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Unit 2 - Lecture 6 - 02.py

@@ -26,7 +26,7 @@ def __str__(self):
 class Field(object):
     def __init__(self):
         self.drunks= {}     # hashable
-    def addDrunk(self., drunk, loc):
+    def addDrunk(self, drunk, loc):
         if drunk in self.drunks:
             raise ValueError('Duplicate drunk')
         else:
@@ -45,7 +45,7 @@ def moveDrunk(self, drunk):
         self.drunks[drunk] = currentLocation.move(xDist, yDist)
 
 class Drunk(object):
-    def __init__(self, Name):
+    def __init__(self, name = None):
         self.name = name
     def __str__(self):
         return 'This drunk is named' + self.name
@@ -75,14 +75,14 @@ def walk(f, d, numSteps):
     return start.distFrom(f.getLoc(d))
 
 # simulate multiple walks
-def simWalks(numSteps, numTrials, drunkClass):
+def simWalks(numSteps, numTrials, dClass):
     """
     Assumes numSteps an int >= 0, numTrials an int > 0,
     drunkClass a subclass of Drunk Simulates numTrials
     walks of numSteps steps each. 
     Return: list of the final distances for each trial
     """
-    Homer = drunkClass()
+    Homer = dClass()
     origin = Location(0, 0)
     distances = []
     for i in range(numTrials):
@@ -91,3 +91,24 @@ def simWalks(numSteps, numTrials, drunkClass):
         distances.append(round(walk(f, Homer, numSteps), 1))
     return distances
 
+# implement complete walks
+def drunkTest(walkLengths, numTrials, dClass):
+    """
+    Assumes walkLengths a sequence of ints >= 0 numTrials an int > 0,
+    dClass a subclass of Drunk. For each number of steps in walkLengths,
+    runs simWalks with numTrials walks and prints results
+    """
+    for numSteps in walkLengths:
+        distances = simWalks(numSteps, numTrials, dClass)
+        print(dClass.__name__, 'random walk of', numSteps, 'steps')
+        print(' Mean =', round(sum(distances)/len(distances), 4))
+        print(' Max =', max(distances),'    Min =', min(distances))
+
+def simAll(drunkKinds, walkLengths, numTrials):
+    for dClass in drunkKinds:
+        drunkTest(walkLengths, numTrials, dClass)
+
+
+# test
+# drunkTest((10, 100, 1000, 1), 100, UsualDrunk)
+simAll((UsualDrunk, ColdDrunk), [1, 10, 100, 1000, 10000], 100)

lect6-segment2.py

@@ -0,0 +1,118 @@
+import random, pylab
+
+class Location(object):
+    def __init__(self, x, y):
+        """x and y are numbers"""
+        self.x = x
+        self.y = y
+
+    def move(self, deltaX, deltaY):
+        """deltaX and deltaY are numbers"""
+        return Location(self.x + deltaX, self.y + deltaY)
+
+    def getX(self):
+        return self.x
+
+    def getY(self):
+        return self.y
+
+    def distFrom(self, other):
+        ox = other.x
+        oy = other.y
+        xDist = self.x - ox
+        yDist = self.y - oy
+        return (xDist**2 + yDist**2)**0.5
+
+    def __str__(self):
+        return '<' + str(self.x) + ', ' + str(self.y) + '>'
+
+class Field(object):
+    def __init__(self):
+        self.drunks = {}
+
+    def addDrunk(self, drunk, loc):
+        if drunk in self.drunks:
+            raise ValueError('Duplicate drunk')
+        else:
+            self.drunks[drunk] = loc
+
+    def moveDrunk(self, drunk):
+        if drunk not in self.drunks:
+            raise ValueError('Drunk not in field')
+        xDist, yDist = drunk.takeStep()
+        currentLocation = self.drunks[drunk]
+        #use move method of Location to get new location
+        self.drunks[drunk] = currentLocation.move(xDist, yDist)
+
+    def getLoc(self, drunk):
+        if drunk not in self.drunks:
+            raise ValueError('Drunk not in field')
+        return self.drunks[drunk]
+
+class Drunk(object):
+    def __init__(self, name = None):
+        """Assumes name is a str"""
+        self.name = name
+
+    def __str__(self):
+        if self != None:
+            return self.name
+        return 'Anonymous'
+
+class UsualDrunk(Drunk):
+    def takeStep(self):
+        stepChoices = [(0,1), (0,-1), (1, 0), (-1, 0)]
+        return random.choice(stepChoices)
+
+def walk(f, d, numSteps):
+    """Assumes: f a Field, d a Drunk in f, and numSteps an int >= 0.
+       Moves d numSteps times, and returns the distance between
+       the final location and the location at the start of the 
+       walk."""
+    start = f.getLoc(d)
+    for s in range(numSteps):
+        f.moveDrunk(d)
+    return start.distFrom(f.getLoc(d))
+
+def simWalks(numSteps, numTrials, dClass):
+    """Assumes numSteps an int >= 0, numTrials an int > 0,
+         dClass a subclass of Drunk
+       Simulates numTrials walks of numSteps steps each.
+       Returns a list of the final distances for each trial"""
+    Homer = dClass()
+    origin = Location(0, 0)
+    distances = []
+    for t in range(numTrials):
+        f = Field()
+        f.addDrunk(Homer, origin)
+        distances.append(round(walk(f, Homer, numSteps), 1))
+    return distances
+
+def drunkTest(walkLengths, numTrials, dClass):
+    """Assumes walkLengths a sequence of ints >= 0
+         numTrials an int > 0, dClass a subclass of Drunk
+       For each number of steps in walkLengths, runs simWalks with
+         numTrials walks and prints results"""
+    for numSteps in walkLengths:
+        distances = simWalks(numSteps, numTrials, dClass)
+        print(dClass.__name__, 'random walk of', numSteps, 'steps')
+        print(' Mean =', round(sum(distances)/len(distances), 4))
+        print(' Max =', max(distances), 'Min =', min(distances))
+
+#random.seed(0)
+#drunkTest((10, 1000, 1000, 10000), 100, UsualDrunk)
+
+
+class ColdDrunk(Drunk):
+    def takeStep(self):
+        stepChoices = [(0.0,0.9), (0.0,-1.1),
+                       (1.0, 0.0), (-1.0, 0.0)]
+        return random.choice(stepChoices)
+
+def simAll(drunkKinds, walkLengths, numTrials):
+    for dClass in drunkKinds:
+        drunkTest(walkLengths, numTrials, dClass)
+
+random.seed(0)
+simAll((UsualDrunk, ColdDrunk),
+       (1, 10, 100, 1000, 10000), 100)