maximum pairwise product fast solution - python

I am trying to apply a stress test on python maximum pairwise product, fast and slow algorithm. However, The fast code appears to return a wrong result in some tests. I think the problem comes from the if condition in the fast algorithm. The condition doesn't occur in some cases, though it should be applies. I wasn't able to figure out the problem. any help?
Here is the problem, I/P, O/P details:
Given a sequence of non-negative integers a0,…,an−1, find the maximum pairwise product, that is, the largest integer that can be obtained by multiplying two different elements from the sequence (or, more formally, max0≤i≠j≤n−1aiaj). Different elements here mean ai and aj with i≠j (it can be the case that ai=aj).
Input format
The first line of the input contains an integer n. The next line contains n non-negative integers a0,…,an−1 (separated by spaces).
Constraints:
2≤n≤2⋅105; 0≤a0,…,an−1≤105.
Output format:
Output a single number — the maximum pairwise product.
from random import randint
from random import randrange
def max_pairwise(n,a):
# n = int(input())
res = 0
# a = [int(x) for x in input().split()]
assert(len(a) == n)
for i in range(0,n):
for j in range(i+1,n):
if a[i]*a[j] > res:
res = a[i]*a[j]
return(res)
def max_pairwise_fast(n,a):
# n = int(input())
# a = [int(x) for x in input().split()]
max_index1 = -1
max_index2 = -1
for i in range(0,n):
if a[i] > a[max_index1]:
max_index1 = i
else:
continue
for j in range(0,n):
if ((a[j] != a[max_index1]) and (a[j] > a[max_index2])):
max_index2 = j
else:
continue
res = a[max_index1]* a[max_index2]
return(res)
#stress_test
while(1):
n = randint(0,9) +2
print(n,"n")
a = []
for i in range (n):
a.append(randrange(9000))
for i in range(n):
print(a[i],'a[i]',"/n")
if (max_pairwise(n,a) == max_pairwise_fast(n,a)):
print(max_pairwise(n,a), max_pairwise_fast(n,a),"true")
else:
print(max_pairwise(n,a), max_pairwise_fast(n,a), "false")
break
This is an example of the result:
6 n
318 a[i] /n
7554 a[i] /n
7531 a[i] /n
7362 a[i] /n
4783 a[i] /n
4897 a[i] /n
56889174 56889174 true
5 n
6879 a[i] /n
6985 a[i] /n
8561 a[i] /n
5605 a[i] /n
3077 a[i] /n
59798585 59798585 true
9 n
8285 a[i] /n
3471 a[i] /n
2280 a[i] /n
2443 a[i] /n
5437 a[i] /n
2605 a[i] /n
1254 a[i] /n
6990 a[i] /n
2943 a[i] /n
57912150 68641225 false

In your fast implementation, when you are finding a largest number, you must also update the second largest to the value of the previous largest, otherwise, there are cases where you end up multiplying numbers that are not the two largest.
def product_of_two_largest(seq):
largest = float("-inf")
second_largest = float("-inf")
for elt in seq:
if elt > largest:
second_largest = largest
largest = elt
elif elt > second_largest:
second_largest = elt
return second_largest * largest
Note 1:
Your while loop must also be updated, you are calculating the values twice instead of once.
while(1):
n = randint(0,9) +2
print(n,"n")
a = []
for i in range (n):
a.append(randrange(9000))
for i in range(n):
print(a[i],'a[i]',"/n")
slow, fast = max_pairwise(n, a), two_largest_product(a)
if (slow == fast):
print(slow, fast, slow == fast)
else: # attention, this never happens now.
break
Note 2:
As we are dealing with only non-negative integers, you will likely have a faster implementation if you simply sort the sequence and multiply the last two numbers (in spite of the fact that sort is O(nlogn), vs O(n) for the fast implementation above.
b = sorted(a)
print("max1 x max2 = ", b[-1] * b[-2])
Note 3:
Using a heap data structure (from collections import heap) is the theoretical best way to find the n largest items, but you'd likely need to have 100,000's of items to make it worth your while.

