# -*- coding: utf8 -*-
"""
1. 使用 memory_profiler 分析指令碼記憶體使用詳情
2. 使用 cProfile 分析指令碼時間使用詳情

Wed Jan 24 19:55:54 2018    matrix_sum.txt

         378806 function calls (378683 primitive calls) in 48.725 seconds

   Ordered by: internal time
   List reduced from 173 to 10 due to restriction <10>

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1   15.762   15.762   15.762   15.762 {numpy.core.multiarray.array}
        1   12.886   12.886   46.854   46.854 memory_profiler.py:656(f)
        1   10.572   10.572   33.969   33.969 profile.test.py:16(matrix_sum)
   100000    7.172    0.000    7.172    0.000 profile.test.py:10(build_matrix_row)
     3600    1.060    0.000    1.258    0.000 _strptime.py:299(_strptime)
   200000    0.344    0.000    0.344    0.000 {method 'randint' of 'mtrand.RandomState' objects}
        1    0.298    0.298    0.298    0.298 {method 'reduce' of 'numpy.ufunc' objects}
        1    0.214    0.214   48.725   48.725 <string>:1(<module>)
        1    0.164    0.164    0.164    0.164 {zip}
     3602    0.094    0.000    0.097    0.000 locale.py:365(normalize)

Line #    Mem usage    Increment   Line Contents
================================================
    16     61.0 MiB     61.0 MiB   @profile
    17                             def matrix_sum(cols_array, duration_tuple_array):
    18                                 matrix = [
    19   2833.7 MiB   2772.8 MiB           row for row in [build_matrix_row(dt) for dt in duration_tuple_array]
    20                                 ]
    21   2834.1 MiB      0.4 MiB       return dict(zip(cols_array, list(array(matrix).sum(0))))

Line #    Mem usage    Increment   Line Contents
================================================
    23     44.1 MiB     44.1 MiB   @profile
    24                             def main():
    25     44.1 MiB      0.0 MiB       cProfile.run(
    26     44.1 MiB      0.0 MiB           "matrix_sum([(datetime.strptime('2018-01-01 12:00:00', '%Y-%m-%d %H:%M:%S')+timedelta(seconds=i)).strftime('%Y-%m-%d %H:%M:%S') for i in range(0, 3600)], [(random.randint(0, 1800), random.randint(1800, 3600)) for i in range(0, 100000)])",
    27     82.6 MiB     38.5 MiB           'matrix_sum.txt'
    28                                 )
    29     82.6 MiB      0.0 MiB       p = pstats.Stats('matrix_sum.txt')
    30     82.6 MiB      0.0 MiB       p.strip_dirs().sort_stats('time').print_stats(10)
"""
import cProfile
import pstats
import StringIO
import random
from numpy import *
from datetime import datetime,timedelta
from memory_profiler import profile

def build_matrix_row(duration_tupple):
    zero_left = int(duration_tupple[0])
    one_middle = int(duration_tupple[1]) - int(duration_tupple[0]) + 1
    zero_right = int(3600 - duration_tupple[1] - 1)
    return [0] * zero_left + [1] * one_middle + [0] * zero_right

@profile
def matrix_sum(cols_array, duration_tuple_array):
    matrix = [
        row for row in [build_matrix_row(dt) for dt in duration_tuple_array]
    ]
    return dict(zip(cols_array, list(array(matrix).sum(0))))

@profile
def main():
    cProfile.run(
        "matrix_sum([(datetime.strptime('2018-01-01 12:00:00', '%Y-%m-%d %H:%M:%S')+timedelta(seconds=i)).strftime('%Y-%m-%d %H:%M:%S') for i in range(0, 3600)], [(random.randint(0, 1800), random.randint(1800, 3600)) for i in range(0, 100000)])",
        'matrix_sum.txt'
    )
    p = pstats.Stats('matrix_sum.txt')
    p.strip_dirs().sort_stats('time').print_stats(10)

if __name__ == '__main__':
    main()