knosmos

import numpy as np
import matplotlib.pyplot as plt

# Functions
def sigmoid(x): # Sigmoidal activation function
    return 1 / (1 + np.exp(-x))

def sigmoid_prime(x): # Derivative of sigmoid
    return sigmoid(x) * (1 - sigmoid(x))

knosmos

words = open("words.txt").read().split("\n")

def partition(word, words):
    # Get how many words will remain for each possible response
    partitions = []
    for a in "MCW":
        for b in "MCW":
            for c in "MCW":
                for d in "MCW":
                    for e in "MCW":

knosmos

# Bower-Watson for Delaunay triangulation
# Mitchell's best-candidate algorithm for semi-random points

import math, random
import pygame, pygame.gfxdraw
from pygame.locals import *
pygame.init()
screen = pygame.display.set_mode((600,600))
pygame.display.set_caption('Delaunay Triangulation')
pygame.mouse.set_visible(False)

knosmos

import curses, time, random
from curses import wrapper

snow = []

def draw(s, on):
    global snow
    s.clear()

    # Star