documented code.

TODO.txt

@@ -7,18 +7,8 @@ ASK USER IF THEY'D LIKE TO ANSWER A FEW MORE QUESTIONS IF GUESS WAS WRONG?
 
 http://net.tutsplus.com/tutorials/javascript-ajax/submit-a-form-without-page-refresh-using-jquery/
 
-change guess to look at the character with the most right? (that might already be what it does. WHO KNOWS?)
-
-display candidates option on ask pages.
-
-BUILD QUESTION MANAGER
-
-FIX FORM ALIGNMENT (checkboxes and radios)
-
 ADMIN PAGE LOGINS
     http://dloewenherz.blogspot.com/2010/01/openid-clickpass-webpy-and-python.html
     or do this the crappy way ourselves. or just don't worry for the project.
 
 guess once value is over 100?
-
-LOOK AT UPDATE_LOCAL_KNOWLEDGEBASE

admin.py

@@ -1,7 +1,15 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 #
-#       admin.py
+'''
+    admin.py
+    
+    Andy Freeland and Dan Levy
+    5 June 2010
+    
+    Provides administrative functions, such as retraining characters and deleting
+    objects and characters. Accessed at the /admin url. Laughably insecure.
+'''
 
 import web
 import config, model
@@ -21,36 +29,43 @@
 
 class admin:
     def GET(self):
+        '''Renders the admin page, presenting a menu of administrative functions.'''
         return render.admin()
 
 class delete_question:
     def GET(self):
+        '''Lists all of the questions so that selected questions can be deleted.'''
         questions = model.get_questions()
         return render.delete_question(questions)
     def POST(self):
+        '''Deletes selected questions and returns to the admin page.'''
         question_ids = web.input()
         for id in question_ids:
             model.delete_question(id)
         raise web.seeother('/')
 
 class delete_object:
     def GET(self):
+        '''Lists all of the objects so that selected objects can be deleted.'''
         objects = model.get_objects()
         return render.delete_object(objects)
     def POST(self):
+        '''Deletes selected objects. and returns to the admin page.'''
         object_ids = web.input()
         for id in object_ids:
             model.delete_object(id)
         raise web.seeother('/')
 
 class data:
     def GET(self):
+        '''Renders a page listing all of the objects so that they can be retrained.'''
         objects = model.get_objects()
-
         return render.data(list(objects))
 
 class retrain:
     def GET(self, object_id):
+        '''Renders a page with all of the questions and values for a specified
+           object_id so that it can be retrained manually.'''
         object = model.get_object_by_id(object_id)
         questions = model.get_questions()
         data = model.get_data_dictionary()
@@ -60,6 +75,7 @@ def GET(self, object_id):
             raise web.seeother('/') # returns to admin page
 
     def POST(self, object_id):
+        '''Updates object_id with the newly selected answers to questions.'''
         inputs = web.input()
         for question_id in inputs:
             answer = inputs[question_id]

twentyquestions.py

@@ -22,42 +22,32 @@
 RETRAIN_SCALE = 2 # scale for weights set through the admin interface
 NEW_QUESTION_SCALE = 5 # scale for weights learned through the new question/guess page
 
+def load_initial_questions():
+    '''Loads questions we always want to ask as well as some random ones so that we can learn more
+       about the objects.'''
+
+    initial_questions = []
+    initial_questions.append(model.get_question_by_id(1)) # is character real
+    questions = list(model.get_questions()) # converts from webpy's IterBetter to a list
+
+    for i in range(2): # up to 2 initial random questions
+        q = random.choice(questions)
+        if not(q in initial_questions):
+            initial_questions.append(q)
+
+    initial_questions.append(model.get_question_by_id(6)) # is the character a man
+
+    return initial_questions
 
-def guess(objects_values):
-    '''Returns the object with the highest value.'''
+def load_objects_values():
+    '''Initializes objects values, a list with an entry for each object, initialized at 0.'''
 
