utils.py

#______________________________________________________________________________
# Simple Data Structures: infinity, Dict, Struct

infinity = 1.0e400
import math

def Dict(**entries):
    """Create a dict out of the argument=value arguments.
    >>> Dict(a=1, b=2, c=3)
    {'a': 1, 'c': 3, 'b': 2}
    """
    return entries


class DefaultDict(dict):
    """Dictionary with a default value for unknown keys."""

    def __init__(self, default):
        self.default = default

    def __getitem__(self, key):
        if key in self: return self.get(key)
        return self.setdefault(key, copy.deepcopy(self.default))

    def __copy__(self):
        copy = DefaultDict(self.default)
        copy.update(self)
        return copy


class Struct:
    """Create an instance with argument=value slots.
    This is for making a lightweight object whose class doesn't matter."""

    def __init__(self, **entries):
        self.__dict__.update(entries)

    def __cmp__(self, other):
        if isinstance(other, Struct):
            return cmp(self.__dict__, other.__dict__)
        else:
            return cmp(self.__dict__, other)

    def __repr__(self):
        args = ['%s=%s' % (k, repr(v)) for (k, v) in list(vars(self).items())]
        return 'Struct(%s)' % ', '.join(args)


def update(x, **entries):
    """Update a dict; or an object with slots; according to entries.
    >>> update({'a': 1}, a=10, b=20)
    {'a': 10, 'b': 20}
    >>> update(Struct(a=1), a=10, b=20)
    Struct(a=10, b=20)
    """
    if isinstance(x, dict):
        x.update(entries)
    else:
        x.__dict__.update(entries)
    return x


#______________________________________________________________________________
# Functions on Sequences (mostly inspired by Common Lisp)
# NOTE: Sequence functions (count_if, find_if, every, some) take function
# argument first (like reduce, filter, and map).

def removeall(item, seq):
    """Return a copy of seq (or string) with all occurences of item removed.
    >>> removeall(3, [1, 2, 3, 3, 2, 1, 3])
    [1, 2, 2, 1]
    >>> removeall(4, [1, 2, 3])
    [1, 2, 3]
    """
    if isinstance(seq, str):
        return seq.replace(item, '')
    else:
        return [x for x in seq if x != item]


def unique(seq):
    """Remove duplicate elements from seq. Assumes hashable elements.
    >>> unique([1, 2, 3, 2, 1])
    [1, 2, 3]
    """
    return list(set(seq))


def product(numbers):
    """Return the product of the numbers.
    >>> product([1,2,3,4])
    24
    """
    return reduce(operator.mul, numbers, 1)


def count_if(predicate, seq):
    """Count the number of elements of seq for which the predicate is true.
    >>> count_if(callable, [42, None, max, min])
    2
    """
    f = lambda count, x: count + (not not predicate(x))
    return reduce(f, seq, 0)


def find_if(predicate, seq):
    """If there is an element of seq that satisfies predicate; return it.
    >>> find_if(callable, [3, min, max])
    <built-in function min>
    >>> find_if(callable, [1, 2, 3])
    """
    for x in seq:
        if predicate(x): return x
    return None


def every(predicate, seq):
    """True if every element of seq satisfies predicate.
    >>> every(callable, [min, max])
    1
    >>> every(callable, [min, 3])
    0
    """
    for x in seq:
        if not predicate(x): return False
    return True


def some(predicate, seq):
    """If some element x of seq satisfies predicate(x), return predicate(x).
    >>> some(callable, [min, 3])
    1
    >>> some(callable, [2, 3])
    0
    """
    for x in seq:
        px = predicate(x)
        if px: return px
    return False


def isin(elt, seq):
    """Like (elt in seq), but compares with is, not ==.
    >>> e = []; isin(e, [1, e, 3])
    True
    >>> isin(e, [1, [], 3])
    False
    """
    for x in seq:
        if elt is x: return True
    return False


#______________________________________________________________________________
# Functions on sequences of numbers
# NOTE: these take the sequence argument first, like min and max,
# and like standard math notation: \sigma (i = 1..n) fn(i)
# A lot of programing is finding the best value that satisfies some condition;
# so there are three versions of argmin/argmax, depending on what you want to
# do with ties: return the first one, return them all, or pick at random.


