fixed all instances of issue #833 (#843)

* test commit

* agents.ipynb

* agents.ipynb

* Fixed all the instances of issue #833

* minor fix and cleared change in agents.ipynb

Author: goswami-rahul

agents.py

@@ -96,7 +96,7 @@ def program(percept):
         self.program = program
 
     def can_grab(self, thing):
-        """Returns True if this agent can grab this thing.
+        """Return True if this agent can grab this thing.
         Override for appropriate subclasses of Agent and Thing."""
         return False
 
@@ -444,7 +444,7 @@ def move_to(self, thing, destination):
         return thing.bump
 
     def add_thing(self, thing, location=(1, 1), exclude_duplicate_class_items=False):
-        """Adds things to the world. If (exclude_duplicate_class_items) then the item won't be
+        """Add things to the world. If (exclude_duplicate_class_items) then the item won't be
         added if the location has at least one item of the same class."""
         if (self.is_inbounds(location)):
             if (exclude_duplicate_class_items and
@@ -809,7 +809,7 @@ def init_world(self, program):
         self.add_thing(Explorer(program), (1, 1), True)
 
     def get_world(self, show_walls=True):
-        """Returns the items in the world"""
+        """Return the items in the world"""
         result = []
         x_start, y_start = (0, 0) if show_walls else (1, 1)
 
@@ -826,7 +826,7 @@ def get_world(self, show_walls=True):
         return result
 
     def percepts_from(self, agent, location, tclass=Thing):
-        """Returns percepts from a given location,
+        """Return percepts from a given location,
         and replaces some items with percepts from chapter 7."""
         thing_percepts = {
             Gold: Glitter(),
@@ -846,7 +846,7 @@ def percepts_from(self, agent, location, tclass=Thing):
         return result if len(result) else [None]
 
     def percept(self, agent):
-        """Returns things in adjacent (not diagonal) cells of the agent.
+        """Return things in adjacent (not diagonal) cells of the agent.
         Result format: [Left, Right, Up, Down, Center / Current location]"""
         x, y = agent.location
         result = []
@@ -907,7 +907,7 @@ def execute_action(self, agent, action):
                 agent.has_arrow = False
 
     def in_danger(self, agent):
-        """Checks if Explorer is in danger (Pit or Wumpus), if he is, kill him"""
+        """Check if Explorer is in danger (Pit or Wumpus), if he is, kill him"""
         for thing in self.list_things_at(agent.location):
             if isinstance(thing, Pit) or (isinstance(thing, Wumpus) and thing.alive):
                 agent.alive = False

csp.py

@@ -351,7 +351,7 @@ def topological_sort(X, root):
 
 
 def build_topological(node, parent, neighbors, visited, stack, parents):
-    """Builds the topological sort and the parents of each node in the graph"""
+    """Build the topological sort and the parents of each node in the graph."""
     visited[node] = True
 
     for n in neighbors[node]:
@@ -427,7 +427,7 @@ def MapColoringCSP(colors, neighbors):
                different_values_constraint)
 
 
-def parse_neighbors(neighbors, variables=[]):
+def parse_neighbors(neighbors, variables=None):
     """Convert a string of the form 'X: Y Z; Y: Z' into a dict mapping
     regions to neighbors. The syntax is a region name followed by a ':'
     followed by zero or more region names, followed by ';', repeated for

knowledge.py

@@ -11,13 +11,14 @@
 # ______________________________________________________________________________
 
 
-def current_best_learning(examples, h, examples_so_far=[]):
+def current_best_learning(examples, h, examples_so_far=None):
     """ [Figure 19.2]
     The hypothesis is a list of dictionaries, with each dictionary representing
     a disjunction."""
     if not examples:
         return h
 
+    examples_so_far = examples_so_far or []
     e = examples[0]
     if is_consistent(e, h):
         return current_best_learning(examples[1:], h, examples_so_far + [e])
@@ -95,7 +96,7 @@ def generalizations(examples_so_far, h):
 
 
 def add_or(examples_so_far, h):
-    """Adds an OR operation to the hypothesis. The AND operations in the disjunction
+    """Add an OR operation to the hypothesis. The AND operations in the disjunction
     are generated by the last example (which is the problematic one)."""
     ors = []
     e = examples_so_far[-1]
@@ -135,7 +136,7 @@ def version_space_update(V, e):
 
 
 def all_hypotheses(examples):
-    """Builds a list of all the possible hypotheses"""
+    """Build a list of all the possible hypotheses"""
     values = values_table(examples)
     h_powerset = powerset(values.keys())
     hypotheses = []
@@ -148,7 +149,7 @@ def all_hypotheses(examples):
 
 
 def values_table(examples):
-    """Builds a table with all the possible values for each attribute.
+    """Build a table with all the possible values for each attribute.
     Returns a dictionary with keys the attribute names and values a list
     with the possible values for the corresponding attribute."""
     values = defaultdict(lambda: [])
@@ -210,7 +211,7 @@ def build_h_combinations(hypotheses):
 
 
 def minimal_consistent_det(E, A):
-    """Returns a minimal set of attributes which give consistent determination"""
+    """Return a minimal set of attributes which give consistent determination"""
     n = len(A)
 
     for i in range(n + 1):
@@ -220,7 +221,7 @@ def minimal_consistent_det(E, A):
 
 
 def consistent_det(A, E):
-    """Checks if the attributes(A) is consistent with the examples(E)"""
+    """Check if the attributes(A) is consistent with the examples(E)"""
     H = {}
 
     for e in E:
@@ -235,9 +236,9 @@ def consistent_det(A, E):
 
 
 class FOIL_container(FolKB):
-    """Holds the kb and other necessary elements required by FOIL"""
+    """Hold the kb and other necessary elements required by FOIL."""
 
