AttributeError: l'objet 'float' n'a pas d'attribut 'get_coords'

Question

J'apprends Python à partir de cette conférence: Lec 19 | MIT 6.00 Introduction to Computer Science and Programming. J'utilise Python 3.6.2, l'exemple de lecture s'exécute sur Python 2.x. Quelle est la bonne façon de définir les valeurs de x et y dans la fonction ans_quest?

x, y = loc_list[-1].get_coords() 

Cette méthode peut-elle être appelée comme ceci? C'était l'exemple dans la conférence.

code complet:

import math, random, pylab, copy 

class Location(object): 
    def __init__(self, x, y): 
     self.x = float(x) 
     self.y = float(y) 
    def move(self, xc, yc): 
     return Location(self.x+float(xc), self.y+float(yc)) 
    def get_coords(self): 
     return self.x, self.y 
    def get_dist(self, other): 
     ox, oy = other.get_coords() 
     x_dist = self.x - ox 
     y_dist = self.y - oy 
     return math.sqrt(x_dist**2 + y_dist**2) 

class Compass_Pt(object): 
    possibles = ('N', 'S', 'E', 'W') 
    def __init__(self, pt): 
     if pt in self.possibles: self.pt = pt 
     else: raise ValueError('in Compass_Pt.__init__') 

    def move(self, dist): 
     if self.pt == 'N': return (0, dist) 
     elif self.pt == 'S': return (0, -dist) 
     elif self.pt == 'E': return (dist, 0) 
     elif self.pt == 'W': return (-dist, 0) 
     else: raise ValueError('in Compass_Pt.move') 

class Field(object): 
    ''' Cartesian plane where object will be located ''' 
    def __init__(self, drunk, loc): 
     self.drunk = drunk 
     self.loc = loc 
    def move(self, cp, dist): 
     old_loc = self.loc 
     xc, yc = cp.move(dist) 
     self.loc = old_loc.move(xc, yc) 
    def get_loc(self): 
     return self.loc 
    def get_drunk(self): 
     return self.drunk 

class Drunk(object): 
    ''' Point itself ''' 
    def __init__(self, name): 
     self.name = name 
    def move(self, field, cp, dist = 1): 
     if field.get_drunk().name != self.name: 
      raise ValueError('Drunk.move called with drunk not in the field') 
     for i in range(dist): 
      field.move(cp, 1) 

class Usual_Drunk(Drunk): 
    def move(self, field, dist = 1): 
     ''' Drunk.move superclass method override. Sends additional cp attribute.''' 
     cp = random.choice(Compass_Pt.possibles) 
     Drunk.move(self, field, Compass_Pt(cp), dist) 


class Cold_Drunk(Drunk): 
    def move(self, field, dist = 1): 
     cp = random.choice(Compass_Pt.possibles) 
     if cp == 'S': 
      Drunk.move(self, field, Compass_Pt(cp), 2*dist) 
     else: 
      Drunk.move(self, field, Compass_Pt(cp), dist) 

class EW_Drunk(Drunk): 
    def move(self, field, time = 1): 
     cp = random.choice(Compass_Pt.possibles) 
     while cp != 'E' and cp != 'W': 
      cp = random.choice(Compass_Pt.possibles) 
     Drunk.move(self, field, Compass_Pt(cp), time) 

def perform_trial(time, f): 
    start = f.get_loc() 
    distances = [0,0] 
    for t in range(1, time + 1): 
     f.get_drunk().move(f) 
     new_loc = f.get_loc() 
     distance = new_loc.get_dist(start) 
     distances.append(distance) 
    return distances 

def perform_sim(time, num_trials, drunk_type): 
    dist_lists = [] 
    loc_lists = [] 
    for trial in range(num_trials): 
     d = drunk_type('Drunk' + str(trial)) 
     f = Field(d, Location(0, 0)) 
     distances = perform_trial(time, f) 
     locs = copy.deepcopy(distances) 
     dist_lists.append(distances) 
     loc_lists.append(locs) 
    return dist_lists, loc_lists 


def ans_quest(max_time, num_trials, drunk_type, title): 
    dist_lists, loc_lists = perform_sim(max_time, num_trials, drunk_type) 
    means = [] 
    for t in range(max_time + 1): 
     tot = 0.0 
     for dist_l in dist_lists: 
      tot += dist_l[t] 
     means.append(tot/len(dist_lists)) 
    pylab.figure() 
    pylab.plot(means) 
    pylab.ylabel('distance') 
    pylab.xlabel('time') 
    pylab.title('{} Ave. Distance'.format(title)) 
    lastX = [] 
    lastY = [] 
    for loc_list in loc_lists: 
     x, y = loc_list[-1].get_coords() 
     lastX.append(x) 
     lastY.append(y) 
    pylab.figure() 
    pylab.scatter(lastX, lastY) 
    pylab.ylabel('NW Distance') 
    pylab.title('{} Final location'.format(title)) 
    pylab.figure() 
    pylab.hist(lastX) 
    pylab.xlabel('EW Value') 
    pylab.ylabel('Number of Trials') 
    pylab.title('{} Distribution of Final EW Values'.format(title)) 


num_steps = 50 
num_trials = 10 


ans_quest(num_steps, num_trials, Usual_Drunk, 'Usual Drunk ' + str(num_trials) + ' Trials') 
ans_quest(num_steps, num_trials, Cold_Drunk, 'Cold Drunk ' + str(num_trials) + ' Trials') 
ans_quest(num_steps, num_trials, EW_Drunk, 'EW Drunk ' + str(num_trials) + ' Trials') 

pylab.show() 

Erreur:

Traceback (most recent call last): 
    File "/home/tihe/Documents/CODING/Project Home/Python/biased_random_walks.py", line 194, in <module> 
    ans_quest(num_steps, num_trials, Usual_Drunk, 'Usual Drunk ' + str(num_trials) + ' Trials') 
    File "/home/tihe/Documents/CODING/Project Home/Python/biased_random_walks.py", line 175, in ans_quest 
    x, y = loc_list[-1].get_coords() 
AttributeError: 'float' object has no attribute 'get_coords' 

Answer 1

Cette méthode pourrait être appelée comme si vous aviez une liste des objets Location. L'erreur est que le loc_list est rempli avec des distances et non des objets Location. Cela se produit dans la fonction perform_sim lorsque, au lieu d'obtenir l'emplacement, vous effectuez une copie complète de distance.

Peut-être que vous pourriez essayer quelque chose comme ceci:

def perform_trial(time, f): 
    start = f.get_loc() 
    distances = [0,0] 
    locations = [] 
    for t in range(1, time + 1): 
     f.get_drunk().move(f) 
     new_loc = f.get_loc() 
     locations.append(new_loc) 
     distance = new_loc.get_dist(start) 
     distances.append(distance) 
    return distances, locations 

def perform_sim(time, num_trials, drunk_type): 
    dist_lists = [] 
    loc_lists = [] 
    for trial in range(num_trials): 
     d = drunk_type('Drunk' + str(trial)) 
     f = Field(d, Location(0, 0)) 
     distances, locations = perform_trial(time, f) 
     dist_lists.append(distances) 
     loc_lists.append(locations) 
    return dist_lists, loc_lists 

J'espère que vous aidé.