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Long Term Support Release
- Bug fixes for general core bugs in 4.1.x will end 13 November 2023 (12 months).
- Bug fixes for security issues in 4.1.x will end 10 November 2025 (36 months).
- PHP version: minimum PHP 7.4.0 Note: minimum PHP version has increased since Moodle 4.0. PHP 8.0.x is supported too.
/analytics/classes/ -> analysis.php (source)
Runs an analysis of the site.
| Copyright: | 2019 David Monllao {@link http://www.davidmonllao.com} |
| License: | http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later |
| File Size: | 959 lines (38 kb) |
| Included or required: | 0 times |
| Referenced: | 0 times |
| Includes or requires: | 0 files |
Defines 1 class
analysis:: (21 methods):
__construct()
run()
get_processed_analysables()
process_analysable()
process_time_splitting()
calculate()
calculate_indicators()
fill_dataset()
update_analysable_analysed_time()
fill_firstanalyses_cache()
add_context_metadata()
get_headers()
filter_out_train_samples()
filter_out_prediction_samples_and_ranges()
get_predict_samples_record()
save_train_samples()
save_prediction_samples()
init_analysable_analysis()
clean_time_splitting_id()
finish_analysable_analysis()
get_insert_batch_size()
Runs an analysis of the site.
| __construct(\core_analytics\local\analyser\base $analyser, bool $includetarget,\core_analytics\local\analysis\result $result) X-Ref |
| Constructor. param: \core_analytics\local\analyser\base $analyser param: bool $includetarget Whether to calculate the target or not. param: \core_analytics\local\analysis\result $result |
| run(array $contexts = []) X-Ref |
| Runs the analysis. param: \context[] $contexts Restrict the analysis to these contexts. No context restrictions if null. return: null |
| get_processed_analysables() X-Ref |
| Get analysables that have been already processed. return: \stdClass[] |
| process_analysable(\core_analytics\analysable $analysable) X-Ref |
| Processes an analysable This method returns the general analysable status, an array of files by time splitting method and an error message if there is any problem. param: \core_analytics\analysable $analysable return: \stdClass[] Results objects by time splitting method |
| process_time_splitting(\core_analytics\local\time_splitting\base $timesplitting,\core_analytics\analysable $analysable, \core_analytics\local\target\base $target) X-Ref |
| Processes the analysable samples using the provided time splitting method. param: \core_analytics\local\time_splitting\base $timesplitting param: \core_analytics\analysable $analysable param: \core_analytics\local\target\base $target return: \stdClass Results object. |
| calculate(\core_analytics\local\time_splitting\base $timesplitting, array &$sampleids,array $ranges, \core_analytics\local\target\base $target) X-Ref |
| Calculates indicators and targets. param: \core_analytics\local\time_splitting\base $timesplitting param: array $sampleids param: array $ranges param: \core_analytics\local\target\base $target return: array|null |
| calculate_indicators(\core_analytics\local\time_splitting\base $timesplitting, array $sampleids,array $ranges) X-Ref |
| Calculates indicators. param: \core_analytics\local\time_splitting\base $timesplitting param: array $sampleids param: array $ranges return: array |
| fill_dataset(\core_analytics\local\time_splitting\base $timesplitting,array &$dataset, ?array $calculatedtarget = null) X-Ref |
| Adds time range indicators and the target to each sample. This will identify the sample as belonging to a specific range. param: \core_analytics\local\time_splitting\base $timesplitting param: array $dataset param: array|null $calculatedtarget return: null |
| update_analysable_analysed_time(array $processedanalysables, int $analysableid) X-Ref |
| Updates the analysable analysis time. param: array $processedanalysables param: int $analysableid return: null |
| fill_firstanalyses_cache(int $modelid, ?int $analysableid = null) X-Ref |
| Fills a cache containing the first time each analysable in the provided model was analysed. param: int $modelid param: int|null $analysableid return: null |
| add_context_metadata(\core_analytics\local\time_splitting\base $timesplitting, array &$dataset,\core_analytics\local\target\base $target) X-Ref |
| Adds dataset context info. The final dataset document will look like this: ---------------------------------------------------- metadata1,metadata2,metadata3,..... value1, value2, value3,..... header1,header2,header3,header4,..... stud1value1,stud1value2,stud1value3,stud1value4,..... stud2value1,stud2value2,stud2value3,stud2value4,..... ..... ---------------------------------------------------- param: \core_analytics\local\time_splitting\base $timesplitting param: array $dataset param: \core_analytics\local\target\base $target return: null |
| get_headers(\core_analytics\local\time_splitting\base $timesplitting,\core_analytics\local\target\base $target) X-Ref |
| Returns the headers for the csv file based on the indicators and the target. param: \core_analytics\local\time_splitting\base $timesplitting param: \core_analytics\local\target\base $target return: string[] |
| filter_out_train_samples(array &$sampleids, \core_analytics\local\time_splitting\base $timesplitting) X-Ref |
| Filters out samples that have already been used for training. param: int[] $sampleids param: \core_analytics\local\time_splitting\base $timesplitting return: null |
| filter_out_prediction_samples_and_ranges(array &$sampleids, array &$ranges,\core_analytics\local\time_splitting\base $timesplitting) X-Ref |
| Filters out samples that have already been used for prediction. param: int[] $sampleids param: array $ranges param: \core_analytics\local\time_splitting\base $timesplitting return: \stdClass|null The analytics_predict_samples record or null |
| get_predict_samples_record(\core_analytics\local\time_splitting\base $timesplitting, int $rangeindex) X-Ref |
| Returns a predict samples record. param: \core_analytics\local\time_splitting\base $timesplitting param: int $rangeindex return: \stdClass|false |
| save_train_samples(array $sampleids, \core_analytics\local\time_splitting\base $timesplitting) X-Ref |
| Saves samples that have just been used for training. param: int[] $sampleids param: \core_analytics\local\time_splitting\base $timesplitting return: null |
| save_prediction_samples(array $sampleids, array $ranges,\core_analytics\local\time_splitting\base $timesplitting, ?\stdClass $predictsamplesrecord = null) X-Ref |
| Saves samples that have just been used for prediction. param: int[] $sampleids param: array $ranges param: \core_analytics\local\time_splitting\base $timesplitting param: \stdClass|null $predictsamplesrecord The existing record or null if there is no record yet. return: null |
| init_analysable_analysis(string $timesplittingid, int $analysableid) X-Ref |
| Flags the analysable element as in-analysis and stores a lock for it. param: string $timesplittingid param: int $analysableid return: bool Success or not |
| clean_time_splitting_id($timesplittingid) X-Ref |
| Remove all possibly problematic chars from the time splitting method id (id = its full class name). param: string $timesplittingid return: string |
| finish_analysable_analysis() X-Ref |
| Mark the currently analysed analysable+timesplitting as analysed. return: null |
| get_insert_batch_size() X-Ref |
| Returns the batch size used for insert_records. This method tries to find the best batch size without getting into dml internals. Maximum 1000 records to save memory. return: int |
