Adding fmean

CHANGELOG.md

@@ -1,5 +1,8 @@
 # Changelog
 
+## 1.1.4 - 2025-04-25
+- Adding `fmean()` method for computing the arithmetic mean with float numbers.
+
 ## 1.1.3 - 2024-12-14
 - Adding `multiply()` method to scale NormalDist by a constant
 

README.md

@@ -93,6 +93,36 @@ $mean = Stat::mean([-1.0, 2.5, 3.25, 5.75]);
 // 2.625
 ```
 
+#### Stat::fmean( array $data, array|null $weights = null, int|null $precision = null )
+Return the arithmetic mean of the array `$data`, as a float, with optional weights and precision control.
+This function behaves like `mean()` but ensures a floating-point result and supports weighted datasets.
+If `$weights` is provided, it computes the weighted average. The result is rounded to a given decimal $precision.
+The result is rounded to `$precision` decimal places. 
+If `$precision` is null, no rounding is applied — this may lead to results with long or unexpected decimal expansions due to the nature of floating-point arithmetic in PHP. Using rounding helps ensure cleaner, more predictable output.
+
+```php 
+use HiFolks\Statistics\Stat;
+
+// Unweighted mean (same as mean but always float)
+$fmean = Stat::fmean([3.5, 4.0, 5.25]);
+// 4.25
+
+// Weighted mean
+$fmean = Stat::fmean([3.5, 4.0, 5.25], [1, 2, 1]);
+// 4.1875
+
+// Custom precision
+$fmean = Stat::fmean([3.5, 4.0, 5.25], null, 2);
+// 4.25
+
+$fmean = Stat::fmean([3.5, 4.0, 5.25], [1, 2, 1], 3);
+// 4.188
+
+```
+
+If the input is empty, or weights are invalid (e.g., length mismatch or sum is zero), an exception is thrown.
+Use this function when you need floating-point accuracy or to apply custom weighting and rounding to your average.
+
 #### Stat::geometricMean( array $data )
 The geometric mean indicates the central tendency or typical value of the data using the product of the values (as opposed to the arithmetic mean which uses their sum).
 

src/Stat.php

@@ -49,6 +49,60 @@ public static function mean(array $data): int|float|null
         return $sum / self::count($data);
     }
 
+    /**
+    * Calculate the float number arithmetic mean of a float numbers dataset with optional weights and precision.
+    *
+    * Supports both unweighted and weighted means. Automatically casts values to float.
+    * Returns `null` if the input data is empty.
+     *
+     * @param  array<float>  $data Array of floating numbers
+     * @param  null|array<float>  $weights Optional array of weights (same length as $data).
+     * @param null|int $precision Optional number of decimal places to round the result (default is null, no round() is applied).
+     * @return float|null arithmetic mean
+     *
+     * @throws InvalidDataInputException if the data is empty
+     */
+    public static function fmean(array $data, array|null $weights = null, int|null $precision = null): float|null
+    {
+        $sum = 0;
+        $count = self::count($data);
+        if ($count === 0) {
+            throw new InvalidDataInputException('The data must not be empty.');
+        }
+
+        // Unweighted mean
+        if ($weights === null) {
+            $sum = array_sum(array_map('floatval', $data));
+            $count = count($data);
+            if ($precision) {
+                return round($sum / $count, $precision);
+            }
+            return $sum / $count;
+        }
+
+        // Check lengths
+        if ($count !== count($weights)) {
+            throw new InvalidDataInputException('The data and weights must be the same length');
+        }
+
+        $weightedSum = 0.0;
+        $weightTotal = 0.0;
+        foreach ($data as $i => $value) {
+            $w = floatval($weights[$i]);
+            $weightedSum += floatval($value) * $w;
+            $weightTotal += $w;
+        }
+
+        if ($weightTotal == 0) {
+            throw new InvalidDataInputException('The sum of weights must be non-zero');
+        }
+
+        if ($precision) {
+            return round($weightedSum / $weightTotal, $precision);
+        }
+        return $weightedSum / $weightTotal;
+    }
+
     /**
      * Return the median (middle value) of data,
      * using the common “mean of middle two” method.

tests/StatTest.php

@@ -15,6 +15,34 @@
     )->toThrow(InvalidDataInputException::class);
 });
 
+it('calculates fmean (static)', function () {
+    expect(
+        Stat::mean([1, 2, 3, 4, 4]),
+    )->toEqual(2.8);
+    expect(
+        Stat::mean([-1.0, 2.5, 3.25, 5.75]),
+    )->toEqual(2.625);
+    expect(
+        fn() => Stat::mean([]),
+    )->toThrow(InvalidDataInputException::class);
+    expect(
+        Stat::fmean([3.5, 4.0, 5.25]),
+    )->toBeFloat()->toEqual(4.25);
+    expect(
+        Stat::fmean([85, 92, 83, 91], [0.20, 0.20, 0.30, 0.30], 2),
+    )->toBeFloat()->toEqual(87.6);
+    expect(
+        Stat::fmean([3.5, 4.0, 5.25], [1, 2, 1]),
+    )->toBeFloat()->toEqual(4.1875);
+    expect(
+        Stat::fmean([3.5, 4.0, 5.25], precision: 2),
+    )->toBeFloat()->toEqual(4.25);
+    expect(
+        Stat::fmean([3.5, 4.0, 5.25], [1, 2, 1], precision: 3),
+    )->toBeFloat()->toEqual(4.188);
+
+});
+
 it('calculates median (static)', function () {
     expect(
         Stat::median([1, 3, 5]),