(solution) There are two python files, one is An in place quick sort and

There are two python files, one is An in place quick sort and other is Binary Heap.

1. the In place quick sort, it uses multiple lists in order to do the search, Revise it to use the same list instead of multiple lists. This will require recursion.

2. For the Binary Heap, it does not handle the max requirement on insert. Revise it, give the class a max value and check it in the insert and then remove the least significant element.  Figure out what is the least significant element in the implementation.

import math

 

import random

 

class BinaryHeap:

 

def __init__(self, array, direction=1, size=100):

 

if(size > len(array)):

 

self.size = len(array)

 

else:

 

self.size = size;

 

self.bBinaryHeap = array[:]

 

if 0 < direction:

 

self.compare = self.greater

 

else:

 

self.compare = self.less

 

self.buildBinaryHeap()

 

def node(self, index):

 

return (index << 1) + 1

 

def parent(self, index):

 

return (index - 1) >> 1

 

def bBinaryHeapifyDown(self, index):

 

swap = self.bBinaryHeap[index]

 

while self.node(index) < self.size:

 

node = self.node(index)

 

if node + 1 < self.size and self.compare(self.bBinaryHeap[node],

 

self.bBinaryHeap[node + 1]) > 0:

 

node += 1

 

if self.compare(swap, self.bBinaryHeap[node]) > 0:

 

self.bBinaryHeap[index] = self.bBinaryHeap[node];

 

else:

 

break

 

index = node

 

self.bBinaryHeap[index] = swap

 

def upheapify(self, index):

 

while 0 < index and self.compare(self.bBinaryHeap[index],

 

self.bBinaryHeap[self.parent(index)]) < 0:

 

parent = self.parent(index)

 

swap = self.bBinaryHeap[parent]

 

self.bBinaryHeap[parent] = self.bBinaryHeap[index]

 

self.bBinaryHeap[index] = swap

 

index = parent

 

def buildBinaryHeap(self):

 

indices = range(0, int(self.size / 2))

 

reversed(indices)

 

for index in indices:

 

self.bBinaryHeapifyDown(index)

 

def insert(self, value):

 

self.shrink()

 

index = self.size

 

self.bBinaryHeap[index] = value

 

self.size += 1

 

self.upheapify(index)

 

def search(self, value):

 

for index in range(self.size):

 

if self.bBinaryHeap[index] == value:

 

return index

 

def delete(self, value): index = self.search(value)

 

self.size -= 1

 

self.bBinaryHeap[index] = self.bBinaryHeap[self.size]

 

parent = self.parent(index)

 

if (index == 0) or (self.compare(self.bBinaryHeap[parent],

 

self.bBinaryHeap[index]) < 0):

 

self.bBinaryHeapifyDown(index)

 

else:

 

self.upheapify(index)

 

def shrink(self):

 

capacity = len(self.bBinaryHeap)

 

if capacity == self.size:

 

self.bBinaryHeap.extend([0] * capacity)

 

def greater(self, value1, value2):

 

if value1 == value2:

 

return 0

 

elif value1 < value2:

 

return 1

 

elif value1 > value2:

 

return -1

 

def less(self, value1, value2):

 

if value1 == value2:

 

return 0

 

elif value1 < value2:

 

return -1

 

elif value1 > value2:

 

return 1

 

def getLevel(self, index):

 

return int(math.floor(math.log(index + 1, 2)))

 

def displayBinaryHeap(self):

 

printBinaryHeap = str(self.bBinaryHeap)

 

height = self.getLevel(self.size)

 

previous = -1

 

for index in range(self.size):

 

getLevel = self.getLevel(index)

 

n = height - getLevel

 

indent = int(math.pow(2, n + 1) - 2)

 

spacing = 2 * indent

 

if getLevel != previous:

 

printBinaryHeap += '

 

'

 

printBinaryHeap += ' ' * indent

 

previous = getLevel

 

else:

 

printBinaryHeap += ' ' * spacing

 

printBinaryHeap += '%4d' % self.bBinaryHeap[index]

 

print(printBinaryHeap) if __name__ == "__main__":

 

size =10

 

array = [random.randint(0, 100) for i in range(size)]

 

bBinaryHeap = BinaryHeap(array, 1, 100)

 

print('Binary bBinaryHeap:')

 

bBinaryHeap.displayBinaryHeap()

 

---

Solution details:

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