Python 作图多项式

在一些帮助下，我生成了以下代码。以下是给定输入的一些期望输出。然而，我在完成这段代码的最后一个任务时遇到了一些困难。在此寻求帮助，非常感谢任何指导或帮助，谢谢

根据以下输入，我得到了以下输出：

poly_horner（[1,2,3,4,5]，2）
129
打印（触发器）
8.
poly_naive（[1,2,3,4,5,2]）
129
打印（触发器）[！[在此处输入图像描述][1][1]
20
np.polyval（[5,4,3,2,1]，2）
129

我假设您想创建一个数字，尽管您的问题很模糊……但我有几分钟的时间在代码运行时消磨时间。不管怎么说，你可能很难策划

import numpy as np
import pylab as pl

x = np.arange(10)
y = x * np.pi

# you can calculate a line of best fit (lobf) using numpy's polyfit function
lobf1 = np.polyfit(x, y, 1)  # first degree polynomial
lobf2 = np.polyfit(x, y, 2)  # second degree polynomial
lobf3 = np.polyfit(x, y, 3)  # third degree polynomial

# you can now use the lines of best fit to calculate the 
# value anywhere within the domain using numpy's polyval function
# FIRST, create a figure and a plotting axis within the fig
fig = pl.figure(figsize=(3.25, 2.5))
ax0 = fig.add_subplot(111)

# now use polyval to calculate your y-values at every x
x = np.arange(0, 20, 0.1)
ax0.plot(x, np.polyval(lobf1, x), 'k')
ax0.plot(x, np.polyval(lobf2, x), 'b')
ax0.plot(x, np.polyval(lobf3, x), 'r')

# add a legend for niceness
ax0.legend(('Degree 1', 'Degree 2', 'Degree 3'), fontsize=8, loc=2)

# you can label the axes whatever you like
ax0.set_ylabel('My y-label', fontsize=8)
ax0.set_xlabel('My x-label', fontsize=8)

# you can show the figure on your screen
fig.show()

# and you can save the figure to your computer in different formats
# specifying bbox_inches='tight' helps eliminate unnecessary whitespace around
# the axis when saving...it just looks better this way.
pl.savefig('figName.png', dpi=500, bbox_inches='tight')
pl.savefig('figName.pdf', bbox_inches='tight')

# don't forget to close the figure
pl.close('all')

---

完成最后一项任务时，您遇到了哪些具体问题？欢迎使用StackOverflow。请按照您创建此帐户时的建议，阅读并遵循帮助文档中的发布指南，在这里申请。StackOverflow不是设计、编码、研究或教程资源。我们需要比“我有麻烦”更具体的东西，特别是因为在线教程和示例中很好地介绍了“绘图”。@martineau我不太确定如何完成这部分内容question@Prune谢谢，我会记住的。用户123：那还是太模糊了。也许下载/安装类似的东西会有所帮助（假设您还没有它，这就是您不确定如何完成任务的意思）。所以我只需要将它添加到我的代码中以使其运行？我还需要使用plt.show（）而不是fig.show（）使我的代码运行！或者这只是一种普通的绘图方式？你原来的帖子模棱两可到了无法回答的程度。我抓住了一个机会，你可能需要帮助创建你的数字…看起来我浪费了我的时间。不，它有帮助！我会看一下，学习如何创造数字

import numpy as np
import pylab as pl

x = np.arange(10)
y = x * np.pi

# you can calculate a line of best fit (lobf) using numpy's polyfit function
lobf1 = np.polyfit(x, y, 1)  # first degree polynomial
lobf2 = np.polyfit(x, y, 2)  # second degree polynomial
lobf3 = np.polyfit(x, y, 3)  # third degree polynomial

# you can now use the lines of best fit to calculate the 
# value anywhere within the domain using numpy's polyval function
# FIRST, create a figure and a plotting axis within the fig
fig = pl.figure(figsize=(3.25, 2.5))
ax0 = fig.add_subplot(111)

# now use polyval to calculate your y-values at every x
x = np.arange(0, 20, 0.1)
ax0.plot(x, np.polyval(lobf1, x), 'k')
ax0.plot(x, np.polyval(lobf2, x), 'b')
ax0.plot(x, np.polyval(lobf3, x), 'r')

# add a legend for niceness
ax0.legend(('Degree 1', 'Degree 2', 'Degree 3'), fontsize=8, loc=2)

# you can label the axes whatever you like
ax0.set_ylabel('My y-label', fontsize=8)
ax0.set_xlabel('My x-label', fontsize=8)

# you can show the figure on your screen
fig.show()

# and you can save the figure to your computer in different formats
# specifying bbox_inches='tight' helps eliminate unnecessary whitespace around
# the axis when saving...it just looks better this way.
pl.savefig('figName.png', dpi=500, bbox_inches='tight')
pl.savefig('figName.pdf', bbox_inches='tight')

# don't forget to close the figure
pl.close('all')