Merge branch 'MDL-58992_master' of git://github.com/dmonllao/moodle
This commit is contained in:
Jake Dallimore
@@ -0,0 +1,92 @@
|
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<?php
|
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// 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/>.
|
||||
|
||||
/**
|
||||
* Multiclass test indicator.
|
||||
*
|
||||
* @package core_analytics
|
||||
* @copyright 2019 Vlad Apetrei
|
||||
* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
|
||||
*/
|
||||
|
||||
defined('MOODLE_INTERNAL') || die();
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||||
|
||||
/**
|
||||
* Multiclass test indicator.
|
||||
*
|
||||
* @package core_analytics
|
||||
* @copyright 2019 Vlad Apetrei
|
||||
* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
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*/
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class test_indicator_multiclass extends \core_analytics\local\indicator\linear {
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|
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/**
|
||||
* Returns a lang_string object representing the name for the indicator.
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||||
*
|
||||
* Used as column identificator.
|
||||
*
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||||
* If there is a corresponding '_help' string this will be shown as well.
|
||||
*
|
||||
* @return \lang_string
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||||
*/
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||||
public static function get_name() : \lang_string {
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||||
// Using a string that exists and contains a corresponding '_help' string.
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||||
return new \lang_string('allowstealthmodules');
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||||
}
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||||
|
||||
/**
|
||||
* include_averages
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||||
*
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||||
* @return bool
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||||
*/
|
||||
protected static function include_averages() {
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return false;
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||||
}
|
||||
|
||||
/**
|
||||
* required_sample_data
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||||
*
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||||
* @return string[]
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||||
*/
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||||
public static function required_sample_data() {
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return array('course');
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||||
}
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|
||||
/**
|
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* calculate_sample
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*
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* @param int $sampleid
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* @param string $samplesorigin
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* @param int $starttime
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* @param int $endtime
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* @return float
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*/
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protected function calculate_sample($sampleid, $samplesorigin, $starttime, $endtime) {
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$course = $this->retrieve('course', $sampleid);
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$firstchar = substr($course->fullname, 0, 1);
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if ($firstchar === 'a') {
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return 1;
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||||
} else if ($firstchar === 'b') {
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return -1;
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||||
} else if ($firstchar === 'c') {
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||||
return 1;
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||||
} else {
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||||
return self::MAX_VALUE;
|
||||
}
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||||
}
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}
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@@ -0,0 +1,211 @@
|
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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/>.
|
||||
|
||||
/**
|
||||
* Multi-class classifier target.
|
||||
*
|
||||
* @package core_analytics
|
||||
* @copyright 2019 Apetrei Vlad
|
||||
* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
|
||||
*/
|
||||
|
||||
defined('MOODLE_INTERNAL') || die();
|
||||
|
||||
/**
|
||||
* Multi-class classifier target.
|
||||
*
|
||||
* @package core_analytics
|
||||
* @copyright 2019 Apetrei Vlad
|
||||
* @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
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||||
*/
|
||||
class test_target_shortname_multiclass extends \core_analytics\local\target\discrete {
|
||||
|
||||
/**
|
||||
* Returns a lang_string object representing the name for the indicator.
|
||||
*
|
||||
* Used as column identificator.
|
||||
*
|
||||
* If there is a corresponding '_help' string this will be shown as well.
|
||||
*
|
||||
* @return \lang_string
|
||||
*/
|
||||
public static function get_name() : \lang_string {
|
||||
// Using a string that exists and contains a corresponding '_help' string.
|
||||
return new \lang_string('allowstealthmodules');
|
||||
}
|
||||
|
||||
/**
|
||||
* predictions
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||||
*
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||||
* @var array
|
||||
*/
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||||
protected $predictions = array();
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||||
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||||
/**
|
||||
* is_linear
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||||
*
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||||
* @return bool
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||||
*/
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||||
public function is_linear() {
|
||||
return false;
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||||
}
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||||
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||||
/**
|
||||
* Returns the target discrete values.
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||||
*
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||||
* Only useful for targets using discrete values, must be overwriten if it is the case.
|
||||
*
|
||||
* @return array
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||||
*/
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||||
public static final function get_classes() {
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return array(0, 1, 2);
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||||
}
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||||
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||||
/**
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||||
* Is the calculated value a positive outcome of this target?
