I have an array and I want to find the longest number sequence from the array that does not contain 3:
#array
x=[1,2,3,4,5,6,5,4,3,3,4,5,2,3,7]
I expect as result as following:
[4, 5, 6, 5, 4]
If I were doing this, I would make groups with itertools.groupby and take the longest one:
from itertools import groupby
a = [1,2,3,4,5,6,5,4,3,3,4,5,2,3,7]
groups = [list(g) for k, g in groupby(a, key=lambda x: x!=3) if k]
max(groups, key = len)
# [4, 5, 6, 5, 4]
Of course there are many other way. If you want to manually loop through the list, you can just keep track of the current longest seen:
a = [1,2,3,4,5,6,5,4,3,3,4,5,2,3,7]
cur = []
longest = cur
for n in a:
if n != 3:
cur.append(n)
if len(cur) > len(longest):
longest = cur
else:
cur = []
print(longest) #[4, 5, 6, 5, 4]
If you want to find sequence (specifically subsequence) then taking all elements which are not 3 will be the result.
But it seems you want to find sub array. Following is my implementation for the same in python
def findLargestSubArray(arr, k):
# collect all the index position of k in arr
kPos = [i for i in range(len(arr)) if arr[i] == k]
largest = 0
left = -1
right = -1
# size of subarray to the left of 1st instance of k
if len(kPos) > 0:
largest = kPos[0] - 1
left = 0
right = kPos[0]
for i in range(1, len(kPos)):
# size of subarray between ith & (i-1)th instance of k
currSize = kPos[i] - kPos[i-1] - 1
if largest < currSize:
largest = currSize
left = kPos[i-1] + 1
right = kPos[i]
# size of subarry to the right of last instance of k
if largest < len(arr) - kPos[-1] - 1:
largest = len(arr) - kPos[-1] - 1
left = kPos[-1] + 1
right = len(arr)
return arr[left: right]
x = [3,3]
print(findLargestSubArray(x, 3))
Related
I was working on a GFG question
Question:
Given two unsorted arrays arr1[] and arr2[]. They may contain duplicates. For each element in arr1[] count elements less than or equal to it in array arr2[].
Example 1:
Input:
m = 6, n = 6
arr1[] = {1,2,3,4,7,9}
arr2[] = {0,1,2,1,1,4}
Output: 4 5 5 6 6 6
Explanation: Number of elements less than
or equal to 1, 2, 3, 4, 7, and 9 in the
second array are respectively 4,5,5,6,6,6
Example 2:
Input:
m = 5, n = 7
arr1[] = {4 8 7 5 1}
arr2[] = {4,48,3,0,1,1,5}
Output: 5 6 6 6 3
Your Task :
Complete the function countEleLessThanOrEqual() that takes two array arr1[], arr2[], m, and n as input and returns an array containing the required results(the count of elements less than or equal to it in arr2 for each element in arr1 where ith output represents the count for ith element in arr1.)
Expected Time Complexity: O((m + n) * log n).
Expected Auxiliary Space: O(1).
Constraints:
1<=m,n<=10^5
1<=arr1[i],arr2[j]<=10^5
My python solution:
def countEleLessThanOrEqual(arr1,n1,arr2,n2):
#returns the required output
res=[]
arr2.sort()
for i in range(n1):
search=arr1[i]
count=0
start=0
end=n2-1
while(start<=end):
mid = int(start+(end-start)/2)
if search==arr2[mid]:
start=mid+1
elif search>arr2[mid]:
start=mid+1
elif search<arr2[mid]:
end=mid-1
count=end+1
res.append(count)
return res
When I submit it, it gives me TLE error even though my solution is similar to the one posted in the editorial:
Editorial solution:
# python implementation of For each element in 1st
# array count elements less than or equal to it
# in 2nd array
# function returns the index of largest element
# smaller than equal to 'x' in 'arr'. For duplicates
# it returns the last index of occurrence of required
# element. If no such element exits then it returns -1
def bin_search(arr, n, x):
l = 0
h = n - 1
while(l <= h):
mid = int((l + h) / 2)
# if 'x' is greater than or equal to arr[mid],
# then search in arr[mid + 1...h]
if(arr[mid] <= x):
l = mid + 1;
else:
# else search in arr[l...mid-1]
h = mid - 1
# required index
return h
# function to count for each element in 1st array,
# elements less than or equal to it in 2nd array
def countElements(arr1, arr2, m, n):
# sort the 2nd array
arr2.sort()
# for each element in first array
for i in range(m):
# last index of largest element
# smaller than or equal to x
index = bin_search(arr2, n, arr1[i])
# required count for the element arr1[i]
print(index + 1)
# driver program to test above function
arr1 = [1, 2, 3, 4, 7, 9]
arr2 = [0, 1, 2, 1, 1, 4]
m = len(arr1)
n = len(arr2)
countElements(arr1, arr2, m, n)
# This code is contributed by Aditi Sharma
You could use a binary search on the second array after sorting it in place:
from bisect import bisect_right
def lowerCount(arr1,arr2):
arr2.sort()
return [bisect_right(arr2,v) for v in arr1]
print(*lowerCount([1,2,3,4,7,9],[0,1,2,1,1,4])) # 4 5 5 6 6 6
print(*lowerCount([4, 8, 7, 5, 1],[4,48,3,0,1,1,5])) # 5 6 6 6 3
Sorting arr2 is O(N log N), and binary searches will take O(M log N) for a total of O( (N+M) log N ).
