def when(predicate, when_true):
  return lambda x: when_true(x) if predicate(x) else x

double_even_numbers = when(lambda x: x % 2 == 0, lambda x : x * 2)
print(double_even_numbers(2)) # 4
print(double_even_numbers(1)) # 1

def key_of_min(d):
  return min(d, key = d.get)

key_of_min({'a':4, 'b':0, 'c':13}) # b

# Function to multiply two matrices
def multiply_matrices(matrix1, matrix2):
    # Check if the matrices can be multiplied
    if len(matrix1[0]) != len(matrix2):
        print("Error: The number of columns in the first matrix must be equal to the number of rows in the second matrix.")
        return None

    # Create the result matrix filled with zeros
    result = [[0 for _ in range(len(matrix2[0]))] for _ in range(len(matrix1))]

    # Perform matrix multiplication
    for i in range(len(matrix1)):
        for j in range(len(matrix2[0])):
            for k in range(len(matrix2)):
                result[i][j] += matrix1[i][k] * matrix2[k][j]

    return result

# Example matrices
matrix1 = [[1, 2, 3],
           [4, 5, 6],
           [7, 8, 9]]

matrix2 = [[10, 11],
           [12, 13],
           [14, 15]]

# Multiply the matrices
result_matrix = multiply_matrices(matrix1, matrix2)

# Display the result
if result_matrix is not None:
    print("Result:")
    for row in result_matrix:
        print(row)

"""
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 = [email protected]

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 itertools

def compute_permutations(string):
    # Generate all permutations of the string
    permutations = itertools.permutations(string)

    # Convert each permutation tuple to a string
    permutations = [''.join(permutation) for permutation in permutations]

    return permutations

# Prompt the user for a string
string = input("Enter a string: ")

# Compute permutations
permutations = compute_permutations(string)

# Display the permutations
print("Permutations:")
for permutation in permutations:
    print(permutation)

def get_ldap_user(member_cn, user, passwrd):
    '''
    Get an LDAP user and return the SAMAccountName
    '''
    #---- Setting up the Connection
    #account used for binding - Avoid putting these in version control
    bindDN = str(user) + "@unt.ad.unt.edu"
    bindPass = passwrd

    #set some tuneables for the LDAP library.
    ldap.set_option(ldap.OPT_X_TLS_REQUIRE_CERT, ldap.OPT_X_TLS_ALLOW)
    #ldap.set_option(ldap.OPT_X_TLS_CACERTFILE, CACERTFILE)
    
    conn = ldap.initialize('ldaps://unt.ad.unt.edu')
    conn.protocol_version = 3
    conn.set_option(ldap.OPT_REFERRALS, 0)

    #authenticate the connection so that you can make additional queries
    try:
        result = conn.simple_bind_s(bindDN, bindPass) 
    except ldap.INVALID_CREDENTIALS:
        result = "Invalid credentials for %s" % user
        sys.exit()

    #build query in the form of (uid=user)
    ldap_query = '(|(displayName=' + member_cn + ')(cn='+ member_cn + ')(name=' + member_cn + '))'
    ldap_info = conn.search_s('DC=unt,DC=ad,DC=unt,DC=edu', ldap.SCOPE_SUBTREE, filterstr=ldap_query)
    sAMAccountName = str(ldap_info[0][1]['sAMAccountName']).replace("[b'", "").replace("']","")
    return sAMAccountName