Python：使用数组值连接列表值

Question

我创造了一个龙卷风情节，灵感来自here。它具有在y轴上标记的输入变量（a1，b1，c1 ......）以及它们旁边的相应相关系数。见下图：

然后，我按照这样的方式对相关系数进行排序：首先绘制最高绝对值而不丢失其符号，然后是下一个最高值，依此类推。使用sorted(values,key=abs, reverse=True)。请参阅下面的结果

如果您注意到，在第二张照片中，即使条形按绝对降序排序，y轴标签仍然保持不变。

问题：如何使y轴标签（变量）连接到相关系数，使其始终与其相关系数相对应。

以下是我的代码：

import numpy as np
from matplotlib import pyplot as plt

#####Importing Data from csv file#####
dataset1 = np.genfromtxt('dataSet1.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0'])
dataset2 = np.genfromtxt('dataSet2.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0'])
dataset3 = np.genfromtxt('dataSet3.csv', dtype = float, delimiter = ',', skip_header = 1, names = ['a', 'b', 'c', 'x0'])

corr1 = np.corrcoef(dataset1['a'],dataset1['x0'])
corr2 = np.corrcoef(dataset1['b'],dataset1['x0'])
corr3 = np.corrcoef(dataset1['c'],dataset1['x0'])
corr4 = np.corrcoef(dataset2['a'],dataset2['x0'])
corr5 = np.corrcoef(dataset2['b'],dataset2['x0'])
corr6 = np.corrcoef(dataset2['c'],dataset2['x0'])
corr7 = np.corrcoef(dataset3['a'],dataset3['x0'])
corr8 = np.corrcoef(dataset3['b'],dataset3['x0'])
corr9 = np.corrcoef(dataset3['c'],dataset3['x0'])

np.set_printoptions(precision=4)
variables = ['a1','b1','c1','a2','b2','c2','a3','b3','c3']
base = 0  
values = np.array([corr1[0,1],corr2[0,1],corr3[0,1],
                   corr4[0,1],corr5[0,1],corr6[0,1],
                   corr7[0,1],corr8[0,1],corr9[0,1]])
values = sorted(values,key=abs, reverse=True)
# The y position for each variable
ys = range(len(values))[::-1]  # top to bottom   
# Plot the bars, one by one
for y, value in zip(ys, values):
    high_width = base + value
    #print high_width

    # Each bar is a "broken" horizontal bar chart
    plt.broken_barh(
        [(base, high_width)],
        (y - 0.4, 0.8),
        facecolors=['red', 'red'],  # Try different colors if you like
        edgecolors=['black', 'black'],
        linewidth=1)
# Draw a vertical line down the middle
plt.axvline(base, color='black')
# Position the x-axis on the top/bottom, hide all the other spines (=axis lines)
axes = plt.gca()  # (gca = get current axes)
axes.spines['left'].set_visible(False)
axes.spines['right'].set_visible(False)
axes.spines['top'].set_visible(False)
axes.xaxis.set_ticks_position('bottom')
# Make the y-axis display the variables
plt.yticks(ys, variables)

plt.ylim(-2, len(variables))
plt.show()

非常感谢提前

Answer 1

使用内置zip函数 - 返回元组列表，其中第i个元组包含来自每个参数序列或迭代的第i个元素。但是要知道返回的列表的长度被截断为最短参数序列的长度。