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- Bug fixes for general core bugs in 4.3.x will end 7 October 2024 (12 months).
- Bug fixes for security issues in 4.3.x will end 21 April 2025 (18 months).
- PHP version: minimum PHP 8.0.0 Note: minimum PHP version has increased since Moodle 4.1. PHP 8.2.x is supported too.
/analytics/tests/ -> prediction_test.php (source)
Differences Between: [Versions 310 and 403] [Versions 311 and 403] [Versions 39 and 403]
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 namespace core_analytics; 18 19 defined('MOODLE_INTERNAL') || die(); 20 21 global $CFG; 22 require_once (__DIR__ . '/fixtures/test_indicator_max.php'); 23 require_once (__DIR__ . '/fixtures/test_indicator_min.php'); 24 require_once (__DIR__ . '/fixtures/test_indicator_null.php'); 25 require_once (__DIR__ . '/fixtures/test_indicator_fullname.php'); 26 require_once (__DIR__ . '/fixtures/test_indicator_random.php'); 27 require_once (__DIR__ . '/fixtures/test_indicator_multiclass.php'); 28 require_once (__DIR__ . '/fixtures/test_target_shortname.php'); 29 require_once (__DIR__ . '/fixtures/test_target_shortname_multiclass.php'); 30 require_once (__DIR__ . '/fixtures/test_static_target_shortname.php'); 31 32 require_once (__DIR__ . '/../../course/lib.php'); 33 34 /** 35 * Unit tests for evaluation, training and prediction. 36 * 37 * NOTE: in order to execute this test using a separate server for the 38 * python ML backend you need to define these variables in your config.php file: 39 * 40 * define('TEST_MLBACKEND_PYTHON_HOST', '127.0.0.1'); 41 * define('TEST_MLBACKEND_PYTHON_PORT', 5000); 42 * define('TEST_MLBACKEND_PYTHON_USERNAME', 'default'); 43 * define('TEST_MLBACKEND_PYTHON_PASSWORD', 'sshhhh'); 44 * 45 * @package core_analytics 46 * @copyright 2017 David Monllaó {@link http://www.davidmonllao.com} 47 * @license http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later 48 */ 49 class prediction_test extends \advanced_testcase { 50 51 /** 52 * Purge all the mlbackend outputs. 53 * 54 * This is done automatically for mlbackends using the web server dataroot but 55 * other mlbackends may store files elsewhere and these files need to be removed. 56 * 57 * @return null 58 */ 59 public function tearDown(): void { 60 $this->setAdminUser(); 61 62 $models = \core_analytics\manager::get_all_models(); 63 foreach ($models as $model) { 64 $model->delete(); 65 } 66 } 67 68 /** 69 * test_static_prediction 70 * 71 * @return void 72 */ 73 public function test_static_prediction() { 74 global $DB; 75 76 $this->resetAfterTest(true); 77 $this->setAdminuser(); 78 79 $model = $this->add_perfect_model('test_static_target_shortname'); 80 $model->enable('\core\analytics\time_splitting\no_splitting'); 81 $this->assertEquals(1, $model->is_enabled()); 82 $this->assertEquals(1, $model->is_trained()); 83 84 // No training for static models. 85 $results = $model->train(); 86 $trainedsamples = $DB->get_records('analytics_train_samples', array('modelid' => $model->get_id())); 87 $this->assertEmpty($trainedsamples); 88 $this->assertEmpty($DB->count_records('analytics_used_files', 89 array('modelid' => $model->get_id(), 'action' => 'trained'))); 90 91 // Now we create 2 hidden courses (only hidden courses are getting predictions). 92 $courseparams = array('shortname' => 'aaaaaa', 'fullname' => 'aaaaaa', 'visible' => 0); 93 $course1 = $this->getDataGenerator()->create_course($courseparams); 94 $courseparams = array('shortname' => 'bbbbbb', 'fullname' => 'bbbbbb', 'visible' => 0); 95 $course2 = $this->getDataGenerator()->create_course($courseparams); 96 97 $result = $model->predict(); 98 99 // Var $course1 predictions should be 1 == 'a', $course2 predictions should be 0 == 'b'. 100 $correct = array($course1->id => 1, $course2->id => 0); 101 foreach ($result->predictions as $uniquesampleid => $predictiondata) { 102 list($sampleid, $rangeindex) = $model->get_time_splitting()->infer_sample_info($uniquesampleid); 103 104 // The range index is not important here, both ranges prediction will be the same. 105 $this->assertEquals($correct[$sampleid], $predictiondata->prediction); 106 } 107 108 // 1 range for each analysable. 109 $predictedranges = $DB->get_records('analytics_predict_samples', array('modelid' => $model->get_id())); 110 $this->assertCount(2, $predictedranges); 111 // 2 predictions for each range. 112 $this->assertEquals(2, $DB->count_records('analytics_predictions', 113 array('modelid' => $model->get_id()))); 114 115 // No new generated records as there are no new courses available. 