Python:元组的情节列表

Question

我有以下数据集.我想用python或gnuplot来绘制数据.元组的形式为(x,y).Y轴应为对数轴.IE日志(y).散点图或线图是理想的.

如何才能做到这一点？

 [(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08), 
 (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09), 
 (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]

Answer 1

如果我正确地得到你的问题,你可以做这样的事情.

>>> import matplotlib.pyplot as plt
>>> testList =[(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08), 
 (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09), 
 (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]
>>> from math import log
>>> testList2 = [(elem1, log(elem2)) for elem1, elem2 in testList]
>>> testList2
[(0, -16.617236475334405), (1, -17.67799605473062), (2, -18.691431541177973), (3, -18.9767093108359), (4, -19.420021520728017), (5, -19.298411635970396)]
>>> zip(*testList2)
[(0, 1, 2, 3, 4, 5), (-16.617236475334405, -17.67799605473062, -18.691431541177973, -18.9767093108359, -19.420021520728017, -19.298411635970396)]
>>> plt.scatter(*zip(*testList2))
>>> plt.show()

这会给你类似的东西

或者作为线图,

>>> plt.plot(*zip(*testList2))
>>> plt.show()

编辑 - 如果要为轴添加标题和标签,可以执行类似的操作

>>> plt.scatter(*zip(*testList2))
>>> plt.title('Random Figure')
>>> plt.xlabel('X-Axis')
>>> plt.ylabel('Y-Axis')
>>> plt.show()

这会给你

Answer 2

在matplotlib中它将是:

import matplotlib.pyplot as plt

data =  [(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08),
 (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09),
 (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]

x_val = [x[0] for x in data]
y_val = [x[1] for x in data]

print x_val
plt.plot(x_val,y_val)
plt.plot(x_val,y_val,'or')
plt.show()

会产生:

Answer 3

正如其他人已经回答,scatter()或plot()将产生你想要的情节.我建议对已经存在的答案进行两处改进:

1. 使用numpy创建x坐标列表和y坐标列表.使用大型数据集比使用其他答案中建议的Python迭代更快.

2. 使用pyplot应用对数刻度而不是直接操作数据,除非您确实想要记录日志.

   import matplotlib.pyplot as plt
   import numpy as np
   
   data = [(2, 10), (3, 100), (4, 1000), (5, 100000)]
   data_in_array = np.array(data)
   '''
   That looks like array([[     2,     10],
                          [     3,    100],
                          [     4,   1000],
                          [     5, 100000]])
   '''
   
   transposed = data_in_array.T
   '''
   That looks like array([[     2,      3,      4,      5],
                          [    10,    100,   1000, 100000]])
   '''    
   
   x, y = transposed 
   
   # Here is the OO method
   # You could also the state-based methods of pyplot
   fig, ax = plt.subplots(1,1) # gets a handle for the AxesSubplot object
   ax.plot(x, y, 'ro')
   ax.plot(x, y, 'b-')
   ax.set_yscale('log')
   fig.show()
   

我也用ax.set_xlim(1, 6),并ax.set_ylim(.1, 1e6)使其相当.

我已经使用面向对象的matplotlib接口.因为它通过使用创建的对象的名称提供了更大的灵活性和明确的清晰度,所以OO接口优于基于交互式状态的接口.

Answer 4

你也可以使用 zip

import matplotlib.pyplot as plt

l = [(0, 6.0705199999997801e-08), (1, 2.1015700100300739e-08),
     (2, 7.6280656623374823e-09), (3, 5.7348209304555086e-09),
     (4, 3.6812203579604238e-09), (5, 4.1572516753310418e-09)]

x, y = zip(*l)

plt.plot(x, y)