1 | /*! |
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2 | * Ext JS Library 3.4.0 |
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3 | * Copyright(c) 2006-2011 Sencha Inc. |
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4 | * licensing@sencha.com |
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5 | * http://www.sencha.com/license |
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6 | */ |
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7 | /** |
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8 | * @class Ext.grid.PivotAxis |
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9 | * @extends Ext.Component |
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10 | * <p>PivotAxis is a class that supports a {@link Ext.grid.PivotGrid}. Each PivotGrid contains two PivotAxis instances - the left |
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11 | * axis and the top axis. Each PivotAxis defines an ordered set of dimensions, each of which should correspond to a field in a |
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12 | * Store's Record (see {@link Ext.grid.PivotGrid} documentation for further explanation).</p> |
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13 | * <p>Developers should have little interaction with the PivotAxis instances directly as most of their management is performed by |
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14 | * the PivotGrid. An exception is the dynamic reconfiguration of axes at run time - to achieve this we use PivotAxis's |
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15 | * {@link #setDimensions} function and refresh the grid:</p> |
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16 | <pre><code> |
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17 | var pivotGrid = new Ext.grid.PivotGrid({ |
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18 | //some PivotGrid config here |
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19 | }); |
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20 | |
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21 | //change the left axis dimensions |
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22 | pivotGrid.leftAxis.setDimensions([ |
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23 | { |
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24 | dataIndex: 'person', |
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25 | direction: 'DESC', |
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26 | width : 100 |
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27 | }, |
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28 | { |
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29 | dataIndex: 'product', |
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30 | direction: 'ASC', |
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31 | width : 80 |
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32 | } |
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33 | ]); |
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34 | |
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35 | pivotGrid.view.refresh(true); |
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36 | </code></pre> |
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37 | * This clears the previous dimensions on the axis and redraws the grid with the new dimensions. |
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38 | */ |
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39 | Ext.grid.PivotAxis = Ext.extend(Ext.Component, { |
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40 | /** |
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41 | * @cfg {String} orientation One of 'vertical' or 'horizontal'. Defaults to horizontal |
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42 | */ |
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43 | orientation: 'horizontal', |
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44 | |
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45 | /** |
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46 | * @cfg {Number} defaultHeaderWidth The width to render each row header that does not have a width specified via |
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47 | {@link #getRowGroupHeaders}. Defaults to 80. |
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48 | */ |
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49 | defaultHeaderWidth: 80, |
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50 | |
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51 | /** |
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52 | * @private |
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53 | * @cfg {Number} paddingWidth The amount of padding used by each cell. |
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54 | * TODO: From 4.x onwards this can be removed as it won't be needed. For now it is used to account for the differences between |
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55 | * the content box and border box measurement models |
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56 | */ |
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57 | paddingWidth: 7, |
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58 | |
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59 | /** |
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60 | * Updates the dimensions used by this axis |
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61 | * @param {Array} dimensions The new dimensions |
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62 | */ |
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63 | setDimensions: function(dimensions) { |
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64 | this.dimensions = dimensions; |
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65 | }, |
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66 | |
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67 | /** |
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68 | * @private |
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69 | * Builds the html table that contains the dimensions for this axis. This branches internally between vertical |
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70 | * and horizontal orientations because the table structure is slightly different in each case |
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71 | */ |
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72 | onRender: function(ct, position) { |
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73 | var rows = this.orientation == 'horizontal' |
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74 | ? this.renderHorizontalRows() |
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75 | : this.renderVerticalRows(); |
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76 | |
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77 | this.el = Ext.DomHelper.overwrite(ct.dom, {tag: 'table', cn: rows}, true); |
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78 | }, |
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79 | |
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80 | /** |
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81 | * @private |
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82 | * Specialised renderer for horizontal oriented axes |
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83 | * @return {Object} The HTML Domspec for a horizontal oriented axis |
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84 | */ |
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85 | renderHorizontalRows: function() { |
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86 | var headers = this.buildHeaders(), |
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87 | rowCount = headers.length, |
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88 | rows = [], |
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89 | cells, cols, colCount, i, j; |
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90 | |
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91 | for (i = 0; i < rowCount; i++) { |
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92 | cells = []; |
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93 | cols = headers[i].items; |
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94 | colCount = cols.length; |
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95 | |
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96 | for (j = 0; j < colCount; j++) { |
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97 | cells.push({ |
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98 | tag: 'td', |
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99 | html: cols[j].header, |
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100 | colspan: cols[j].span |
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101 | }); |
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102 | } |
