自定义 class 使用字典 pythonic

Question

2019年4月，我已经做了一道题，而且我已经进步到喜欢了class。

我现在的问题，我的代码是否已经可重用？因为在使用行为添加新数据时我应该重复这个：

self.data[index] = {'weight':weight, 'visual':visual, 'step':step, 'fitness':fitness}

任何建议和支持我，非常感谢你们

python 代码，自定义词典，class python

中词典的包装函数


class Data:

  def __init__(self):
      self.data = {}

  def initial(self, index, weight, visual, step, fitness)
      self.data[index] = {'weight':weight, 'visual':visual, 'step':step, 'fitness':fitness}

  def add_following(self, index, behavior)
      self.data[index] = {'weight':weight, 'visual':visual, 'step':step, 'fitness':fitness, 'following':behavior}

  def mod_data(self, index, weight, visual, step, fitness)   
      self.data[index] = {'weight':weight, 'visual':visual, 'step':step, 'fitness':fitness}

  def del_data(self, index)
      del self.data[index]

  def __iter__(self):
    return iter(self.fish)

  def keys(self):
    return self.data.keys()

  def items(self):
    return self.data.items()

  def values(self):
    return self.data.values()

------------------------------------------------------------

import random

data = Data()

data_length = 3
weight_length = 2

visual = [random.random(0,1) for _ in range(data_length)]
weight = [[random.random(0,1) for _ in range(weight_length)] for _ in range(data_length)]
step = [random.random(0,1) for _ in range(data_length)]
behavior = [[random.random(0,1) for _ in range(weight_length)] for _ in range(data_length)]

for index in data.items():
   data.initial(index, visual[index], weight[index], step[index], fitness[index])

for beh in data.items():
   data.behavior(beh, visual[beh], weight[beh], step[beh], fitness[beh], behavior[beh])

我预期的结果是

0 {{'position': {'current': 0, 'target': [1, 2]}, 'weight': [0.4, 0.5], 'visual': 0.9, 'step': 0.32, 'fitness': 0.2,'following':{[0.4, 0.5], 'swarming':[0.1, 0.2]}
1 {{'position': {'current': 1, 'target': [0, 2]}, 'weight': [0.4, 0.59], 'visual': 0.3, 'step': 0.32, 'fitness': 0.2,'following':{[0.4, 0.5], 'swarming':[0.4, 0.5]}
2 {{'position': {'current': 2, 'target': [0, 1]}, 'weight': [0.41, 0.50], 'visual': 0.97, 'step': 0.75, 'fitness': 0.24,'following':{[0.42, 0.59], 'swarming':[0.21, 0.28]}

Answer 1

根据评论，这里是您可以开始构建的一个可能示例：

通过键 0、1、2、... 表示 list 比 dict 更好的结构来存储值.

在这里，我使用 collections.namedtuple 创建命名元组 Fish，属性为 weight、visual、step、fitness、behavior、following。 class 的行为就像一个元组，所以你可以把它放在 for-loop 等中。如果你需要更多的定制，我建议定制 class.

在循环中，我根据需要创建尽可能多的 Fish 个实例 - 在本例中为 data_length:

import random
from collections import namedtuple

Fish = namedtuple('Fish', 'weight visual step fitness behavior following')

data = []

data_length = 3
weight_length = 2

visual = [random.random() for _ in range(data_length)]
weight = [[random.random() for _ in range(weight_length)] for _ in range(data_length)]
step = [random.random() for _ in range(data_length)]
fitness = [random.random() for _ in range(data_length)]
behavior = [[random.random() for _ in range(weight_length)] for _ in range(data_length)]

for _visual, _weight, _step, _behavior, _fitness in zip(visual, weight, step, behavior, fitness):
    data.append(Fish(visual=_visual, weight=_weight, step=_step, fitness=_fitness, behavior=_behavior, following={} ))

for idx, item in enumerate(data):
    print(idx, item)

打印：

0 Fish(weight=[0.9995716623548419, 0.8374864488049845], visual=0.7545821331560755, step=0.18314419318293407, fitness=0.44659753047474804, behavior=[0.999274242465972, 0.8045066303545176], following={})
1 Fish(weight=[0.774064177559705, 0.8007058597932238], visual=0.040803565655900376, step=0.06891491826550344, fitness=0.8789611721939403, behavior=[0.231633308916408, 0.7496932726479902], following={})
2 Fish(weight=[0.3625792694324431, 0.46596868362347066], visual=0.20884834045098444, step=0.5649025875470652, fitness=0.27357142247178146, behavior=[0.12066601826166246, 0.3992293204074744], following={})

# You can acces the date like this:
data[0].following['some data'] = 1.234
print(data[0])

打印：

Fish(weight=[0.9995716623548419, 0.8374864488049845], visual=0.7545821331560755, step=0.18314419318293407, fitness=0.44659753047474804, behavior=[0.999274242465972, 0.8045066303545176], following={'some data': 1.234})

自定义 class 使用字典 pythonic

Custom class using dictionary pythonic

dictionary

class

object

nested-loops

python-3.x