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   1  <?php
   2  /**
   3   * PHPExcel
   4   *
   5   * Copyright (c) 2006 - 2014 PHPExcel
   6   *
   7   * This library is free software; you can redistribute it and/or
   8   * modify it under the terms of the GNU Lesser General Public
   9   * License as published by the Free Software Foundation; either
  10   * version 2.1 of the License, or (at your option) any later version.
  11   *
  12   * This library is distributed in the hope that it will be useful,
  13   * but WITHOUT ANY WARRANTY; without even the implied warranty of
  14   * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
  15   * Lesser General Public License for more details.
  16   *
  17   * You should have received a copy of the GNU Lesser General Public
  18   * License along with this library; if not, write to the Free Software
  19   * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
  20   *
  21   * @category   PHPExcel
  22   * @package    PHPExcel_Shared_Trend
  23   * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
  24   * @license    http://www.gnu.org/licenses/old-licenses/lgpl-2.1.txt    LGPL
  25   * @version    ##VERSION##, ##DATE##
  26   */
  27  
  28  
  29  /**
  30   * PHPExcel_Best_Fit
  31   *
  32   * @category   PHPExcel
  33   * @package    PHPExcel_Shared_Trend
  34   * @copyright  Copyright (c) 2006 - 2014 PHPExcel (http://www.codeplex.com/PHPExcel)
  35   */
  36  class PHPExcel_Best_Fit
  37  {
  38      /**
  39       * Indicator flag for a calculation error
  40       *
  41       * @var    boolean
  42       **/
  43      protected $_error                = False;
  44  
  45      /**
  46       * Algorithm type to use for best-fit
  47       *
  48       * @var    string
  49       **/
  50      protected $_bestFitType            = 'undetermined';
  51  
  52      /**
  53       * Number of entries in the sets of x- and y-value arrays
  54       *
  55       * @var    int
  56       **/
  57      protected $_valueCount            = 0;
  58  
  59      /**
  60       * X-value dataseries of values
  61       *
  62       * @var    float[]
  63       **/
  64      protected $_xValues                = array();
  65  
  66      /**
  67       * Y-value dataseries of values
  68       *
  69       * @var    float[]
  70       **/
  71      protected $_yValues                = array();
  72  
  73      /**
  74       * Flag indicating whether values should be adjusted to Y=0
  75       *
  76       * @var    boolean
  77       **/
  78      protected $_adjustToZero        = False;
  79  
  80      /**
  81       * Y-value series of best-fit values
  82       *
  83       * @var    float[]
  84       **/
  85      protected $_yBestFitValues        = array();
  86  
  87      protected $_goodnessOfFit         = 1;
  88  
  89      protected $_stdevOfResiduals    = 0;
  90  
  91      protected $_covariance            = 0;
  92  
  93      protected $_correlation            = 0;
  94  
  95      protected $_SSRegression        = 0;
  96  
  97      protected $_SSResiduals            = 0;
  98  
  99      protected $_DFResiduals            = 0;
 100  
 101      protected $_F                    = 0;
 102  
 103      protected $_slope                = 0;
 104  
 105      protected $_slopeSE                = 0;
 106  
 107      protected $_intersect            = 0;
 108  
 109      protected $_intersectSE            = 0;
 110  
 111      protected $_Xoffset                = 0;
 112  
 113      protected $_Yoffset                = 0;
 114  
 115  
 116  	public function getError() {
 117          return $this->_error;
 118      }    //    function getBestFitType()
 119  
 120  
 121  	public function getBestFitType() {
 122          return $this->_bestFitType;
 123      }    //    function getBestFitType()
 124  
 125  
 126      /**
 127       * Return the Y-Value for a specified value of X
 128       *
 129       * @param     float        $xValue            X-Value
 130       * @return     float                        Y-Value
 131       */
 132  	public function getValueOfYForX($xValue) {
 133          return False;
 134      }    //    function getValueOfYForX()
 135  
 136  
 137      /**
 138       * Return the X-Value for a specified value of Y
 139       *
 140       * @param     float        $yValue            Y-Value
 141       * @return     float                        X-Value
 142       */
 143  	public function getValueOfXForY($yValue) {
 144          return False;
 145      }    //    function getValueOfXForY()
 146  
 147  
 148      /**
 149       * Return the original set of X-Values
 150       *
 151       * @return     float[]                X-Values
 152       */
 153  	public function getXValues() {
 154          return $this->_xValues;
 155      }    //    function getValueOfXForY()
 156  
 157  
 158      /**
 159       * Return the Equation of the best-fit line
 160       *
 161       * @param     int        $dp        Number of places of decimal precision to display
 162       * @return     string
 163       */
 164  	public function getEquation($dp=0) {
 165          return False;
