# Python program for Bitonic Sort. Note that this program
# works only when size of input is a power of 2.

# The parameter dir indicates the sorting direction, ASCENDING
# or DESCENDING; if (a[i] > a[j]) agrees with the direction,
# then a[i] and a[j] are interchanged.*/
def compAndSwap(a, i, j, dire):
	if (dire==1 and a[i] > a[j]) or (dire==0 and a[i] > a[j]):
		a[i],a[j] = a[j],a[i]

# It recursively sorts a bitonic sequence in ascending order,
# if dir = 1, and in descending order otherwise (means dir=0).
# The sequence to be sorted starts at index position low,
# the parameter cnt is the number of elements to be sorted.
def bitonicMerge(a, low, cnt, dire):
	if cnt > 1:
		k = cnt/2
		for i in range(low , low+k):
			compAndSwap(a, i, i+k, dire)
		bitonicMerge(a, low, k, dire)
		bitonicMerge(a, low+k, k, dire)

# This funcion first produces a bitonic sequence by recursively
# sorting its two halves in opposite sorting orders, and then
# calls bitonicMerge to make them in the same order
def bitonicSort(a, low, cnt,dire):
	if cnt > 1:
		k = cnt/2
		bitonicSort(a, low, k, 1)
		bitonicSort(a, low+k, k, 0)
		bitonicMerge(a, low, cnt, dire)

# Caller of bitonicSort for sorting the entire array of length N
# in ASCENDING order
def sort(a,N, up):
	bitonicSort(a,0, N, up)

# Driver code to test above
a = [3, 7, 4, 8, 6, 2, 1, 5]
n = len(a)
up = 1

sort(a, n, up)
print ("\n\nSorted array is")
for i in range(n):
	print("%d" %a[i]),

"""
Assignment 6

The goal is to make a graph of
who bit who and who was bitten.
There should be 10 nodes and 15 edges.
3 arrows of biting each other and
3 arrows of someone biting themselves.
Networkx can not do self biting
arrows, but it is in the code.
"""

from graphviz import Digraph as DDotGraph
from graphviz import Graph as UDotGraph
import networkx as nx
from networkx.algorithms.dag import transitive_closure
import graphviz as gv
import matplotlib.pyplot as plt
import numpy as np
from numpy.linalg import matrix_power

"""
class DGraph:
    def __init__(self):
        self.d = dict()

    def clear(self):
        self.d = dict()

    def add_node(self,n):
        if not self.d.get(n):
            self.d[n] = set()

    def add_edge(self,e):
        f,t=e
        self.add_node(f)
        self.add_node(t)
        vs=self.d.get(f)
        if not vs:
            self.d[f] = {t}
        else:
            vs.add(t)

    def add_edges_from(self,es):
        for e in es:
            self.add_edge(e)

    def edges(self):
        for f in self.d:
            for t in self.d[f]:
                yield (f,t)

    def number_of_nodes(self):
        return len(self.d)

    def __repr__(self):
        return self.d.__repr__()

    def show(self):
        dot = gv.Digraph()
        for e in self.edges():
            #print(e)
            f, t = e
            dot.edge(str(f), str(t), label='')
        #print(dot.source)
        show(dot)

# displays graph with graphviz
def show(dot, show=True, file_name='graph.gv'):
    dot.render(file_name, view=show)


def showGraph(g,label="",directed=True):
    if directed:
        dot = gv.Digraph()
    else:
        dot = gv.Graph()

    for e in g.edges():
        print(e)
        f, t = e
        dot.edge(str(f), str(t), label=label)
    print(dot.source)
    show(dot)


def bit():
    G = DGraph()
    G.add_edge(("Blade","Samara"))
    G.add_edge(("Shadow","Wolfe"))
    G.add_edge(("Raven", "Austin"))
    G.add_edge(("Blade", "Alice"))
    G.add_edge(("Alice","Brandon"))
    G.add_edge(("Blade", "Wolfe"))
    G.add_edge(("Samara", "Robin"))
    G.add_edge(("Samara", "Raven"))
    G.add_edge(("Samara", "Hamed"))
    G.add_edge(("Wolfe", "Blade"))
    G.add_edge(("Hamed", "Samara"))
    G.add_edge(("Wolfe", "Shadow"))
    G.add_edge(("Brandon", "Brandon"))
    G.add_edge(("Hamed", "Hamed"))
    G.add_edge(("Austin", "Austin"))
    showGraph(G, label="bit")

