import time
from collections import defaultdict
from inspect import getsource
import ipywidgets as widgets
import matplotlib.pyplot as plt
import networkx as nx
import numpy as np
from IPython.display import HTML
from IPython.display import display
from PIL import Image
from matplotlib import lines
from games import TicTacToe, alpha_beta_player, random_player, Fig52Extended
from learning import DataSet
from logic import parse_definite_clause, standardize_variables, unify_mm, subst
from search import GraphProblem, romania_map
# ______________________________________________________________________________
# Magic Words
def pseudocode(algorithm):
"""Print the pseudocode for the given algorithm."""
from urllib.request import urlopen
from IPython.display import Markdown
algorithm = algorithm.replace(' ', '-')
url = "https://raw.githubusercontent.com/aimacode/aima-pseudocode/master/md/{}.md".format(algorithm)
f = urlopen(url)
md = f.read().decode('utf-8')
md = md.split('\n', 1)[-1].strip()
md = '#' + md
return Markdown(md)
def psource(*functions):
"""Print the source code for the given function(s)."""
source_code = '\n\n'.join(getsource(fn) for fn in functions)
try:
from pygments.formatters import HtmlFormatter
from pygments.lexers import PythonLexer
from pygments import highlight
display(HTML(highlight(source_code, PythonLexer(), HtmlFormatter(full=True))))
except ImportError:
print(source_code)
# ______________________________________________________________________________
# Iris Visualization
def show_iris(i=0, j=1, k=2):
"""Plots the iris dataset in a 3D plot.
The three axes are given by i, j and k,
which correspond to three of the four iris features."""
plt.rcParams.update(plt.rcParamsDefault)
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
iris = DataSet(name="iris")
buckets = iris.split_values_by_classes()
features = ["Sepal Length", "Sepal Width", "Petal Length", "Petal Width"]
f1, f2, f3 = features[i], features[j], features[k]
a_setosa = [v[i] for v in buckets["setosa"]]
b_setosa = [v[j] for v in buckets["setosa"]]
c_setosa = [v[k] for v in buckets["setosa"]]
a_virginica = [v[i] for v in buckets["virginica"]]
b_virginica = [v[j] for v in buckets["virginica"]]
c_virginica = [v[k] for v in buckets["virginica"]]
a_versicolor = [v[i] for v in buckets["versicolor"]]
b_versicolor = [v[j] for v in buckets["versicolor"]]
c_versicolor = [v[k] for v in buckets["versicolor"]]
for c, m, sl, sw, pl in [('b', 's', a_setosa, b_setosa, c_setosa),
('g', '^', a_virginica, b_virginica, c_virginica),
('r', 'o', a_versicolor, b_versicolor, c_versicolor)]:
ax.scatter(sl, sw, pl, c=c, marker=m)
ax.set_xlabel(f1)
ax.set_ylabel(f2)
ax.set_zlabel(f3)
plt.show()
# ______________________________________________________________________________
# MNIST
def load_MNIST(path="aima-data/MNIST/Digits", fashion=False):
import os, struct
import array
import numpy as np
if fashion:
path = "aima-data/MNIST/Fashion"
plt.rcParams.update(plt.rcParamsDefault)
plt.rcParams['figure.figsize'] = (10.0, 8.0)
plt.rcParams['image.interpolation'] = 'nearest'
plt.rcParams['image.cmap'] = 'gray'
train_img_file = open(os.path.join(path, "train-images-idx3-ubyte"), "rb")
train_lbl_file = open(os.path.join(path, "train-labels-idx1-ubyte"), "rb")
test_img_file = open(os.path.join(path, "t10k-images-idx3-ubyte"), "rb")
test_lbl_file = open(os.path.join(path, 't10k-labels-idx1-ubyte'), "rb")
magic_nr, tr_size, tr_rows, tr_cols = struct.unpack(">IIII", train_img_file.read(16))
tr_img = array.array("B", train_img_file.read())
train_img_file.close()
magic_nr, tr_size = struct.unpack(">II", train_lbl_file.read(8))
tr_lbl = array.array("b", train_lbl_file.read())
train_lbl_file.close()
