Create placeholder_python_code.py

placeholder_python_code.py

@@ -0,0 +1,57 @@
+
+pi_1 = """
+import time
+def calculate(iterations, p1, p2):
+    result = 1.0 
+    for i in range(1, iterations+1):
+        j = i * p1 - p2
+        result -= (1/j)
+        j = i * p1 + p2
+        result += (1/j)
+    return result
+### USE Or MODIFY THIS CODE BELOW IF YOU NEED CODE EXECUTION CHECK -- EXAMPLE BELOW: 
+start_time = time.time()
+final_result = calculate(100_000_000, 4, 1) * 4
+end_time = time.time()
+print(f"Result: {final_result:.12f}")
+print(f"Execution Time: {(end_time - start_time):.6f} seconds")
+"""
+
+pi_2 = """
+import time
+def lcg(seed, a=1664525, c=1013904223, m=2**32):
+    value = seed
+    while True:
+        value = (a * value + c) % m
+        yield value
+def max_subarray_sum(n, seed, min_val, max_val):
+    '''Generate n pseudo-random numbers using LCG and find max subarray sum.'''
+    lcg_gen = lcg(seed)
+    random_numbers = [next(lcg_gen) % (max_val - min_val + 1) + min_val for _ in range(n)]
+    # Kadane’s Algorithm
+    max_sum = float('-inf')
+    current_sum = 0
+    for x in random_numbers:
+        current_sum = max(x, current_sum + x)
+        max_sum = max(max_sum, current_sum)
+    return max_sum, random_numbers
+def total_max_subarray_sum(n, initial_seed, min_val, max_val):
+    total_sum = 0
+    lcg_gen = lcg(initial_seed)
+    for _ in range(20):
+        seed = next(lcg_gen)
+        max_sum, _ = max_subarray_sum(n, seed, min_val, max_val)  # unpack tuple
+        total_sum += max_sum
+    return total_sum
+# Parameters
+n = 10000
+initial_seed = 42
+min_val = -10
+max_val = 10
+# Timing
+start_time = time.time()
+result = total_max_subarray_sum(n, initial_seed, min_val, max_val)
+end_time = time.time()
+print("Total Maximum Subarray Sum (20 runs):", result)
+print("Execution Time: {:.6f} seconds".format(end_time - start_time))
+"""