Python绘图错误：annotate为参数“ xy”获得了多个值

问题描述

在我的绘图中，我试图在每个点使用多个值进行注释。

weights = [np.array([w,1-w]) for w in np.linspace(0,1,5)]

mu = [0.5,0.25]

def portfolio_return(weights,returns):
    return weights.T @ returns

rets = [portfolio_return(w,mu) for w in weights]

S = [[0.493,0.11],[0.11,0.16]]
def portfolio_vol(weights,cov):
    return (weights.T @ cov @ weights)**0.5

vols = [portfolio_vol(w,S) for w in weights]

import matplotlib.pyplot as plt
%matplotlib inline
%config InlineBackend.figure_format = 'svg'

markers_on = [1,3]
fig = plt.figure()
ax = fig.add_subplot(111)
plt.plot(vols,rets,'g-')

for marker in markers_on:
    plt.plot(vols[marker],rets[marker],'bs')
    w1,w2 = weights[marker][0],weights[marker][1]
    ax.annotate(f'w = ({w1:.1f},{w2:.1f})',(w1,w2),xy=(vols[marker]+.08,rets[marker]-.03))

plt.xlabel('Risk')
plt.ylabel('Return')
plt.show()

这将返回错误-

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-8-0e29da296b76> in <module>
     11     plt.plot(vols[marker],'bs')
     12     w1,weights[marker][1]
---> 13     ax.annotate(f'w = ({w1:.1f},rets[marker]-.03))

TypeError: annotate() got multiple values for argument 'xy'

Python情节的新手。我想做的就是在图中标注两个点，每个点都显示两个权重。

---------------------------------------------------------------------------

注意-在@ewong的评论之后进行了以下更改。

for marker in markers_on:
    plt.plot(vols[marker],weights[marker][1]
    ax.annotate(r'w = ({w1:%.2f},{w2:%.2f})',w2))

没有错误，这很好。不幸的是，尽管它标记了两个位置，但没有显示权重。

在剧情出现之前，还有大量的空白。我必须在jupyter笔记本中向下滚动。

----------------------------------------------------------------------------------

进行了进一步的更改。使用所有三个标记获取图。但不是重量。

for marker in markers_on:
    plt.plot(vols[marker],weights[marker][1]
    text = f'w = ({w1:.2f},{w2:.2f})',w2)
    ax.annotate(s = text,rets[marker]-.03))

解决方法

之所以看不到粗细，是因为您使用xy=(vols[marker]+.08,rets[marker]-.03)调整了文字位置。从您的图片中，我注意到x max为0.0225。 0.08大于0.0225，因此文本超出范围。

import numpy as np
import matplotlib.pyplot as plt

weights = [np.array([w,1-w]) for w in np.linspace(0,1,5)]

mu = [0.5,0.25]

def portfolio_return(weights,returns):
    return weights.T @ returns

rets = [portfolio_return(w,mu) for w in weights]

S = [[0.493,0.11],[0.11,0.16]]
def portfolio_vol(weights,cov):
    return (weights.T @ cov @ weights)**0.5

vols = [portfolio_vol(w,S) for w in weights]


markers_on = [1,3]
fig = plt.figure()
ax = fig.add_subplot(111)
plt.plot(vols,rets,'g-')

for marker in markers_on:
    plt.plot(vols[marker],rets[marker],'bs')
    w1,w2 = weights[marker][0],weights[marker][1]
    text = f'w = ({w1:.1f},{w2:.1f})'
    ax.annotate(text,xy=(vols[marker]+.005,rets[marker]-0.005))

plt.xlabel('Risk')
plt.ylabel('Return')
plt.show()