magic_nr, te_size, te_rows, te_cols = struct.unpack(">IIII", test_img_file.read(16))
te_img = array.array("B", test_img_file.read())
test_img_file.close()
magic_nr, te_size = struct.unpack(">II", test_lbl_file.read(8))
te_lbl = array.array("b", test_lbl_file.read())
test_lbl_file.close()
# print(len(tr_img), len(tr_lbl), tr_size)
# print(len(te_img), len(te_lbl), te_size)
train_img = np.zeros((tr_size, tr_rows * tr_cols), dtype=np.int16)
train_lbl = np.zeros((tr_size,), dtype=np.int8)
for i in range(tr_size):
train_img[i] = np.array(tr_img[i * tr_rows * tr_cols: (i + 1) * tr_rows * tr_cols]).reshape((tr_rows * te_cols))
train_lbl[i] = tr_lbl[i]
test_img = np.zeros((te_size, te_rows * te_cols), dtype=np.int16)
test_lbl = np.zeros((te_size,), dtype=np.int8)
for i in range(te_size):
test_img[i] = np.array(te_img[i * te_rows * te_cols: (i + 1) * te_rows * te_cols]).reshape((te_rows * te_cols))
test_lbl[i] = te_lbl[i]
return (train_img, train_lbl, test_img, test_lbl)
digit_classes = [str(i) for i in range(10)]
fashion_classes = ["T-shirt/top", "Trouser", "Pullover", "Dress", "Coat",
"Sandal", "Shirt", "Sneaker", "Bag", "Ankle boot"]
def show_MNIST(labels, images, samples=8, fashion=False):
if not fashion:
classes = digit_classes
else:
classes = fashion_classes
num_classes = len(classes)
for y, cls in enumerate(classes):
idxs = np.nonzero([i == y for i in labels])
idxs = np.random.choice(idxs[0], samples, replace=False)
for i, idx in enumerate(idxs):
plt_idx = i * num_classes + y + 1
plt.subplot(samples, num_classes, plt_idx)
plt.imshow(images[idx].reshape((28, 28)))
plt.axis("off")
if i == 0:
plt.title(cls)
plt.show()
def show_ave_MNIST(labels, images, fashion=False):
if not fashion:
item_type = "Digit"
classes = digit_classes
else:
item_type = "Apparel"
classes = fashion_classes
num_classes = len(classes)
for y, cls in enumerate(classes):
idxs = np.nonzero([i == y for i in labels])
print(item_type, y, ":", len(idxs[0]), "images.")
ave_img = np.mean(np.vstack([images[i] for i in idxs[0]]), axis=0)
# print(ave_img.shape)
plt.subplot(1, num_classes, y + 1)
plt.imshow(ave_img.reshape((28, 28)))
plt.axis("off")
plt.title(cls)
plt.show()
# ______________________________________________________________________________
# MDP
def make_plot_grid_step_function(columns, rows, U_over_time):
"""ipywidgets interactive function supports single parameter as input.
This function creates and return such a function by taking as input
other parameters."""
def plot_grid_step(iteration):
data = U_over_time[iteration]
data = defaultdict(lambda: 0, data)
grid = []
for row in range(rows):
current_row = []
for column in range(columns):
current_row.append(data[(column, row)])
grid.append(current_row)
grid.reverse() # output like book
fig = plt.imshow(grid, cmap=plt.cm.bwr, interpolation='nearest')
plt.axis('off')
fig.axes.get_xaxis().set_visible(False)
fig.axes.get_yaxis().set_visible(False)
for col in range(len(grid)):
for row in range(len(grid[0])):
magic = grid[col][row]
fig.axes.text(row, col, "{0:.2f}".format(magic), va='center', ha='center')
plt.show()
return plot_grid_step
def make_visualize(slider):
"""Takes an input a sliderand returns callback function
for timer and animation."""
def visualize_callback(visualize, time_step):
if visualize is True:
for i in range(slider.min, slider.max + 1):
slider.value = i
time.sleep(float(time_step))
return visualize_callback
# ______________________________________________________________________________
_canvas = """
""" # noqa
class Canvas:
"""Inherit from this class to manage the HTML canvas element in jupyter notebooks.
To create an object of this class any_name_xyz = Canvas("any_name_xyz")
The first argument given must be the name of the object being created.
