Changed NotImplemented to something that actually complains. Lack of this bit me.

darius · darius · commit 3f2f99efe367 · 2011-10-23T22:12:06.000Z
diff --git a/learning.py b/learning.py
@@ -339,11 +339,11 @@ def decision_list_learning(examples):
     def find_examples(examples):
         """Find a set of examples that all have the same outcome under
         some test. Return a tuple of the test, outcome, and examples."""
-        NotImplemented
+        unimplemented()
 
     def passes(example, test):
         "Does the example pass the test?"
-        NotImplemented
+        unimplemented()
 
     def predict(example):
         "Predict the outcome for the first passing test."
@@ -363,24 +363,24 @@ def NeuralNetLearner(dataset, sizes):
    weights = []
 
    def predict(example):
-      NotImplemented
+      unimplemented()
 
    return predict
 
 class NNUnit:
    """Unit of a neural net."""
    def __init__(self):
-       NotImplemented
+       unimplemented()
 
 def PerceptronLearner(dataset, sizes):
    def predict(example):
       return sum([])
-   NotImplemented
+   unimplemented()
 #______________________________________________________________________________
 
 def Linearlearner(dataset):
    """Fit a linear model to the data."""
-   NotImplemented
+   unimplemented()
 #______________________________________________________________________________
 
 def EnsembleLearner(learners):
@@ -418,7 +418,7 @@ def train(dataset):
     return train
 
 def WeightedMajority(h, z):
-    raise NotImplementedError
+    unimplemented()
 
 #_____________________________________________________________________________
 # Functions for testing learners on examples
diff --git a/probability.py b/probability.py
@@ -303,13 +303,13 @@ def is_hidden(var, X, e):
     return var != X and var not in e
 
 def Factor(var, e):
-    NotImplemented
+    unimplemented()
 
 def pointwise_product(factors):
-    NotImplemented
+    unimplemented()
 
 def sum_out(var, factors):
-    NotImplemented
+    unimplemented()
 
 #______________________________________________________________________________
 
diff --git a/rl.py b/rl.py
@@ -7,9 +7,9 @@
 class PassiveADPAgent(agents.Agent):
     """Passive (non-learning) agent that uses adaptive dynamic programming
     on a given MDP and policy. [Fig. 21.2]"""
-    NotImplementedError
+    NotImplemented
 
 class PassiveTDAgent(agents.Agent):
     """Passive (non-learning) agent that uses temporal differences to learn
     utility estimates. [Fig. 21.4]"""
-    NotImplementedError
+    NotImplemented
diff --git a/search.py b/search.py
@@ -174,11 +174,11 @@ def depth_first_graph_search(problem):
 
 def breadth_first_search(problem):
     "Fig. 3.11"
-    NotImplemented
+    unimplemented()
 
 def uniform_cost_search(problem):
     "Fig. 3.14"
-    NotImplemented
+    unimplemented()
 
 def depth_limited_search(problem, limit=50):
     "[Fig. 3.17]"
@@ -302,15 +302,15 @@ def simulated_annealing(problem, schedule=exp_schedule()):
 
 def and_or_graph_search(problem):
     "[Fig. 4.11]"
-    NotImplemented
+    unimplemented()
 
 def online_dfs_agent(s1):
     "[Fig. 4.21]"
-    NotImplemented
+    unimplemented()
 
 def lrta_star_agent(s1):
     "[Fig. 4.24]"
-    NotImplemented
+    unimplemented()
 
 #______________________________________________________________________________
 # Genetic Algorithm
diff --git a/utils.py b/utils.py
@@ -366,7 +366,6 @@ def isin(elt, seq):
 # 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)
@@ -526,6 +525,7 @@ def normalize(numbers):
     total = float(sum(numbers))
     return [n / total 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.
@@ -655,6 +655,9 @@ def DataFile(name, mode='r'):
     "Return a file in the AIMA /data directory."
     return AIMAFile(['..', 'data', name], mode)
 
+def unimplemented():
+    "Use this as a stub for not-yet-implemented functions."
+    raise NotImplementedError
 
 #______________________________________________________________________________
 # Queues: Stack, FIFOQueue, PriorityQueue
