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|
- # util.py
- # -------
- # Licensing Information: Please do not distribute or publish solutions to this
- # project. You are free to use and extend these projects for educational
- # purposes. The Pacman AI projects were developed at UC Berkeley, primarily by
- # John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
- # For more info, see http://inst.eecs.berkeley.edu/~cs188/sp09/pacman.html
- import sys
- import inspect
- import heapq, random
- """
- Data structures useful for implementing SearchAgents
- """
- class Stack:
- "A container with a last-in-first-out (LIFO) queuing policy."
- def __init__(self):
- self.list = []
- def push(self, item):
- "Push 'item' onto the stack"
- self.list.append(item)
- def pop(self):
- "Pop the most recently pushed item from the stack"
- return self.list.pop()
- def isEmpty(self):
- "Returns true if the stack is empty"
- return len(self.list) == 0
- class Queue:
- "A container with a first-in-first-out (FIFO) queuing policy."
- def __init__(self):
- self.list = []
- def push(self, item):
- "Enqueue the 'item' into the queue"
- self.list.insert(0, item)
- def pop(self):
- """
- Dequeue the earliest enqueued item still in the queue. This
- operation removes the item from the queue.
- """
- return self.list.pop()
- def isEmpty(self):
- "Returns true if the queue is empty"
- return len(self.list) == 0
- class PriorityQueue:
- """
- Implements a priority queue data structure. Each inserted item
- has a priority associated with it and the client is usually interested
- in quick retrieval of the lowest-priority item in the queue. This
- data structure allows O(1) access to the lowest-priority item.
-
- Note that this PriorityQueue does not allow you to change the priority
- of an item. However, you may insert the same item multiple times with
- different priorities.
- """
- def __init__(self):
- self.heap = []
- self.init = False
- def push(self, item, priority):
- if not self.init:
- self.init = True
- try:
- item < item
- except:
- item.__class__.__lt__ = lambda x, y: (True)
- pair = (priority, item)
- heapq.heappush(self.heap, pair)
- def pop(self):
- (priority, item) = heapq.heappop(self.heap)
- return item
- def isEmpty(self):
- return len(self.heap) == 0
- class PriorityQueueWithFunction(PriorityQueue):
- """
- Implements a priority queue with the same push/pop signature of the
- Queue and the Stack classes. This is designed for drop-in replacement for
- those two classes. The caller has to provide a priority function, which
- extracts each item's priority.
- """
- def __init__(self, priorityFunction):
- "priorityFunction (item) -> priority"
- self.priorityFunction = priorityFunction # store the priority function
- PriorityQueue.__init__(self) # super-class initializer
- def push(self, item):
- "Adds an item to the queue with priority from the priority function"
- PriorityQueue.push(self, item, self.priorityFunction(item))
- def manhattanDistance(xy1, xy2):
- "Returns the Manhattan distance between points xy1 and xy2"
- return abs(xy1[0] - xy2[0]) + abs(xy1[1] - xy2[1])
- """
- Data structures and functions useful for various course projects
-
- The search project should not need anything below this line.
- """
- class Counter(dict):
- """
- A counter keeps track of counts for a set of keys.
-
- The counter class is an extension of the standard python
- dictionary type. It is specialized to have number values
- (integers or floats), and includes a handful of additional
- functions to ease the task of counting data. In particular,
- all keys are defaulted to have value 0. Using a dictionary:
-
- a = {}
- print(a['test'])
-
- would give an error, while the Counter class analogue:
-
- >>> a = Counter()
- >>> print(a['test'])
- 0
- returns the default 0 value. Note that to reference a key
- that you know is contained in the counter,
- you can still use the dictionary syntax:
-
- >>> a = Counter()
- >>> a['test'] = 2
- >>> print(a['test'])
- 2
-
- This is very useful for counting things without initializing their counts,
- see for example:
-
- >>> a['blah'] += 1
- >>> print(a['blah'])
- 1
-
- The counter also includes additional functionality useful in implementing
- the classifiers for this assignment. Two counters can be added,
- subtracted or multiplied together. See below for details. They can
- also be normalized and their total count and arg max can be extracted.
- """
- def __getitem__(self, idx):
- self.setdefault(idx, 0)
- return dict.__getitem__(self, idx)
- def incrementAll(self, keys, count):
- """
- Increments all elements of keys by the same count.