If you can't use libraries, you could always write your own bisect_right function:
def bisect_right(A,x):
lo,hi = 0,len(A)-1
while lo <= hi:
mid = (lo+hi)//2
if A[mid] <= x: lo = mid+1
else: hi = mid-1
return hi+1
#AasthaJha, would you like to try this similar but simplified alternative version:
def bin_search(A, n, x):
low, high = 0, n-1
while low <= high:
mid = (low + high) // 2
# if 'x' is greater than or equal to A[mid],
# then search in arr[mid + 1...h]
if A[mid] <= x:
low = mid + 1;
else:
high = mid -1 # else search in A[l...mid-1]
return high
# function to count for each element in 1st array,
# elements less than or equal to it in 2nd array
def countElements(A, B, m, n):
B.sort()
result = []
# loop element in A - first array
for i in range(m):
# last index of largest element smaller than or equal to x
index = bin_search(B, n, A[i])
print(index + 1) # count
result.append(index + 1)
return result
# Testing
A = [1, 2, 3, 4, 7, 9]
B = [0, 1, 2, 1, 1, 4]
m, n = len(A), len(B)
print(countElements(A, B, m, n))
A peak in an array is any value that is no smaller than its two adjacent neighbors. If its the first or last element of the array we only need to compare with one neighbor. I wrote some recursive code to find peaks in python which is fast in principle as it runs in O(log n) time:
def peak_recursive(A):
n = len(A)
if n == 1:
print("n == 1")
return 0
if n == 2:
return 0 if A[0] >= A[1] else 1
if A[n//2] >= A[n//2+1] and A[n//2] >= A[n//2 - 1]:
return n//2
elif A[n//2 - 1] >= A[n//2]:
return peak_recursive(A[0:n//2])
else:
return n//2 + 1 + peak_recursive(A[n//2+1:])
However, python isn't very good at recursion so I think it would be better iteratively. How can I convert this to iterative code?
Update
It turns out this code is very slow as A[n//2+1:] and A[0:n//2] make copies of the lists.
One simple solution is to iterate over the list and compare the previous and next values. You also need to consider the first element and last element situation:
# Import numpy to create random vector
import numpy as np
l = np.random.randint(0, 10, 20).tolist()
print(l)
# [6, 7, 2, 7, 1, 4, 2, 8, 9, 1, 3, 7, 0, 5, 4, 6, 9, 0, 5, 7]
def peak_iter(A):
out = [] # Output
n = len(A) # Number element A
for i, curr in enumerate(A): # Iterate over A
condi = True # Peak condition
if i > 0: condi = A[i-1] < curr # Update peak condition from previous value
if i < n - 1: condi = curr > A[i + 1] # Update peak condition from next value
if condi: out.append(curr) # If condition satisfied: add value to output
return out
print(peak_iter(l))
# [7, 7, 4, 9, 7, 5, 9, 7]
As well, you can easily get the index instead of the value (or the both) by replacing out.append(curr) with out.append(i) or out.append([curr, i]).
Update:
If you just want to get the one peak, you can exit the function after finding one element meeting condition. The following returns the first values:
def peak_iter_first(A):
out = None # Output
n = len(A) # Number element A
for i, curr in enumerate(A): # Iterate over A
condi = True # Peak condition
if i > 0: condi = A[i-1] < curr # Update peak condition from previous value
if i < n - 1: condi = curr > A[i + 1] # Update peak condition from next value
if condi: return curr # If condition satisfied: return value
return out
print(peak_iter_first(l))
# 7
Update 2:
The translation of the recursive function to an iterative one might looks something like this:
def peak_iterative(A):
n = len(A)
out = 0
while True:
if n == 1:
out += 0
break
if n == 2:
out += 0 if A[0] >= A[1] else 1
break
if A[n//2] >= A[n//2+1] and A[n//2] >= A[n//2 - 1]:
out += n//2
break
elif A[n//2 - 1] >= A[n//2]:
A = A[0:n//2]
else:
out += n//2 + 1
A = A[n//2+1:]
n = len(A)
return out
Who's the faster ?