116 $model->predict(); 117 $predictedranges = $DB->get_records('analytics_predict_samples', array('modelid' => $model->get_id())); 118 $this->assertCount(2, $predictedranges); 119 $this->assertEquals(2, $DB->count_records('analytics_predictions', 120 array('modelid' => $model->get_id()))); 121 } 122 123 /** 124 * test_model_contexts 125 */ 126 public function test_model_contexts() { 127 global $DB; 128 129 $this->resetAfterTest(true); 130 $this->setAdminuser(); 131 132 $misc = $DB->get_record('course_categories', ['name' => get_string('defaultcategoryname')]); 133 $miscctx = \context_coursecat::instance($misc->id); 134 135 $category = $this->getDataGenerator()->create_category(); 136 $categoryctx = \context_coursecat::instance($category->id); 137 138 // One course per category. 139 $courseparams = array('shortname' => 'aaaaaa', 'fullname' => 'aaaaaa', 'visible' => 0, 140 'category' => $category->id); 141 $course1 = $this->getDataGenerator()->create_course($courseparams); 142 $course1ctx = \context_course::instance($course1->id); 143 $courseparams = array('shortname' => 'bbbbbb', 'fullname' => 'bbbbbb', 'visible' => 0, 144 'category' => $misc->id); 145 $course2 = $this->getDataGenerator()->create_course($courseparams); 146 147 $model = $this->add_perfect_model('test_static_target_shortname'); 148 149 // Just 1 category. 150 $model->update(true, false, '\core\analytics\time_splitting\no_splitting', false, [$categoryctx->id]); 151 $this->assertCount(1, $model->predict()->predictions); 152 153 // Now with 2 categories. 154 $model->update(true, false, false, false, [$categoryctx->id, $miscctx->id]); 155 156 // The courses in the new category are processed. 157 $this->assertCount(1, $model->predict()->predictions); 158 159 // Clear the predictions generated by the model and predict() again. 160 $model->clear(); 161 $this->assertCount(2, $model->predict()->predictions); 162 163 // Course context restriction. 164 $model->update(true, false, '\core\analytics\time_splitting\no_splitting', false, [$course1ctx->id]); 165 166 // Nothing new as the course was already analysed. 167 $result = $model->predict(); 168 $this->assertTrue(empty($result->predictions)); 169 170 $model->clear(); 171 $this->assertCount(1, $model->predict()->predictions); 172 } 173 174 /** 175 * test_ml_training_and_prediction 176 * 177 * @dataProvider provider_ml_training_and_prediction 178 * @param string $timesplittingid 179 * @param int $predictedrangeindex 180 * @param int $nranges 181 * @param string $predictionsprocessorclass 182 * @param array $forcedconfig 183 * @return void 184 */ 185 public function test_ml_training_and_prediction($timesplittingid, $predictedrangeindex, $nranges, $predictionsprocessorclass, 186 $forcedconfig) { 187 global $DB; 188 189 $this->resetAfterTest(true); 190 191 $this->set_forced_config($forcedconfig); 192 $predictionsprocessor = $this->is_predictions_processor_ready($predictionsprocessorclass); 193 194 $this->setAdminuser(); 195 set_config('enabled_stores', 'logstore_standard', 'tool_log'); 196 197 // Generate training data. 198 $ncourses = 10; 199 $this->generate_courses($ncourses); 200 201 $model = $this->add_perfect_model(); 202 203 $model->update(true, false, $timesplittingid, get_class($predictionsprocessor)); 204 205 // No samples trained yet. 206 $this->assertEquals(0, $DB->count_records('analytics_train_samples', array('modelid' => $model->get_id()))); 207 208 $results = $model->train(); 209 $this->assertEquals(1, $model->is_enabled()); 210 $this->assertEquals(1, $model->is_trained()); 211 212 // 20 courses * the 3 model indicators * the number of time ranges of this time splitting method. 213 $indicatorcalc = 20 * 3 * $nranges; 214 $this->assertEquals($indicatorcalc, $DB->count_records('analytics_indicator_calc')); 215 216 // 1 training file was created. 217 $trainedsamples = $DB->get_records('analytics_train_samples', array('modelid' => $model->get_id())); 218 $this->assertCount(1, $trainedsamples); 219 $samples = json_decode(reset($trainedsamples)->sampleids, true); 220 $this->assertCount($ncourses * 2, $samples); 221 $this->assertEquals(1, $DB->count_records('analytics_used_files', 222 array('modelid' => $model->get_id(), 'action' => 'trained'))); 223 // Check that analysable files for training are stored under labelled filearea. 224 $fs = get_file_storage(); 225 $this->assertCount(1, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 226 \core_analytics\dataset_manager::LABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 227 $this->assertEmpty($fs->get_directory_files(\context_system::instance()->id, 'analytics', 228 \core_analytics\dataset_manager::UNLABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 229 230 $params = [ 231 'startdate' => mktime(0, 0, 0, 10, 24, 2015), 232 'enddate' => mktime(0, 0, 0, 2, 24, 2016), 233 ]; 234 $courseparams = $params + array('shortname' => 'aaaaaa', 'fullname' => 'aaaaaa', 'visible' => 0); 235 $course1 = $this->getDataGenerator()->create_course($courseparams); 236 $courseparams = $params + array('shortname' => 'bbbbbb', 'fullname' => 'bbbbbb', 'visible' => 0); 237 $course2 = $this->getDataGenerator()->create_course($courseparams); 238 239 // They will not be skipped for prediction though. 