def max_pairwise_fast(n, a):
max_index1 = 0
max_index2 = 0
for i in range(n):
if a[i] > max_index1:
max_index2 = max_index1
max_index1 = a[I]
elif a[i] > max_index2:
max_index2 = a[I]
return max_index1 * max_index2
if __name__ == '__main__':
input_n = int(input())
input_numbers = [int(x) for x in input().split()]
print(max_pairwise_fast(input_n, input_numbers))

This might not help you.
I was attempting this question at Coursera ( Assignment ) and found that we don't need to make the solution more complex. We can simply store the first two largest integers while scanning from the user and print their product. A complex solution is the main reason for the TLE error.
code in c
#include<stdio.h>
int main() {
long long n, a = 0, b = 0, i = 0, numb = 1;
scanf("%lld", &n);
for (i = 0; i < n; i++){
scanf("%lld", &numb);
if(numb >= a){
b = a;
a = numb;
}
else if(numb > b)
b = numb;
}
printf("%lld", a * b);
return 0;
}

With input array data:
Example: [1, 2, 3]
def max(arr):
a = 0
b = 0
for i in range(len(arr)):
if a == 0 & arr[i]>a:
a = arr[i]
else:
if arr[i]>a:
b = a
a = arr[i]
else:
if arr[i]>b:
b = arr[i]
return a*b;

def max_pairwise_fast(n, a):
max_index1 = 0
max_index2 = 0
for i in range(n):
if a[i] > max_index1:
max_index2 = max_index1
max_index1 = a[i]
elif a[i] > max_index2:
max_index2 = a[i]
return max_index1 * max_index2
if __name__ == '__main__':
input_n = int(input())
input_numbers = [int(x) for x in input().split()]
print(max_pairwise_fast(input_n, input_numbers))

Related

What should I do? I have a recursive function that returns the mth item of a n-bonacci sequence. It has for loop. I am banned from using loops

I have the following recursive function to get the mth term of a n-bonacci sequence as shown below this question. My problem is that the use of for and while loops is totally banned from the code, so I need to get rid off
for i in range(1, n+1):
temp += n_bonacci(n,m-i)
and convert the code into something that is not a loop but nevertheless achieves the same effect. Among the things I can use, but this is not an exclusive enumeration, is: (1) use built-in functions like sum() and .join() and (2) use list comprehensions.
The full code is as follows:
def n_bonacci(n,m): #n is the number of n initial terms; m is the mth term.
if (m < n-1):
return 0
elif (m == n-1):
return 1
else:
temp = 0
#[temp += n_bonacci(n,m-i) for i in range(n)] #this is an attempt at using list comprehension
for i in range(1, n+1):
temp += n_bonacci(n,m-i)
return temp
print("n_bonacci:",n_bonacci(2,10))
print("n_bonacci:",n_bonacci(7,20))
Here's a solution that avoids any type of loop, including loops hidden inside comprehensions:
def n_bonacci_loopless(n, m):
def inner(i, c):
if i == m:
return sum(c)
else:
return inner(i+1, c[-(n-1):] + [sum(c)])
if m < n-1:
return 0
elif (m == n-1):
return 1
else:
return inner(n, [0] * (n-1) + [1])
The base cases are the same, but for recursive cases it initialises a list of collected results c with n-1 zeroes, followed by a one, the sum of which would be the correct answer for m == n.
For m > n, the inner function is called again as long as i < m, summing the list and appending the result to the end of the last n-1 elements of the list so far.
If you are allowed to use comprehensions, the answer is trivial:
def n_bonacci(n,m):
if (m < n-1):
return 0
elif (m == n-1):
return 1
else:
return sum(n_bonacci(n, m-i) for i in range(1, n+1))
You can rewrite the code as follows using list comprehensions:
def n_bonacci(n,m): #n is the number of n initial terms; m is the mth term.
if (m < n-1):
return 0
elif (m == n-1):
return 1
else:
return sum(n_bonacci(n, m-i) for i in range(1, n + 1))
print("n_bonacci:",n_bonacci(2,10))
print("n_bonacci:",n_bonacci(7,20))
To go beyond #Grismar 's answer you can write your own version of sum which doesn't use loops.
def n_bonacci_loopless(n, m):
def recsum(l, s=0):
return recsum(l[1:], s + l[0])
def inner(i, c):
if i == m:
return recsum(c)
else:
return inner(i+1, c[-(n-1):] + [recsum(c)])
if m < n-1:
return 0
elif (m == n-1):
return 1
else:
return inner(n, [0] * (n-1) + [1])