-
- >>> a = Counter()
- >>> a.incrementAll(['one','two', 'three'], 1)
- >>> a['one']
- 1
- >>> a['two']
- 1
- """
- for key in keys:
- self[key] += count
- def argMax(self):
- """
- Returns the key with the highest value.
- """
- if len(self.keys()) == 0: return None
- all = list(self.items())
- values = [x[1] for x in all]
- maxIndex = values.index(max(values))
- return all[maxIndex][0]
- def sortedKeys(self):
- """
- Returns a list of keys sorted by their values. Keys
- with the highest values will appear first.
-
- >>> a = Counter()
- >>> a['first'] = -2
- >>> a['second'] = 4
- >>> a['third'] = 1
- >>> a.sortedKeys()
- ['second', 'third', 'first']
- """
- sortedItems = list(self.items())
- sortedItems.sort(key=lambda item: -item[1])
- return [x[0] for x in sortedItems]
- def totalCount(self):
- """
- Returns the sum of counts for all keys.
- """
- return sum(self.values())
- def normalize(self):
- """
- Edits the counter such that the total count of all
- keys sums to 1. The ratio of counts for all keys
- will remain the same. Note that normalizing an empty
- Counter will result in an error.
- """
- total = float(self.totalCount())
- if total == 0: return
- for key in self.keys():
- self[key] = self[key] / total
- def divideAll(self, divisor):
- """
- Divides all counts by divisor
- """
- divisor = float(divisor)
- for key in self:
- self[key] /= divisor
- def copy(self):
- """
- Returns a copy of the counter
- """
- return Counter(dict.copy(self))
- def __mul__(self, y):
- """
- Multiplying two counters gives the dot product of their vectors where
- each unique label is a vector element.
-
- >>> a = Counter()
- >>> b = Counter()
- >>> a['first'] = -2
- >>> a['second'] = 4
- >>> b['first'] = 3
- >>> b['second'] = 5
- >>> a['third'] = 1.5
- >>> a['fourth'] = 2.5
- >>> a * b
- 14
- """
- sum = 0
- x = self
- if len(x) > len(y):
- x, y = y, x
- for key in x:
- if key not in y:
- continue
- sum += x[key] * y[key]
- return sum
- def __radd__(self, y):
- """
- Adding another counter to a counter increments the current counter
- by the values stored in the second counter.
-
- >>> a = Counter()
- >>> b = Counter()
- >>> a['first'] = -2
- >>> a['second'] = 4
- >>> b['first'] = 3
- >>> b['third'] = 1
- >>> a += b
- >>> a['first']
- 1
- """
- for key, value in y.items():
- self[key] += value
- def __add__(self, y):
- """
- Adding two counters gives a counter with the union of all keys and
- counts of the second added to counts of the first.
- >>> a = Counter()
- >>> b = Counter()
- >>> a['first'] = -2
- >>> a['second'] = 4
- >>> b['first'] = 3
- >>> b['third'] = 1
- >>> (a + b)['first']
- 1
- """
- addend = Counter()
- for key in self:
- if key in y:
- addend[key] = self[key] + y[key]
- else:
- addend[key] = self[key]
- for key in y:
- if key in self:
- continue
- addend[key] = y[key]
- return addend
- def __sub__(self, y):
- """
- Subtracting a counter from another gives a counter with the union of all keys and
- counts of the second subtracted from counts of the first.
