class PriorityQueue: def __init__(self, values=None): self.binary_heap = [0] self.size = 0 if values is not None: for num in values: self.insert(num) self.size = len(values)

def __str__(self): return str(self.binary_heap)

def __len__(self): return self.size

def percolate_up(self, i): while i // 2 > 0 and self.binary_heap[i]

def get_smaller_child_index(self, i): if i * 2 + 1 > self.size: return i * 2 else: if self.binary_heap[i*2]

def percolate_down(self, i): while (i * 2) self.binary_heap[min_child_index]: self.binary_heap[min_child_index], self.binary_heap[i] = self.binary_heap[i], self.binary_heap[min_child_index] i = min_child_index

def insert(self, item): self.binary_heap.append(item) self.size += 1 self.percolate_up(self.size)

def get_minimum(self): return self.binary_heap[1]

def delete_minimum(self): return_val = self.binary_heap[1] self.binary_heap[1] = self.binary_heap[self.size] self.size = self.size - 1 self.binary_heap.pop() self.percolate_down(1) return return_val

In the answer box is a class Priorityqueue as discussed in the lecture. Add a method named heap_update(self, index, value) into the PriorityQueue class. The method takes an integer index and a value as parameters, replaces the item at the list position index with value, and then ensures the order property with the minimum number of operations possible (you are allowed to use any operations from the class Priorityeue). If the index is invalid, i.e., not the index of an element currently in the heap, then the method should do nothing. For example: Answer: (penalty regime: 0,0,5,10,15,20,25,30,35,40,45,50% )