You are policeman and you are playing a game with Slavik. The game is turn-based and each turn consists of two phases. During the first phase you make your move and during the second phase Slavik makes his move.

There are n doors, the i-th door initially has durability equal to a_i.

During your move you can try to break one of the doors. If you choose door i and its current durability is b_i then you reduce its durability to max(0, b_i - x) (the value x is given).

During Slavik's move he tries to repair one of the doors. If he chooses door i and its current durability is b_i then he increases its durability to b_i + y (the value y is given). Slavik cannot repair doors with current durability equal to 0.

The game lasts 10^{100} turns. If some player cannot make his move then he has to skip it.

Your goal is to maximize the number of doors with durability equal to 0 at the end of the game. You can assume that Slavik wants to minimize the number of such doors. What is the number of such doors in the end if you both play optimally?

Input

The first line of the input contains three integers n, x and y (1 ≤ n ≤ 100, 1 ≤ x, y ≤ 10^5) — the number of doors, value x and value y, respectively.

The second line of the input contains n integers a_1, a_2, ..., a_n (1 ≤ a_i ≤ 10^5), where a_i is the initial durability of the i-th door.

Output

Print one integer — the number of doors with durability equal to 0 at the end of the game, if you and Slavik both play optimally.

Examples

Input


6 3 2
2 3 1 3 4 2


Output


6


Input


5 3 3
1 2 4 2 3


Output


2


Input


5 5 6
1 2 6 10 3


Output


2

Note

Clarifications about the optimal strategy will be ignored.
''' CODED WITH LOVE BY SATYAM KUMAR '''


from sys import stdin, stdout
import cProfile, math
from collections import Counter
from bisect import bisect_left,bisect,bisect_right
import itertools
from copy import deepcopy
from fractions import Fraction
import sys, threading
import operator as op
from functools import reduce
sys.setrecursionlimit(10**6) # max depth of recursion
threading.stack_size(2**27)  # new thread will get stack of such size

printHeap = str()
memory_constrained = False
P = 10**9+7
import sys
sys.setrecursionlimit(10000000)

class Operation:
    def __init__(self, name, function, function_on_equal, neutral_value=0):
        self.name = name
        self.f = function
        self.f_on_equal = function_on_equal
def add_multiple(x, count):
    return x * count
def min_multiple(x, count):
    return x
def max_multiple(x, count):
    return x
sum_operation = Operation("sum", sum, add_multiple, 0)
min_operation = Operation("min", min, min_multiple, 1e9)
max_operation = Operation("max", max, max_multiple, -1e9)
class SegmentTree:
    def __init__(self,
                 array,
                 operations=[sum_operation, min_operation, max_operation]):
        self.array = array
        if type(operations) != list:
            raise TypeError("operations must be a list")
        self.operations = {}
        for op in operations:
            self.operations[op.name] = op
        self.root = SegmentTreeNode(0, len(array) - 1, self)
    def query(self, start, end, operation_name):
        if self.operations.get(operation_name) == None:
            raise Exception("This operation is not available")
        return self.root._query(start, end, self.operations[operation_name])
    def summary(self):
        return self.root.values
    def update(self, position, value):
        self.root._update(position, value)
    def update_range(self, start, end, value):
        self.root._update_range(start, end, value)
    def __repr__(self):
        return self.root.__repr__()
class SegmentTreeNode:
    def __init__(self, start, end, segment_tree):
        self.range = (start, end)
        self.parent_tree = segment_tree
        self.range_value = None
        self.values = {}
        self.left = None
        self.right = None
        if start == end:
            self._sync()
            return
        self.left = SegmentTreeNode(start, start + (end - start) // 2,
                                    segment_tree)
        self.right = SegmentTreeNode(start + (end - start) // 2 + 1, end,
                                     segment_tree)
        self._sync()
    def _query(self, start, end, operation):
        if end < self.range[0] or start > self.range[1]:
            return None
        if start <= self.range[0] and self.range[1] <= end:
            return self.values[operation.name]
        self._push()
        left_res = self.left._query(start, end,
                                    operation) if self.left else None
        right_res = self.right._query(start, end,
                                      operation) if self.right else None
        if left_res is None:
            return right_res
        if right_res is None:
            return left_res
        return operation.f([left_res, right_res])
    def _update(self, position, value):
        if position < self.range[0] or position > self.range[1]:
            return
        if position == self.range[0] and self.range[1] == position:
            self.parent_tree.array[position] = value
            self._sync()
            return
        self._push()
        self.left._update(position, value)
        self.right._update(position, value)
        self._sync()
    def _update_range(self, start, end, value):
        if end < self.range[0] or start > self.range[1]:
            return
        if start <= self.range[0] and self.range[1] <= end:
            self.range_value = value
            self._sync()
            return
        self._push()
        self.left._update_range(start, end, value)
        self.right._update_range(start, end, value)
        self._sync()
    def _sync(self):
        if self.range[0] == self.range[1]:
            for op in self.parent_tree.operations.values():
                current_value = self.parent_tree.array[self.range[0]]
                if self.range_value is not None:
                    current_value = self.range_value
                self.values[op.name] = op.f([current_value])
        else:
            for op in self.parent_tree.operations.values():
                result = op.f(
                    [self.left.values[op.name], self.right.values[op.name]])
                if self.range_value is not None:
                    bound_length = self.range[1] - self.range[0] + 1
                    result = op.f_on_equal(self.range_value, bound_length)
                self.values[op.name] = result
    def _push(self):
        if self.range_value is None:
            return
        if self.left:
            self.left.range_value = self.range_value
            self.right.range_value = self.range_value
            self.left._sync()
            self.right._sync()
            self.range_value = None
    def __repr__(self):
        ans = "({}, {}): {}\n".format(self.range[0], self.range[1],
                                      self.values)
        if self.left:
            ans += self.left.__repr__()
        if self.right:
            ans += self.right.__repr__()
        return ans