240 $result = $model->predict(); 241 242 // Var $course1 predictions should be 1 == 'a', $course2 predictions should be 0 == 'b'. 243 $correct = array($course1->id => 1, $course2->id => 0); 244 foreach ($result->predictions as $uniquesampleid => $predictiondata) { 245 list($sampleid, $rangeindex) = $model->get_time_splitting()->infer_sample_info($uniquesampleid); 246 247 // The range index is not important here, both ranges prediction will be the same. 248 $this->assertEquals($correct[$sampleid], $predictiondata->prediction); 249 } 250 251 // 1 range will be predicted. 252 $predictedranges = $DB->get_records('analytics_predict_samples', array('modelid' => $model->get_id())); 253 $this->assertCount(1, $predictedranges); 254 foreach ($predictedranges as $predictedrange) { 255 $this->assertEquals($predictedrangeindex, $predictedrange->rangeindex); 256 $sampleids = json_decode($predictedrange->sampleids, true); 257 $this->assertCount(2, $sampleids); 258 $this->assertContainsEquals($course1->id, $sampleids); 259 $this->assertContainsEquals($course2->id, $sampleids); 260 } 261 $this->assertEquals(1, $DB->count_records('analytics_used_files', 262 array('modelid' => $model->get_id(), 'action' => 'predicted'))); 263 // 2 predictions. 264 $this->assertEquals(2, $DB->count_records('analytics_predictions', 265 array('modelid' => $model->get_id()))); 266 267 // Check that analysable files to get predictions are stored under unlabelled filearea. 268 $this->assertCount(1, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 269 \core_analytics\dataset_manager::LABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 270 $this->assertCount(1, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 271 \core_analytics\dataset_manager::UNLABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 272 273 // No new generated files nor records as there are no new courses available. 274 $model->predict(); 275 $predictedranges = $DB->get_records('analytics_predict_samples', array('modelid' => $model->get_id())); 276 $this->assertCount(1, $predictedranges); 277 foreach ($predictedranges as $predictedrange) { 278 $this->assertEquals($predictedrangeindex, $predictedrange->rangeindex); 279 } 280 $this->assertEquals(1, $DB->count_records('analytics_used_files', 281 array('modelid' => $model->get_id(), 'action' => 'predicted'))); 282 $this->assertEquals(2, $DB->count_records('analytics_predictions', 283 array('modelid' => $model->get_id()))); 284 285 // New samples that can be used for prediction. 286 $courseparams = $params + array('shortname' => 'cccccc', 'fullname' => 'cccccc', 'visible' => 0); 287 $course3 = $this->getDataGenerator()->create_course($courseparams); 288 $courseparams = $params + array('shortname' => 'dddddd', 'fullname' => 'dddddd', 'visible' => 0); 289 $course4 = $this->getDataGenerator()->create_course($courseparams); 290 291 $result = $model->predict(); 292 293 $predictedranges = $DB->get_records('analytics_predict_samples', array('modelid' => $model->get_id())); 294 $this->assertCount(1, $predictedranges); 295 foreach ($predictedranges as $predictedrange) { 296 $this->assertEquals($predictedrangeindex, $predictedrange->rangeindex); 297 $sampleids = json_decode($predictedrange->sampleids, true); 298 $this->assertCount(4, $sampleids); 299 $this->assertContainsEquals($course1->id, $sampleids); 300 $this->assertContainsEquals($course2->id, $sampleids); 301 $this->assertContainsEquals($course3->id, $sampleids); 302 $this->assertContainsEquals($course4->id, $sampleids); 303 } 304 $this->assertEquals(2, $DB->count_records('analytics_used_files', 305 array('modelid' => $model->get_id(), 'action' => 'predicted'))); 306 $this->assertEquals(4, $DB->count_records('analytics_predictions', 307 array('modelid' => $model->get_id()))); 308 $this->assertCount(1, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 309 \core_analytics\dataset_manager::LABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 310 $this->assertCount(2, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 311 \core_analytics\dataset_manager::UNLABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 312 313 // New visible course (for training). 314 $course5 = $this->getDataGenerator()->create_course(array('shortname' => 'aaa', 'fullname' => 'aa')); 315 $course6 = $this->getDataGenerator()->create_course(); 316 $result = $model->train(); 317 $this->assertEquals(2, $DB->count_records('analytics_used_files', 318 array('modelid' => $model->get_id(), 'action' => 'trained'))); 319 $this->assertCount(2, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 320 \core_analytics\dataset_manager::LABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 321 $this->assertCount(2, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 322 \core_analytics\dataset_manager::UNLABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 323 324 // Confirm that the files associated to the model are deleted on clear and on delete. The ML backend deletion 325 // processes will be triggered by these actions and any exception there would result in a failed test. 326 $model->clear(); 327 $this->assertEquals(0, $DB->count_records('analytics_used_files', 328 array('modelid' => $model->get_id(), 'action' => 'trained'))); 329 $this->assertCount(0, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 330 \core_analytics\dataset_manager::LABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 331 $this->assertCount(0, $fs->get_directory_files(\context_system::instance()->id, 'analytics', 332 \core_analytics\dataset_manager::UNLABELLED_FILEAREA, $model->get_id(), '/analysable/', true, false)); 333 $model->delete(); 334 335 set_config('enabled_stores', '', 'tool_log'); 336 get_log_manager(true); 337 } 338 339 /** 340 * provider_ml_training_and_prediction 341 * 342 * @return array 343 */ 344 public function provider_ml_training_and_prediction() { 345 $cases = array( 346 'no_splitting' => array('\core\analytics\time_splitting\no_splitting', 0, 1), 347 'quarters' => array('\core\analytics\time_splitting\quarters', 3, 4) 348 ); 349 350 // We need to test all system prediction processors. 351 return $this->add_prediction_processors($cases); 352 } 353 354 /** 355 * test_ml_export_import 356 * 357 * @param string $predictionsprocessorclass The class name 358 * @param array $forcedconfig 359 * @dataProvider provider_ml_processors 360 */ 361 public function test_ml_export_import($predictionsprocessorclass, $forcedconfig) { 362 $this->resetAfterTest(true); 363 364 $this->set_forced_config($forcedconfig); 365 $predictionsprocessor = $this->is_predictions_processor_ready($predictionsprocessorclass); 366 367 $this->setAdminuser(); 368 set_config('enabled_stores', 'logstore_standard', 'tool_log'); 369 370 // Generate training data. 371 $ncourses = 10; 372 $this->generate_courses($ncourses); 373 374 $model = $this->add_perfect_model(); 375 376 $model->update(true, false, '\core\analytics\time_splitting\quarters', get_class($predictionsprocessor)); 377 378 $model->train(); 379 $this->assertTrue($model->trained_locally()); 380 381 $this->generate_courses(10, ['visible' => 0]); 382 383 $originalresults = $model->predict(); 384 385 $zipfilename = 'model-zip-' . microtime() . '.zip'; 386 $zipfilepath = $model->export_model($zipfilename); 387 388 $modelconfig = new \core_analytics\model_config(); 389 list($modelconfig, $mlbackend) = $modelconfig->extract_import_contents($zipfilepath); 390 $this->assertNotFalse($mlbackend); 391 392 $importmodel = \core_analytics\model::import_model($zipfilepath); 393 $importmodel->enable(); 394 395 // Now predict using the imported model without prior training. 396 $importedmodelresults = $importmodel->predict(); 397 398 foreach ($originalresults->predictions as $sampleid => $prediction) { 399 $this->assertEquals($importedmodelresults->predictions[$sampleid]->prediction, $prediction->prediction); 400 } 401 402 $this->assertFalse($importmodel->trained_locally()); 403 404 $zipfilename = 'model-zip-' . microtime() . '.zip'; 405 $zipfilepath = $model->export_model($zipfilename, false); 406 407 $modelconfig = new \core_analytics\model_config(); 408 list($modelconfig, $mlbackend) = $modelconfig->extract_import_contents($zipfilepath); 409 $this->assertFalse($mlbackend); 410 411 set_config('enabled_stores', '', 'tool_log'); 412 get_log_manager(true); 413 } 414 415 /** 416 * provider_ml_processors 417 * 418 * @return array 419 */ 420 public function provider_ml_processors() { 421 $cases = [ 422 'case' => [], 423 ]; 424 425 // We need to test all system prediction processors. 426 return $this->add_prediction_processors($cases); 427 } 428 /** 429 * Test the system classifiers returns. 430 * 431 * This test checks that all mlbackend plugins in the system are able to return proper status codes 432 * even under weird situations. 433 * 434 * @dataProvider provider_ml_classifiers_return 435 * @param int $success 436 * @param int $nsamples 437 * @param int $classes 438 * @param string $predictionsprocessorclass 439 * @param array $forcedconfig 440 * @return void 441 */ 442 public function test_ml_classifiers_return($success, $nsamples, $classes, $predictionsprocessorclass, $forcedconfig) { 443 $this->resetAfterTest(); 444 445 $this->set_forced_config($forcedconfig); 446 $predictionsprocessor = $this->is_predictions_processor_ready($predictionsprocessorclass); 447 448 if ($nsamples % count($classes) != 0) { 449 throw new \coding_exception('The number of samples should be divisible by the number of classes'); 450 } 451 $samplesperclass = $nsamples / count($classes); 452 453 // Metadata (we pass 2 classes even if $classes only provides 1 class samples as we want to test 454 // what the backend does in this case. 455 $dataset = "nfeatures,targetclasses,targettype" . PHP_EOL; 456 $dataset .= "3,\"[0,1]\",\"discrete\"" . PHP_EOL; 457 458 // Headers. 459 $dataset .