Add RandomForest exception tests (#251)

src/Classification/DecisionTree/DecisionTreeLeaf.php

@@ -29,12 +29,12 @@ class DecisionTreeLeaf
     public $columnIndex;
 
     /**
-     * @var ?DecisionTreeLeaf
+     * @var DecisionTreeLeaf|null
      */
     public $leftLeaf;
 
     /**
-     * @var ?DecisionTreeLeaf
+     * @var DecisionTreeLeaf|null
      */
     public $rightLeaf;
 

src/Classification/Ensemble/RandomForest.php

@@ -4,9 +4,9 @@ declare(strict_types=1);
 
 namespace Phpml\Classification\Ensemble;
 
-use Exception;
 use Phpml\Classification\Classifier;
 use Phpml\Classification\DecisionTree;
+use Phpml\Exception\InvalidArgumentException;
 
 class RandomForest extends Bagging
 {
@@ -41,20 +41,20 @@ class RandomForest extends Bagging
      * Default value for the ratio is 'log' which results in log(numFeatures, 2) + 1
      * features to be taken into consideration while selecting subspace of features
      *
-     * @param mixed $ratio string or float should be given
-     *
-     * @return $this
-     *
-     * @throws \Exception
+     * @param string|float $ratio
      */
-    public function setFeatureSubsetRatio($ratio)
+    public function setFeatureSubsetRatio($ratio): self
     {
+        if (!is_string($ratio) && !is_float($ratio)) {
+            throw new InvalidArgumentException('Feature subset ratio must be a string or a float');
+        }
+
         if (is_float($ratio) && ($ratio < 0.1 || $ratio > 1.0)) {
-            throw new Exception('When a float given, feature subset ratio should be between 0.1 and 1.0');
+            throw new InvalidArgumentException('When a float is given, feature subset ratio should be between 0.1 and 1.0');
         }
 
         if (is_string($ratio) && $ratio != 'sqrt' && $ratio != 'log') {
-            throw new Exception("When a string given, feature subset ratio can only be 'sqrt' or 'log' ");
+            throw new InvalidArgumentException("When a string is given, feature subset ratio can only be 'sqrt' or 'log'");
         }
 
         $this->featureSubsetRatio = $ratio;
@@ -66,13 +66,11 @@ class RandomForest extends Bagging
      * RandomForest algorithm is usable *only* with DecisionTree
      *
      * @return $this
-     *
-     * @throws \Exception
      */
     public function setClassifer(string $classifier, array $classifierOptions = [])
     {
         if ($classifier != DecisionTree::class) {
-            throw new Exception('RandomForest can only use DecisionTree as base classifier');
+            throw new InvalidArgumentException('RandomForest can only use DecisionTree as base classifier');
         }
 
         return parent::setClassifer($classifier, $classifierOptions);
@@ -133,7 +131,7 @@ class RandomForest extends Bagging
     {
         if (is_float($this->featureSubsetRatio)) {
             $featureCount = (int) ($this->featureSubsetRatio * $this->featureCount);
-        } elseif ($this->featureCount == 'sqrt') {
+        } elseif ($this->featureSubsetRatio == 'sqrt') {
             $featureCount = (int) sqrt($this->featureCount) + 1;
         } else {
             $featureCount = (int) log($this->featureCount, 2) + 1;

tests/Classification/Ensemble/RandomForestTest.php

@@ -7,19 +7,44 @@ namespace Phpml\Tests\Classification\Ensemble;
 use Phpml\Classification\DecisionTree;
 use Phpml\Classification\Ensemble\RandomForest;
 use Phpml\Classification\NaiveBayes;
-use Throwable;
+use Phpml\Exception\InvalidArgumentException;
 
 class RandomForestTest extends BaggingTest
 {
-    public function testOtherBaseClassifier(): void
+    public function testThrowExceptionWithInvalidClassifier(): void
     {
-        try {
-            $classifier = new RandomForest();
-            $classifier->setClassifer(NaiveBayes::class);
-            $this->assertEquals(0, 1);
-        } catch (Throwable $ex) {
-            $this->assertEquals(1, 1);
-        }
+        $this->expectException(InvalidArgumentException::class);
+        $this->expectExceptionMessage('RandomForest can only use DecisionTree as base classifier');
+
+        $classifier = new RandomForest();
+        $classifier->setClassifer(NaiveBayes::class);
+    }
+
+    public function testThrowExceptionWithInvalidFeatureSubsetRatioType(): void
+    {
+        $this->expectException(InvalidArgumentException::class);
+        $this->expectExceptionMessage('Feature subset ratio must be a string or a float');
+
+        $classifier = new RandomForest();
+        $classifier->setFeatureSubsetRatio(1);
+    }
+
+    public function testThrowExceptionWithInvalidFeatureSubsetRatioFloat(): void
+    {
+        $this->expectException(InvalidArgumentException::class);
+        $this->expectExceptionMessage('When a float is given, feature subset ratio should be between 0.1 and 1.0');
+
+        $classifier = new RandomForest();
+        $classifier->setFeatureSubsetRatio(1.1);
+    }
+
+    public function testThrowExceptionWithInvalidFeatureSubsetRatioString(): void
+    {
+        $this->expectException(InvalidArgumentException::class);
+        $this->expectExceptionMessage("When a string is given, feature subset ratio can only be 'sqrt' or 'log'");
+
+        $classifier = new RandomForest();
+        $classifier->setFeatureSubsetRatio('pow');
     }
 
     protected function getClassifier($numBaseClassifiers = 50)