def minSubsequences(A, B):
v = [[] for i in range(26)]
minIndex = -1
cnt = 1
j = 0
flag = 0
for i in range(len(A)):
p = ord(A[i]) - 97
v[p].append(i)
while (j < len(B)):
p = ord(B[j]) - 97
k = upper_bound(v[p], minIndex)
if (len(v[p]) == 0):
flag = 1
break
if (k != len(v[p])):
minIndex = v[p][k]
j = j + 1
else:
cnt = cnt + 1
minIndex = -1
if (flag == 1):
return -1
return cnt
def binaryMedian(m, r, d):
mi = m[0][0]
mx = 0
for i in range(r):
if m[i][0] < mi:
mi = m[i][0]
if m[i][d - 1] > mx:
mx = m[i][d - 1]
desired = (r * d + 1) // 2
while (mi < mx):
mid = mi + (mx - mi) // 2
place = [0]
# Find count of elements smaller than mid
for i in range(r):
j = upper_bound(m[i], mid)
place[0] = place[0] + j
if place[0] < desired:
mi = mid + 1
else:
mx = mid
print("Median is", mi)
return
def findKth(self, a, m, n, mi, mx, desired):
while mi < mx:
mid = (mi + mx) // 2
left = 0
for i in range(m):
tmp = upper_bound(a[i], mid)
left += tmp
if left < desired:
mi = mid + 1
else:
mx = mid
return mi
def binaryMedian(m, r, d):
mi = m[0][0]
mx = 0
for i in range(r):
if m[i][0] < mi:
mi = m[i][0]
if m[i][d - 1] > mx:
mx = m[i][d - 1]
desired = (r * d + 1) // 2
while (mi < mx):
mid = mi + (mx - mi) // 2
place = [0]
for i in range(r):
j = upper_bound(m[i], mid)
place[0] = place[0] + j
if place[0] < desired:
mi = mid + 1
else:
mx = mid
print('Median = ', mi)
return
def findMedian(self, A):
n = len(A)
m = len(A[0])
mi = 0
ma = 0
for i in range(n):
if mi>A[i][0]:
mi = A[i][0]
if ma<A[i][-1]:
ma = A[i][-1]
desired = (m*n+1)//2
while mi<ma:
place = [0]
mid = mi+(ma-mi)//2
for i in range(n):
u = upper_bound(A[i],mid)
place[0]+=u
if place[0]<desired:
mi = mid+1
else:
ma = mid
return ma
def findFrequency(arr,n,left,right,element):
#lower bound gives takes list of locations
#where element is present in orgnal array
#and the left range
# and returns the index of element from
#that list which is greater equal to given
#left range.
a=lower_bound(store[element],left)
#upper bound gives takes list of locations
#where element is present in orgnal array
#and the right range
# and returns the index of element from
#that list which is less than or equal to
#given right range.
b=upper_bound(store[element],right)
#return last index where element exists
#in range - the first index where it
#exist of the list of occurances
return b-a
def median(arr, r, c):
mn = float('inf')
mx = -float('inf')
for i in range(r):
mn = min(arr[i][0], mn)
mx = max(arr[i][-1], mn)
#print(mn,mx)
des = (r * c + 1) // 2
while mn < mx:
temp = 0
mid = mn + (mx - mn) // 2
#print(mn,mx)
for i in range(r):
j = upper_bound(arr[i], mid)
#print(j,mid)
temp += j
if temp < des:
mn = mid + 1
else:
mx = mid
return mn
def binaryMedian(m, r, c):
min = sys.maxsize
max = -sys.maxsize
for i in range(0, r):
if m[i][0] < min:
min = m[i][0]
if m[i][c - 1] > max:
max = m[i][c - 1]
median = (r * c + 1) // 2
while (min < max):
mid = min + (max - min) // 2
place = [0]
for i in range(r):
j = upper_bound(m[i], mid)
place[0] = place[0] + j
if place[0] < median:
min = mid + 1
else:
max = mid
return min
def count_k(arr, n, k):
# Variable to store final answer
ans = 0
# Loop to find prefix-sum
for i in range(1, n):
arr[i] += arr[i - 1]
if (arr[i] > k or arr[i] < -1 * k):
ans += 1
if (arr[0] > k or arr[0] < -1 * k):
ans += 1
# Sorting prefix-sum array
arr = sorted(arr)
# Loop to find upper_bound
# for each element
for i in range(n):
ans += n - upper_bound(arr, arr[i] + k)
# Returning final answer
return ans
def findMedian(self, A):
R = len(A)
C = len(A[0])
mi = A[0][0]
mx = 0
for i in range(R):
if A[i][0] < mi:
mi = A[i][0]
if A[i][C - 1] > mx:
mx = A[i][C - 1]
desired = (R * C + 1) / 2
while mi < mx:
mid = mi + (mx - mi) // 2
place = [0]
for i in range(R):
j = upper_bound(A[i], mid)
place[0] = place[0] + j
if place[0] < desired:
mi = mid + 1
else:
mx = mid
return mi
def findMedian(arr):
n = len(arr)
m = len(arr[0])
# Find min and max element of matrix
min_el, max_el = arr[0][0], 0
for i in range(n):
min_el = min(min_el, arr[i][0])
max_el = max(max_el, arr[i][-1])
target = (1 + n*m) // 2
while min_el <= max_el:
mid = min_el + (max_el - min_el) // 2
count = 0
# count no_of_elements smaller than mid
for i in range(n):
count += upper_bound(arr[i], mid)
if count < target:
min_el = mid + 1
else:
max_el = mid - 1
return min_el
def binary_median(m, r, d):
mi = m[0][0]
mx = 0
for i in range(r):
if m[i][0] < mi:
mi = m[i][0]
if m[i][d - 1] > mx:
mx = m[i][d - 1]
desired = (r * d + 1) // 2
while mi < mx:
mid = mi + (mx - mi) // 2
place = 0
for i in range(r):
j = upper_bound(m[i], mid)
print("J: ", j, "M[i] ", m[i], "Mid:", mid)
place = place + j
print("Place: ", place, "Desired", desired)
if place < desired:
mi = mid + 1
else:
mx = mid
print("Median is", mi)
return
from bisect import bisect_right as upper_bound
#arr = [[1, 3, 5], [2, 6, 9], [3, 6, 9]]
arr = [[1],[3],[3]]
r = len(arr)
c = len(arr[0])
lg = r*c // 2
mini = arr[0][0]
maxi = 0
for i in range(r):
if arr[i][0] < mini:
mini = arr[i][0]
if arr[i][c-1] > maxi:
maxi = arr[i][c-1]
print(mini,maxi)
while mini < maxi:
mid = mini + (maxi - mini) // 2
j = 0
for i in range(r):
j += upper_bound(arr[i],mid)
if j > lg:
maxi = mid
else:
mini = mid + 1
print(f"Median is {mini}")
