[cs] remove more unused comments (#146)

* [cs] remove more unused comments * [cs] remove unused array phpdocs * [cs] remove empty lines in docs * [cs] space-proof useless docs * [cs] remove empty @param lines * [cs] remove references arrays
baudryj · Nov 13, 2017 · d85bfed · d85bfed
1 parent f4650c6
commit d85bfed
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diff --git a/src/Phpml/Classification/DecisionTree.php b/src/Phpml/Classification/DecisionTree.php
@@ -72,10 +72,6 @@ public function __construct(int $maxDepth = 10)
         $this->maxDepth = $maxDepth;
     }
 
-    /**
-     * @param array $samples
-     * @param array $targets
-     */
     public function train(array $samples, array $targets)
     {
         $this->samples = array_merge($this->samples, $samples);
@@ -104,11 +100,6 @@ public function train(array $samples, array $targets)
         }
     }
 
-    /**
-     * @param array $samples
-     *
-     * @return array
-     */
     public static function getColumnTypes(array $samples) : array
     {
         $types = [];
@@ -122,10 +113,6 @@ public static function getColumnTypes(array $samples) : array
         return $types;
     }
 
-    /**
-     * @param array $records
-     * @param int   $depth
-     */
     protected function getSplitLeaf(array $records, int $depth = 0) : DecisionTreeLeaf
     {
         $split = $this->getBestSplit($records);
@@ -239,8 +226,6 @@ protected function getBestSplit(array $records) : DecisionTreeLeaf
      *
      * If any of above methods were not called beforehand, then all features
      * are returned by default.
-     *
-     * @return array
      */
     protected function getSelectedFeatures() : array
     {
@@ -296,11 +281,6 @@ public function getGiniIndex($baseValue, array $colValues, array $targets) : flo
         return array_sum($giniParts) / count($colValues);
     }
 
-    /**
-     * @param array $samples
-     *
-     * @return array
-     */
     protected function preprocess(array $samples) : array
     {
         // Detect and convert continuous data column values into
@@ -325,9 +305,6 @@ protected function preprocess(array $samples) : array
         return array_map(null, ...$columns);
     }
 
-    /**
-     * @param array $columnValues
-     */
     protected static function isCategoricalColumn(array $columnValues) : bool
     {
         $count = count($columnValues);

diff --git a/src/Phpml/Classification/Linear/Adaline.php b/src/Phpml/Classification/Linear/Adaline.php
@@ -52,7 +52,6 @@ public function __construct(
     /**
      * Adapts the weights with respect to given samples and targets
      * by use of gradient descent learning rule
-     * @param array $targets
      */
     protected function runTraining(array $samples, array $targets)
     {

diff --git a/src/Phpml/Classification/Linear/LogisticRegression.php b/src/Phpml/Classification/Linear/LogisticRegression.php
@@ -138,9 +138,6 @@ protected function runTraining(array $samples, array $targets)
 
     /**
      * Executes Conjugate Gradient method to optimize the weights of the LogReg model
-     *
-     * @param array    $samples
-     * @param array    $targets
      */
     protected function runConjugateGradient(array $samples, array $targets, \Closure $gradientFunc)
     {

diff --git a/src/Phpml/Classification/WeightedClassifier.php b/src/Phpml/Classification/WeightedClassifier.php
@@ -13,8 +13,6 @@ abstract class WeightedClassifier implements Classifier
 
     /**
      * Sets the array including a weight for each sample
-     *
-     * @param array $weights
      */
     public function setSampleWeights(array $weights)
     {

diff --git a/src/Phpml/Dataset/ArrayDataset.php b/src/Phpml/Dataset/ArrayDataset.php
@@ -19,9 +19,6 @@ class ArrayDataset implements Dataset
     protected $targets = [];
 
     /**
-     * @param array $samples
-     * @param array $targets
-     *
      * @throws InvalidArgumentException
      */
     public function __construct(array $samples, array $targets)
@@ -34,17 +31,11 @@ public function __construct(array $samples, array $targets)
         $this->targets = $targets;
     }
 
-    /**
-     * @return array
-     */
     public function getSamples() : array
     {
         return $this->samples;
     }
 