Merge sort in python: slicing vs iterating - impact on complexity

I want to check that my understanding of how python handles slices is correct.
Here's my implementation of merge sort:
def merge_sort(L):
def merge(a, b):
i, j = 0, 0
c = []
while i < len(a) and j < len(b):
if a[i] < b[j]:
c.append(a[i])
i += 1
elif b[j] < a[i]:
c.append(b[j])
j += 1
if a[i:]:
c.extend(a[i:])
if b[j:]:
c.extend(b[j:])
return c
if len(L) <= 1:
return L
else:
mid = len(L) // 2
left = merge_sort(L[:mid])
right = merge_sort(L[mid:])
return merge(left, right)
Am I right in thinking that I could replace this:
if a[i:]:
c.extend(a[i:])
if b[j:]:
c.extend(b[j:])
With this:
while i < len(a):
c.append(a[i])
i += 1
while j < len(b):
c.append(b[j])
j += 1
And have the exact same level of complexity? My understanding of slicing is that its complexity is equivalent to slice length? Is that correct?
Does the fact that I'm calling a slice twice (first in the condition, second time inside of it) make it 2x complexity?
Your implementation of mergesort has problems:
in the merge function's main loop, you do nothing if the values in a[i] and b[j] are equal, or more precisely if you have neither a[i] < b[i] nor a[i] > b[i]. This causes an infinite loop.
there is no need to define merge as a local function, actually there is no need to make it a separate function, you could inline the code and save the overhead of a function call.
Here is a modified version:
def merge_sort(L):
if len(L) <= 1:
return L
else:
mid = len(L) // 2
a = merge_sort(L[:mid])
b = merge_sort(L[mid:])
i, j = 0, 0
c = []
while i < len(a) and j < len(b):
if a[i] <= b[j]:
c.append(a[i])
i += 1
else:
c.append(b[j])
j += 1
if a[i:]:
c.extend(a[i:])
else:
c.extend(b[j:])
return c
Regarding performance, slicing or iterating has no impact on complexity since both operations have linear time cost.
Regarding performance, here are directions to try:
replace the test if a[i:] with if i < len(a). Creating the slice twice is costly.
perform the sort in place, avoiding the append operations
restructure the main loop to have a single test per iteration
Here is a modified version:
def merge_sort(L):
if len(L) <= 1:
return L
else:
mid = len(L) // 2
a = merge_sort(L[:mid])
b = merge_sort(L[mid:])
i, j, k = 0, 0, 0
while True:
if a[i] <= b[j]:
L[k] = a[i]
k += 1
i += 1
if (i == len(a)):
L[k:] = b[j:]
return L
else:
L[k] = b[j]
k += 1
j += 1
if (j == len(b)):
L[k:] = a[i:]
return L

Python Maximum Pairwise Fast Solution [dup]

