Matplotlib:ValueError:x和y必须具有相同的第一维 [英] Matplotlib: ValueError: x and y must have same first dimension

问题描述

我正在尝试将最合适的线性线拟合到我的matplotlib图.我不断收到x和y不具有相同的第一维的错误.但是它们的长度都为15.我在做什么错了?

I am trying to fit a linear line of best fit to my matplotlib graph. I keep getting the error that x and y do not have the same first dimension. But they both have lengths of 15. What am I doing wrong?

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()

推荐答案

您应该创建x和y numpy数组，而不是列表:

You should make x and y numpy arrays, not lists:

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])

进行此更改后，将生成期望图.如果它们是列表，则m * x不会产生您期望的结果，而是一个空列表.请注意，m是numpy.float64标量，而不是标准的Python float.

With this change, it produces the expect plot. If they are lists, m * x will not produce the result you expect, but an empty list. Note that m is anumpy.float64 scalar, not a standard Python float.

我实际上认为这是Numpy的可疑行为.在普通的Python中，将列表与整数相乘只会重复该列表:

I actually consider this a bit dubious behavior of Numpy. In normal Python, multiplying a list with an integer just repeats the list:

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

将列表与浮点数相乘会产生错误(我认为应该这样):

while multiplying a list with a float gives an error (as I think it should):

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'

奇怪的是，将Python列表与Numpy标量相乘显然可行:

The weird thing is that multiplying a Python list with a Numpy scalar apparently works:

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]

因此，似乎浮点数被截断为一个int，然后您得到重复列表的标准Python行为，这是非常意外的行为.最好的办法是引发一个错误(这样您就可以自己发现问题，而不必在Stackoverflow上提问)或仅显示预期的逐元素乘法(在这种情况下您的代码就可以工作) .有趣的是，列表和Numpy标量之间的加法确实起作用:

So it seems that the float gets truncated to an int, after which you get the standard Python behavior of repeating the list, which is quite unexpected behavior. The best thing would have been to raise an error (so that you would have spotted the problem yourself instead of having to ask your question on Stackoverflow) or to just show the expected element-wise multiplication (in which your code would have just worked). Interestingly, addition between a list and a Numpy scalar does work:

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

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