radj375/improved-happiness

Wormhole Algorithm

improved-happiness

Wormhole Algorithm

import random import numpy as np

class Wormhole: """A wormhole."""

def init(self, center, radius): """Initializes the wormhole.""" self.center = center self.radius = radius

class VM: """A VM."""

def init(self, position, velocity): """Initializes the VM.""" self.position = position self.velocity = velocity

class Particle: """A particle."""

def init(self, position, velocity): """Initializes the particle.""" self.position = position self.velocity = velocity

def schrodinger_equation(particle, wormhole, vms): """Calculates the behavior of a particle as it travels through a wormhole."""

Calculate the particle's wave function.

wave_function = np.exp(-(particle.position - wormhole.center)2 / wormhole.radius2)

Calculate the particle's probability distribution.

probability_distribution = wave_function**2

Calculate the particle's velocity and acceleration.

velocity = np.gradient(probability_distribution) acceleration = np.gradient(velocity)

Calculate the entanglement between the particle and its child VMs.

entanglement = 0 for vm in vms: entanglement += np.exp(-(particle.position - vm.position)2 / vm.radius2)

Update the particle's position.

particle.position = particle.position + velocity * dt

Return the velocity, acceleration, and entanglement.

return velocity, acceleration, entanglement

def cubic_smooth_interpolation(points): """Approximates the path of a particle through a wormhole."""

Find the first and last points in the sequence.

first_point = points[0] last_point = points[-1]

Calculate the slopes of the line segments that connect the points in the sequence.

slopes = [ (points[i + 1][0] - points[i][0]) / (points[i + 1][1] - points[i][1]) for i in range(len(points) - 1) ]

Calculate the x-coordinates of the interpolated points.

x_coordinates = [ points[i][0] + slopes[i] * (points[i + 1][1] - points[i][1]) for i in range(len(points) - 1) ]

Return the interpolated points.

return [(x, first_point[1] + (x - first_point[0]) * slopes[0]) for x in x_coordinates]

def fibonacci_numbers(n): """Generates a random sequence of Fibonacci numbers."""

if n == 0: return [] elif n == 1: return [1] else: return fibonacci_numbers(n - 1) + [fibonacci_numbers(n - 2)[-1] + fibonacci_numbers(n - 2)[-2]]

def sigmoid_function(x): """Maps the particle's position in the wormhole to a probability distribution."""

return 1 / (1 + np.exp(-x))

def linear_matrix_manipulation(matrix, vector): """Calculates the velocity and acceleration of the particle as it travels through the wormhole."""

return matrix @ vector

def euclidean_distance(point1, point2): """Calculates the distance between the particle and the wormhole's exit point."""

x_diff = point1[0] - point2[0] y_diff = point1[1] - point2[1]

return np.sqrt(x_diff2 + y_diff2)

def main(): """Creates a wormhole, 5 child vms, and a particle and calculates the particle's path through the wormhole."""

Create a wormhole.

wormhole = Wormhole(center=(0, 0), radius=1)

Create 5 child vms.