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  • Bug fixes for general core bugs in 4.2.x will end 22 April 2024 (12 months).
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Differences Between: [Versions 310 and 402] [Versions 311 and 402] [Versions 39 and 402]

Python predictions processor

Copyright: 2016 David Monllao {@link http://www.davidmonllao.com}
License: http://www.gnu.org/copyleft/gpl.html GNU GPL v3 or later
File Size: 747 lines (25 kb)
Included or required:0 times
Referenced: 0 times
Includes or requires: 0 files

Defines 1 class


Class: processor  - X-Ref

Python predictions processor.

__construct()   X-Ref
The constructor.


is_ready()   X-Ref
Is the plugin ready to be used?.

return: bool|string Returns true on success, a string detailing the error otherwise

is_webserver_ready()   X-Ref
Checks if the python package is available in the web server executing this script.

return: bool|string Returns true on success, a string detailing the error otherwise

is_python_server_ready()   X-Ref
Checks if the server can be accessed.

return: bool|string True or an error string.

clear_model($uniqueid, $modelversionoutputdir)   X-Ref
Delete the model version output directory.

param: string $uniqueid
param: string $modelversionoutputdir
return: null

delete_output_dir($modeloutputdir, $uniqueid)   X-Ref
Delete the model output directory.

param: string $modeloutputdir
param: string $uniqueid
return: null

train_classification($uniqueid, \stored_file $dataset, $outputdir)   X-Ref
Trains a machine learning algorithm with the provided dataset.

param: string $uniqueid
param: \stored_file $dataset
param: string $outputdir
return: \stdClass

classify($uniqueid, \stored_file $dataset, $outputdir)   X-Ref
Classifies the provided dataset samples.

param: string $uniqueid
param: \stored_file $dataset
param: string $outputdir
return: \stdClass

evaluate_classification($uniqueid, $maxdeviation, $niterations, \stored_file $dataset,$outputdir, $trainedmodeldir)   X-Ref
Evaluates this processor classification model using the provided supervised learning dataset.

param: string $uniqueid
param: float $maxdeviation
param: int $niterations
param: \stored_file $dataset
param: string $outputdir
param: string $trainedmodeldir
return: \stdClass

export(string $uniqueid, string $modeldir)   X-Ref
Exports the machine learning model.

param: string $uniqueid  The model unique id
param: string $modeldir  The directory that contains the trained model.
return: string            The path to the directory that contains the exported model.

import(string $uniqueid, string $modeldir, string $importdir)   X-Ref
Imports the provided machine learning model.

param: string $uniqueid The model unique id
param: string $modeldir  The directory that will contain the trained model.
param: string $importdir The directory that contains the files to import.
return: bool Success

train_regression($uniqueid, \stored_file $dataset, $outputdir)   X-Ref
Train this processor regression model using the provided supervised learning dataset.

param: string $uniqueid
param: \stored_file $dataset
param: string $outputdir
return: \stdClass

estimate($uniqueid, \stored_file $dataset, $outputdir)   X-Ref
Estimates linear values for the provided dataset samples.

param: string $uniqueid
param: \stored_file $dataset
param: mixed $outputdir
return: void

evaluate_regression($uniqueid, $maxdeviation, $niterations, \stored_file $dataset,$outputdir, $trainedmodeldir)   X-Ref
Evaluates this processor regression model using the provided supervised learning dataset.

param: string $uniqueid
param: float $maxdeviation
param: int $niterations
param: \stored_file $dataset
param: string $outputdir
param: string $trainedmodeldir
return: \stdClass

get_file_path(\stored_file $file)   X-Ref
Returns the path to the dataset file.

param: \stored_file $file
return: string

check_pip_package_version($actual, $required = self::REQUIRED_PIP_PACKAGE_VERSION)   X-Ref
Check that the given package version can be used and return the error status.

When evaluating the version, we assume the sematic versioning scheme as described at
https://semver.org/.

param: string $actual The actual Python package version
param: string $required The required version of the package
return: int -1 = actual version is too low, 1 = actual version too high, 0 = actual version is ok

exec_command(string $modulename, array $params, string $errorlangstr)   X-Ref
Executes the specified module.

param: string $modulename
param: array  $params
param: string $errorlangstr
return: array [0] is the result body and [1] the exit code.

format_error_info(\stdClass $resultobj)   X-Ref
Formats the errors and info in a single info string.

param: \stdClass $resultobj
return: \stdClass

get_server_url(?string $path = null)   X-Ref
Returns the url to the python ML server.

param: string|null $path
return: \moodle_url

server_request($url, string $method, array $requestparams, ?array $options = null)   X-Ref
Sends a request to the python ML server.

param: \moodle_url      $url            The requested url in the python ML server
param: string           $method         The curl method to use
param: array            $requestparams  Curl request params
param: array|null       $options        Curl request options
return: array                            [0] for the response body and [1] for the http code

add_extra_result_info(\stdClass $resultobj)   X-Ref
Adds extra information to results info.

param: \stdClass $resultobj
return: \stdClass

version_check_return($actual, $vercheck)   X-Ref
Returns the proper return value for the version checking.

param: string $actual   Actual moodlemlbackend version
param: int    $vercheck Version checking result
return: true|string      Returns true on success, a string detailing the error otherwise

hash_dir(string $dir)   X-Ref
Hashes the provided dir as a string.

param: string $dir Directory path
return: string Hash

zip_dir(string $dir)   X-Ref
Zips the provided directory.

param: string $dir Directory path
return: string The zip filename

server_error_str(int $httpstatuscode, string $responsebody)   X-Ref
Error string for httpcode !== 200

param: int       $httpstatuscode The HTTP status code
param: string    $responsebody   The body of the response