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Name	Size	Permission
local	[ DIR ]	drwxrwxr-x
privacy	[ DIR ]	drwxrwxr-x
admin_setting_predictor.php	2.55 KB	-rw-rw-r--
analysable.php	2.08 KB	-rw-rw-r--
calculable.php	8.53 KB	-rw-rw-r--
classifier.php	2.2 KB	-rw-rw-r--
course.php	17.52 KB	-rw-rw-r--
dataset_manager.php	15.65 KB	-rw-rw-r--
manager.php	21.83 KB	-rw-rw-r--
model.php	51.34 KB	-rw-rw-r--
prediction.php	6 KB	-rw-rw-r--
prediction_action.php	3.03 KB	-rw-rw-r--
predictor.php	2.58 KB	-rw-rw-r--
regressor.php	2.19 KB	-rw-rw-r--
requirements_exception.php	1.22 KB	-rw-rw-r--
site.php	2.47 KB	-rw-rw-r--

Code Editor : prediction.php

<?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/>.

/**
 * Representation of a prediction.
 *
 * @package   core_analytics
 * @copyright 2017 David Monllao {@link http://www.davidmonllao.com}
 * @license   http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
 */

namespace core_analytics;

defined('MOODLE_INTERNAL') || die();

/**
     * Prediction details (one of the default prediction actions)
     */
    const ACTION_PREDICTION_DETAILS = 'predictiondetails';

/**
     * Prediction not useful (one of the default prediction actions)
     */
    const ACTION_NOT_USEFUL = 'notuseful';

/**
     * Prediction already fixed (one of the default prediction actions)
     */
    const ACTION_FIXED = 'fixed';

/**
     * @var \stdClass
     */
    private $prediction;

/**
     * @var array
     */
    private $sampledata;

/**
     * @var array
     */
    private $calculations = array();

/**
     * Constructor
     *
     * @param \stdClass|int $prediction
     * @param array $sampledata
     * @return void
     */
    public function __construct($prediction, $sampledata) {
        global $DB;

if (is_scalar($prediction)) {
            $prediction = $DB->get_record('analytics_predictions', array('id' => $prediction), '*', MUST_EXIST);
        }
        $this->prediction = $prediction;

$this->sampledata = $sampledata;

$this->format_calculations();
    }

/**
     * Get prediction object data.
     *
     * @return \stdClass
     */
    public function get_prediction_data() {
        return $this->prediction;
    }

/**
     * Get prediction sample data.
     *
     * @return array
     */
    public function get_sample_data() {
        return $this->sampledata;
    }

/**
     * Gets the prediction calculations
     *
     * @return array
     */
    public function get_calculations() {
        return $this->calculations;
    }

/**
     * Stores the executed action.

* Prediction instances should be retrieved using \core_analytics\manager::get_prediction,
     * It is the caller responsability to check that the user can see the prediction.
     *
     * @param string $actionname
     * @param \core_analytics\local\target\base $target
     */
    public function action_executed($actionname, \core_analytics\local\target\base $target) {
        global $USER, $DB;

$context = \context::instance_by_id($this->get_prediction_data()->contextid, IGNORE_MISSING);
        if (!$context) {
            throw new \moodle_exception('errorpredictioncontextnotavailable', 'analytics');
        }

// Check that the provided action exists.
        $actions = $target->prediction_actions($this, true);
        foreach ($actions as $action) {
            if ($action->get_action_name() === $actionname) {
                $found = true;
            }
        }
        if (empty($found)) {
            throw new \moodle_exception('errorunknownaction', 'analytics');
        }

$predictionid = $this->get_prediction_data()->id;

$action = new \stdClass();
        $action->predictionid = $predictionid;
        $action->userid = $USER->id;
        $action->actionname = $actionname;
        $action->timecreated = time();
        $DB->insert_record('analytics_prediction_actions', $action);

$eventdata = array (
            'context' => $context,
            'objectid' => $predictionid,
            'other' => array('actionname' => $actionname)
        );
        \core\event\prediction_action_started::create($eventdata)->trigger();
    }

/**
     * format_calculations
     *
     * @return \stdClass[]
     */
    private function format_calculations() {

$calculations = json_decode($this->prediction->calculations, true);

foreach ($calculations as $featurename => $value) {

list($indicatorclass, $subtype) = $this->parse_feature_name($featurename);

if ($indicatorclass === 'range') {
                // Time range indicators don't belong to any indicator class, we don't store them.
                continue;
            } else if (!\core_analytics\manager::is_valid($indicatorclass, '\core_analytics\local\indicator\base')) {
                throw new \moodle_exception('errorpredictionformat', 'analytics');
            }

$this->calculations[$featurename] = new \stdClass();
            $this->calculations[$featurename]->subtype = $subtype;
            $this->calculations[$featurename]->indicator = \core_analytics\manager::get_indicator($indicatorclass);
            $this->calculations[$featurename]->value = $value;
        }
    }

/**
     * parse_feature_name
     *
     * @param string $featurename
     * @return string[]
     */
    private function parse_feature_name($featurename) {

$indicatorclass = $featurename;
        $subtype = false;

// Some indicator result in more than 1 feature, we need to see which feature are we dealing with.
        $separatorpos = strpos($featurename, '/');
        if ($separatorpos !== false) {
            $subtype = substr($featurename, ($separatorpos + 1));
            $indicatorclass = substr($featurename, 0, $separatorpos);
        }

return array($indicatorclass, $subtype);
    }
}

${this.title}

Code Editor : prediction.php