Matplotlib：ValueError：x和y必须具有相同的第一维

Question

我试图拟合最适合我的matplotlib图的线性线。我不断收到x和y不具有相同第一维的错误。但他们都有15的长度。我做错了什么？

import matplotlib.pyplot as plt 
from scipy import stats 
import numpy as np 

x = [0.46,0.59,0.68,0.99,0.39,0.31,1.09,0.77,0.72,0.49,0.55,0.62,0.58,0.88,0.78] 
y = [0.315,0.383,0.452,0.650,0.279,0.215,0.727,0.512,0.478,0.335,0.365,0.424,0.390,0.585,0.511] 
xerr = [0.01]*15 
yerr = [0.001]*15 

plt.rc('font', family='serif', size=13) 
m, b = np.polyfit(x, y, 1) 
plt.plot(x,y,'s',color='#0066FF') 
plt.plot(x, m*x + b, 'r-') #BREAKS ON THIS LINE 
plt.errorbar(x,y,xerr=xerr,yerr=0,linestyle="None",color='black') 
plt.xlabel('$\Delta t$ $(s)$',fontsize=20) 
plt.ylabel('$\Delta p$ $(hPa)$',fontsize=20) 
plt.autoscale(enable=True, axis=u'both', tight=False) 
plt.grid(False) 
plt.xlim(0.2,1.2) 
plt.ylim(0,0.8) 
plt.show() 

Answer 1

你应该让x和y numpy的阵列，而不是名单：

x = np.array([0.46,0.59,0.68,0.99,0.39,0.31,1.09, 
       0.77,0.72,0.49,0.55,0.62,0.58,0.88,0.78]) 
y = np.array([0.315,0.383,0.452,0.650,0.279,0.215,0.727,0.512, 
       0.478,0.335,0.365,0.424,0.390,0.585,0.511]) 

随着这一变化，它产生的预期情节。如果他们是名单，m * x不会产生你期望的结果，但是是一个空的名单。请注意，m是标量，而不是标准Python float。

我实际上认为这有点可疑的Numpy行为。在普通的Python，乘以一个整数的列表只是重复列表：

In [42]: 2 * [1, 2, 3] 
Out[42]: [1, 2, 3, 1, 2, 3] 

同时用浮动乘以一个列表给出了一个错误（因为我认为它应该）：

In [43]: 1.5 * [1, 2, 3] 
--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-43-d710bb467cdd> in <module>() 
----> 1 1.5 * [1, 2, 3] 
TypeError: can't multiply sequence by non-int of type 'float' 

怪异的事情是一个numpy的标量乘以一个Python列表显然作品：

In [45]: np.float64(0.5) * [1, 2, 3] 
Out[45]: [] 

In [46]: np.float64(1.5) * [1, 2, 3] 
Out[46]: [1, 2, 3] 

In [47]: np.float64(2.5) * [1, 2, 3] 
Out[47]: [1, 2, 3, 1, 2, 3] 

如此看来，浮子被截断为int，之后你会得到重复的次标准的Python行为e列表，这是非常意想不到的行为。最好的事情是提出一个错误（以便你自己发现了问题，而不必在Stackoverflow上提出你的问题），或者只是显示预期的元素方式的乘法（你的代码刚刚工作） 。有趣的是，列表和numpy的标量之间除了做工作：

In [69]: np.float64(0.123) + [1, 2, 3] 
Out[69]: array([ 1.123, 2.123, 3.123]) 

Answer 2

更改您的列表，以numpy阵列将做的工作！

import matplotlib.pyplot as plt 
from scipy import stats 
import numpy as np 

x = np.array([0.46,0.59,0.68,0.99,0.39,0.31,1.09,0.77,0.72,0.49,0.55,0.62,0.58,0.88,0.78]) # x is a numpy array now 
y = np.array([0.315,0.383,0.452,0.650,0.279,0.215,0.727,0.512,0.478,0.335,0.365,0.424,0.390,0.585,0.511]) # y is a numpy array now 
xerr = [0.01]*15 
yerr = [0.001]*15 

plt.rc('font', family='serif', size=13) 
m, b = np.polyfit(x, y, 1) 
plt.plot(x,y,'s',color='#0066FF') 
plt.plot(x, m*x + b, 'r-') #BREAKS ON THIS LINE 
plt.errorbar(x,y,xerr=xerr,yerr=0,linestyle="None",color='black') 
plt.xlabel('$\Delta t$ $(s)$',fontsize=20) 
plt.ylabel('$\Delta p$ $(hPa)$',fontsize=20) 
plt.autoscale(enable=True, axis=u'both', tight=False) 
plt.grid(False) 
plt.xlim(0.2,1.2) 
plt.ylim(0,0.8) 
plt.show()