I'm taking an algorithms course online and I am trying to calculate the maximum pairwise product in a list of numbers. This question has already been answered before:
maximum pairwise product fast solution and
Python for maximum pairwise product
I was able to pass the assignment by looking at those two posts. I was hoping that maybe someone could help me figure out how to correct my solution. I was able to apply a stress test and found out if the largest number in the array is in the starting index it will just multiply itself twice.
This is the test case I failed using the assignment automatic grader
Input:
2
100000 90000
Your output:
10000000000
Correct output:
9000000000
Here is my pairwise method and stress test
from random import randint
def max_pairwise_product(numbers):
n = len(numbers)
max_product = 0
for first in range(n):
for second in range(first + 1, n):
max_product = max(max_product,
numbers[first] * numbers[second])
return max_product
def pairwise1(numbers):
max_index1 = 0
max_index2 = 0
#find the highest number
for i, val in enumerate(numbers):
if int(numbers[i]) > int(numbers[max_index1]):
max_index1 = i
#find the second highest number
for j, val in enumerate(numbers):
if j != max_index1 and int(numbers[j]) > int(numbers[max_index2]):
max_index2 = j
#print(max_index1)
#print(max_index2)
return int(numbers[max_index1]) * int(numbers[max_index2])
def stressTest():
while True:
arr = []
for x in range(5):
random_num = randint(2,101)
arr.append(random_num)
print(arr)
print('####')
result1 = max_pairwise_product(arr)
result2 = pairwise1(arr)
print("Result 1 {}, Result2 {}".format(result1,result2))
if result1 != result2:
print("wrong answer: {} **** {}".format(result1, result2))
break
else:
print("############################################# \n Ok", result1, result2)
if __name__ == '__main__':
stressTest()
'''
length = input()
a = [int(x) for x in input().split()]
answer = pairwise1(a)
print(answer)
'''
Any feedback will be greatly appreciated.
Thanks.
When max number is on position 0, you will get both max_index1 and max_index2 as 0.
That's why you are getting like this .
Add the following lines before #find the second highest number in pairwise1 function .
if max_index1==0:
max_index2=1
else:
max_index2=0
So function will be like:
def pairwise1(numbers):
max_index1 = 0
max_index2 = 0
#find the highest number
for i, val in enumerate(numbers):
if int(numbers[i]) > int(numbers[max_index1]):
max_index1 = i
if max_index1==0:
max_index2=1
else:
max_index2=0
#find the second highest number
for j, val in enumerate(numbers):
if j != max_index1 and int(numbers[j]) > int(numbers[max_index2]):
max_index2 = j
#print(max_index1)
#print(max_index2)
return int(numbers[max_index1]) * int(numbers[max_index2])

Basic Python Algorithm Stress Test

Hi I am learning the basics of algorithms using python, this is my first stress testing script (I am still new to python).
When i run the test both the variables fast and result are printed as 0, the random number generator i included doesn't seem to be creating numbers for the functions mpp and mppf to use, either that or they are not assigning their results to the relevant variable, hence the variable remains = 0 and the loop keeps printing '0 0 OK'
I am receiving no errors except for the fact that my script isn't doing what i want it too!
import random
result = 0
fast = 0
while result == fast:
if __name__ == '__main__':
n = (random.randint(2, 11))
a = list(random.randint(0, 99999) for r in range(n))
assert (len(a) == n)
def max_pairwise_product(n, a):
global result
for i in range(0, n):
for j in range(i + 1, n):
if a[i] * a[j] > result:
result = a[i] * a[j]
return result
def max_pairwise_product_fast(n, a):
global fast
max_index1 = -1
for i in range(n):
if max_index1 == -1 or a[i] > a[max_index1]:
max_index1 = i
max_index2 = -1
for i in range(n):
if i != max_index1 and (max_index2 == -1 or a[i] > a[max_index2]):
max_index2 = i
fast = a[max_index1] * a[max_index2]
return fast
print(fast, result, "OK")
else:
print("Wrong Answer")
I think this seems to work:
import random
def max_pairwise_product_fast(n, a):
global fast
max_index1 = -1
for i in range(n):
if max_index1 == -1 or a[i] > a[max_index1]:
max_index1 = i
max_index2 = -1
for i in range(n):
if i != max_index1 and (max_index2 == -1 or a[i] > a[max_index2]):
max_index2 = i
fast = a[max_index1] * a[max_index2]
return fast
def max_pairwise_product(n, a):
global result
for i in range(0, n):
for j in range(i + 1, n):
if a[i] * a[j] > result:
result = a[i] * a[j]
return result
result = 0
fast = 0
while result == fast:
if __name__ == '__main__':
n = (random.randint(2, 11))
result=0;fast=0
a = list(random.randint(0, 99999) for r in range(n))
assert (len(a) == n)
result = max_pairwise_product(n, a)
fast=max_pairwise_product_fast(n, a)
print(fast, result, "OK")
else:
print("Wrong Answer")
I don't know what your code is suppose to do but it now seems to run.
You should not keep you defined function inside your loop.
Hope this helps.