= "feature1,feature2,feature3,target" . PHP_EOL; 460 foreach ($classes as $class) { 461 for ($i = 0; $i < $samplesperclass; $i++) { 462 $dataset .= "1,0,1,$class" . PHP_EOL; 463 } 464 } 465 466 $trainingfile = array( 467 'contextid' => \context_system::instance()->id, 468 'component' => 'analytics', 469 'filearea' => 'labelled', 470 'itemid' => 123, 471 'filepath' => '/', 472 'filename' => 'whocares.csv' 473 ); 474 $fs = get_file_storage(); 475 $dataset = $fs->create_file_from_string($trainingfile, $dataset); 476 477 // Training should work correctly if at least 1 sample of each class is included. 478 $dir = make_request_directory(); 479 $modeluniqueid = 'whatever' . microtime(); 480 $result = $predictionsprocessor->train_classification($modeluniqueid, $dataset, $dir); 481 482 switch ($success) { 483 case 'yes': 484 $this->assertEquals(\core_analytics\model::OK, $result->status); 485 break; 486 case 'no': 487 $this->assertNotEquals(\core_analytics\model::OK, $result->status); 488 break; 489 case 'maybe': 490 default: 491 // We just check that an object is returned so we don't have an empty check, 492 // what we really want to check is that an exception was not thrown. 493 $this->assertInstanceOf(\stdClass::class, $result); 494 } 495 496 // Purge the directory used in this test (useful in case the mlbackend is storing files 497 // somewhere out of the default moodledata/models dir. 498 $predictionsprocessor->delete_output_dir($dir, $modeluniqueid); 499 } 500 501 /** 502 * test_ml_classifiers_return provider 503 * 504 * We can not be very specific here as test_ml_classifiers_return only checks that 505 * mlbackend plugins behave and expected and control properly backend errors even 506 * under weird situations. 507 * 508 * @return array 509 */ 510 public function provider_ml_classifiers_return() { 511 // Using verbose options as the first argument for readability. 512 $cases = array( 513 '1-samples' => array('maybe', 1, [0]), 514 '2-samples-same-class' => array('maybe', 2, [0]), 515 '2-samples-different-classes' => array('yes', 2, [0, 1]), 516 '4-samples-different-classes' => array('yes', 4, [0, 1]) 517 ); 518 519 // We need to test all system prediction processors. 520 return $this->add_prediction_processors($cases); 521 } 522 523 /** 524 * Tests correct multi-classification. 525 * 526 * @dataProvider provider_test_multi_classifier 527 * @param string $timesplittingid 528 * @param string $predictionsprocessorclass 529 * @param array|null $forcedconfig 530 * @throws coding_exception 531 * @throws moodle_exception 532 */ 533 public function test_ml_multi_classifier($timesplittingid, $predictionsprocessorclass, $forcedconfig) { 534 global $DB; 535 536 $this->resetAfterTest(true); 537 $this->setAdminuser(); 538 set_config('enabled_stores', 'logstore_standard', 'tool_log'); 539 540 $this->set_forced_config($forcedconfig); 541 542 $predictionsprocessor = \core_analytics\manager::get_predictions_processor($predictionsprocessorclass, false); 543 if ($predictionsprocessor->is_ready() !== true) { 544 $this->markTestSkipped('Skipping ' . $predictionsprocessorclass . ' as the predictor is not ready.'); 545 } 546 // Generate training courses. 547 $ncourses = 5; 548 $this->generate_courses_multiclass($ncourses); 549 $model = $this->add_multiclass_model(); 550 $model->update(true, false, $timesplittingid, get_class($predictionsprocessor)); 551 $results = $model->train(); 552 553 $params = [ 554 'startdate' => mktime(0, 0, 0, 10, 24, 2015), 555 'enddate' => mktime(0, 0, 0, 2, 24, 2016), 556 ]; 557 $courseparams = $params + array('shortname' => 'aaaaaa', 'fullname' => 'aaaaaa', 'visible' => 0); 558 $course1 = $this->getDataGenerator()->create_course($courseparams); 559 $courseparams = $params + array('shortname' => 'bbbbbb', 'fullname' => 'bbbbbb', 'visible' => 0); 560 $course2 = $this->getDataGenerator()->create_course($courseparams); 561 $courseparams = $params + array('shortname' => 'cccccc', 'fullname' => 'cccccc', 'visible' => 0); 562 $course3 = $this->getDataGenerator()->create_course($courseparams); 563 564 // They will not be skipped for prediction though. 565 $result = $model->predict(); 566 // The $course1 predictions should be 0 == 'a', $course2 should be 1 == 'b' and $course3 should be 2 == 'c'. 567 $correct = array($course1->id => 0, $course2->id => 1, $course3->id => 2); 568 foreach ($result->predictions as $uniquesampleid => $predictiondata) { 569 list($sampleid, $rangeindex) = $model->get_time_splitting()->infer_sample_info($uniquesampleid); 570 571 // The range index is not important here, both ranges prediction will be the same. 572 $this->assertEquals($correct[$sampleid], $predictiondata->prediction); 573 } 574 575 set_config('enabled_stores', '', 'tool_log'); 576 get_log_manager(true); 577 } 578 579 /** 580 * Provider for the multi_classification test. 581 * 582 * @return array 583 */ 584 public function provider_test_multi_classifier() { 585 $cases = array( 586 'notimesplitting' => array('\core\analytics\time_splitting\no_splitting'), 587 ); 588 589 // Add all system prediction processors. 