Matplotlib：ValueError：x和y必須具有相同的第一維

Question

我試圖擬合最適合我的matplotlib圖的線性線。我不斷收到x和y不具有相同第一維的錯誤。但他們都有15的長度。我做錯了什麼？

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

你應該讓x和y numpy的陣列，而不是名單：

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]) 

隨着這一變化，它產生的預期情節。如果他們是名單，m * x不會產生你期望的結果，但是是一個空的名單。請注意，m是標量，而不是標準Python float。

我實際上認爲這有點可疑的Numpy行爲。在普通的Python，乘以一個整數的列表只是重複列表：

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

同時用浮動乘以一個列表給出了一個錯誤（因爲我認爲它應該）：

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' 

怪異的事情是一個numpy的標量乘以一個Python列表顯然作品：

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] 

如此看來，浮子被截斷爲int，之後你會得到重複的次標準的Python行爲e列表，這是非常意想不到的行爲。最好的事情是提出一個錯誤（以便你自己發現了問題，而不必在Stackoverflow上提出你的問題），或者只是顯示預期的元素方式的乘法（你的代碼剛剛工作） 。有趣的是，列表和numpy的標量之間除了做工作：

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陣列將做的工作！

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()