 166      }    //    function getEquation()
 167  
 168  
 169      /**
 170       * Return the Slope of the line
 171       *
 172       * @param     int        $dp        Number of places of decimal precision to display
 173       * @return     string
 174       */
 175  	public function getSlope($dp=0) {
 176          if ($dp != 0) {
 177              return round($this->_slope,$dp);
 178          }
 179          return $this->_slope;
 180      }    //    function getSlope()
 181  
 182  
 183      /**
 184       * Return the standard error of the Slope
 185       *
 186       * @param     int        $dp        Number of places of decimal precision to display
 187       * @return     string
 188       */
 189  	public function getSlopeSE($dp=0) {
 190          if ($dp != 0) {
 191              return round($this->_slopeSE,$dp);
 192          }
 193          return $this->_slopeSE;
 194      }    //    function getSlopeSE()
 195  
 196  
 197      /**
 198       * Return the Value of X where it intersects Y = 0
 199       *
 200       * @param     int        $dp        Number of places of decimal precision to display
 201       * @return     string
 202       */
 203  	public function getIntersect($dp=0) {
 204          if ($dp != 0) {
 205              return round($this->_intersect,$dp);
 206          }
 207          return $this->_intersect;
 208      }    //    function getIntersect()
 209  
 210  
 211      /**
 212       * Return the standard error of the Intersect
 213       *
 214       * @param     int        $dp        Number of places of decimal precision to display
 215       * @return     string
 216       */
 217  	public function getIntersectSE($dp=0) {
 218          if ($dp != 0) {
 219              return round($this->_intersectSE,$dp);
 220          }
 221          return $this->_intersectSE;
 222      }    //    function getIntersectSE()
 223  
 224  
 225      /**
 226       * Return the goodness of fit for this regression
 227       *
 228       * @param     int        $dp        Number of places of decimal precision to return
 229       * @return     float
 230       */
 231  	public function getGoodnessOfFit($dp=0) {
 232          if ($dp != 0) {
 233              return round($this->_goodnessOfFit,$dp);
 234          }
 235          return $this->_goodnessOfFit;
 236      }    //    function getGoodnessOfFit()
 237  
 238  
 239  	public function getGoodnessOfFitPercent($dp=0) {
 240          if ($dp != 0) {
 241              return round($this->_goodnessOfFit * 100,$dp);
 242          }
 243          return $this->_goodnessOfFit * 100;
 244      }    //    function getGoodnessOfFitPercent()
 245  
 246  
 247      /**
 248       * Return the standard deviation of the residuals for this regression
 249       *
 250       * @param     int        $dp        Number of places of decimal precision to return
 251       * @return     float
 252       */
 253  	public function getStdevOfResiduals($dp=0) {
 254          if ($dp != 0) {
 255              return round($this->_stdevOfResiduals,$dp);
 256          }
 257          return $this->_stdevOfResiduals;
 258      }    //    function getStdevOfResiduals()
 259  
 260  
 261  	public function getSSRegression($dp=0) {
 262          if ($dp != 0) {
 263              return round($this->_SSRegression,$dp);
 264          }
 265          return $this->_SSRegression;
 266      }    //    function getSSRegression()
 267  
 268  
 269  	public function getSSResiduals($dp=0) {
 270          if ($dp != 0) {
 271              return round($this->_SSResiduals,$dp);
 272          }
 273          return $this->_SSResiduals;
 274      }    //    function getSSResiduals()
 275  
 276  
 277  	public function getDFResiduals($dp=0) {
 278          if ($dp != 0) {
 279              return round($this->_DFResiduals,$dp);
 280          }
 281          return $this->_DFResiduals;
 282      }    //    function getDFResiduals()
 283  
 284  
 285  	public function getF($dp=0) {
 286          if ($dp != 0) {
 287              return round($this->_F,$dp);
 288          }
 289          return $this->_F;
 290      }    //    function getF()
 291  
 292  
 293  	public function getCovariance($dp=0) {
 294          if ($dp != 0) {
 295              return round($this->_covariance,$dp);
 296          }
 297          return $this->_covariance;
 298      }    //    function getCovariance()
 299  
 300  
 301  	public function getCorrelation($dp=0) {
 302          if ($dp != 0) {
 303              return round($this->_correlation,$dp);
 304          }
 305          return $this->_correlation;
 306      }    //    function getCorrelation()
 307  
 308  
 309  	public function getYBestFitValues() {
 310          return $this->_yBestFitValues;
 311      }    //    function getYBestFitValues()
 312  
 313  
 314  	protected function _calculateGoodnessOfFit($sumX,$sumY,$sumX2,$sumY2,$sumXY,$meanX,$meanY, $const) {
 315          $SSres = $SScov = $SScor = $SStot = $SSsex = 0.0;
 316          foreach($this->_xValues as $xKey => $xValue) {
 317              $bestFitY = $this->_yBestFitValues[$xKey] = $this->getValueOfYForX($xValue);
 318  
