python中MATLAB结构的替代品

Question

我在MATLAB中有一个结构，看起来像这样：

model(1:2).energy(1:3).voltage(1:4).time(1:10000)  
model(1:2).energy(1:3).voltage(1:4).current(1:10000)

我正在执行的基本操作是绘制当前与时间的关系。

我想开始使用python，但我对它不是很熟悉。我可以使用哪种具有类似功能的 python 结构？

据我所知，嵌套类可以完成这项工作。有没有其他更有效的方法？

Answer 1

有很多选项可以使用字典，或者如您所说构建自己的类。如果要从 matlab 迁移，还要考虑 numpy 模块，因为它使操作数组(或矩阵(变得轻而易举。下面是如何使用它们的简短示例。

import numpy as np
import matplotlib.pyplot as plt
time = np.linspace(0.0, 10.0, 51)
current = np.random.randint(115,125,size=(51))
voltage =  current*(time**2)

#Dictionary Example
model_dict = {'time': time, 'voltage': voltage, 'current': current}
plt_attr = {'color': ['r','b','g','k']}
fig, ax1 = plt.subplots(2,1)
ax1[0].title.set_text('Dictionary Example')
ax1[0].set_xlabel('time (s)')
ax1[0].set_ylabel('Voltage [V]', color=plt_attr['color'][0])
# Note how the variables are called
ax1[0].plot(model_dict['time'], model_dict['voltage'], color=plt_attr['color'][0])
ax1[0].tick_params(axis='y', labelcolor=plt_attr['color'][0])
ax2 = ax1[0].twinx()  # instantiate a second axes that shares the same x-axis
ax2.set_ylabel('Current [Amp]', color=plt_attr['color'][1])  # we already handled the x-label with ax1
# Note how the variables are called
ax2.plot(model_dict['time'], model_dict['current'], color=plt_attr['color'][1])
ax2.tick_params(axis='y', labelcolor=plt_attr['color'][1])
#Class Example
class model:
def __init__(self, name, i = None, v = None, e = None, t = None):
self.name = name
self.current = i
self.voltage = v
self.energy = e
self.time = t
model_class = model('model_1', i = current, v = voltage, t = time)   
ax1[1].title.set_text('Class Example')
ax1[1].set_xlabel('time (s)')
ax1[1].set_ylabel('Voltage [V]', color=plt_attr['color'][2])
# Note how the variables are called
ax1[1].plot(model_class.time, model_class.voltage, color=plt_attr['color'][2])
ax1[1].tick_params(axis='y', labelcolor=plt_attr['color'][2])
ax2 = ax1[1].twinx()  # instantiate a second axes that shares the same x-axis
ax2.set_ylabel('Current [Amp]', color=plt_attr['color'][3])  # we already handled the x-label with ax1
# Note how the variables are called
ax2.plot(model_class.time, model_class.current, color=plt_attr['color'][3])
ax2.tick_params(axis='y', labelcolor=plt_attr['color'][3])
plt.show()