-    if objects_values == {}: # nothing in the database :(
-        return None
-    else:
-        chosen = get_nearby_objects(objects_values, how_many=1)[0]     
-        return chosen
-
-def learn_character(asked_questions, name):
-    '''Adds a new object to the database and then learns that object. Returns
-       the id of that object.'''
-    if name.strip() != '':
-        object = model.get_object_by_name(name)
-        if object: # character in database
-            learn(asked_questions, object.id)
-            return object.id
-        else:
-            new_object_id = model.add_object(name) ### adds to database and trains
-            learn(asked_questions, new_object_id)
-            return new_object_id
-
-def learn(asked_questions, object_id):
-    '''Updates the data for the correct object based on information in asked_questions.
-       Also updates times played for the object and stores the playlog.'''
-    for question in asked_questions:
-        current_weight = model.get_value(object_id, question)
-        if not(current_weight): current_weight = 0
-
-        new_weight = current_weight + asked_questions[question]
-        model.update_data(object_id, question, new_weight)
-
-    model.update_times_played(object_id)
-
-    model.record_playlog(object_id, asked_questions, True)
+    objects_values = {}
+    objects = model.get_objects()
+    for object in objects:
+        objects_values[object.id] = 0
+
+    return objects_values
 
 def sort_objects_values(objects_values):
     '''Returns a list of the objects with the highest values in the local knowledge base.'''
@@ -66,7 +56,7 @@ def sort_objects_values(objects_values):
     sorted_objects_values.reverse()
 
     return sorted_objects_values
-
+    
 def get_nearby_objects(objects_values, how_many=10):
     '''Returns how_many objects with the highest values in the local knowledge base.
        Default: how_many=10.'''
@@ -145,7 +135,7 @@ def simple_entropy(objects,question):
     question_entropy += unknowns * 5 # arbitrary weight to discourage questions with lots of unknowns
 
     return abs(question_entropy)
-                        
+
 def choose_question(initial_questions, objects_values, asked_questions, how_many=10):
     '''Returns a question with the lowest entropy.'''
 
@@ -210,32 +200,42 @@ def update_local_knowledgebase(objects_values, asked_questions, question_id, ans
                 objects_values[weight.object_id] += answer*value
         asked_questions[question_id] = answer
 
-def load_initial_questions():
-    '''Loads questions we always want to ask as well as some random ones so that we can learn more
-       about the objects.'''
-
-    initial_questions = []
-    initial_questions.append(model.get_question_by_id(1)) # is character real
-    questions = list(model.get_questions()) # converts from webpy's IterBetter to a list
-
-    for i in range(2): # up to 2 initial random questions
-        q = random.choice(questions)
-        if not(q in initial_questions):
-            initial_questions.append(q)
-
-    initial_questions.append(model.get_question_by_id(6)) # is the character a man
+def guess(objects_values):
+    '''Returns the object with the highest value.'''
 
-    return initial_questions
+    if objects_values == {}: # nothing in the database :(
+        return None
+    else:
+        chosen = get_nearby_objects(objects_values, how_many=1)[0]     
+        return chosen
+
+def learn_character(asked_questions, name):
+    '''Adds a new object to the database and then learns that object. Returns
+       the id of that object.'''
+    if name.strip() != '':
+        object = model.get_object_by_name(name)
+        if object: # character in database
+            learn(asked_questions, object.id)
+            return object.id
+        else:
+            new_object_id = model.add_object(name) ### adds to database and trains
+            learn(asked_questions, new_object_id)
+            return new_object_id
+
+def learn(asked_questions, object_id):
+    '''Updates the data for the correct object based on information in asked_questions.
+       Also updates times played for the object and stores the playlog.'''
+    for question in asked_questions:
+        current_weight = model.get_value(object_id, question)
+        if not(current_weight): current_weight = 0
+
+        new_weight = current_weight + asked_questions[question]
+        model.update_data(object_id, question, new_weight)
+
+    model.update_times_played(object_id)
+
+    model.record_playlog(object_id, asked_questions, True)
 
-def load_objects_values():
-    '''Initializes objects values, a list with an entry for each object, initialized at 0.'''
-
-    objects_values = {}
-    objects = model.get_objects()
-    for object in objects:
-        objects_values[object.id] = 0
-
-    return objects_values
 
 if __name__ == '__main__':
     ##### Tests entropy! #####