The recursive one is a bit faster than the iterative method:
import timeit
import functools
# Bigger array (2000 elements)
l = np.random.randint(0, 10, 2000).tolist()
t = timeit.Timer(functools.partial(peak_recursive, l))
print (t.timeit(50))
# 3.950000000019216e-05
t = timeit.Timer(functools.partial(peak_iterative, l))
print (t.timeit(50))
# 7.049999999986234e-05
Hope that helps !
I've tried to find the sub-array(s) from a given which contain elements of maximum sum than any other sub array.
Below function has parameter as input a and the output needs to be returned. There can be more than one subarray as their maximum sum can be equal. The code did not seem to be working as expected.
def max_sum_subarray(a):
N, sub_sum, max_sum, subArrays = len(a), 0, 0, {}
p,q=0,0 #starting and ending indices of a max sub arr
for i in range(N):
q=i
sub_sum+=a[i]
if(a[i]<0):
q-=1
if(sub_sum>=max_sum):
if(sub_sum>max_sum):
subArrays.clear()
subArrays[sub_sum]=[(p,q)]
else:
subArrays[sub_sum].append((p,q))
sub_sum=0
p=i+1
if(sub_sum>=max_sum):
if(sub_sum>max_sum):
subArrays.clear()
subArrays[sub_sum]=[(p,q)]
else:
subArrays[sub_sum].append((p,q))
return(subArrays[p:q+1])
When I tried to run for input
a=[ 1, 2, 5, -7, 2, 5 ]
Expected output is [1, 2, 5] but it gave [2, 5] instead. Can anyone please post the solution in python?
It seems like you making this harder than necessary. You can just keep track of max array seen to far and the current one you're pushing into -- you don't really need to care about anything else. When you hit a negative (or the end of the array) decide if the current should be the new max:
def maxSub(a):
max_so_far = []
max_sum = 0
cur = []
for n in a:
if n >= 0:
cur.append(n)
else:
cur_sum = sum(cur)
if cur_sum > max_sum:
max_sum = cur_sum
max_so_far = cur
cur = []
return max([max_so_far, cur], key = sum)
a=[ 1, 2, 5, -7, 2, 5 ]
maxSub(a)
# [1, 2, 5]
Of course itertools.groupby makes this a one-liner:
from itertools import groupby
a=[ 1, 2, 5, -7, 2, 5 ]
max([list(g) for k,g in groupby(a, key=lambda x: x>0) if k == True], key=sum)
For the following conditions:
NOTE 1: If there is a tie, then compare with segment’s length and
return segment which has maximum length
NOTE 2: If there is still a tie, then return the segment with minimum
starting index
Here is my working code in python:
def check(max_arr,curr):
if sum(curr) > sum(max_arr):
max_arr = curr
elif sum(curr) == sum(max_arr):
if len(curr) > len(max_arr):
max_arr = curr
elif len(curr) == len(max_arr):
if max_arr and (curr[0] > max_arr[0]):
max_arr = curr
return max_arr
def maxset(A):
curr = []
max_arr = []
for i in A:
if i >= 0:
curr.append(i)
else:
max_arr = check(max_arr,curr)
curr = []
max_arr = check(max_arr,curr)
return max_arr
How would I go about reading integers until -1 is input and then printing the length of the longest continuous sequence of numbers where there are
alternating odd then even numbers?
I've achieved the first section but it went downhill from there.
Some testing lists:
[1,2,3,4,5,10,6,7,8,20,25,30,40,-1]
[6,7,8,20,25,30,40,1,2,3,4,5,10,15,20,-1]
Here is my code:
evenOdd=[]
while True:
try:
n=int(input())
if n != -1:
evenOdd.append(n)
except:
break
evenOdd=[]
longest = 0
length = 0
for i in range(len(evenOdd)):
if ((evenOdd[i-2]% 2 == 0) and (evenOdd[i-1]% 2 == 1) and (evenOdd[i]% 2 == 0):
length += 1
else:
longest = max(longest, length)
length = 0
print(longest)
One option would be to keep track of the longest sequence as you go:
longest = []
current = []
while True:
n = int(input("Enter value: "))
if n == -1:
break
if current and current[-1] % 2 != n % 2:
current.append(n)
else:
current = [n]
if len(current) > len(longest):
longest = current
The upside here is there's no post-processing to be done when the -1 is entered, the result is ready to go.