 319              $SSres += ($this->_yValues[$xKey] - $bestFitY) * ($this->_yValues[$xKey] - $bestFitY);
 320              if ($const) {
 321                  $SStot += ($this->_yValues[$xKey] - $meanY) * ($this->_yValues[$xKey] - $meanY);
 322              } else {
 323                  $SStot += $this->_yValues[$xKey] * $this->_yValues[$xKey];
 324              }
 325              $SScov += ($this->_xValues[$xKey] - $meanX) * ($this->_yValues[$xKey] - $meanY);
 326              if ($const) {
 327                  $SSsex += ($this->_xValues[$xKey] - $meanX) * ($this->_xValues[$xKey] - $meanX);
 328              } else {
 329                  $SSsex += $this->_xValues[$xKey] * $this->_xValues[$xKey];
 330              }
 331          }
 332  
 333          $this->_SSResiduals = $SSres;
 334          $this->_DFResiduals = $this->_valueCount - 1 - $const;
 335  
 336          if ($this->_DFResiduals == 0.0) {
 337              $this->_stdevOfResiduals = 0.0;
 338          } else {
 339              $this->_stdevOfResiduals = sqrt($SSres / $this->_DFResiduals);
 340          }
 341          if (($SStot == 0.0) || ($SSres == $SStot)) {
 342              $this->_goodnessOfFit = 1;
 343          } else {
 344              $this->_goodnessOfFit = 1 - ($SSres / $SStot);
 345          }
 346  
 347          $this->_SSRegression = $this->_goodnessOfFit * $SStot;
 348          $this->_covariance = $SScov / $this->_valueCount;
 349          $this->_correlation = ($this->_valueCount * $sumXY - $sumX * $sumY) / sqrt(($this->_valueCount * $sumX2 - pow($sumX,2)) * ($this->_valueCount * $sumY2 - pow($sumY,2)));
 350          $this->_slopeSE = $this->_stdevOfResiduals / sqrt($SSsex);
 351          $this->_intersectSE = $this->_stdevOfResiduals * sqrt(1 / ($this->_valueCount - ($sumX * $sumX) / $sumX2));
 352          if ($this->_SSResiduals != 0.0) {
 353              if ($this->_DFResiduals == 0.0) {
 354                  $this->_F = 0.0;
 355              } else {
 356                  $this->_F = $this->_SSRegression / ($this->_SSResiduals / $this->_DFResiduals);
 357              }
 358          } else {
 359              if ($this->_DFResiduals == 0.0) {
 360                  $this->_F = 0.0;
 361              } else {
 362                  $this->_F = $this->_SSRegression / $this->_DFResiduals;
 363              }
 364          }
 365      }    //    function _calculateGoodnessOfFit()
 366  
 367  
 368  	protected function _leastSquareFit($yValues, $xValues, $const) {
 369          // calculate sums
 370          $x_sum = array_sum($xValues);
 371          $y_sum = array_sum($yValues);
 372          $meanX = $x_sum / $this->_valueCount;
 373          $meanY = $y_sum / $this->_valueCount;
 374          $mBase = $mDivisor = $xx_sum = $xy_sum = $yy_sum = 0.0;
 375          for($i = 0; $i < $this->_valueCount; ++$i) {
 376              $xy_sum += $xValues[$i] * $yValues[$i];
 377              $xx_sum += $xValues[$i] * $xValues[$i];
 378              $yy_sum += $yValues[$i] * $yValues[$i];
 379  
 380              if ($const) {
 381                  $mBase += ($xValues[$i] - $meanX) * ($yValues[$i] - $meanY);
 382                  $mDivisor += ($xValues[$i] - $meanX) * ($xValues[$i] - $meanX);
 383              } else {
 384                  $mBase += $xValues[$i] * $yValues[$i];
 385                  $mDivisor += $xValues[$i] * $xValues[$i];
 386              }
 387          }
 388  
 389          // calculate slope
 390  //        $this->_slope = (($this->_valueCount * $xy_sum) - ($x_sum * $y_sum)) / (($this->_valueCount * $xx_sum) - ($x_sum * $x_sum));
 391          $this->_slope = $mBase / $mDivisor;
 392  
 393          // calculate intersect
 394  //        $this->_intersect = ($y_sum - ($this->_slope * $x_sum)) / $this->_valueCount;
 395          if ($const) {
 396              $this->_intersect = $meanY - ($this->_slope * $meanX);
 397          } else {
 398              $this->_intersect = 0;
 399          }
 400  
 401          $this->_calculateGoodnessOfFit($x_sum,$y_sum,$xx_sum,$yy_sum,$xy_sum,$meanX,$meanY,$const);
 402      }    //    function _leastSquareFit()
 403  
 404  
 405      /**
 406       * Define the regression
 407       *
 408       * @param    float[]        $yValues    The set of Y-values for this regression
 409       * @param    float[]        $xValues    The set of X-values for this regression
 410       * @param    boolean        $const
 411       */
 412  	function __construct($yValues, $xValues=array(), $const=True) {
 413          //    Calculate number of points
 414          $nY = count($yValues);
 415          $nX = count($xValues);
 416  
 417          //    Define X Values if necessary
 418          if ($nX == 0) {
 419              $xValues = range(1,$nY);
 420              $nX = $nY;
 421          } elseif ($nY != $nX) {
 422              //    Ensure both arrays of points are the same size
 423              $this->_error = True;
 424              return False;
 425          }
 426  
 427          $this->_valueCount = $nY;
 428          $this->_xValues = $xValues;
 429          $this->_yValues = $yValues;
 430      }    //    function __construct()
 431  
 432  }    //    class bestFit