Extend testing and timing

Author: gjbex

source-code/interfaciing-c-c++-fortran/Pybind11/Stats/test.py

@@ -1,15 +1,40 @@
 #!/usr/bin/env python
 
+import argparse
 import numpy as np
-from stats import Statistics, compute_stats
-
-n = 10
-data = np.empty(n)
-my_stats = Statistics()
-for i in range(n):
-    value = 0.3*i
-    my_stats.add(value)
-    data[i] = value
-print(my_stats.mean())
-my_stats = compute_stats(data)
-print(my_stats.mean())
+import stats
+import timeit
+
+
+def compute_stats(data):
+    my_stats = stats.Statistics()
+    for value in data:
+        my_stats.add(value)
+    return my_stats
+
+def main():
+    parser = argparse.ArgumentParser(description='Compute statistics for a given number of random numbers')
+    parser.add_argument('--n', type=int, default=10,
+                        help='number of data values')
+    parser.add_argument('--repetitions', type=int, default=1,
+                        help='number of repetitions')
+    parser.add_argument('--check', action='store_true',
+                        help='check the results')
+    args = parser.parse_args()
+    data = np.random.uniform(size=args.n)
+    time = timeit.timeit(lambda: compute_stats(data), number=args.repetitions)
+    print(f'{time/args.repetitions:.6f} s (Statistics iterative mean)')
+    time = timeit.timeit(lambda: stats.compute_stats(data), number=args.repetitions)
+    print(f'{time/args.repetitions:.6f} s (Statistics numpy access mean)')
+    time = timeit.timeit(lambda: data.mean(), number=args.repetitions)
+    print(f'{time/args.repetitions:.6f} s (numpy mean)')
+    if args.check:
+        print()
+        my_stats = compute_stats(data)
+        print(f'{my_stats.mean()} (Statistics iterative mean)')
+        my_stats = stats.compute_stats(data)
+        print(f'{my_stats.mean()} (Statistics numpy access mean)')
+        print(f'{data.mean()} (numpy mean)')
+
+if __name__ == '__main__':
+    main()