Merge remote-tracking branch 'rubixml/3.0' into tools

.github/workflows/ci.yml

@@ -20,7 +20,7 @@ jobs:
  with:
  php-version: ${{ matrix.php-versions }}
  tools: composer, pecl
- extensions: svm, mbstring, gd, fileinfo
+ extensions: svm, mbstring, gd, fileinfo, swoole
  ini-values: memory_limit=-1
 
  - name: Validate composer.json

.gitignore

@@ -7,6 +7,7 @@ Thumbs.db
 .DS_Store
 debug.log
 /test.png
+pyvenv.cfg
 .venv
 .idea
 .vscode

CHANGELOG.md

@@ -12,6 +12,9 @@
 - 2.5.0
  - Added Vantage Point Spatial tree
  - Blob Generator can now `simulate()` a Dataset object
+ - Added Wrapper interface
+ - Added Swoole Backend
+ - Plus Plus added check for min number of sample seeds
 
 - 2.4.1
  - Sentence Tokenizer fix Arabic and Farsi language support

benchmarks/Classifiers/OneVsRestBench.php

@@ -2,18 +2,22 @@
 
 namespace Rubix\ML\Benchmarks\Classifiers;
 
+use Rubix\ML\Backends\Backend;
 use Rubix\ML\Classifiers\OneVsRest;
 use Rubix\ML\Datasets\Generators\Blob;
 use Rubix\ML\Classifiers\LogisticRegression;
 use Rubix\ML\NeuralNet\Optimizers\Stochastic;
 use Rubix\ML\Datasets\Generators\Agglomerate;
+use Rubix\ML\Tests\DataProvider\BackendProviderTrait;
 
 /**
  * @Groups({"Classifiers"})
  * @BeforeMethods({"setUp"})
  */
 class OneVsRestBench
 {
+ use BackendProviderTrait;
+
  protected const TRAINING_SIZE = 10000;
 
  protected const TESTING_SIZE = 10000;
@@ -45,16 +49,20 @@
 
  $this->testing = $generator->generate(self::TESTING_SIZE);
 
  $this->estimator = new OneVsRest(new LogisticRegression(64, new Stochastic(0.001)));
  }
 
  /**
  * @Subject
  * @Iterations(5)
  * @OutputTimeUnit("seconds", precision=3)
+ * @ParamProviders("provideBackends")
+ * @param array{ backend: Backend } $params
  */
- public function trainPredict() : void
+ public function trainPredict(array $params) : void
  {
+ $this->estimator->setBackend($params['backend']);
+
  $this->estimator->train($this->training);
 
  $this->estimator->predict($this->testing);

benchmarks/Classifiers/RandomForestBench.php

@@ -2,17 +2,21 @@
 
 namespace Rubix\ML\Benchmarks\Classifiers;
 
+use Rubix\ML\Backends\Backend;
 use Rubix\ML\Classifiers\RandomForest;
 use Rubix\ML\Datasets\Generators\Blob;
 use Rubix\ML\Classifiers\ClassificationTree;
 use Rubix\ML\Datasets\Generators\Agglomerate;
+use Rubix\ML\Tests\DataProvider\BackendProviderTrait;
 use Rubix\ML\Transformers\IntervalDiscretizer;
 
 /**
  * @Groups({"Classifiers"})
  */
 class RandomForestBench
 {
+ use BackendProviderTrait;
+
  protected const TRAINING_SIZE = 10000;
 
  protected const TESTING_SIZE = 10000;
@@ -70,9 +74,13 @@ public function setUpCategorical() : void
  * @Iterations(5)
  * @BeforeMethods({"setUpContinuous"})
  * @OutputTimeUnit("seconds", precision=3)
+ * @ParamProviders("provideBackends")
+ * @param array{ backend: Backend } $params
  */
- public function continuous() : void
+ public function continuous(array $params) : void
  {
+ $this->estimator->setBackend($params['backend']);
+
  $this->estimator->train($this->training);
 
  $this->estimator->predict($this->testing);
@@ -83,9 +91,13 @@ public function continuous() : void
  * @Iterations(5)
  * @BeforeMethods({"setUpCategorical"})
  * @OutputTimeUnit("seconds", precision=3)
+ * @ParamProviders("provideBackends")
+ * @param array{ backend: Backend } $params
  */
- public function categorical() : void
+ public function categorical(array $params) : void
  {
+ $this->estimator->setBackend($params['backend']);
+
  $this->estimator->train($this->training);
 
