Data commit

Task/Knuths-algorithm-S/Python/knuths-algorithm-s-1.py

@@ -0,0 +1,34 @@
+from random import randrange
+
+def s_of_n_creator(n):
+    sample, i = [], 0
+    def s_of_n(item):
+        nonlocal i
+
+        i += 1
+        if i <= n:
+            # Keep first n items
+            sample.append(item)
+        elif randrange(i) < n:
+            # Keep item
+            sample[randrange(n)] = item
+        return sample
+    return s_of_n
+
+if __name__ == '__main__':
+    bin = [0]* 10
+    items = range(10)
+    print("Single run samples for n = 3:")
+    s_of_n = s_of_n_creator(3)
+    for item in items:
+        sample = s_of_n(item)
+        print("  Item: %i -> sample: %s" % (item, sample))
+    #
+    for trial in range(100000):
+        s_of_n = s_of_n_creator(3)
+        for item in items:
+            sample = s_of_n(item)
+        for s in sample:
+            bin[s] += 1
+    print("\nTest item frequencies for 100000 runs:\n ",
+          '\n  '.join("%i:%i" % x for x in enumerate(bin)))

Task/Knuths-algorithm-S/Python/knuths-algorithm-s-2.py

@@ -0,0 +1,16 @@
+class S_of_n_creator():
+    def __init__(self, n):
+        self.n = n
+        self.i = 0
+        self.sample = []
+
+    def __call__(self, item):
+        self.i += 1
+        n, i, sample = self.n, self.i, self.sample
+        if i <= n:
+            # Keep first n items
+            sample.append(item)
+        elif randrange(i) < n:
+            # Keep item
+            sample[randrange(n)] = item
+        return sample

Task/Knuths-algorithm-S/Python/knuths-algorithm-s-3.py

@@ -0,0 +1 @@
+s_of_n = S_of_n_creator(3)