def sort(num, num_range=None, sort=None, print_arrays=False, timed=False, print_time=False): if num_range==None: num_range=num if timed: s=Stopwatch() s.start() a=[(i%num_range) for i in range(0,num)] if timed: build_array_time=s.lap() if print_time: print " Time to build array of %s elements, range 0-%s: %s"%(num_to_words(num), num_to_words(num_range), float(build_array_time)) random.shuffle(a) if timed: shuffle_time=s.lap() if print_time: print " Time to shuffle array: %s"%float(shuffle_time) if print_arrays: print "\n Unsorted:\n %s"%a if sort is not None: if sort.lower()=="mergesort": mergesort(a) if sort.lower()=="quicksort": quicksort(a) if sort.lower()=="mergesort_rec": mergesort_rec(a) if sort.lower()=="heapsort": heapsort(a) else: # something I made from test data... if float(num)/float(num_range) > 6 and num<=50000 : mergesort(a) sort="mergesort" elif float(num)/float(num_range) < 100 and num>=50000 and num<500000: quicksort(a) sort="quicksort" else: mergesort(a) sort="mergesort" if timed: sort_time=s.lap() if print_time: print " Time to sort array: %s"%float(sort_time) s.stop() if print_arrays: print "\n Sorted:\n %s"%a # print "\n Sorted: %s"%is_sorted(a) # print "Used: %s"%sort if timed: return sort_time
def use_case(n): print "N=%s"%n s=Stopwatch() s.start() print Binom_coeff_tab(n, int(n/2)) print str(s.lap()) +" seconds" print Binom_coeff_mem_driver(n, int(n/2)) print str(s.lap()) +" seconds" print Binom_coeff_rec(n, int(n/2)) print str(s.lap()) +" seconds" s.stop() print "\n\n"
def use_case(n):
print "N=%s" % n
s = Stopwatch()
s.start()
print Binom_coeff_tab(n, int(n / 2))
print str(s.lap()) + " seconds"
print Binom_coeff_mem_driver(n, int(n / 2))
print str(s.lap()) + " seconds"
print Binom_coeff_rec(n, int(n / 2))
print str(s.lap()) + " seconds"
s.stop()
print "\n\n"
def sort(num,
num_range=None,
sort=None,
print_arrays=False,
timed=False,
print_time=False):
if num_range == None:
num_range = num
if timed:
s = Stopwatch()
s.start()
a = [(i % num_range) for i in range(0, num)]
if timed:
build_array_time = s.lap()
if print_time:
print " Time to build array of %s elements, range 0-%s: %s" % (
num_to_words(num), num_to_words(num_range),
float(build_array_time))
random.shuffle(a)
if timed:
shuffle_time = s.lap()
if print_time:
print " Time to shuffle array: %s" % float(shuffle_time)
if print_arrays:
print "\n Unsorted:\n %s" % a
if sort is not None:
if sort.lower() == "mergesort":
mergesort(a)
if sort.lower() == "quicksort":
quicksort(a)
if sort.lower() == "mergesort_rec":
mergesort_rec(a)
if sort.lower() == "heapsort":
heapsort(a)
else:
# something I made from test data...
if float(num) / float(num_range) > 6 and num <= 50000:
mergesort(a)
sort = "mergesort"
elif float(num) / float(
num_range) < 100 and num >= 50000 and num < 500000:
quicksort(a)
sort = "quicksort"
else:
mergesort(a)
sort = "mergesort"
if timed:
sort_time = s.lap()
if print_time:
print " Time to sort array: %s" % float(sort_time)
s.stop()
if print_arrays:
print "\n Sorted:\n %s" % a
# print "\n Sorted: %s"%is_sorted(a)
# print "Used: %s"%sort
if timed:
return sort_time
# For example, length of LIS for { 10, 22, 9, 33, 21, 50, 41, 60, 80 } is 6 and the LIS is {10, 22, 33, 50, 60, 80}.
# This is a Dynamic Programming Problem
import random
from misc_functions import Stopwatch
s=Stopwatch()
def LIS(arr): # O(n^2) algorithm...an O(n.log(n)) solution also exists, using binary search.
lis=[]
maximum=0
for i in range(0,len(arr)): # for (i=0; i<len(arr); i++){
lis.append(1)
# print lis
for i in range(0,len(arr)):
for j in range(0,i):
if arr[i]>arr[j] and lis[i]<lis[j]+1:
lis[i]=lis[j]+1
# print lis
maximum=max(lis)
return maximum
num=1000
num_range=1000
arr=[(i%num_range) for i in range(0,num)]
random.shuffle(arr)
s.start()
print "Length of Longest Increasing Subsequence: %s"%LIS(arr)
print s.stop()