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Radix sort

Nov 19, 2022CodeCatch
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AnyTree Randomizer

Apr 15, 2021NoahEaton

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import anytree as at
import random as rm
# Generate a tree with node_count many nodes. Each has a number key that shows when it was made and a randomly selected color, red or white.
def random_tree(node_count):
# Generates the list of nodes
nodes = []
for i in range(node_count):
test = rm.randint(1,2)
if test == 1:
nodes.append(at.Node(str(i),color="white"))
else:
nodes.append(at.Node(str(i),color="red"))
#Creates the various main branches
for i in range(node_count):
for j in range(i, len(nodes)):
test = rm.randint(1,len(nodes))
if test == 1 and nodes[j].parent == None and (not nodes[i] == nodes[j]):
nodes[j].parent = nodes[i]
#Collects all the main branches into a single tree with the first node being the root
for i in range(1, node_count):
if nodes[i].parent == None and (not nodes[i] == nodes[0]):
nodes[i].parent = nodes[0]
return nodes[0]

Find Coin

Oct 4, 2023AustinLeath

0 likes • 10 views

weigh = lambda a,b: sum(b)-sum(a)
FindCoin = lambda A: 0 if (n := len(A)) == 1 else (m := n//3) * (w := 1 + weigh(A[:m], A[2*m:])) + FindCoin(A[m*w:m*(w+1)])
print(FindCoin([1,1,1,1,1,1,1,2,1]))

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)

return byte size

Nov 19, 2022CodeCatch

0 likes • 1 view

def byte_size(s):
return len(s.encode('utf-8'))
byte_size('😀') # 4
byte_size('Hello World') # 11

Bogo Sort

Nov 19, 2022CodeCatch

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# Python program for implementation of Bogo Sort
import random
# Sorts array a[0..n-1] using Bogo sort
def bogoSort(a):
n = len(a)
while (is_sorted(a)== False):
shuffle(a)
# To check if array is sorted or not
def is_sorted(a):
n = len(a)
for i in range(0, n-1):
if (a[i] > a[i+1] ):
return False
return True
# To generate permuatation of the array
def shuffle(a):
n = len(a)
for i in range (0,n):
r = random.randint(0,n-1)
a[i], a[r] = a[r], a[i]
# Driver code to test above
a = [3, 2, 4, 1, 0, 5]
bogoSort(a)
print("Sorted array :")
for i in range(len(a)):
print ("%d" %a[i]),

Factorial of N

Nov 19, 2022CodeCatch

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import math
def factorial(n):
print(math.factorial(n))
return (math.factorial(n))
factorial(5)
factorial(10)
factorial(15)