def manual_time(filename, compare = False):
"""Calculates the runtime of given functions using time module and
writes the results to file
Args:
filename (str): Filename of the report
Compares (bool): A variable to extract the runtime using timeit module
"""
total_time = []
function_names = ["random_array", "snake_loop", "loop"]
# Timing the functions
iterations = 3
for i in range(iterations):
start_time = time.time()
array = tst.random_array(1e5)
end_time = time.time()
a = round(end_time - start_time, 5)
start_time = time.time()
filtered_array = tst.snake_loop(array)
end_time = time.time()
b = round(end_time - start_time, 5)
start_time = time.time()
filtered_array_snack = tst.loop(array)
end_time = time.time()
c = round(end_time - start_time, 5)
# Creating the table format to the report
if a > b and a > c:
d = "random_array"
elif b > a and b > c:
d = "snake_loop"
else:
d = "loop"
t = "Measurement " + str(i+1)
column = t, a, b, c, d
total_time.append(column)
if compare:
return total_time
else:
Write_Results_To_File(filename, function_names, total_time)
else:
raise ValueError(
"'order' keyword must be 'fast', 'slow' or one of the profiled function's name"
)
# Newline for nicer formatting
outputs.append("\nTiming performed using: 'time.time'")
# If only one function is profiled
else:
outputs.append("Timing performed using: 'time.time'")
# Write results to file
with open(filename, "w") as f:
f.write("\n".join(outputs))
if __name__ == "__main__":
from test_slow_rectangle import loop, random_array, snake_loop
n_experiments = 5
array = random_array(1e5)
funcs = [random_array, loop, snake_loop]
args = [1e5, array, array]
timer_results(n_experiments,
"manual_report.txt",
funcs,
args,
order="slow")
import test_slow_rectangle as tsr
import timeit as tit
import numpy as np
file = open("timeit_reportit.txt", "w")
for i in range(3):
start_random_array = tit.default_timer()
array = tsr.random_array(1e5)
end_random_array = tit.default_timer()
# times['random_array']= float(end_random_array - start_random_array)
start_snake_loop = tit.default_timer()
filtered_array = tsr.snake_loop(array)
end_snake_loop = tit.default_timer()
# times['snake_loop']= float(end_snake_loop - start_snake_loop)
start_snack_loop = tit.default_timer()
filtered_array_snack = tsr.loop(array)
end_snack_loop = tit.default_timer()
# times['snack_loop']= float(end_snack_loop - start_snack_loop)
times = {'random_array': float(end_random_array - start_random_array), \
'snake_loop': float(end_snake_loop - start_snake_loop), \
'snack_loop': float(end_snack_loop - start_snack_loop)}
file.write(f"-------- run number {i} ------- \n \n")
import time
import test_slow_rectangle as t
global arr, t0, t1, smallest, runtime
f = open("manual_report.txt", "w")
for i in range(1, 4):
smallest = float("inf")
t0 = time.time()
arr = t.random_array(1e5)
t1 = time.time()
runtime = t1 - t0
if i == 0:
smallest = runtime
elif runtime < smallest:
smallest = runtime
print("Method random_array() took: {:.4}s".format(t1 - t0))
f.write("random_array() runtime: {:.4}s\n".format(smallest))
for i in range(3):
smallest = float("inf")
t0 = time.time()
t.loop(arr)
t1 = time.time()
runtime = t1 - t0
if i == 0:
smallest = runtime
elif runtime < smallest:
smallest = runtime
print("Method loop() took: {:.4}s".format(t1 - t0))
import test_slow_rectangle as tsr
import numpy as np
import cProfile
import pstats
import io
pr = cProfile.Profile()
pr.enable()
random_array = tsr.random_array(1E5)
pr.disable()
s = io.StringIO()
ps = pstats.Stats(pr, stream=s).sort_stats('tottime')
ps.print_stats()
print("random_array")
with open('cProfile_report.txt', 'w+') as f:
f.write("random array \n")
f.write(s.getvalue())
pr.enable()
filtered_array = tsr.snake_loop(random_array)
pr.disable()
s = io.StringIO()
ps = pstats.Stats(pr, stream=s).sort_stats('tottime')
ps.print_stats()
print("snake_loop")