print(“Hello World”)

"""
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)

from math import pi

def rads_to_degrees(rad):
  return (rad * 180.0) / pi

rads_to_degrees(pi / 2) # 90.0

""" Binary Search Algorithm 
----------------------------------------
"""
#iterative implementation of binary search in Python
def binary_search(a_list, item):
    """Performs iterative binary search to find the position of an integer in a given, sorted, list.
    a_list -- sorted list of integers
    item -- integer you are searching for the position of
    """
    first = 0
    last = len(a_list) - 1
    while first <= last:
        i = (first + last) / 2
        if a_list[i] == item:
            return ' found at position '.format(item=item, i=i)
        elif a_list[i] > item:
            last = i - 1
        elif a_list[i] < item:
            first = i + 1
        else:
            return ' not found in the list'.format(item=item)
#recursive implementation of binary search in Python
def binary_search_recursive(a_list, item):
    """Performs recursive binary search of an integer in a given, sorted, list.
    a_list -- sorted list of integers
    item -- integer you are searching for the position of
    """
    first = 0
    last = len(a_list) - 1
    if len(a_list) == 0:
        return ' was not found in the list'.format(item=item)
    else:
        i = (first + last) // 2
        if item == a_list[i]:
            return ' found'.format(item=item)
        else:
            if a_list[i] < item:
                return binary_search_recursive(a_list[i+1:], item)
            else:
                return binary_search_recursive(a_list[:i], item)

# question3.py
from itertools import product
V='∀'
E='∃'

def tt(f,n) :
  xss=product((0,1),repeat=n)
  print('function:',f.__name__)
  for xs in xss : print(*xs,':',int(f(*xs)))
  print('')

# this is the logic for part A (p\/q\/r) /\ (p\/q\/~r) /\ (p\/~q\/r) /\ (p\/~q\/~r) /\ (~p\/q\/r) /\ (~p\/q\/~r) /\ (~p\/~q\/r) /\ (~p\/~q\/~r)

def parta(p,q,r) :
  
  a=(p or q or r) and (p or q or not r) and (p or not q or r)and (p or not q or  not r)
  b=(not p or q or r ) and (not p or q or not r) and (not p or not q or r) and (not p or not q or not r)
  c= a and b
  return c

def partb(p,q,r) :
  a=(p or q and r) and (p or not q or not r) and (p or not q or not  r)and (p or q or  not r)
  b=(not p or q or r ) and (not p or q or not r) and (not p or not q or r) and (not p or not q or not r)
  c= a and b
  return c

print("part A:")
tt(parta,3)

print("part B:")
tt(partb,3)

# Function to check Armstrong number
def is_armstrong_number(number):
    # Convert number to string to iterate over its digits
    num_str = str(number)
    
    # Calculate the sum of the cubes of each digit
    digit_sum = sum(int(digit) ** len(num_str) for digit in num_str)
    
    # Compare the sum with the original number
    if digit_sum == number:
        return True
    else:
        return False

# Prompt user for a number
number = int(input("Enter a number: "))

# Check if the number is an Armstrong number
if is_armstrong_number(number):
    print(number, "is an Armstrong number.")
else:
    print(number, "is not an Armstrong number.")