Python Iterating and Comparing Multiple Lists

I have two lists of equal length: a and b. List b contains several of the same floating point numbers as list a at the same indices, but the other indices are replaced with zeros. These lists also contain several thousand values each.
I would like to iterate through list b until it gets to a non-zero value then iterate through list a from the same index until a greater value is reached. I want to then append that greater value to an empty list and then continue to iterate through list b until the next non-zero value and repeat.
c=[]
i = 0
j = 0
while i < len(a):
if b[i] == 0:
i = i + 1
if b[i] > 0:
j = i
if a[j] < b[i]:
j = j + 1
if a[j] == b[i]:
j = j + 1
if a[j] > b[i]:
c.append(a[j])
i = i + 1
I have tried multiple ways to do this with for and while loops and either end up just appending the whole of list a into the empty list or I create an infinite while loop, so any help or advice on how to get started would be greatly appreciated!
Incorporating #MichaelButscher's answer into this and adding another list d that contains dates that correspond to the values in lists a and b, I then appended the dates for the values that met the condition if a[j] > b[i]: into a new list e.
d=['05/01/2000','06/01/2000','07/01/2000','10/01/2000','11/01/2000','12/01/2000','23/10/2000','24/10/2000','25/10/2000','13/12/2000','14/12/2000','15/12/2000','20/02/2001','21/02/2001','21/09/2001','19/06/2002','20/06/2002']
a=[1.86,1.85,1.89,1.82,1.82,1.83,1.846,1.898,1.869,1.923,1.926,1.9677,1.959,2.02,2.802,2.7312,2.8035]
b=[0,0,1.89,0,0,0,0,0,0,0,0,1.9677,0,0,2.802,0,0]
c=[]
e=[]
i = 0
j = 0
# Run until break
while True:
while i < len(a):
if b[i] != 0:
break # break inner while
i += 1
else:
break # break outer while
# At this point: i < len(a) and b[i] != 0
j = i
while j < len(a):
if a[j] > b[i]:
# At this point: i < len(a) and b[i] != 0 and j < len(a) and a[j] > b[i]
c.append(a[j])
e.append(d[j])
break
j += 1
# At this point either appropriate j was found or j == len(a)
# Anyway, next i to check
i += 1
lists c and e were then printed in columns:
24/10/2000 1.898
24/10/2000 1.898
21/02/2001 2.02
10/09/2001 2.606
20/06/2002 2.8035
24/09/2002 3.8132
22/09/2015 4.0667
04/09/2015 3.853
01/09/2015 3.7031
10/05/2004 3.148
Some of the data is repeated and isn't in ascending date order even though the dates in list d were.
This can be done by nesting while loops. Outer while just runs forever (until break) inner while loops check for desired state.
Untested but should work:
c=[]
i = 0
j = 0
# Run until break
while True:
while i < len(a):
if b[i] != 0:
break # break inner while
i += 1
else:
break # break outer while
# At this point: i < len(a) and b[i] != 0
j = i
while j < len(a):
if a[j] > b[i]:
# At this point: i < len(a) and b[i] != 0 and j < len(a) and a[j] > b[i]
c.append(a[j])
break
j += 1
# At this point either appropriate j was found or j == len(a)
# Anyway, next i to check
i += 1

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