Merge pull request lcompilers#769 from Madhav2310/stats

Mean, Geometric Mean & Harmonic mean Functions implemented in Statistics.py module

integration_tests/CMakeLists.txt

@@ -181,6 +181,7 @@ RUN(NAME test_max_min        LABELS cpython llvm)
 RUN(NAME test_integer_bitnot LABELS cpython llvm)
 RUN(NAME test_unary_minus    LABELS cpython llvm)
 RUN(NAME test_unary_plus     LABELS cpython llvm)
+RUN(NAME test_statistics     LABELS cpython)
 RUN(NAME test_bool_binop     LABELS cpython llvm)
 RUN(NAME test_issue_518      LABELS cpython llvm)
 RUN(NAME structs_01          LABELS cpython llvm c)

integration_tests/test_statistics.py

@@ -0,0 +1,40 @@
+from statistics import (mean, geometric_mean, harmonic_mean)
+from ltypes import i32, f64, i64
+
+eps: f64
+eps = 1e-12
+
+def test_mean():
+    b: list[i32]
+    b = [9, 4, 10]
+    j: f64
+    j = mean(b)
+    assert abs(j - 7.666666666666667) < eps
+
+    c: list[f64]
+    c = [2.0, 3.1, 11.1]
+    k: f64
+    k = mean(c)
+    assert abs(k - 5.4) < eps
+
+def test_geometric_mean():
+    c: list[i32]
+    c = [1,2,3]
+    k: f64
+    k = geometric_mean(c)
+    assert abs(k - 1.8171205928321397) < eps
+
+def test_harmonic_mean():
+    c: list[i32]
+    c = [9,2,46]
+    k: f64
+    k = harmonic_mean(c)
+    assert abs(k - 4.740458015267175) < eps
+
+
+def check():
+    test_mean()
+    test_geometric_mean()
+    test_harmonic_mean()
+
+check()

src/runtime/statistics.py

@@ -0,0 +1,64 @@
+from ltypes import i32, f64
+
+@overload
+def mean(x: list[i32]) -> f64:
+    k: i32 = len(x)
+    if k == 0:
+        return 0.0
+    sum: f64
+    sum = 0.0
+    i: i32
+
+    for i in range(k):
+        sum += x[i]
+    ans: f64
+    ans = sum/k
+    return ans
+
+@overload
+def mean(x: list[f64]) -> f64:
+    k: i32 = len(x)
+    if k == 0:
+        return 0.0
+    sum: f64
+    sum = 0.0
+    i: i32
+    for i in range(k):
+        sum += x[i]
+    ans: f64
+    ans = sum/k
+    return ans
+
+@overload
+def geometric_mean(x: list[i32]) -> f64:
+    k: i32 = len(x)
+    if k == 0:
+        return 0.0
+    product: f64
+    product = 1.0
+    i: i32
+    for i in range(k):
+        if x[i] < 1:
+            raise ValueError('geometric mean requires a non-empty dataset  containing positive numbers')
+        product *= x[i]
+    ans: f64
+    ans = product**(1/k)
+    return ans
+
+@overload
+def harmonic_mean(x: list[i32]) -> f64:
+    k: i32 = len(x)
+    if k == 0:
+        return 0.0
+    sum: f64
+    sum = 0.0
+    i: i32
+    for i in range(k):
+        if x[i] < 0:
+            raise ValueError('harmonic mean does not support negative values')
+        if x[i] ==0:
+            return 0.0
+        sum += 1 / x[i]
+    ans: f64
+    ans = k/sum
+    return ans