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103 | |
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104 | rows[i] = { |
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105 | tag: 'tr', |
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106 | cn: cells |
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107 | }; |
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108 | } |
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109 | |
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110 | return rows; |
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111 | }, |
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112 | |
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113 | /** |
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114 | * @private |
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115 | * Specialised renderer for vertical oriented axes |
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116 | * @return {Object} The HTML Domspec for a vertical oriented axis |
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117 | */ |
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118 | renderVerticalRows: function() { |
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119 | var headers = this.buildHeaders(), |
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120 | colCount = headers.length, |
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121 | rowCells = [], |
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122 | rows = [], |
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123 | rowCount, col, row, colWidth, i, j; |
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124 | |
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125 | for (i = 0; i < colCount; i++) { |
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126 | col = headers[i]; |
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127 | colWidth = col.width || 80; |
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128 | rowCount = col.items.length; |
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129 | |
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130 | for (j = 0; j < rowCount; j++) { |
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131 | row = col.items[j]; |
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132 | |
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133 | rowCells[row.start] = rowCells[row.start] || []; |
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134 | rowCells[row.start].push({ |
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135 | tag : 'td', |
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136 | html : row.header, |
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137 | rowspan: row.span, |
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138 | width : Ext.isBorderBox ? colWidth : colWidth - this.paddingWidth |
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139 | }); |
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140 | } |
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141 | } |
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142 | |
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143 | rowCount = rowCells.length; |
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144 | for (i = 0; i < rowCount; i++) { |
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145 | rows[i] = { |
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146 | tag: 'tr', |
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147 | cn : rowCells[i] |
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148 | }; |
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149 | } |
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150 | |
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151 | return rows; |
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152 | }, |
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153 | |
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154 | /** |
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155 | * @private |
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156 | * Returns the set of all unique tuples based on the bound store and dimension definitions. |
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157 | * Internally we construct a new, temporary store to make use of the multi-sort capabilities of Store. In |
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158 | * 4.x this functionality should have been moved to MixedCollection so this step should not be needed. |
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159 | * @return {Array} All unique tuples |
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160 | */ |
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161 | getTuples: function() { |
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162 | var newStore = new Ext.data.Store({}); |
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163 | |
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164 | newStore.data = this.store.data.clone(); |
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165 | newStore.fields = this.store.fields; |
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166 | |
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167 | var sorters = [], |
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168 | dimensions = this.dimensions, |
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169 | length = dimensions.length, |
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170 | i; |
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171 | |
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172 | for (i = 0; i < length; i++) { |
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173 | sorters.push({ |
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174 | field : dimensions[i].dataIndex, |
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175 | direction: dimensions[i].direction || 'ASC' |
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176 | }); |
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177 | } |
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178 | |
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179 | newStore.sort(sorters); |
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180 | |
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181 | var records = newStore.data.items, |
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182 | hashes = [], |
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183 | tuples = [], |
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184 | recData, hash, info, data, key; |
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185 | |
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186 | length = records.length; |
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187 | |
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188 | for (i = 0; i < length; i++) { |
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189 | info = this.getRecordInfo(records[i]); |
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190 | data = info.data; |
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191 | hash = ""; |
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192 | |
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193 | for (key in data) { |
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194 | hash += data[key] + '---'; |
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195 | } |
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196 | |
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197 | if (hashes.indexOf(hash) == -1) { |
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198 | hashes.push(hash); |
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199 | tuples.push(info); |
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200 | } |
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201 | } |
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202 | |
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203 | newStore.destroy(); |
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204 | |
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205 | return tuples; |
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206 | }, |
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207 | |
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208 | /** |
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209 | * @private |
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210 | */ |
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211 | getRecordInfo: function(record) { |
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212 | var dimensions = this.dimensions, |
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213 | length = dimensions.length, |
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214 | data = {}, |
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215 | dimension, dataIndex, i; |
