human
Maximize value at Kth index to create N size array with adjacent difference 1 and sum less than M | Function to calculate maximum value that can be placed at the Kth index in a distribution in which difference of adjacent elements is less than 1 and total sum of distribution is M ..
Variable to store final answer.
Variables for binary search.
Binary search.
Variable for binary search.
Variable to store total sum of array.
Number of indices on the left excluding the Kth index.
Number of indices on the left excluding the Kth index.
Add mid to final sum.
Distribution on left side is possible.
Sum of distribution on the left side.
Sum of distribution on the left side with ( L - mid ) 1 s.
Distribution on right side is possible.
Sum of distribution on the right side.
Sum of distribution on the left side with ( R - mid ) 1 s.
Distribution is valid.
Return answer.
Input.
Function call"
How can the above be solved in Python?
 ... Write me a code to maximize value at Kth index to create N size array with adjacent difference 1 and sum less than M and the other steps required?
assistant
#Here is code to maximize value at Kth index to create N size array with adjacent difference 1 and sum less than M and the other steps required.
 def calculateMax ( N , M , K ) :
	ans = - 1
	low = 0
	high = M
	while ( low <= high ) :
		mid = ( low + high ) / 2
		val = 0
		L = K - 1
		R = N - K
		val += mid
		if ( mid >= L ) :
			val += ( L ) * ( 2 * mid - L - 1 ) / 2
		else :
			val += mid * ( mid - 1 ) / 2 + ( L - mid )
		if ( mid >= R ) :
			val += ( R ) * ( 2 * mid - R - 1 ) / 2
		else :
			val += mid * ( mid - 1 ) / 2 + ( R - mid )
		if ( val <= M ) :
			ans = max ( ans , mid )
			low = mid + 1
		else :
			high = mid - 1
	return int ( ans )
N = 7
M = 100
K = 6
print ( calculateMax ( N , M , K ) ) ;