def argmin(seq, fn):
    """Return an element with lowest fn(seq[i]) score; tie goes to first one.
    >>> argmin(['one', 'to', 'three'], len)
    'to'
    """
    best = seq[0];
    best_score = fn(best)
    for x in seq:
        x_score = fn(x)
        if x_score < best_score:
            best, best_score = x, x_score
    return best


def argmin_list(seq, fn):
    """Return a list of elements of seq[i] with the lowest fn(seq[i]) scores.
    >>> argmin_list(['one', 'to', 'three', 'or'], len)
    ['to', 'or']
    """
    best_score, best = fn(seq[0]), []
    for x in seq:
        x_score = fn(x)
        if x_score < best_score:
            best, best_score = [x], x_score
        elif x_score == best_score:
            best.append(x)
    return best


def argmin_random_tie(seq, fn):
    """Return an element with lowest fn(seq[i]) score; break ties at random.
    Thus, for all s,f: argmin_random_tie(s, f) in argmin_list(s, f)"""
    best_score = fn(seq[0]);
    n = 0
    for x in seq:
        x_score = fn(x)
        if x_score < best_score:
            best, best_score = x, x_score;
            n = 1
        elif x_score == best_score:
            n += 1
            if random.randrange(n) == 0:
                best = x
    return best


def argmax(seq, fn):
    """Return an element with highest fn(seq[i]) score; tie goes to first one.
    >>> argmax(['one', 'to', 'three'], len)
    'three'
    """
    return argmin(seq, lambda x: -fn(x))


def argmax_list(seq, fn):
    """Return a list of elements of seq[i] with the highest fn(seq[i]) scores.
    >>> argmax_list(['one', 'three', 'seven'], len)
    ['three', 'seven']
    """
    return argmin_list(seq, lambda x: -fn(x))


def argmax_random_tie(seq, fn):
    "Return an element with highest fn(seq[i]) score; break ties at random."
    return argmin_random_tie(seq, lambda x: -fn(x))


#______________________________________________________________________________
# Statistical and mathematical functions

def histogram(values, mode=0, bin_function=None):
    """Return a list of (value, count) pairs, summarizing the input values.
    Sorted by increasing value, or if mode=1, by decreasing count.
    If bin_function is given, map it over values first."""
    if bin_function: values = list(map(bin_function, values))
    bins = {}
    for val in values:
        bins[val] = bins.get(val, 0) + 1
    if mode:
        return sorted(list(bins.items()), key=lambda v: v[1], reverse=True)
    else:
        return sorted(bins.items())


def log2(x):
    """Base 2 logarithm.
    >>> log2(1024)
    10.0
    """
    return math.log10(x) / math.log10(2)


def mode(values):
    """Return the most common value in the list of values.
    >>> mode([1, 2, 3, 2])
    2
    """
    return histogram(values, mode=1)[0][0]


def median(values):
    """Return the middle value, when the values are sorted.
    If there are an odd number of elements, try to average the middle two.
    If they can't be averaged (e.g. they are strings), choose one at random.
    >>> median([10, 100, 11])
    11
    >>> median([1, 2, 3, 4])
    2.5
    """
    n = len(values)
    values = sorted(values)
    if n % 2 == 1:
        return values[n / 2]
    else:
        middle2 = values[(n / 2) - 1:(n / 2) + 1]
        try:
            return mean(middle2)
        except TypeError:
            return random.choice(middle2)


def mean(values):
    """Return the arithmetic average of the values."""
    return sum(values) / float(len(values))


def stddev(values, meanval=None):
    """The standard deviation of a set of values.
    Pass in the mean if you already know it."""
    if meanval == None: meanval = mean(values)
    return math.sqrt(sum([(x - meanval) ** 2 for x in values]) / (len(values) - 1))


def dotproduct(X, Y):
    """Return the sum of the element-wise product of vectors x and y.
    >>> dotproduct([1, 2, 3], [1000, 100, 10])
    1230
    """
    return sum([x * y for x, y in zip(X, Y)])


def vector_add(a, b):
    """Component-wise addition of two vectors.
    >>> vector_add((0, 1), (8, 9))
    (8, 10)
    """
    return tuple(map(operator.add, a, b))