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*
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||||
* @param string $value
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||||
* @param string $ignoredsubtype
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||||
* @return int
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||||
*/
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||||
public function get_calculation_outcome($value, $ignoredsubtype = false) {
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if (!self::is_a_class($value)) {
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throw new \moodle_exception('errorpredictionformat', 'analytics');
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}
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if (in_array($value, $this->ignored_predicted_classes(), false)) {
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// Just in case, if it is ignored the prediction should not even be recorded but if it would, it is ignored now,
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||||
// which should mean that is it nothing serious.
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||||
return self::OUTCOME_VERY_POSITIVE;
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}
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||||
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||||
// By default binaries are danger when prediction = 1.
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||||
if ($value) {
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||||
return self::OUTCOME_VERY_NEGATIVE;
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}
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||||
return self::OUTCOME_VERY_POSITIVE;
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||||
}
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||||
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||||
/**
|
||||
* get_analyser_class
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||||
*
|
||||
* @return string
|
||||
*/
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||||
public function get_analyser_class() {
|
||||
return '\core\analytics\analyser\site_courses';
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||||
}
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||||
/**
|
||||
* We don't want to discard results.
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||||
* @return float
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||||
*/
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||||
protected function min_prediction_score() {
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||||
return null;
|
||||
}
|
||||
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||||
/**
|
||||
* We don't want to discard results.
|
||||
* @return array
|
||||
*/
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||||
public function ignored_predicted_classes() {
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||||
return array();
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||||
}
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||||
|
||||
/**
|
||||
* is_valid_analysable
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||||
*
|
||||
* @param \core_analytics\analysable $analysable
|
||||
* @param bool $fortraining
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||||
* @return bool
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||||
*/
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||||
public function is_valid_analysable(\core_analytics\analysable $analysable, $fortraining = true) {
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||||
// This is testing, let's make things easy.
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||||
return true;
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||||
}
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||||
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||||
/**
|
||||
* is_valid_sample
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||||
*
|
||||
* @param int $sampleid
|
||||
* @param \core_analytics\analysable $analysable
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||||
* @param bool $fortraining
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||||
* @return bool
|
||||
*/
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||||
public function is_valid_sample($sampleid, \core_analytics\analysable $analysable, $fortraining = true) {
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// We skip not-visible courses during training as a way to emulate the training data / prediction data difference.
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||||
// In normal circumstances is_valid_sample will return false when they receive a sample that can not be
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// processed.
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if (!$fortraining) {
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return true;
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||||
}
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||||
|
||||
$sample = $this->retrieve('course', $sampleid);
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||||
if ($sample->visible == 0) {
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return false;
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||||
}
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||||
return true;
|
||||
}
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||||
|
||||
/**
|
||||
* classes_description
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||||
*
|
||||
* @return string[]
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||||
*/
|
||||
protected static function classes_description() {
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||||
return array(
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||||
get_string('first class'),
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||||
get_string('second class'),
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||||
get_string('third class')
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* calculate_sample
|
||||
*
|
||||
* @param int $sampleid
|
||||
* @param \core_analytics\analysable $analysable
|
||||
* @param int $starttime
|
||||
* @param int $endtime
|
||||
* @return float
|
||||
*/
|
||||
protected function calculate_sample($sampleid, \core_analytics\analysable $analysable, $starttime = false, $endtime = false) {
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|
||||
$sample = $this->retrieve('course', $sampleid);
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||||
|
||||
$firstchar = substr($sample->shortname, 0, 1);
|
||||
switch ($firstchar) {
|
||||
case 'a':
|
||||
return 0;
|
||||
case 'b':
|
||||
return 1;
|
||||
case 'c':
|
||||
return 2;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Can the provided time-splitting method be used on this target?.
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||||
*
|
||||
* Time-splitting methods not matching the target requirements will not be selectable by models based on this target.
|
||||
*
|
||||
* @param \core_analytics\local\time_splitting\base $timesplitting
|
||||
* @return bool
|
||||
*/
|
||||
public function can_use_timesplitting(\core_analytics\local\time_splitting\base $timesplitting):bool {
|
||||
return true;
|
||||
}
|
||||
}
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||||
@@ -30,7 +30,9 @@ require_once(__DIR__ . '/fixtures/test_indicator_min.php');
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||||
require_once(__DIR__ . '/fixtures/test_indicator_null.php');
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require_once(__DIR__ . '/fixtures/test_indicator_fullname.php');
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||||
require_once(__DIR__ . '/fixtures/test_indicator_random.php');
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require_once(__DIR__ . '/fixtures/test_indicator_multiclass.php');
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||||
require_once(__DIR__ . '/fixtures/test_target_shortname.php');
|
||||
require_once(__DIR__ . '/fixtures/test_target_shortname_multiclass.php');
|
||||
require_once(__DIR__ . '/fixtures/test_static_target_shortname.php');
|
||||
|
||||
require_once(__DIR__ . '/../../course/lib.php');
|
||||
@@ -433,6 +435,70 @@ class core_analytics_prediction_testcase extends advanced_testcase {
|
||||
return $this->add_prediction_processors($cases);
|
||||
}
|
||||
|
||||
/**
|
||||
* Tests correct multi-classification.
