Data commit

Task/Cumulative-standard-deviation/Lobster/cumulative-standard-deviation.lobster

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+// Stats computes a running mean and variance
+// See Knuth TAOCP vol 2, 3rd edition, page 232
+
+class Stats:
+    M = 0.0
+    S = 0.0
+    n = 0
+    def incl(x):
+        n += 1
+        if n == 1:
+            M = x
+        else:
+            let mm = (x - M)
+            M += mm / n
+            S += mm * (x - M)
+    def mean(): return M
+    //def variance(): return (if n > 1.0: S / (n - 1.0) else: 0.0) // Bessel's correction
+    def variance(): return (if n > 0.0: S / n else: 0.0)
+    def stddev(): return sqrt(variance())
+    def count(): return n
+
+def test_stdv() -> float:
+    let v = [2,4,4,4,5,5,7,9]
+    let s = Stats {}
+    for(v) x: s.incl(x+0.0)
+    print concat_string(["Mean: ", string(s.mean()), ", Std.Deviation: ", string(s.stddev())], "")
+
+test_stdv()