Chapter 13. Random Walks and More About Data Vizualization 183

The parameter dClass of simWalks is of type class, and is used in the first line of code to create a Drunk of the appropriate subclass. Later, when drunk.takeStep is invoked from Field.moveDrunk, the method from the appropriate subclass is automatically selected.

The function drunkTest also has a parameter, dClass, of type class. It is used twice, once in the call to simWalks and once in the first print statement. In the print statement, the built-in class attribute __name__ is used to get a string with the name of the class. The function drunkTest calculates the coefficient of variation of the distance from the origin using the CV function defined in Figure 12.7.

Figure 13.4 The drunkards walk (with a bug)

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 difference 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, 0.0) distances = [] for t in range(numTrials): f = Field() f.addDrunk(Homer, origin) distances.append(walk(f, Homer, numTrials)) 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 =', sum(distances)/len(distances),\ 'CV =', CV(distances) print ' Max =', max(distances), 'Min =', min(distances)