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Plotting Fibonacci

Nov 19, 2022CodeCatch
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Palindrome checker

Nov 19, 2022CodeCatch

0 likes • 6 views

# function which return reverse of a string
def isPalindrome(s):
return s == s[::-1]
# Driver code
s = "malayalam"
ans = isPalindrome(s)
if ans:
print("Yes")
else:
print("No")

UNT CSCE 2100 Assignment 6

Nov 18, 2022AustinLeath

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"""
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)

Compute all the Permutation of a String

May 31, 2023CodeCatch

0 likes • 2 views

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)

Shuffle Deck of Cards

May 31, 2023CodeCatch

0 likes • 1 view

import random
# Define the ranks, suits, and create a deck
ranks = ['Ace', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'Jack', 'Queen', 'King']
suits = ['Hearts', 'Diamonds', 'Clubs', 'Spades']
deck = [(rank, suit) for rank in ranks for suit in suits]
# Shuffle the deck
random.shuffle(deck)
# Display the shuffled deck
for card in deck:
print(card[0], "of", card[1])

print indices

Nov 18, 2022AustinLeath

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# List
lst = [1, 2, 3, 'Alice', 'Alice']
# One-Liner
indices = [i for i in range(len(lst)) if lst[i]=='Alice']
# Result
print(indices)
# [3, 4]

Return Letter Combinations

Nov 18, 2022AustinLeath

0 likes • 0 views

# @return a list of strings, [s1, s2]
def letterCombinations(self, digits):
if '' == digits: return []
kvmaps = {
'2': 'abc',
'3': 'def',
'4': 'ghi',
'5': 'jkl',
'6': 'mno',
'7': 'pqrs',
'8': 'tuv',
'9': 'wxyz'
}
return reduce(lambda acc, digit: [x + y for x in acc for y in kvmaps[digit]], digits, [''])