bit()

def bitten():
    G=DGraph()
    G.add_edge(("Samara","Blade"))
    G.add_edge(("Wolfe","Shadow"))
    G.add_edge(("Austin", "Raven"))
    G.add_edge(("Alice","Blade"))
    G.add_edge(("Brandon", "Alice"))
    G.add_edge(("Wolfe", "Blade" ))
    G.add_edge(("Robin", "Samara"))
    G.add_edge(("Raven", "Samara"))
    G.add_edge(("Hamed", "Samara"))
    G.add_edge(("Blade", "Wolfe"))
    G.add_edge(("Samara", "Hamed"))
    G.add_edge(("Shadow", "Wolfe"))
    G.add_edge(("Brandon", "Brandon"))
    G.add_edge(("Hamed", "Hamed"))
    G.add_edge(("Austin", "Austin"))
    showGraph(G, label="bitten by")

#bitten()

family = ["Blade", "Samara", "Shadow", "Wolfe", "Raven", "Alice"]
"""

#Do transitive closure call out and the
#matrix power operation should be the same
D = nx.DiGraph()
#D.add_nodes_from("SamaraBladeWolfeShadowAliceRavenBrandonRobinHamedAustin")
D.add_edge("Blade","Samara")
D.add_edge("Shadow","Wolfe")
D.add_edge("Raven", "Austin")
D.add_edge("Blade", "Alice")
D.add_edge("Alice","Brandon")
D.add_edge("Blade", "Wolfe")
D.add_edge("Samara", "Robin")
D.add_edge("Samara", "Raven")
D.add_edge("Samara", "Hamed")
D.add_edge("Wolfe", "Blade")
D.add_edge("Hamed", "Samara")
D.add_edge("Wolfe", "Shadow")
D.add_edge("Brandon", "Brandon")
D.add_edge("Hamed", "Hamed")
D.add_edge("Austin", "Austin")

T = transitive_closure(D)

for e in D.edges(): print(e)
for n in D.nodes(): print(n)

def show(H):
    nx.draw(H, with_labels=True, font_weight='bold')
    plt.show()
#Use nx.to_numpy_matrix instead of nx.adjacency_matrix

# M = nx.adjacency_matrix(D)
# MT = nx.adjacency_matrix(T)
M = nx.to_numpy_matrix(D)
MT = nx.to_numpy_matrix(T)
M2 = M@M

def mPower(M, k): #M is numpy matrix
    assert k >= 1
    P = M
    for _ in range(k):
       P = P @ M
    return P

def tc(M):
    #compute transitive closure
    pass

D1 = nx.DiGraph(M)
D2 = nx.DiGraph(M2)

print('Matrix for Original\n', M)
N = nx.to_numpy_array(D,dtype=int)
print('np_array for Original\n', N)
print('\nMatrix for Transitive Closure\n', MT)
N2 = nx.to_numpy_array(T,dtype=int)
print('np_array for Transitive Closure\n', N2)

show(D) #can use D, T, and numpy matrix power operation
show(T)
show(T)

import sys

# sample Tuples
Tuple1 = ("A", 1, "B", 2, "C", 3)
Tuple2 = ("Geek1", "Raju", "Geek2", "Nikhil", "Geek3", "Deepanshu")
Tuple3 = ((1, "Lion"), ( 2, "Tiger"), (3, "Fox"), (4, "Wolf"))

# print the sizes of sample Tuples
print("Size of Tuple1: " + str(sys.getsizeof(Tuple1)) + "bytes")
print("Size of Tuple2: " + str(sys.getsizeof(Tuple2)) + "bytes")
print("Size of Tuple3: " + str(sys.getsizeof(Tuple3)) + "bytes")