You can use itertools.cycle to alternate between a remainder of 0 and 1, and use itertools.groupby to group odd-even sequences:
from itertools import groupby, cycle
l = [1,2,3,4,5,10,6,7,8,20,25,30,40]
r = cycle((0, 1))
print(max(sum(1 for i in g) for _, g in groupby(l, key=lambda n: n % 2 == next(r))))
This outputs: 6 (since the longest odd-even sequence is 1,2,3,4,5,10)
This is how I did. I think this might be simpler than the above examples.
def alternating(lst):
longSeries = []
currentSeries=[]
for i in range (len(lst)-1):
if i == 0:
currentSeries = [lst[0]]
if(abs(lst[i] - lst[i+1]) % 2 == 1):
currentSeries.append(lst[i+1])
else:
currentSeries = [lst[i+1]]
if(len(currentSeries) > len(longSeries)):
longSeries = currentSeries
print ("The longest series is: " +str(longSeries))
print(len(longSeries))
You can apply itertools.groupby twice:
import itertools
d = [[1,2,3,4,5,10,6,7,8,20,25,30,40,-1], [6,7,8,20,25,30,40,1,2,3,4,5,10,15,20,-1]]
def key_func(d):
start= not d[0]%2
for i in d[1:]:
if i%2 == start:
start = (not i%2)
else:
return False
return True
for l in d:
new_l = [list(b) for _, b in itertools.groupby(l, key=lambda x:x%2)]
second_l = [[i for [i] in b] for a, b in itertools.groupby(new_l, key=lambda x:len(x) ==1) if a]
print(max(second_l, key=lambda x:[key_func(x), len(x)]))
Output:
[1, 2, 3, 4, 5]
[1, 2, 3, 4, 5, 10, 15, 20, -1]
I am trying to write a selection sort algorithm for sorting lists of numbers from lowest to highest.
def sortlh(numList):
if type(numList) != list:
print("Input must be a list of numbers.")
else:
inf = float("inf")
sortList = [0]*len(numList)
count = 0
while count < len(numList):
index = 0
indexLowest = 0
lowest = numList[index]
while index < (len(numList) - 1):
if numList[index + 1] < numList[index]:
lowest = numList[index + 1]
indexLowest = index + 1
index = index + 1
else:
index = index + 1
sortList[count] = lowest
numList[indexLowest] = inf
count = count + 1
return sortList
When I run this code on:
sortlh([9,8,7,6,5,4,3,2,1])
I get (as expected):
[1, 2, 3, 4, 5, 6, 7, 8, 9]
However, when I try another example, I get:
sortlh([1,3,2,4,5,7,6,9,8])
[8, 6, 9, 2, 4, 5, 7, 1, 3]
Does anyone see what is going on here?
Here is how I would suggest rewriting your program.
def sortlh(lst_input):
lst = list(lst_input) # make a copy of lst_input
i = 0
while i < len(lst):
j = i + 1
i_lowest = i
lowest = lst[i_lowest]
while j < len(lst):
if lst[j] < lowest:
i_lowest = j
lowest = lst[i_lowest]
j += 1
lst[i], lst[i_lowest] = lst[i_lowest], lst[i] # swap
i += 1
return lst
test = [9,8,7,6,5,4,3,2,1]
assert sortlh(test) == sorted(test)
test = [1,3,2,4,5,7,6,9,8]
assert sortlh(test) == sorted(test)
We don't test the type of the input. Anything that acts like a list will work, and even an iterator will work.
We don't "mutate" the original input list. We only work on a copy of the data.
When we find the lowest number, we swap it with the first number, and then only look at the remaining numbers. Thus we have less work to do on each loop as we have fewer and fewer unsorted numbers.
EDIT:
If you are a beginner, this part might seem too tricky. If it confuses you or you don't like it, just ignore it for now.
This is a more-advanced way to solve this problem in Python. The inner loop simply finds the lowest number and the index of the lowest number. We can use the Python built-in function min() to do this!
We build a "generator expression" that loops over the list, yielding up tuples. Each tuple is the number and its position. Since we want lower numbers to sort lower, we put the number first in the tuple so that min() can properly compare the tuples. Then min() will find the lowest tuple and we get the value and index.
Also, the outer loop is now a for loop with enumerate rather than a while loop using indexing.
def sortlh(lst_input):
lst = list(lst_input) # make a copy of lst_input
for i, x in enumerate(lst):
lowest, i_lowest = min((n, j) for j, n in enumerate(lst) if j >= i)
lst[i], lst[i_lowest] = lst[i_lowest], lst[i] # swap
return lst
test = [9,8,7,6,5,4,3,2,1]
assert sortlh(test) == sorted(test)
test = [1,3,2,4,5,7,6,9,8]
assert sortlh(test) == sorted(test)