590 return $this->add_prediction_processors($cases); 591 } 592 593 /** 594 * Basic test to check that prediction processors work as expected. 595 * 596 * @coversNothing 597 * @dataProvider provider_ml_test_evaluation_configuration 598 * @param string $modelquality 599 * @param int $ncourses 600 * @param array $expected 601 * @param string $predictionsprocessorclass 602 * @param array $forcedconfig 603 * @return void 604 */ 605 public function test_ml_evaluation_configuration($modelquality, $ncourses, $expected, $predictionsprocessorclass, 606 $forcedconfig) { 607 $this->resetAfterTest(true); 608 609 $this->set_forced_config($forcedconfig); 610 $predictionsprocessor = $this->is_predictions_processor_ready($predictionsprocessorclass); 611 612 $this->setAdminuser(); 613 set_config('enabled_stores', 'logstore_standard', 'tool_log'); 614 615 $sometimesplittings = '\core\analytics\time_splitting\single_range,' . 616 '\core\analytics\time_splitting\quarters'; 617 set_config('defaulttimesplittingsevaluation', $sometimesplittings, 'analytics'); 618 619 if ($modelquality === 'perfect') { 620 $model = $this->add_perfect_model(); 621 } else if ($modelquality === 'random') { 622 $model = $this->add_random_model(); 623 } else { 624 throw new \coding_exception('Only perfect and random accepted as $modelquality values'); 625 } 626 627 // Generate training data. 628 $this->generate_courses($ncourses); 629 630 $model->update(false, false, false, get_class($predictionsprocessor)); 631 $results = $model->evaluate(); 632 633 // We check that the returned status includes at least $expectedcode code. 634 foreach ($results as $timesplitting => $result) { 635 $message = 'The returned status code ' . $result->status . ' should include ' . $expected[$timesplitting]; 636 $filtered = $result->status & $expected[$timesplitting]; 637 $this->assertEquals($expected[$timesplitting], $filtered, $message); 638 639 $options = ['evaluation' => true, 'reuseprevanalysed' => true]; 640 $result = new \core_analytics\local\analysis\result_file($model->get_id(), true, $options); 641 $timesplittingobj = \core_analytics\manager::get_time_splitting($timesplitting); 642 $analysable = new \core_analytics\site(); 643 $cachedanalysis = $result->retrieve_cached_result($timesplittingobj, $analysable); 644 $this->assertInstanceOf(\stored_file::class, $cachedanalysis); 645 } 646 647 set_config('enabled_stores', '', 'tool_log'); 648 get_log_manager(true); 649 } 650 651 /** 652 * Tests the evaluation of already trained models. 653 * 654 * @coversNothing 655 * @dataProvider provider_ml_processors 656 * @param string $predictionsprocessorclass 657 * @param array $forcedconfig 658 * @return null 659 */ 660 public function test_ml_evaluation_trained_model($predictionsprocessorclass, $forcedconfig) { 661 $this->resetAfterTest(true); 662 663 $this->set_forced_config($forcedconfig); 664 $predictionsprocessor = $this->is_predictions_processor_ready($predictionsprocessorclass); 665 666 $this->setAdminuser(); 667 set_config('enabled_stores', 'logstore_standard', 'tool_log'); 668 669 $model = $this->add_perfect_model(); 670 671 // Generate training data. 672 $this->generate_courses(50); 673 674 $model->update(true, false, '\\core\\analytics\\time_splitting\\quarters', get_class($predictionsprocessor)); 675 $model->train(); 676 677 $zipfilename = 'model-zip-' . microtime() . '.zip'; 678 $zipfilepath = $model->export_model($zipfilename); 679 $importmodel = \core_analytics\model::import_model($zipfilepath); 680 681 $results = $importmodel->evaluate(['mode' => 'trainedmodel']); 682 $this->assertEquals(0, $results['\\core\\analytics\\time_splitting\\quarters']->status); 683 $this->assertEquals(1, $results['\\core\\analytics\\time_splitting\\quarters']->score); 684 685 set_config('enabled_stores', '', 'tool_log'); 686 get_log_manager(true); 687 } 688 689 /** 690 * test_read_indicator_calculations 691 * 692 * @return void 693 */ 694 public function test_read_indicator_calculations() { 695 global $DB; 696 697 $this->resetAfterTest(true); 698 699 $starttime = 123; 700 $endtime = 321; 701 $sampleorigin = 'whatever'; 702 703 $indicator = $this->getMockBuilder('test_indicator_max')->onlyMethods(['calculate_sample'])->getMock(); 704 $indicator->expects($this->never())->method('calculate_sample'); 705 706 $existingcalcs = array(111 => 1, 222 => -1); 707 $sampleids = array(111 => 111, 222 => 222); 708 list($values, $unused) = $indicator->calculate($sampleids, $sampleorigin, $starttime, $endtime, $existingcalcs); 709 } 710 711 /** 712 * test_not_null_samples 713 */ 714 public function test_not_null_samples() { 715 $this->resetAfterTest(true); 716 717 $timesplitting = \core_analytics\manager::get_time_splitting('\core\analytics\time_splitting\quarters'); 718 $timesplitting->set_analysable(new \core_analytics\site()); 