-    def __init__(self, clauses=[]):
+    def __init__(self, clauses=None):
         self.const_syms = set()
         self.pred_syms = set()
         FolKB.__init__(self, clauses)
@@ -251,7 +252,7 @@ def tell(self, sentence):
             raise Exception("Not a definite clause: {}".format(sentence))
 
     def foil(self, examples, target):
-        """Learns a list of first-order horn clauses
+        """Learn a list of first-order horn clauses
         'examples' is a tuple: (positive_examples, negative_examples).
         positive_examples and negative_examples are both lists which contain substitutions."""
         clauses = []
@@ -268,10 +269,10 @@ def foil(self, examples, target):
         return clauses
 
     def new_clause(self, examples, target):
-        """Finds a horn clause which satisfies part of the positive
+        """Find a horn clause which satisfies part of the positive
         examples but none of the negative examples.
         The horn clause is specified as [consequent, list of antecedents]
-        Return value is the tuple (horn_clause, extended_positive_examples)"""
+        Return value is the tuple (horn_clause, extended_positive_examples)."""
         clause = [target, []]
         # [positive_examples, negative_examples]
         extended_examples = examples
@@ -284,14 +285,14 @@ def new_clause(self, examples, target):
         return (clause, extended_examples[0])
 
     def extend_example(self, example, literal):
-        """Generates extended examples which satisfy the literal"""
+        """Generate extended examples which satisfy the literal."""
         # find all substitutions that satisfy literal
         for s in self.ask_generator(subst(example, literal)):
             s.update(example)
             yield s
 
     def new_literals(self, clause):
-        """Generates new literals based on known predicate symbols.
+        """Generate new literals based on known predicate symbols.
         Generated literal must share atleast one variable with clause"""
         share_vars = variables(clause[0])
         for l in clause[1]:
@@ -304,7 +305,7 @@ def new_literals(self, clause):
                     yield Expr(pred, *[var for var in args])
 
     def choose_literal(self, literals, examples):
-        """Chooses the best literal based on the information gain"""
+        """Choose the best literal based on the information gain."""
         def gain(l):
             pre_pos = len(examples[0])
             pre_neg = len(examples[1])
@@ -328,8 +329,8 @@ def represents(d):
         return max(literals, key=gain)
 
     def update_examples(self, target, examples, extended_examples):
-        """Adds to the kb those examples what are represented in extended_examples
-        List of omitted examples is returned"""
+        """Add to the kb those examples what are represented in extended_examples
+        List of omitted examples is returned."""
         uncovered = []
         for example in examples:
             def represents(d):
@@ -346,7 +347,7 @@ def represents(d):
 
 
 def check_all_consistency(examples, h):
-    """Check for the consistency of all examples under h"""
+    """Check for the consistency of all examples under h."""
     for e in examples:
         if not is_consistent(e, h):
             return False
@@ -355,7 +356,7 @@ def check_all_consistency(examples, h):
 
 
 def check_negative_consistency(examples, h):
-    """Check if the negative examples are consistent under h"""
+    """Check if the negative examples are consistent under h."""
     for e in examples:
         if e['GOAL']:
             continue
@@ -367,7 +368,7 @@ def check_negative_consistency(examples, h):
 
 
 def disjunction_value(e, d):
-    """The value of example e under disjunction d"""
+    """The value of example e under disjunction d."""
     for k, v in d.items():
         if v[0] == '!':
             # v is a NOT expression
@@ -381,7 +382,7 @@ def disjunction_value(e, d):
 
 
 def guess_value(e, h):
-    """Guess value of example e under hypothesis h"""
+    """Guess value of example e under hypothesis h."""
     for d in h:
         if disjunction_value(e, d):
             return True
@@ -394,16 +395,8 @@ def is_consistent(e, h):
 
 
 def false_positive(e, h):
-    if e["GOAL"] == False:
-        if guess_value(e, h):
-            return True
-
-    return False
+    return guess_value(e, h) and not e["GOAL"]
 
 
 def false_negative(e, h):
-    if e["GOAL"] == True:
-        if not guess_value(e, h):
-            return True
-
-    return False
+    return e["GOAL"] and not guess_value(e, h)

logic.py

@@ -901,10 +901,11 @@ class FolKB(KB):
     False
     """
 
-    def __init__(self, initial_clauses=[]):
+    def __init__(self, initial_clauses=None):
         self.clauses = []  # inefficient: no indexing
-        for clause in initial_clauses:
-            self.tell(clause)
+        if initial_clauses:
+            for clause in initial_clauses:
+                self.tell(clause)
 
     def tell(self, sentence):
         if is_definite_clause(sentence):

nlp.py

@@ -272,7 +272,7 @@ def __repr__(self):
 class Chart:
 
     """Class for parsing sentences using a chart data structure.
-    >>> chart = Chart(E0);
+    >>> chart = Chart(E0)
     >>> len(chart.parses('the stench is in 2 2'))
     1
     """