def display(string_to_print):
    stdout.write(str(string_to_print) + "\n")

def ncr(n, r):
    r = min(r, n-r)
    numer = reduce(op.mul, range(n, n-r, -1), 1)
    denom = reduce(op.mul, range(1, r+1), 1)
    return numer / denom

def primeFactors(n): #n**0.5 complex 
    factors = dict()
    for i in range(2,math.ceil(math.sqrt(n))+1):  
        while n % i== 0: 
            if i in factors:
                factors[i]+=1
            else: factors[i]=1
            n = n // i 
    if n>2:
        factors[n]=1
    return (factors)
    
def isprime(n):
    """Returns True if n is prime."""
    if n < 4:
        return True
    if n % 2 == 0:
        return False
    if n % 3 == 0:
        return False
    i = 5
    w = 2
    while i * i <= n:
        if n % i == 0:
            return False
        i += w
        w = 6 - w
    return True

def test_print(*args):
    if testingMode:
        print(args)

def display_list(list1, sep=" "):
    stdout.write(sep.join(map(str, list1)) + "\n")

def get_int():
    return int(stdin.readline().strip())

def get_tuple():
    return map(int, stdin.readline().split())

def get_list():
    return list(map(int, stdin.readline().split()))

memory = dict()
def clear_cache():
    global memory
    memory = dict()
def cached_fn(fn, *args):
    global memory
    if args in memory:
        return memory[args]
    else:
        result = fn(*args)
        memory[args] = result
        return result


# -------------------------------------------------------------- MAIN PROGRAM
TestCases = False
testingMode = False
optimiseForReccursion = False #Can not be used clubbed with TestCases
     

def main():
    n,x,y=get_tuple()
    li = get_list()
    if x>y:
        print(n)
        return
    c=0
    for i in li:
        if i<=x:
            c+=1
    print(math.ceil(c/2))
    


# --------------------------------------------------------------------- END


if TestCases: 
    for _ in range(get_int()): 
        cProfile.run('main()') if testingMode else main() 
else: (cProfile.run('main()') if testingMode else main()) if not optimiseForReccursion else threading.Thread(target=main).start()