# Python program for Plotting Fibonacci 
# spiral fractal using Turtle 
import turtle 
import math 
  
def fiboPlot(n): 
    a = 0
    b = 1
    square_a = a 
    square_b = b 
  
    # Setting the colour of the plotting pen to blue 
    x.pencolor("blue") 
  
    # Drawing the first square 
    x.forward(b * factor) 
    x.left(90) 
    x.forward(b * factor) 
    x.left(90) 
    x.forward(b * factor) 
    x.left(90) 
    x.forward(b * factor) 
  
    # Proceeding in the Fibonacci Series 
    temp = square_b 
    square_b = square_b + square_a 
    square_a = temp 
      
    # Drawing the rest of the squares 
    for i in range(1, n): 
        x.backward(square_a * factor) 
        x.right(90) 
        x.forward(square_b * factor) 
        x.left(90) 
        x.forward(square_b * factor) 
        x.left(90) 
        x.forward(square_b * factor) 
  
        # Proceeding in the Fibonacci Series 
        temp = square_b 
        square_b = square_b + square_a 
        square_a = temp 
  
    # Bringing the pen to starting point of the spiral plot 
    x.penup() 
    x.setposition(factor, 0) 
    x.seth(0) 
    x.pendown() 
  
    # Setting the colour of the plotting pen to red 
    x.pencolor("red") 
  
    # Fibonacci Spiral Plot 
    x.left(90) 
    for i in range(n): 
        print(b) 
        fdwd = math.pi * b * factor / 2
        fdwd /= 90
        for j in range(90): 
            x.forward(fdwd) 
            x.left(1) 
        temp = a 
        a = b 
        b = temp + b 
  
  
# Here 'factor' signifies the multiplicative  
# factor which expands or shrinks the scale 
# of the plot by a certain factor. 
factor = 1
  
# Taking Input for the number of  
# Iterations our Algorithm will run 
n = int(input('Enter the number of iterations (must be > 1): ')) 
  
# Plotting the Fibonacci Spiral Fractal  
# and printing the corresponding Fibonacci Number 
if n > 0: 
    print("Fibonacci series for", n, "elements :") 
    x = turtle.Turtle() 
    x.speed(100) 
    fiboPlot(n) 
    turtle.done() 
else: 
    print("Number of iterations must be > 0")

def generate_pascals_triangle(num_rows):
    triangle = []
    for row in range(num_rows):
        # Initialize the row with 1
        current_row = [1]

        # Calculate the values for the current row
        if row > 0:
            previous_row = triangle[row - 1]
            for i in range(len(previous_row) - 1):
                current_row.append(previous_row[i] + previous_row[i + 1])

        # Append 1 at the end of the row
        current_row.append(1)

        # Add the current row to the triangle
        triangle.append(current_row)

    return triangle


def display_pascals_triangle(triangle):
    for row in triangle:
        for number in row:
            print(number, end=" ")
        print()


# Prompt the user for the number of rows
num_rows = int(input("Enter the number of rows for Pascal's Triangle: "))

# Generate Pascal's Triangle
pascals_triangle = generate_pascals_triangle(num_rows)

# Display Pascal's Triangle
display_pascals_triangle(pascals_triangle)

# Python program to reverse a linked list
# Time Complexity : O(n)
# Space Complexity : O(n) as 'next'
#variable is getting created in each loop.

# Node class


class Node:

	# Constructor to initialize the node object
	def __init__(self, data):
		self.data = data
		self.next = None


class LinkedList:

	# Function to initialize head
	def __init__(self):
		self.head = None

	# Function to reverse the linked list
	def reverse(self):
		prev = None
		current = self.head
		while(current is not None):
			next = current.next
			current.next = prev
			prev = current
			current = next
		self.head = prev

	# Function to insert a new node at the beginning
	def push(self, new_data):
		new_node = Node(new_data)
		new_node.next = self.head
		self.head = new_node

	# Utility function to print the linked LinkedList
	def printList(self):
		temp = self.head
		while(temp):
			print temp.data,
			temp = temp.next


# Driver program to test above functions
llist = LinkedList()
llist.push(20)
llist.push(4)
llist.push(15)
llist.push(85)

print "Given Linked List"
llist.printList()
llist.reverse()
print "\nReversed Linked List"
llist.printList()