fernandotenorio

import numpy as np

class Linalg(object):
	Zero = np.array([[1.0], [0.0]])
	One = np.array([[0.0], [1.0]])
	Plus = (Zero + One)/np.linalg.norm(Zero + One)

	P0 = np.dot(Zero, Zero.T)
	P1 = np.dot(One, One.T)

fernandotenorio

import numpy as np

class Gate(object):
	# Identity
	I = np.eye(2)

	# Hadamard
	H = (1.0/np.sqrt(2)) * np.array([[1, 1], [1, -1]])

	# Pauli-X (NOT)

fernandotenorio

from CA import CARoom, CACell
from itertools import product
import multiprocessing as mp
import numpy as np
from CustomRoom import CustomRoom

class Experiment(object):
	def __init__(self, repeats=30):
		self.repeats = repeats
		self.results = []

fernandotenorio

import pygame
from pygame import gfxdraw
from CA import CACell, CARoom
from random import random, randint, seed, Random
from CustomRoom import CustomRoom

class SimuPanel(object):
	def __init__(self, room, cell_size_px):
		self.room = room
		self.cell_size_px = cell_size_px

fernandotenorio

from CA import CARoom, CACell
from itertools import product
from random import random, Random
import multiprocessing as mp

class CustomRoom(object):
	@staticmethod
	def make_2_obstacle_room(full_factor=0.67, pos_seed=None, panic_prob=0.01, exit_size=2):
		room_w = 20
		room_h = 20

fernandotenorio

from itertools import product
from math import ceil
from dijkstra import dijkstra
import numpy as np
from random import shuffle, choice, random


class CACell(object):
	EMPTY_STATE = 0
	PERSON_STATE = 1

fernandotenorio

from queue import PriorityQueue

def dijkstra(edges, start_vertex):
	D = {v:float('inf') for v in edges}
	D[start_vertex] = 0

	pq = PriorityQueue()
	pq.put((0, start_vertex))
	visited = []

fernandotenorio

get.testbed = function(arms = 10, plays = 500, u = 0, sdev.arm = 1, sdev.rewards = 1){
  
  optimal = rnorm(arms, u, sdev.arm)
  rewards = sapply(optimal, function(x)rnorm(plays, x, sdev.rewards))
  
  list(optimal = optimal, rewards = rewards)
}

play.slots = function(arms = 10, plays = 500, u = 0, sdev.arm = 1, sdev.rewards = 1, eps = 0.1){
  

fernandotenorio

# TSP with 10 cities around a circular pattern
 require(gaoptim)

 op <- par(mfrow = c(2, 1))
 n = 10
 R = 10
 angs = seq(0, 2*pi, length = n)
 xp = R * cos(angs) + rnorm(n)
 yp = R * sin(angs) + rnorm(n)
 xp = c(xp, xp[1])

fernandotenorio

get.dist = function(x)
{
  sqrt(x[1]^2 + x[2]^2)
}

get.pairs = function(N)
{
  M = matrix(0, nrow = N * (N - 1)/2, ncol = 2)
  x = 1:N
  k = 1