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<?php// This file is part of Moodle - http://moodle.org///// Moodle is free software: you can redistribute it and/or modify// it under the terms of the GNU General Public License as published by// the Free Software Foundation, either version 3 of the License, or// (at your option) any later version.//// Moodle is distributed in the hope that it will be useful,// but WITHOUT ANY WARRANTY; without even the implied warranty of// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the// GNU General Public License for more details.//// You should have received a copy of the GNU General Public License// along with Moodle. If not, see <http://www.gnu.org/licenses/>./*** Base time splitting method.** @package core_analytics* @copyright 2016 David Monllao {@link http://www.davidmonllao.com}* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later*/namespace core_analytics\local\time_splitting;defined('MOODLE_INTERNAL') || die();/*** Base time splitting method.** @package core_analytics* @copyright 2016 David Monllao {@link http://www.davidmonllao.com}* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later*/abstract class base {/*** @var string*/protected $id;/*** The model id.** @var int*/protected $modelid;/*** @var \core_analytics\analysable*/protected $analysable;/*** @var array*/protected $ranges = [];/*** Define the time splitting methods ranges.** 'time' value defines when predictions are executed, their values will be compared with* the current time in ready_to_predict. The ranges should be sorted by 'time' in* ascending order.** @return array('start' => time(), 'end' => time(), 'time' => time())*/abstract protected function define_ranges();/*** Returns a lang_string object representing the name for the time splitting method.** Used as column identificator.** If there is a corresponding '_help' string this will be shown as well.** @return \lang_string*/abstract public static function get_name(): \lang_string;/*** Returns the time splitting method id.** @return string*/public function get_id() {return '\\' . get_class($this);}/*** Assigns the analysable and updates the time ranges according to the analysable start and end dates.** @param \core_analytics\analysable $analysable* @return void*/public function set_analysable(\core_analytics\analysable $analysable) {$this->analysable = $analysable;$this->ranges = $this->define_ranges();$this->validate_ranges();}/*** Assigns the model id to this time-splitting method it case it needs it.** @param int $modelid*/public function set_modelid(int $modelid) {$this->modelid = $modelid;}/*** get_analysable** @return \core_analytics\analysable*/public function get_analysable() {return $this->analysable;}/*** Returns whether the course can be processed by this time splitting method or not.** @param \core_analytics\analysable $analysable* @return bool*/public function is_valid_analysable(\core_analytics\analysable $analysable) {return true;}/*** Should we predict this time range now?** @param array $range* @return bool*/public function ready_to_predict($range) {if ($range['time'] <= time()) {return true;}return false;}/*** Should we use this time range for training?** @param array $range* @return bool*/public function ready_to_train($range) {$now = time();if ($range['time'] <= $now && $range['end'] <= $now) {return true;}return false;}/*** Returns the ranges used by this time splitting method.** @return array*/public function get_all_ranges() {return $this->ranges;}/*** By default all ranges are for training.** @return array*/public function get_training_ranges() {return $this->ranges;}/*** Returns the distinct range indexes in this time splitting method.** @return int[]*/public function get_distinct_ranges() {if ($this->include_range_info_in_training_data()) {return array_keys($this->ranges);} else {return [0];}}/*** Returns the most recent range that can be used to predict.** This method is only called when calculating predictions.** @return array*/public function get_most_recent_prediction_range() {$ranges = $this->get_all_ranges();// Opposite order as we are interested in the last range that can be used for prediction.krsort($ranges);// We already provided the analysable to the time splitting method, there is no need to feed it back.foreach ($ranges as $rangeindex => $range) {if ($this->ready_to_predict($range)) {// We need to maintain the same indexes.return array($rangeindex => $range);}}return array();}/*** Returns range data by its index.** @param int $rangeindex* @return array|false Range data or false if the index is not part of the existing ranges.*/public function get_range_by_index($rangeindex) {if (!isset($this->ranges[$rangeindex])) {return false;}return $this->ranges[$rangeindex];}/*** Generates a unique sample id (sample in a range index).** @param int $sampleid* @param int $rangeindex* @return string*/final public function append_rangeindex($sampleid, $rangeindex) {return $sampleid . '-' . $rangeindex;}/*** Returns the sample id and the range index from a uniquesampleid.** @param string $uniquesampleid* @return array array($sampleid, $rangeindex)*/final public function infer_sample_info($uniquesampleid) {return explode('-', $uniquesampleid);}/*** Whether to include the range index in the training data or not.** By default, we consider that the different time ranges included in a time splitting method may not be* compatible between them (i.e. the indicators calculated at the end of the course can easily* differ from indicators calculated at the beginning of the course). So we include the range index as* one of the variables that the machine learning backend uses to generate predictions.** If the indicators calculated using the different time ranges available in this time splitting method* are comparable you can overwrite this method to return false.** Note that:* - This is only relevant for models whose predictions are not based on assumptions* (i.e. the ones using a machine learning backend to generate predictions).* - The ranges can only be included in the training data when* we know the final number of ranges the time splitting method will have. E.g.* We can not know the final number of ranges of a 'daily' time splitting method* as we will have one new range every day.* @return bool*/public function include_range_info_in_training_data() {return true;}/*** Whether to cache or not the indicator calculations.** Indicator calculations are stored to be reused across models. The calculations* are indexed by the calculation start and end time, and these times depend on the* time-splitting method. You should overwrite this method and return false if the time* frames generated by your time-splitting method are unique and / or can hardly be* reused by further models.** @return bool*/public function cache_indicator_calculations(): bool {return true;}/*** Is this method valid to evaluate prediction models?** @return bool*/public function valid_for_evaluation(): bool {return true;}/*** Validates the time splitting method ranges.** @throws \coding_exception* @return void*/protected function validate_ranges() {foreach ($this->ranges as $key => $range) {if (!isset($this->ranges[$key]['start']) || !isset($this->ranges[$key]['end']) ||!isset($this->ranges[$key]['time'])) {throw new \coding_exception($this->get_id() . ' time splitting method "' . $key .'" range is not fully defined. We need a start timestamp and an end timestamp.');}}}}