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stock_bn_ben.py
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stock_bn_ben.py
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__author__ = 'Mateusz Bednarski'
from counting_sort import counting_sort
from qsort import QuickSort
#from qsort2 import qsort1 as QuickSort
from qsort_iter import QuickSortIterative
from heap_sort import heap_sort
from shell import shell_sort
from utils import measure_exe_time
from generators import *
from sys import setrecursionlimit
from stock import kadane, prepare
from time import clock
import numpy as np
probe_sizes = [10, 1000, 10000,50000,100000,500000,750000,1000000,5000000,10000000]
b_param = [10000,100000,1000000,2500000,5000000,7500000,10000000,15000000,20000000]
#probe_sizes = [10,100, 1000, 10000,20000]
repeats = 5
def single_algo(gen):
dd = np.zeros((len(b_param), len(probe_sizes)))
#dd[0, :] = probe_sizes
#dd[:, 0] = b_param
#to fill
algo = counting_sort
nc = 0
bc = 0
for n in probe_sizes:
bc = 0
for b in b_param:
print 'n=', n, ' b=', b
r = []
for xd in range(repeats):
data = generate_random_sequence(n, max_val=b)
start = clock()
ddd = prepare(data)
kadane(ddd)
stop = clock()
r.append(stop - start)
dd[bc, nc] = np.mean(r)
bc += 1
nc += 1
'''probeIndex = 0
too_deep = False
for probe in probe_sizes:
if too_deep:
break
print 'Probe size ', probe, '(Index ', probeIndex, ')...'
for row in range(1, repeats + 1):
print 'Repeat ', row, '...'
data = gen(probe)
try:
perf = measure_exe_time(algo, data)
dd[row, probeIndex] = perf
print perf
except RuntimeError:
dd[row, probeIndex] = 0
too_deep = True
probeIndex += 1'''
return dd
if __name__ == '__main__':
setrecursionlimit(10000)
print 'random'
random = single_algo(generate_random_sequence)
'''print 'asc'
asc = single_algo(generate_ascending_sequence)
print 'desc'
desc = single_algo(generate_descending_sequence)
print 'v'
v = single_algo(generate_v_sequence)
'''
#print measure_exe_time(QuickSortIterative, generate_ascending_sequence(20000))
#to fill
hdr = 'csort'
np.savetxt('bnstock', random, fmt='%f', header=hdr)