource(); |
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129 | else |
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130 | counter++; |
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131 | } |
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132 | } |
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133 | } |
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134 | |
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135 | NeuronDrawer.prototype.drawConnection = function (id, neurons, connections, einfos) { |
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136 | |
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137 | var n2; |
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138 | neuroId = connections[id].getDestination(); |
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139 | //this is hack trick to change order of inputs |
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140 | var maxVal = this._inputY(this._getNumberOfInputs(neuroId,connections), connections, neuroId); |
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141 | |
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142 | for(var input = 0; input < this._getNumberOfInputs(neuroId,connections); input++) |
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143 | { |
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144 | n2 = this._neurons[this._getConnection(connections, neuroId, input)]; |
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145 | var points = []; |
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146 | |
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147 | var yw = this._inputY(input, connections, neuroId); |
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148 | var xw = (maxVal-yw) / 4; |
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149 | |
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150 | yw += this._neurons[neuroId].y;//add position of object to y |
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151 | |
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152 | points.push(this._neurons[neuroId].x);//x |
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153 | points.push(yw);//y |
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154 | |
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155 | points.push(this._neurons[neuroId].x - xw);//x |
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156 | points.push(yw);//y |
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157 | |
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158 | points.push(n2.x+n2.sizeX); |
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159 | points.push(n2.y + n2.sizeY/2); |
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160 | |
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161 | /*if(diagram?) |
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162 | { |
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163 | //straight forward |
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164 | } |
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165 | else |
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166 | { |
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167 | //U-shape |
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168 | }*/ |
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169 | |
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170 | var line = new Kinetic.Line({ |
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171 | points: points, |
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172 | stroke: 'black', |
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173 | strokeWidth: 1 |
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174 | }); |
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175 | this._layer.add(line); |
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176 | } |
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177 | |
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178 | } |
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179 | |
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180 | NeuronDrawer.prototype._inputY = function(number, connections, id){ |
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181 | return ((1 + number)* this._neurons[id].sizeY) / ((this._getNumberOfInputs(id, connections)) + 1); |
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182 | } |
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183 | |
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184 | NeuronDrawer.prototype.finalize = function() |
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185 | { |
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186 | this._stage.add(this._layer); |
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187 | } |
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188 | |
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189 | NeuronDrawer.prototype._getNumberOfInputs = function(number, connections){ |
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190 | |
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191 | var counter = 0; |
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192 | |
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193 | for(var i = 0; i < connections.length; i++){ |
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194 | if(connections[i].getDestination() == number) |
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195 | counter++; |
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196 | } |
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197 | |
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198 | return counter; |
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199 | } |
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200 | |
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201 | NeuronDrawer.prototype._getNumberOfOutputs = function(number, connections){ |
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202 | var counter = 0; |
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203 | |
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204 | for(var i = 0; i < connections.length; i++){ |
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205 | if(connections[i].getSource() == number) |
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206 | counter++; |
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207 | } |
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208 | |
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209 | return counter; |
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210 | } |
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211 | |
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212 | |
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213 | |
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214 | NeuronDrawer.prototype._chooseSchema = function(number, neurons, connections, classes) |
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215 | { |
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216 | var schema = this._unknown_symbol; |
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217 | var type = neurons[number].getSchemeID(); |
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218 | |
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219 | if(type != undefined) |
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220 | { |
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221 | if(classes[type].getScheme().length != 0) |
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222 | { |
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223 | if(this._getNumberOfInputs(number, connections) == 0) |
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224 | schema = this._outputonly_symbol; |
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225 | else if (this._getNumberOfOutputs(number, connections) == 0) |
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226 | schema = this._inputonly_symbol; |
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227 | else |
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228 | schema = this._neuron_symbol; |
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229 | } |
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230 | } |
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231 | |
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232 | return schema; |
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233 | } |
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234 | |
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235 | NeuronDrawer.prototype._getSize = function(scheme) |
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236 | { |
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237 | var neuron = {sizeX: 0, sizeY: 0, x: 0, y: 0}; |
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238 | |
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239 | |
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240 | var minX = Number.MAX_VALUE; |
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241 | var maxX = -1; |
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242 | |
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243 | var minY = Number.MAX_VALUE; |
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244 | var maxY = -1; |
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245 | |
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246 | var position = 0; |
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247 | var noOfBlocks = scheme[position++];//number of "blocks" to draw |
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248 | var noOfLines = 0;//number of line to draw |
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249 | |
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250 | for (var i = 0; i < noOfBlocks; i++) { |
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251 | noOfLines = scheme[position++]; |
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252 | |
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253 | for (var j = 0; j < noOfLines; j++) { |
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254 | |
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255 | |
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256 | if(scheme[position] > maxX) |
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257 | maxX = scheme[position]; |
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258 | if(scheme[position] < minX) |
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259 | minX = scheme[position]; |
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260 | position++; |
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261 | |
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262 | if(scheme[position] > maxY) |
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263 | maxX = scheme[position]; |
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264 | if(scheme[position] < minY) |
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265 | minY = scheme[position]; |
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266 | position++; |
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267 | |
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268 | |
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269 | if(scheme[position] > maxX) |
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270 | maxX = scheme[position]; |
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271 | if(scheme[position] < minX) |
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272 | minX = scheme[position]; |
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273 | position++; |
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274 | |
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275 | if(scheme[position] > maxY) |
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276 | maxY = scheme[position]; |
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277 | if(scheme[position] < minY) |
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278 | minY = scheme[position]; |
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279 | position++; |
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280 | |
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281 | position = position - 2; |
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282 | } |
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283 | position = position + 2;//move to value which define number of lines to draw |
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284 | neuron.sizeX = maxX - minX; |
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285 | neuron.sizeY = maxY - minY; |
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286 | neuron.x = minX; |
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287 | neuron.y = minY; |
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288 | } |
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289 | return neuron; |
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290 | } |
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