def probability(p):
    "Return true with probability p."
    return p > random.uniform(0.0, 1.0)


def num_or_str(x):
    """The argument is a string; convert to a number if possible, or strip it.
    >>> num_or_str('42')
    42
    >>> num_or_str(' 42x ')
    '42x'
    """
    if isnumber(x): return x
    try:
        return int(x)
    except ValueError:
        try:
            return float(x)
        except ValueError:
            return str(x).strip()


def normalize(numbers, total=1.0):
    """Multiply each number by a constant such that the sum is 1.0 (or total).
    >>> normalize([1,2,1])
    [0.25, 0.5, 0.25]
    """
    k = total / sum(numbers)
    return [k * n for n in numbers]

## OK, the following are not as widely useful utilities as some of the other
## functions here, but they do show up wherever we have 2D grids: Wumpus and
## Vacuum worlds, TicTacToe and Checkers, and markov decision Processes.

orientations = [(1, 0), (0, 1), (-1, 0), (0, -1)]


def turn_right(orientation):
    return orientations[orientations.index(orientation) - 1]


def turn_left(orientation):
    return orientations[(orientations.index(orientation) + 1) % len(orientations)]


def distance(xxx_todo_changeme, xxx_todo_changeme1):
    "The distance between two (x, y) points."
    (ax, ay) = xxx_todo_changeme
    (bx, by) = xxx_todo_changeme1
    return math.hypot((ax - bx), (ay - by))


def distance2(xxx_todo_changeme2, xxx_todo_changeme3):
    "The square of the distance between two (x, y) points."
    (ax, ay) = xxx_todo_changeme2
    (bx, by) = xxx_todo_changeme3
    return (ax - bx) ** 2 + (ay - by) ** 2


def clip(vector, lowest, highest):
    """Return vector, except if any element is less than the corresponding
    value of lowest or more than the corresponding value of highest, clip to
    those values.
    >>> clip((-1, 10), (0, 0), (9, 9))
    (0, 9)
    """
    return type(vector)(list(map(min, list(map(max, vector, lowest)), highest)))


#______________________________________________________________________________
# Misc Functions

def printf(format, *args):
    """Format args with the first argument as format string, and write.
    Return the last arg, or format itself if there are no args."""
    sys.stdout.write(str(format) % args)
    return if_(args, args[-1], format)


def caller(n=1):
    """Return the name of the calling function n levels up in the frame stack.
    >>> caller(0)
    'caller'
    >>> def f():
    ...     return caller()
    >>> f()
    'f'
    """
    import inspect

    return inspect.getouterframes(inspect.currentframe())[n][3]


def memoize(fn, slot=None):
    """Memoize fn: make it remember the computed value for any argument list.
    If slot is specified, store result in that slot of first argument.
    If slot is false, store results in a dictionary."""
    if slot:
        def memoized_fn(obj, *args):
            if hasattr(obj, slot):
                return getattr(obj, slot)
            else:
                val = fn(obj, *args)
                setattr(obj, slot, val)
                return val
    else:
        def memoized_fn(*args):
            if args not in memoized_fn.cache:
                memoized_fn.cache[args] = fn(*args)
            return memoized_fn.cache[args]

        memoized_fn.cache = {}
    return memoized_fn


def if_(test, result, alternative):
    """Like C++ and Java's (test ? result : alternative), except
    both result and alternative are always evaluated. However, if
    either evaluates to a function, it is applied to the empty arglist,
    so you can delay execution by putting it in a lambda.
    >>> if_(2 + 2 == 4, 'ok', lambda: expensive_computation())
    'ok'
    """
    if test:
        if callable(result): return result()
        return result
    else:
        if callable(alternative): return alternative()
        return alternative


def name(object):
    "Try to find some reasonable name for the object."
    return (getattr(object, 'name', 0) or getattr(object, '__name__', 0)
            or getattr(getattr(object, '__class__', 0), '__name__', 0)
            or str(object))


def isnumber(x):
    "Is x a number? We say it is if it has a __int__ method."
    return hasattr(x, '__int__')


def issequence(x):
    "Is x a sequence? We say it is if it has a __getitem__ method."
    return hasattr(x, '__getitem__')