719 720 $ranges = array( 721 array('start' => 111, 'end' => 222, 'time' => 222), 722 array('start' => 222, 'end' => 333, 'time' => 333) 723 ); 724 $samples = array(123 => 123, 321 => 321); 725 726 $target = \core_analytics\manager::get_target('test_target_shortname'); 727 $indicators = array('test_indicator_null', 'test_indicator_min'); 728 foreach ($indicators as $key => $indicator) { 729 $indicators[$key] = \core_analytics\manager::get_indicator($indicator); 730 } 731 $model = \core_analytics\model::create($target, $indicators, '\core\analytics\time_splitting\no_splitting'); 732 733 $analyser = $model->get_analyser(); 734 $result = new \core_analytics\local\analysis\result_array($model->get_id(), false, $analyser->get_options()); 735 $analysis = new \core_analytics\analysis($analyser, false, $result); 736 737 // Samples with at least 1 not null value are returned. 738 $params = array( 739 $timesplitting, 740 $samples, 741 $ranges 742 ); 743 $dataset = \phpunit_util::call_internal_method($analysis, 'calculate_indicators', $params, 744 '\core_analytics\analysis'); 745 $this->assertArrayHasKey('123-0', $dataset); 746 $this->assertArrayHasKey('123-1', $dataset); 747 $this->assertArrayHasKey('321-0', $dataset); 748 $this->assertArrayHasKey('321-1', $dataset); 749 750 751 $indicators = array('test_indicator_null'); 752 foreach ($indicators as $key => $indicator) { 753 $indicators[$key] = \core_analytics\manager::get_indicator($indicator); 754 } 755 $model = \core_analytics\model::create($target, $indicators, '\core\analytics\time_splitting\no_splitting'); 756 757 $analyser = $model->get_analyser(); 758 $result = new \core_analytics\local\analysis\result_array($model->get_id(), false, $analyser->get_options()); 759 $analysis = new \core_analytics\analysis($analyser, false, $result); 760 761 // Samples with only null values are not returned. 762 $params = array( 763 $timesplitting, 764 $samples, 765 $ranges 766 ); 767 $dataset = \phpunit_util::call_internal_method($analysis, 'calculate_indicators', $params, 768 '\core_analytics\analysis'); 769 $this->assertArrayNotHasKey('123-0', $dataset); 770 $this->assertArrayNotHasKey('123-1', $dataset); 771 $this->assertArrayNotHasKey('321-0', $dataset); 772 $this->assertArrayNotHasKey('321-1', $dataset); 773 } 774 775 /** 776 * provider_ml_test_evaluation_configuration 777 * 778 * @return array 779 */ 780 public function provider_ml_test_evaluation_configuration() { 781 782 $cases = array( 783 'bad' => array( 784 'modelquality' => 'random', 785 'ncourses' => 50, 786 'expectedresults' => array( 787 '\core\analytics\time_splitting\single_range' => \core_analytics\model::LOW_SCORE, 788 '\core\analytics\time_splitting\quarters' => \core_analytics\model::LOW_SCORE, 789 ) 790 ), 791 'good' => array( 792 'modelquality' => 'perfect', 793 'ncourses' => 50, 794 'expectedresults' => array( 795 '\core\analytics\time_splitting\single_range' => \core_analytics\model::OK, 796 '\core\analytics\time_splitting\quarters' => \core_analytics\model::OK, 797 ) 798 ) 799 ); 800 return $this->add_prediction_processors($cases); 801 } 802 803 /** 804 * add_random_model 805 * 806 * @return \core_analytics\model 807 */ 808 protected function add_random_model() { 809 810 $target = \core_analytics\manager::get_target('test_target_shortname'); 811 $indicators = array('test_indicator_max', 'test_indicator_min', 'test_indicator_random'); 812 foreach ($indicators as $key => $indicator) { 813 $indicators[$key] = \core_analytics\manager::get_indicator($indicator); 814 } 815 816 $model = \core_analytics\model::create($target, $indicators); 817 818 // To load db defaults as well. 819 return new \core_analytics\model($model->get_id()); 820 } 821 822 /** 823 * add_perfect_model 824 * 825 * @param string $targetclass 826 * @return \core_analytics\model 827 */ 828 protected function add_perfect_model($targetclass = 'test_target_shortname') { 829 $target = \core_analytics\manager::get_target($targetclass); 830 $indicators = array('test_indicator_max', 'test_indicator_min', 'test_indicator_fullname'); 831 foreach ($indicators as $key => $indicator) { 832 $indicators[$key] = \core_analytics\manager::get_indicator($indicator); 833 } 834 835 $model = \core_analytics\model::create($target, $indicators); 836 837 // To load db defaults as well. 838 return new \core_analytics\model($model->get_id()); 839 } 840 841 /** 842 * Generates model for multi-classification 843 * 844 * @param string $targetclass 845 * @return \core_analytics\model 846 * @throws coding_exception 847 * @throws moodle_exception 848 */ 849 public function add_multiclass_model($targetclass = 'test_target_shortname_multiclass') { 850 $target = \core_analytics\manager::get_target($targetclass); 851 $indicators = array('test_indicator_fullname', 'test_indicator_multiclass'); 852 foreach ($indicators as $key => $indicator) { 853 $indicators[$key] = \core_analytics\manager::get_indicator($indicator); 854 } 855 856 $model = \core_analytics\model::create($target, $indicators); 857 return new \core_analytics\model($model->get_id()); 858 } 859 860 /** 861 * Generates $ncourses courses 862 * 863 * @param int $ncourses The number of courses to be generated. 