- >>> a = Counter()
- >>> b = Counter()
- >>> a['first'] = -2
- >>> a['second'] = 4
- >>> b['first'] = 3
- >>> b['third'] = 1
- >>> (a - b)['first']
- -5
- """
- addend = Counter()
- for key in self:
- if key in y:
- addend[key] = self[key] - y[key]
- else:
- addend[key] = self[key]
- for key in y:
- if key in self:
- continue
- addend[key] = -1 * y[key]
- return addend
- def raiseNotDefined():
- print("Method not implemented: %s" % inspect.stack()[1][3])
- sys.exit(1)
- def normalize(vectorOrCounter):
- """
- normalize a vector or counter by dividing each value by the sum of all values
- """
- normalizedCounter = Counter()
- if type(vectorOrCounter) == type(normalizedCounter):
- counter = vectorOrCounter
- total = float(counter.totalCount())
- if total == 0: return counter
- for key in counter.keys():
- value = counter[key]
- normalizedCounter[key] = value / total
- return normalizedCounter
- else:
- vector = vectorOrCounter
- s = float(sum(vector))
- if s == 0: return vector
- return [el / s for el in vector]
- def nSample(distribution, values, n):
- if sum(distribution) != 1:
- distribution = normalize(distribution)
- rand = [random.random() for i in range(n)]
- rand.sort()
- samples = []
- samplePos, distPos, cdf = 0, 0, distribution[0]
- while samplePos < n:
- if rand[samplePos] < cdf:
- samplePos += 1
- samples.append(values[distPos])
- else:
- distPos += 1
- cdf += distribution[distPos]
- return samples
- def sample(distribution, values=None):
- if type(distribution) == Counter:
- items = distribution.items()
- distribution = [i[1] for i in items]
- values = [i[0] for i in items]
- if sum(distribution) != 1:
- distribution = normalize(distribution)
- choice = random.random()
- i, total = 0, distribution[0]
- while choice > total:
- i += 1
- total += distribution[i]
- return values[i]
- def sampleFromCounter(ctr):
- items = ctr.items()
- return sample([v for k, v in items], [k for k, v in items])
- def getProbability(value, distribution, values):
- """
- Gives the probability of a value under a discrete distribution
- defined by (distributions, values).
- """
- total = 0.0
- for prob, val in zip(distribution, values):
- if val == value:
- total += prob
- return total
- def flipCoin(p):
- r = random.random()
- return r < p
- def chooseFromDistribution(distribution):
- """
- Takes either a counter or a list of (prob, key) pairs and samples
- """
- if type(distribution) == dict or type(distribution) == Counter:
- return sample(distribution)
- r = random.random()
- base = 0.0
- for prob, element in distribution:
- base += prob
- if r <= base: return element
- def nearestPoint(pos):
- """
- Finds the nearest grid point to a position (discretizes).
- """
- (current_row, current_col) = pos
- grid_row = int(current_row + 0.5)
- grid_col = int(current_col + 0.5)
- return (grid_row, grid_col)
- def sign(x):
- """
- Returns 1 or -1 depending on the sign of x
- """
- if (x >= 0):
- return 1
- else:
- return -1
- def arrayInvert(array):
- """
- Inverts a matrix stored as a list of lists.
- """
- result = [[] for i in array]
- for outer in array:
- for inner in range(len(outer)):
- result[inner].append(outer[inner])
- return result
- def matrixAsList(matrix, value=True):
- """
- Turns a matrix into a list of coordinates matching the specified value
- """
- rows, cols = len(matrix), len(matrix[0])
- cells = []
- for row in range(rows):
- for col in range(cols):
- if matrix[row][col] == value:
- cells.append((row, col))
- return cells
- def lookup(name, namespace):
- """
- Get a method or class from any imported module from its name.
- Usage: lookup(functionName, globals())
- """
- dots = name.count('.')
- if dots > 0:
- moduleName, objName = '.'.join(name.split('.')[:-1]), name.split('.')[-1]
- module = __import__(moduleName)
- return getattr(module, objName)
- else:
- modules = [obj for obj in namespace.values() if str(type(obj)) == "<type 'module'>"]
- options = [getattr(module, name) for module in modules if name in dir(module)]
- options += [obj[1] for obj in namespace.items() if obj[0] == name]
- if len(options) == 1: return options[0]
- if len(options) > 1: raise Exception('Name conflict for %s')
- raise Exception('%s not found as a method or class' % name)
- def pause():
- """
- Pauses the output stream awaiting user feedback.
- """
- print("<Press enter/return to continue>")
- input()
- ## code to handle timeouts
- import signal
- class TimeoutFunctionException(Exception):
- """
- Exception to raise on a timeout
- """
- pass
- class TimeoutFunction:
- def __init__(self, function, timeout):
- """
- timeout must be at least 1 second. WHY??
- """
- self.timeout = timeout
- self.function = function
- def handle_timeout(self, signum, frame):
- raise TimeoutFunctionException()
- def __call__(self, *args):
- if not 'SIGALRM' in dir(signal):
- return self.function(*args)
- old = signal.signal(signal.SIGALRM, self.handle_timeout)
- signal.alarm(self.timeout)
- try:
- result = self.function(*args)
- finally:
- signal.signal(signal.SIGALRM, old)
- signal.alarm(0)
- return result
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