  $this->estimator->predict($this->testing);

composer.json

@@ -44,7 +44,8 @@
  "wamania/php-stemmer": "^3.0"
  },
  "require-dev": {
- "phpunit/phpunit": "^9.0"
+ "phpunit/phpunit": "^9.0",
+ "swoole/ide-helper": "^5.1"
  },
  "suggest": {
  "ext-tensor": "For fast Matrix/Vector computing",
@@ -104,7 +105,11 @@
  },
  "config": {
  "preferred-install": "dist",
- "sort-packages": true
+ "sort-packages": true,
+ "process-timeout": 3000,
+ "allow-plugins": {
+ "phpstan/extension-installer": true
+ }
  },
  "funding": [
  {

docs/cross-validation/metrics/rand-index.md

@@ -7,7 +7,7 @@ $$
 {\displaystyle ARI = {\frac {\left.\sum _{ij}{\binom {n_{ij}}{2}}-\left[\sum _{i}{\binom {a_{i}}{2}}\sum _{j}{\binom {b_{j}}{2}}\right]\right/{\binom {n}{2}}}{\left.{\frac {1}{2}}\left[\sum _{i}{\binom {a_{i}}{2}}+\sum _{j}{\binom {b_{j}}{2}}\right]-\left[\sum _{i}{\binom {a_{i}}{2}}\sum _{j}{\binom {b_{j}}{2}}\right]\right/{\binom {n}{2}}}}}
 $$
 
-**Estimator Compatibility:** Regressor
+**Estimator Compatibility:** Clusterer
 
 **Score Range:** -1 to 1
 

phpstan.neon

@@ -6,3 +6,4 @@ parameters:
  - 'benchmarks'
  excludePaths:
  - src/Backends/Amp.php
+ - src/Backends/Swoole.php

phpunit.xml

@@ -1,5 +1,18 @@
 <?xml version="1.0" encoding="UTF-8"?>
-<phpunit xmlns:xsi="https://www.w3.org/2001/XMLSchema-instance" backupGlobals="false" backupStaticAttributes="false" bootstrap="vendor/autoload.php" colors="true" convertErrorsToExceptions="true" convertNoticesToExceptions="true" convertWarningsToExceptions="true" forceCoversAnnotation="true" processIsolation="false" stopOnFailure="false" xsi:noNamespaceSchemaLocation="https://schema.phpunit.de/9.3/phpunit.xsd">
+<phpunit
+ xmlns:xsi="https://www.w3.org/2001/XMLSchema-instance"
+ backupGlobals="false"
+ backupStaticAttributes="false"
+ bootstrap="vendor/autoload.php"
+ colors="true"
+ convertErrorsToExceptions="true"
+ convertNoticesToExceptions="true"
+ convertWarningsToExceptions="true"
+ forceCoversAnnotation="true"
+ processIsolation="true"
+ stopOnFailure="false"
+ xsi:noNamespaceSchemaLocation="https://schema.phpunit.de/9.3/phpunit.xsd"
+>
  <coverage processUncoveredFiles="true">
  <include>
  <directory suffix=".php">src</directory>

src/AnomalyDetectors/LocalOutlierFactor.php

@@ -67,7 +67,7 @@ class LocalOutlierFactor implements Estimator, Learner, Scoring, Persistable
  *
  * @var Spatial
  */
- protected \Rubix\ML\Graph\Trees\Spatial $tree;
+ protected Spatial $tree;
 
  /**
  * The precomputed k distances between each training sample and its k'th nearest neighbor.

src/AnomalyDetectors/Loda.php

@@ -100,7 +100,7 @@ class Loda implements Estimator, Learner, Online, Scoring, Persistable
  *
  * @var \Tensor\Matrix|null
  */
- protected ?\Tensor\Matrix $r = null;
+ protected ?Matrix $r = null;
 
  /**
  * The edges and bin counts of each histogram.

src/AnomalyDetectors/OneClassSVM.php

@@ -44,7 +44,7 @@ class OneClassSVM implements Estimator, Learner
  *
  * @var svm
  */
- protected \svm $svm;
+ protected svm $svm;
 
  /**
  * The hyper-parameters of the model.
@@ -58,7 +58,7 @@ class OneClassSVM implements Estimator, Learner
  *
  * @var \svmmodel|null
  */
- protected ?\svmmodel $model = null;
+ protected ?svmmodel $model = null;
 
  /**
  * @param float $nu