IPython must be able to reference the variable name that is being passed."""
def __init__(self, varname, width=800, height=600, cid=None):
self.name = varname
self.cid = cid or varname
self.width = width
self.height = height
self.html = _canvas.format(self.cid, self.width, self.height, self.name)
self.exec_list = []
display_html(self.html)
def mouse_click(self, x, y):
"""Override this method to handle mouse click at position (x, y)"""
raise NotImplementedError
def mouse_move(self, x, y):
raise NotImplementedError
def execute(self, exec_str):
"""Stores the command to be executed to a list which is used later during update()"""
if not isinstance(exec_str, str):
print("Invalid execution argument:", exec_str)
self.alert("Received invalid execution command format")
prefix = "{0}_canvas_object.".format(self.cid)
self.exec_list.append(prefix + exec_str + ';')
def fill(self, r, g, b):
"""Changes the fill color to a color in rgb format"""
self.execute("fill({0}, {1}, {2})".format(r, g, b))
def stroke(self, r, g, b):
"""Changes the colors of line/strokes to rgb"""
self.execute("stroke({0}, {1}, {2})".format(r, g, b))
def strokeWidth(self, w):
"""Changes the width of lines/strokes to 'w' pixels"""
self.execute("strokeWidth({0})".format(w))
def rect(self, x, y, w, h):
"""Draw a rectangle with 'w' width, 'h' height and (x, y) as the top-left corner"""
self.execute("rect({0}, {1}, {2}, {3})".format(x, y, w, h))
def rect_n(self, xn, yn, wn, hn):
"""Similar to rect(), but the dimensions are normalized to fall between 0 and 1"""
x = round(xn * self.width)
y = round(yn * self.height)
w = round(wn * self.width)
h = round(hn * self.height)
self.rect(x, y, w, h)
def line(self, x1, y1, x2, y2):
"""Draw a line from (x1, y1) to (x2, y2)"""
self.execute("line({0}, {1}, {2}, {3})".format(x1, y1, x2, y2))
def line_n(self, x1n, y1n, x2n, y2n):
"""Similar to line(), but the dimensions are normalized to fall between 0 and 1"""
x1 = round(x1n * self.width)
y1 = round(y1n * self.height)
x2 = round(x2n * self.width)
y2 = round(y2n * self.height)
self.line(x1, y1, x2, y2)
def arc(self, x, y, r, start, stop):
"""Draw an arc with (x, y) as centre, 'r' as radius from angles 'start' to 'stop'"""
self.execute("arc({0}, {1}, {2}, {3}, {4})".format(x, y, r, start, stop))
def arc_n(self, xn, yn, rn, start, stop):
"""Similar to arc(), but the dimensions are normalized to fall between 0 and 1
The normalizing factor for radius is selected between width and height by
seeing which is smaller."""
x = round(xn * self.width)
y = round(yn * self.height)
r = round(rn * min(self.width, self.height))
self.arc(x, y, r, start, stop)
def clear(self):
"""Clear the HTML canvas"""
self.execute("clear()")
def font(self, font):
"""Changes the font of text"""
self.execute('font("{0}")'.format(font))
def text(self, txt, x, y, fill=True):
"""Display a text at (x, y)"""
if fill:
self.execute('fill_text("{0}", {1}, {2})'.format(txt, x, y))
else:
self.execute('stroke_text("{0}", {1}, {2})'.format(txt, x, y))
def text_n(self, txt, xn, yn, fill=True):
"""Similar to text(), but with normalized coordinates"""
x = round(xn * self.width)
y = round(yn * self.height)
self.text(txt, x, y, fill)
def alert(self, message):
"""Immediately display an alert"""
display_html(''.format(message))
def update(self):
"""Execute the JS code to execute the commands queued by execute()"""
exec_code = ""
self.exec_list = []
display_html(exec_code)
def display_html(html_string):
display(HTML(html_string))
################################################################################
class Canvas_TicTacToe(Canvas):
"""Play a 3x3 TicTacToe game on HTML canvas"""
def __init__(self, varname, player_1='human', player_2='random',
width=300, height=350, cid=None):
valid_players = ('human', 'random', 'alpha_beta')
if player_1 not in valid_players or player_2 not in valid_players:
raise TypeError("Players must be one of {}".format(valid_players))
super().__init__(varname, width, height, cid)
self.ttt = TicTacToe()
self.state = self.ttt.initial
self.turn = 0
self.strokeWidth(5)
self.players = (player_1, player_2)
self.font("20px Arial")
self.draw_board()
def mouse_click(self, x, y):
player = self.players[self.turn]
if self.ttt.terminal_test(self.state):
if 0.55