|
||||
*
|
||||
* @dataProvider provider_test_multi_classifier
|
||||
* @param string $timesplittingid
|
||||
* @param string $predictionsprocessorclass
|
||||
* @throws coding_exception
|
||||
* @throws moodle_exception
|
||||
*/
|
||||
public function test_ml_multi_classifier($timesplittingid, $predictionsprocessorclass) {
|
||||
global $DB;
|
||||
|
||||
$this->resetAfterTest(true);
|
||||
$this->setAdminuser();
|
||||
set_config('enabled_stores', 'logstore_standard', 'tool_log');
|
||||
|
||||
$predictionsprocessor = \core_analytics\manager::get_predictions_processor($predictionsprocessorclass, false);
|
||||
if ($predictionsprocessor->is_ready() !== true) {
|
||||
$this->markTestSkipped('Skipping ' . $predictionsprocessorclass . ' as the predictor is not ready.');
|
||||
}
|
||||
// Generate training courses.
|
||||
$ncourses = 5;
|
||||
$this->generate_courses_multiclass($ncourses);
|
||||
$model = $this->add_multiclass_model();
|
||||
$model->update(true, false, $timesplittingid, get_class($predictionsprocessor));
|
||||
$results = $model->train();
|
||||
|
||||
$params = [
|
||||
'startdate' => mktime(0, 0, 0, 10, 24, 2015),
|
||||
'enddate' => mktime(0, 0, 0, 2, 24, 2016),
|
||||
];
|
||||
$courseparams = $params + array('shortname' => 'aaaaaa', 'fullname' => 'aaaaaa', 'visible' => 0);
|
||||
$course1 = $this->getDataGenerator()->create_course($courseparams);
|
||||
$courseparams = $params + array('shortname' => 'bbbbbb', 'fullname' => 'bbbbbb', 'visible' => 0);
|
||||
$course2 = $this->getDataGenerator()->create_course($courseparams);
|
||||
$courseparams = $params + array('shortname' => 'cccccc', 'fullname' => 'cccccc', 'visible' => 0);
|
||||
$course3 = $this->getDataGenerator()->create_course($courseparams);
|
||||
|
||||
// They will not be skipped for prediction though.
|
||||
$result = $model->predict();
|
||||
// The $course1 predictions should be 0 == 'a', $course2 should be 1 == 'b' and $course3 should be 2 == 'c'.
|
||||
$correct = array($course1->id => 0, $course2->id => 1, $course3->id => 2);
|
||||
foreach ($result->predictions as $uniquesampleid => $predictiondata) {
|
||||
list($sampleid, $rangeindex) = $model->get_time_splitting()->infer_sample_info($uniquesampleid);
|
||||
|
||||
// The range index is not important here, both ranges prediction will be the same.
|
||||
$this->assertEquals($correct[$sampleid], $predictiondata->prediction);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Provider for the multi_classification test.
|
||||
*
|
||||
* @return array
|
||||
*/
|
||||
public function provider_test_multi_classifier() {
|
||||
$cases = array(
|
||||
'notimesplitting' => array('\core\analytics\time_splitting\no_splitting'),
|
||||
);
|
||||
|
||||
// Add all system prediction processors.
|
||||
return $this->add_prediction_processors($cases);
|
||||
}
|
||||
|
||||
/**
|
||||
* Basic test to check that prediction processors work as expected.
