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   1  <?php
   2  // This file is part of Moodle - http://moodle.org/
   3  //
   4  // Moodle is free software: you can redistribute it and/or modify
   5  // it under the terms of the GNU General Public License as published by
   6  // the Free Software Foundation, either version 3 of the License, or
   7  // (at your option) any later version.
   8  //
   9  // Moodle is distributed in the hope that it will be useful,
  10  // but WITHOUT ANY WARRANTY; without even the implied warranty of
  11  // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
  12  // GNU General Public License for more details.
  13  //
  14  // You should have received a copy of the GNU General Public License
  15  // along with Moodle.  If not, see <http://www.gnu.org/licenses/>.
  16  
  17  /**
  18   * Abstract linear indicator.
  19   *
  20   * @package   core_analytics
  21   * @copyright 2017 David Monllao {@link http://www.davidmonllao.com}
  22   * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
  23   */
  24  
  25  namespace core_analytics\local\indicator;
  26  
  27  defined('MOODLE_INTERNAL') || die();
  28  
  29  /**
  30   * Abstract linear indicator.
  31   *
  32   * @package   core_analytics
  33   * @copyright 2017 David Monllao {@link http://www.davidmonllao.com}
  34   * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
  35   */
  36  abstract class linear extends base {
  37  
  38      /**
  39       * Set to false to avoid context features to be added as dataset features.
  40       *
  41       * @return bool
  42       */
  43      protected static function include_averages() {
  44          return true;
  45      }
  46  
  47      /**
  48       * get_feature_headers
  49       *
  50       * @return array
  51       */
  52      public static function get_feature_headers() {
  53  
  54          $fullclassname = '\\' . get_called_class();
  55  
  56          if (static::include_averages()) {
  57              // The calculated value + context indicators.
  58              $headers = array($fullclassname, $fullclassname . '/mean');
  59          } else {
  60              $headers = array($fullclassname);
  61          }
  62          return $headers;
  63      }
  64  
  65      /**
  66       * Show only the main feature.
  67       *
  68       * @param float $value
  69       * @param string $subtype
  70       * @return bool
  71       */
  72      public function should_be_displayed($value, $subtype) {
  73          if ($subtype != false) {
  74              return false;
  75          }
  76          return true;
  77      }
  78  
  79      /**
  80       * get_display_value
  81       *
  82       * @param float $value
  83       * @param string $subtype
  84       * @return string
  85       */
  86      public function get_display_value($value, $subtype = false) {
  87          $diff = static::get_max_value() - static::get_min_value();
  88          return round(100 * ($value - static::get_min_value()) / $diff) . '%';
  89      }
  90  
  91      /**
  92       * get_calculation_outcome
  93       *
  94       * @param float $value
  95       * @param string $subtype
  96       * @return int
  97       */
  98      public function get_calculation_outcome($value, $subtype = false) {
  99          if ($value < 0) {
 100              return self::OUTCOME_NEGATIVE;
 101          } else {
 102              return self::OUTCOME_OK;
 103          }
 104      }
 105  
 106      /**
 107       * Converts the calculated values to a list of features for the dataset.
 108       *
 109       * @param array $calculatedvalues
 110       * @return array
 111       */
 112      protected function to_features($calculatedvalues) {
 113  
 114          // Null mean if all calculated values are null.
 115          $nullmean = true;
 116          foreach ($calculatedvalues as $value) {
 117              if (!is_null($value)) {
 118                  // Early break, we don't want to spend a lot of time here.
 119                  $nullmean = false;
 120                  break;
 121              }
 122          }
 123  
 124          if ($nullmean) {
 125              $mean = null;
 126          } else {
 127              $mean = round(array_sum($calculatedvalues) / count($calculatedvalues), 2);
 128          }
 129  
 130          foreach ($calculatedvalues as $sampleid => $calculatedvalue) {
 131  
 132              if (!is_null($calculatedvalue)) {
 133                  $calculatedvalue = round($calculatedvalue, 2);
 134              }
 135  
 136              if (static::include_averages()) {
 137                  $calculatedvalues[$sampleid] = array($calculatedvalue, $mean);
 138              } else {
 139                  // Basically just convert the scalar to an array of scalars with a single value.
 140                  $calculatedvalues[$sampleid] = array($calculatedvalue);
 141              }
 142          }
 143  
 144          // Returns each sample as an array of values, appending the mean to the calculated value.
 145          return $calculatedvalues;
 146      }
 147  }