def print_table(table, header=None, sep=' ', numfmt='%g'):
    """Print a list of lists as a table, so that columns line up nicely.
    header, if specified, will be printed as the first row.
    numfmt is the format for all numbers; you might want e.g. '%6.2f'.
    (If you want different formats in differnt columns, don't use print_table.)
    sep is the separator between columns."""
    justs = [if_(isnumber(x), 'rjust', 'ljust') for x in table[0]]
    if header:
        table = [header] + table
    table = [[if_(isnumber(x), lambda: numfmt % x, x) for x in row]
             for row in table]
    maxlen = lambda seq: max(list(map(len, seq)))
    sizes = list(map(maxlen, list(zip(*[list(map(str, row)) for row in table]))))
    for row in table:
        for (j, size, x) in zip(justs, sizes, row):
            print(getattr(str(x), j)(size), sep, end=' ')
        print()


def AIMAFile(components, mode='r'):
    "Open a file based at the AIMA root directory."
    import utils

    dir = os.path.dirname(utils.__file__)
    return open(os.path.join(*[dir] + components), mode)


def DataFile(name, mode='r'):
    "Return a file in the AIMA /data directory."
    return AIMAFile(['..', 'data', name], mode)


#______________________________________________________________________________
# Queues: Stack, FIFOQueue

class Queue:
    """Queue is an abstract class/interface. There are three types:
        Stack(): A Last In First Out Queue.
        FIFOQueue(): A First In First Out Queue.
        PriorityQueue(lt): Queue where items are sorted by lt, (default <).
    Each type supports the following methods and functions:
        q.append(item)  -- add an item to the queue
        q.extend(items) -- equivalent to: for item in items: q.append(item)
        q.pop()         -- return the top item from the queue
        len(q)          -- number of items in q (also q.__len())
    Note that isinstance(Stack(), Queue) is false, because we implement stacks
    as lists.  If Python ever gets interfaces, Queue will be an interface."""

    def __init__(self):
        abstract

    def extend(self, items):
        for item in items:
            self.append(item)


def Stack():
    """Return an empty list, suitable as a Last-In-First-Out Queue."""
    return []


class FIFOQueue(Queue):
    """A First-In-First-Out Queue."""

    def __init__(self):
        self.A = []
        self.start = 0
        self.expanded = 0

    def append(self, item):
        self.A.append(item)

    def __len__(self):
        return len(self.A) - self.start

    def extend(self, items):
        self.A.extend(items)
        self.expanded += 1


    def pop(self):
        self.A=sorted(self.A, key=lambda x: x.path_cost) #Pendiente de revisión
        e = self.A[self.start]
        self.start += 1
        if self.start > 5 and self.start > len(self.A) / 2:
            self.A = self.A[self.start:]
            self.start = 0
        return e

class PriorityQueue(Queue):
    """Returns a sorted list by cost_so_far"""

    def __init__(self):
        self.A = []
        self.start = 0
        self.expanded = 0

    def append(self, item):
        self.A.append(item)

    def __len__(self):
        return len(self.A) - self.start

    def extend(self, items):
        self.A.extend(items)
        self.expanded += 1
        self.A.sort(key=lambda node: node.path_cost)

    def pop(self):
        e = self.A[self.start]
        self.start += 1
        if self.start > 5 and self.start > len(self.A) / 2:
            self.A = self.A[self.start:]
            self.start = 0
        return e

class PriorityQueueBabs(Queue):
    """Returns a sorted list by heuristic cost"""

    def __init__(self, problem):
        self.A = []
        self.start = 0
        self.problem = problem
        self.expanded = 0

    def append(self, item):
        self.A.append(item)

    def __len__(self):
        return len(self.A) - self.start

    def extend(self, items):
        self.A.extend(items)
        self.expanded += 1
        self.A.sort(key=lambda node: node.path_cost + self.problem.h(node))

    def pop(self):
        e = self.A[self.start]
        self.start += 1
        if self.start > 5 and self.start > len(self.A) / 2:
            self.A = self.A[self.start:]
            self.start = 0
        return e


## Fig: The idea is we can define things like Fig[3,10] later.
## Alas, it is Fig[3,10] not Fig[3.10], because that would be the same as Fig[3.1]
Fig = {}