864 * @param array $params Course params 865 * @return null 866 */ 867 protected function generate_courses($ncourses, array $params = []) { 868 869 $params = $params + [ 870 'startdate' => mktime(0, 0, 0, 10, 24, 2015), 871 'enddate' => mktime(0, 0, 0, 2, 24, 2016), 872 ]; 873 874 for ($i = 0; $i < $ncourses; $i++) { 875 $name = 'a' . random_string(10); 876 $courseparams = array('shortname' => $name, 'fullname' => $name) + $params; 877 $this->getDataGenerator()->create_course($courseparams); 878 } 879 for ($i = 0; $i < $ncourses; $i++) { 880 $name = 'b' . random_string(10); 881 $courseparams = array('shortname' => $name, 'fullname' => $name) + $params; 882 $this->getDataGenerator()->create_course($courseparams); 883 } 884 } 885 886 /** 887 * Generates ncourses for multi-classification 888 * 889 * @param int $ncourses The number of courses to be generated. 890 * @param array $params Course params 891 * @return null 892 */ 893 protected function generate_courses_multiclass($ncourses, array $params = []) { 894 895 $params = $params + [ 896 'startdate' => mktime(0, 0, 0, 10, 24, 2015), 897 'enddate' => mktime(0, 0, 0, 2, 24, 2016), 898 ]; 899 900 for ($i = 0; $i < $ncourses; $i++) { 901 $name = 'a' . random_string(10); 902 $courseparams = array('shortname' => $name, 'fullname' => $name) + $params; 903 $this->getDataGenerator()->create_course($courseparams); 904 } 905 for ($i = 0; $i < $ncourses; $i++) { 906 $name = 'b' . random_string(10); 907 $courseparams = array('shortname' => $name, 'fullname' => $name) + $params; 908 $this->getDataGenerator()->create_course($courseparams); 909 } 910 for ($i = 0; $i < $ncourses; $i++) { 911 $name = 'c' . random_string(10); 912 $courseparams = array('shortname' => $name, 'fullname' => $name) + $params; 913 $this->getDataGenerator()->create_course($courseparams); 914 } 915 } 916 917 /** 918 * Forces some configuration values. 919 * 920 * @param array $forcedconfig 921 */ 922 protected function set_forced_config($forcedconfig) { 923 \core_analytics\manager::reset_prediction_processors(); 924 925 if (empty($forcedconfig)) { 926 return; 927 } 928 foreach ($forcedconfig as $pluginname => $pluginconfig) { 929 foreach ($pluginconfig as $name => $value) { 930 set_config($name, $value, $pluginname); 931 } 932 } 933 } 934 935 /** 936 * Is the provided processor ready using the current configuration in the site? 937 * 938 * @param string $predictionsprocessorclass 939 * @return \core_analytics\predictor 940 */ 941 protected function is_predictions_processor_ready(string $predictionsprocessorclass) { 942 // We repeat the test for all prediction processors. 943 $predictionsprocessor = \core_analytics\manager::get_predictions_processor($predictionsprocessorclass, false); 944 $ready = $predictionsprocessor->is_ready(); 945 if ($ready !== true) { 946 $this->markTestSkipped('Skipping ' . $predictionsprocessorclass . ' as the predictor is not ready: ' . $ready); 947 } 948 949 return $predictionsprocessor; 950 } 951 952 /** 953 * add_prediction_processors 954 * 955 * @param array $cases 956 * @return array 957 */ 958 protected function add_prediction_processors($cases) { 959 960 $return = array(); 961 962 if (defined('TEST_MLBACKEND_PYTHON_HOST') && defined('TEST_MLBACKEND_PYTHON_PORT') 963 && defined('TEST_MLBACKEND_PYTHON_USERNAME') && defined('TEST_MLBACKEND_PYTHON_USERNAME')) { 964 $testpythonserver = true; 965 } 966 967 // We need to test all prediction processors in the system. 968 $predictionprocessors = \core_analytics\manager::get_all_prediction_processors(); 969 foreach ($predictionprocessors as $classfullname => $predictionsprocessor) { 970 foreach ($cases as $key => $case) { 971 972 if (!$predictionsprocessor instanceof \mlbackend_python\processor || empty($testpythonserver)) { 973 $extraparams = ['predictionsprocessor' => $classfullname, 'forcedconfig' => null]; 974 $return[$key . '-' . $classfullname] = $case + $extraparams; 975 } else { 976 977 // We want the configuration to be forced during the test as things like importing models create new 978 // instances of ML backend processors during the process. 979 $forcedconfig = ['mlbackend_python' => ['useserver' => true, 'host' => TEST_MLBACKEND_PYTHON_HOST, 980 'port' => TEST_MLBACKEND_PYTHON_PORT, 'secure' => false, 'username' => TEST_MLBACKEND_PYTHON_USERNAME, 981 'password' => TEST_MLBACKEND_PYTHON_PASSWORD]]; 982 $casekey = $key . '-' . $classfullname . '-server'; 983 $return[$casekey] = $case + ['predictionsprocessor' => $classfullname, 'forcedconfig' => $forcedconfig]; 984 } 985 } 986 } 987 988 return $return; 989 } 990 }
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