zeopix / MachineLearning

src/MachineLearning/Domain/Model/Value/VectorValue.php

Doc Comments +1 added lines, -1 removed lines

@@ -18,7 +18,7 @@
     }
 
     /**
-     * @return \float[]
+     * @return double[]
      */
     public function getValue()
     {

Spacing +2 added lines, -2 removed lines

@@ -31,8 +31,8 @@
     public function scalar(ValueInterface $value)
     {
         $result = 0;
-        for ($i=0; $i<count($this->value); $i++) {
-            $result += $this->value[$i]*$value->getValue()[$i];
+        for ($i = 0; $i < count($this->value); $i++) {
+            $result += $this->value[$i] * $value->getValue()[$i];
         }
         return $result;
     }

src/MachineLearning/Application/Algorithm/GradientDescendent.php

Spacing +1 added lines, -1 removed lines

@@ -71,7 +71,7 @@
         $coefficientVector[0] = 0;
         $incrementVector = array_fill(0, $features+1, 0);
 
-        while(!$convergence && !$divergence) {
+        while (!$convergence && !$divergence) {
             $coefficient = new VectorValue($coefficientVector);
 
             $costVector = array_fill(0, $features+1, 0);

src/MachineLearning/Application/Normalization/MeanScaleNormalization.php

Spacing +4 added lines, -4 removed lines

@@ -26,10 +26,10 @@ 
         //@todo we could validate if value and coefficient have same same dimension
         //should be done in a upper layer, in order not to execute it every row
 
-        for ($i=0; $i<count($rawValue); $i++) {
+        for ($i = 0; $i < count($rawValue); $i++) {
             $rawValue[$i] =
                 (
-                    $rawValue[$i] - $rawCoefficient[static::COEFFICIENT_AVERAGE][$i]
+                    $rawValue[$i]-$rawCoefficient[static::COEFFICIENT_AVERAGE][$i]
                 )
                 / $rawCoefficient[static::COEFFICIENT_RANGE][$i]
             ;
@@ -67,8 +67,8 @@ 
 
         foreach ($featuresAverage as $i => $featureAverage) {
             $featuresAverage[$i] = $featureAverage / count($data);
-            $featuresRange[$i] = ($featuresMaximumValue[$i] - $featuresMinimumValue[$i]) > 0 ?
-                ($featuresMaximumValue[$i] - $featuresMinimumValue[$i])
+            $featuresRange[$i] = ($featuresMaximumValue[$i]-$featuresMinimumValue[$i]) > 0 ?
+                ($featuresMaximumValue[$i]-$featuresMinimumValue[$i])
                 : 1;
         }
 

src/MachineLearning/Domain/Model/Value/ScalarValue.php

Spacing +1 added lines, -1 removed lines

@@ -30,7 +30,7 @@
      */
     public function scalar(ValueInterface $value)
     {
-        return $value->getValue()*$this->getValue();
+        return $value->getValue() * $this->getValue();
     }
 
 

src/MachineLearning/Domain/Hypothesis/Linear.php

Spacing +2 added lines, -2 removed lines

@@ -15,7 +15,7 @@ 
      */
     public function calculate(ValueInterface $coefficient, ValueInterface $variable)
     {
-        if (! $variable instanceof VectorValue) {
+        if (!$variable instanceof VectorValue) {
             throw new WrongVariableForHypothesisException();
         }
 
@@ -30,7 +30,7 @@ 
      */
     public function derivative(ValueInterface $coefficient, ValueInterface $variable, $partialVariable)
     {
-        if (! $variable instanceof VectorValue) {
+        if (!$variable instanceof VectorValue) {
             throw new WrongVariableForHypothesisException();
         }