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216 | |
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217 | //get an object containing just the data we are interested in based on the configured dimensions |
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218 | for (i = 0; i < length; i++) { |
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219 | dimension = dimensions[i]; |
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220 | dataIndex = dimension.dataIndex; |
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221 | |
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222 | data[dataIndex] = record.get(dataIndex); |
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223 | } |
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224 | |
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225 | //creates a specialised matcher function for a given tuple. The returned function will return |
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226 | //true if the record passed to it matches the dataIndex values of each dimension in this axis |
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227 | var createMatcherFunction = function(data) { |
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228 | return function(record) { |
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229 | for (var dataIndex in data) { |
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230 | if (record.get(dataIndex) != data[dataIndex]) { |
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231 | return false; |
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232 | } |
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233 | } |
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234 | |
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235 | return true; |
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236 | }; |
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237 | }; |
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238 | |
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239 | return { |
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240 | data: data, |
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241 | matcher: createMatcherFunction(data) |
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242 | }; |
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243 | }, |
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244 | |
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245 | /** |
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246 | * @private |
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247 | * Uses the calculated set of tuples to build an array of headers that can be rendered into a table using rowspan or |
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248 | * colspan. Basically this takes the set of tuples and spans any cells that run into one another, so if we had dimensions |
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249 | * of Person and Product and several tuples containing different Products for the same Person, those Products would be |
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250 | * spanned. |
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251 | * @return {Array} The headers |
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252 | */ |
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253 | buildHeaders: function() { |
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254 | var tuples = this.getTuples(), |
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255 | rowCount = tuples.length, |
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256 | dimensions = this.dimensions, |
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257 | dimension, |
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258 | colCount = dimensions.length, |
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259 | headers = [], |
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260 | tuple, rows, currentHeader, previousHeader, span, start, isLast, changed, i, j; |
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261 | |
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262 | for (i = 0; i < colCount; i++) { |
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263 | dimension = dimensions[i]; |
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264 | rows = []; |
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265 | span = 0; |
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266 | start = 0; |
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267 | |
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268 | for (j = 0; j < rowCount; j++) { |
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269 | tuple = tuples[j]; |
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270 | isLast = j == (rowCount - 1); |
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271 | currentHeader = tuple.data[dimension.dataIndex]; |
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272 | |
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273 | /* |
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274 | * 'changed' indicates that we need to create a new cell. This should be true whenever the cell |
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275 | * above (previousHeader) is different from this cell, or when the cell on the previous dimension |
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276 | * changed (e.g. if the current dimension is Product and the previous was Person, we need to start |
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277 | * a new cell if Product is the same but Person changed, so we check the previous dimension and tuple) |
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278 | */ |
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279 | changed = previousHeader != undefined && previousHeader != currentHeader; |
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280 | if (i > 0 && j > 0) { |
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281 | changed = changed || tuple.data[dimensions[i-1].dataIndex] != tuples[j-1].data[dimensions[i-1].dataIndex]; |
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282 | } |
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283 | |
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284 | if (changed) { |
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285 | rows.push({ |
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286 | header: previousHeader, |
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287 | span : span, |
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288 | start : start |
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289 | }); |
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290 | |
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291 | start += span; |
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292 | span = 0; |
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293 | } |
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294 | |
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295 | if (isLast) { |
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296 | rows.push({ |
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297 | header: currentHeader, |
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298 | span : span + 1, |
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299 | start : start |
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300 | }); |
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301 | |
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302 | start += span; |
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303 | span = 0; |
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304 | } |
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305 | |
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306 | previousHeader = currentHeader; |
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307 | span++; |
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308 | } |
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309 | |
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310 | headers.push({ |
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311 | items: rows, |
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312 | width: dimension.width || this.defaultHeaderWidth |
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313 | }); |
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314 | |
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315 | previousHeader = undefined; |
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316 | } |
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317 | |
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318 | return headers; |
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319 | } |
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320 | }); |
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