-    /**
-     * @return array
-     */
     public function getTargets() : array
     {
         return $this->targets;

diff --git a/src/Phpml/DimensionReduction/EigenTransformerBase.php b/src/Phpml/DimensionReduction/EigenTransformerBase.php
@@ -47,8 +47,6 @@ abstract class EigenTransformerBase
      * Calculates eigenValues and eigenVectors of the given matrix. Returns
      * top eigenVectors along with the largest eigenValues. The total explained variance
      * of these eigenVectors will be no less than desired $totalVariance value
-     *
-     * @param array $matrix
      */
     protected function eigenDecomposition(array $matrix)
     {
@@ -85,10 +83,6 @@ protected function eigenDecomposition(array $matrix)
 
     /**
      * Returns the reduced data
-     *
-     * @param array $data
-     *
-     * @return array
      */
     protected function reduce(array $data) : array
     {

diff --git a/src/Phpml/FeatureExtraction/TfIdfTransformer.php b/src/Phpml/FeatureExtraction/TfIdfTransformer.php
@@ -13,19 +13,13 @@ class TfIdfTransformer implements Transformer
      */
     private $idf;
 
-    /**
-     * @param array $samples
-     */
     public function __construct(array $samples = null)
     {
         if ($samples) {
             $this->fit($samples);
         }
     }
 
-    /**
-     * @param array $samples
-     */
     public function fit(array $samples)
     {
         $this->countTokensFrequency($samples);
@@ -36,9 +30,6 @@ public function fit(array $samples)
         }
     }
 
-    /**
-     * @param array $samples
-     */
     public function transform(array &$samples)
     {
         foreach ($samples as &$sample) {
@@ -48,9 +39,6 @@ public function transform(array &$samples)
         }
     }
 
-    /**
-     * @param array $samples
-     */
     private function countTokensFrequency(array $samples)
     {
         $this->idf = array_fill_keys(array_keys($samples[0]), 0);

diff --git a/src/Phpml/Helper/Optimizer/ConjugateGradient.php b/src/Phpml/Helper/Optimizer/ConjugateGradient.php
@@ -17,12 +17,6 @@
  */
 class ConjugateGradient extends GD
 {
-    /**
-     * @param array    $samples
-     * @param array    $targets
-     *
-     * @return array
-     */
     public function runOptimization(array $samples, array $targets, \Closure $gradientCb) : array
     {
         $this->samples = $samples;

diff --git a/src/Phpml/Math/LinearAlgebra/EigenvalueDecomposition.php b/src/Phpml/Math/LinearAlgebra/EigenvalueDecomposition.php
@@ -2,7 +2,6 @@
 
 declare(strict_types=1);
 /**
- *
  *	Class to obtain eigenvalues and eigenvectors of a real matrix.
  *
  *	If A is symmetric, then A = V*D*V' where the eigenvalue matrix D
@@ -88,8 +87,6 @@ class EigenvalueDecomposition
 
     /**
      *	Constructor: Check for symmetry, then construct the eigenvalue decomposition
-     *
-     * @param array $Arg
      */
     public function __construct(array $Arg)
     {

diff --git a/src/Phpml/Math/Product.php b/src/Phpml/Math/Product.php
@@ -7,9 +7,6 @@
 class Product
 {
     /**
-     * @param array $a
-     * @param array $b
-     *
      * @return mixed
      */
     public static function scalar(array $a, array $b)

diff --git a/src/Phpml/Math/Statistic/Mean.php b/src/Phpml/Math/Statistic/Mean.php
@@ -9,8 +9,6 @@
 class Mean
 {
     /**
-     * @param array $numbers
-     *
      * @throws InvalidArgumentException
      */
     public static function arithmetic(array $numbers) : float
@@ -21,8 +19,6 @@ public static function arithmetic(array $numbers) : float
     }
 
     /**
-     * @param array $numbers
-     *
      * @return float|mixed
      *
      * @throws InvalidArgumentException
@@ -44,8 +40,6 @@ public static function median(array $numbers)
     }
 
     /**
-     * @param array $numbers
-     *
      * @return mixed
      *
      * @throws InvalidArgumentException
@@ -60,8 +54,6 @@ public static function mode(array $numbers)
     }
 