|
||||
*
|
||||
@@ -670,7 +736,6 @@ class core_analytics_prediction_testcase extends advanced_testcase {
|
||||
* @return \core_analytics\model
|
||||
*/
|
||||
protected function add_perfect_model($targetclass = 'test_target_shortname') {
|
||||
|
||||
$target = \core_analytics\manager::get_target($targetclass);
|
||||
$indicators = array('test_indicator_max', 'test_indicator_min', 'test_indicator_fullname');
|
||||
foreach ($indicators as $key => $indicator) {
|
||||
@@ -683,6 +748,25 @@ class core_analytics_prediction_testcase extends advanced_testcase {
|
||||
return new \core_analytics\model($model->get_id());
|
||||
}
|
||||
|
||||
/**
|
||||
* Generates model for multi-classification
|
||||
*
|
||||
* @param string $targetclass
|
||||
* @return \core_analytics\model
|
||||
* @throws coding_exception
|
||||
* @throws moodle_exception
|
||||
*/
|
||||
public function add_multiclass_model($targetclass = 'test_target_shortname_multiclass') {
|
||||
$target = \core_analytics\manager::get_target($targetclass);
|
||||
$indicators = array('test_indicator_fullname', 'test_indicator_multiclass');
|
||||
foreach ($indicators as $key => $indicator) {
|
||||
$indicators[$key] = \core_analytics\manager::get_indicator($indicator);
|
||||
}
|
||||
|
||||
$model = \core_analytics\model::create($target, $indicators);
|
||||
return new \core_analytics\model($model->get_id());
|
||||
}
|
||||
|
||||
/**
|
||||
* Generates $ncourses courses
|
||||
*
|
||||
@@ -709,6 +793,37 @@ class core_analytics_prediction_testcase extends advanced_testcase {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Generates ncourses for multi-classification
|
||||
*
|
||||
* @param int $ncourses The number of courses to be generated.
|
||||
* @param array $params Course params
|
||||
* @return null
|
||||
*/
|
||||
protected function generate_courses_multiclass($ncourses, array $params = []) {
|
||||
|
||||
$params = $params + [
|
||||
'startdate' => mktime(0, 0, 0, 10, 24, 2015),
|
||||
'enddate' => mktime(0, 0, 0, 2, 24, 2016),
|
||||
];
|
||||
|
||||
for ($i = 0; $i < $ncourses; $i++) {
|
||||
$name = 'a' . random_string(10);
|
||||
$courseparams = array('shortname' => $name, 'fullname' => $name) + $params;
|
||||
$this->getDataGenerator()->create_course($courseparams);
|
||||
}
|
||||
for ($i = 0; $i < $ncourses; $i++) {
|
||||
$name = 'b' . random_string(10);
|
||||
$courseparams = array('shortname' => $name, 'fullname' => $name) + $params;
|
||||
$this->getDataGenerator()->create_course($courseparams);
|
||||
}
|
||||
for ($i = 0; $i < $ncourses; $i++) {
|
||||
$name = 'c' . random_string(10);
|
||||
$courseparams = array('shortname' => $name, 'fullname' => $name) + $params;
|
||||
$this->getDataGenerator()->create_course($courseparams);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* add_prediction_processors
|
||||
*
|
||||
|
||||
@@ -132,8 +132,7 @@ class processor implements \core_analytics\classifier, \core_analytics\regressor
|
||||
$nsamples = count($samples);
|
||||
if ($nsamples === self::BATCH_SIZE) {
|
||||
// Training it batches to avoid running out of memory.
|
||||
|
||||
$classifier->partialTrain($samples, $targets, array(0, 1));
|
||||
$classifier->partialTrain($samples, $targets, json_decode($metadata['targetclasses']));
|
||||
$samples = array();
|
||||
$targets = array();
|
||||
}
|
||||
@@ -152,7 +151,7 @@ class processor implements \core_analytics\classifier, \core_analytics\regressor
|
||||
|
||||
// Train the remaining samples.
|
||||
if ($samples) {
|
||||
$classifier->partialTrain($samples, $targets, array(0, 1));
|
||||
$classifier->partialTrain($samples, $targets, json_decode($metadata['targetclasses']));
|
||||
}
|
||||
|
||||
$resultobj = new \stdClass();
|
||||
|
||||
@@ -38,7 +38,7 @@ class processor implements \core_analytics\classifier, \core_analytics\regresso
|
||||
/**
|
||||
* The required version of the python package that performs all calculations.
|
||||
*/
|
||||
const REQUIRED_PIP_PACKAGE_VERSION = '2.0.0';
|
||||
const REQUIRED_PIP_PACKAGE_VERSION = '2.1.0';
|
||||
|
||||
/**
|
||||
* The path to the Python bin.
|
||||
|
||||
Reference in New Issue
Block a user