     /**
-     * @param array $array
-     *
      * @throws InvalidArgumentException
      */
     private static function checkArrayLength(array $array)

diff --git a/src/Phpml/Metric/Accuracy.php b/src/Phpml/Metric/Accuracy.php
@@ -9,10 +9,6 @@
 class Accuracy
 {
     /**
-     * @param array $actualLabels
-     * @param array $predictedLabels
-     * @param bool  $normalize
-     *
      * @return float|int
      *
      * @throws InvalidArgumentException

diff --git a/src/Phpml/Metric/ClassificationReport.php b/src/Phpml/Metric/ClassificationReport.php
@@ -130,12 +130,6 @@ private function computeF1Score(float $precision, float $recall) : float
         return 2.0 * (($precision * $recall) / $divider);
     }
 
-    /**
-     * @param array $actualLabels
-     * @param array $predictedLabels
-     *
-     * @return array
-     */
     private static function getLabelIndexedArray(array $actualLabels, array $predictedLabels) : array
     {
         $labels = array_values(array_unique(array_merge($actualLabels, $predictedLabels)));

diff --git a/src/Phpml/Metric/ConfusionMatrix.php b/src/Phpml/Metric/ConfusionMatrix.php
@@ -6,13 +6,6 @@
 
 class ConfusionMatrix
 {
-    /**
-     * @param array $actualLabels
-     * @param array $predictedLabels
-     * @param array $labels
-     *
-     * @return array
-     */
     public static function compute(array $actualLabels, array $predictedLabels, array $labels = null) : array
     {
         $labels = $labels ? array_flip($labels) : self::getUniqueLabels($actualLabels);
@@ -38,11 +31,6 @@ public static function compute(array $actualLabels, array $predictedLabels, arra
         return $matrix;
     }
 
-    /**
-     * @param array $labels
-     *
-     * @return array
-     */
     private static function generateMatrixWithZeros(array $labels) : array
     {
         $count = count($labels);
@@ -55,11 +43,6 @@ private static function generateMatrixWithZeros(array $labels) : array
         return $matrix;
     }
 
-    /**
-     * @param array $labels
-     *
-     * @return array
-     */
     private static function getUniqueLabels(array $labels) : array
     {
         $labels = array_values(array_unique($labels));

diff --git a/src/Phpml/NeuralNetwork/Network/LayeredNetwork.php b/src/Phpml/NeuralNetwork/Network/LayeredNetwork.php
@@ -39,9 +39,6 @@ public function getOutputLayer(): Layer
         return $this->layers[count($this->layers) - 1];
     }
 
-    /**
-     * @return array
-     */
     public function getOutput() : array
     {
         $result = [];

diff --git a/src/Phpml/NeuralNetwork/Node/Neuron/Synapse.php b/src/Phpml/NeuralNetwork/Node/Neuron/Synapse.php
@@ -19,7 +19,6 @@ class Synapse
     protected $node;
 
     /**
-     * @param Node       $node
      * @param float|null $weight
      */
     public function __construct(Node $node, float $weight = null)

diff --git a/src/Phpml/Pipeline.php b/src/Phpml/Pipeline.php
@@ -18,7 +18,6 @@ class Pipeline implements Estimator
 
     /**
      * @param array|Transformer[] $transformers
-     * @param Estimator           $estimator
      */
     public function __construct(array $transformers, Estimator $estimator)
     {
@@ -52,10 +51,6 @@ public function getEstimator(): Estimator
         return $this->estimator;
     }
 
-    /**
-     * @param array $samples
-     * @param array $targets
-     */
     public function train(array $samples, array $targets)
     {
         foreach ($this->transformers as $transformer) {
@@ -67,8 +62,6 @@ public function train(array $samples, array $targets)
     }
 
     /**
-     * @param array $samples
-     *
      * @return mixed
      */
     public function predict(array $samples)
@@ -78,9 +71,6 @@ public function predict(array $samples)
         return $this->estimator->predict($samples);
     }
 
-    /**
-     * @param array $samples
-     */
     private function transformSamples(array &$samples)
     {
         foreach ($this->transformers as $transformer) {
-Original file line number
+Diff line change
@@ Expand Up / @@ -13,8 +13,6 @@ abstract class WeightedClassifier implements Classifier @@
         /**
          * Sets the array including a weight for each sample
-         *
-         * @param array $weights
          */
         public function setSampleWeights(array $weights)
         {
@@ Expand Down @@