I am trying to plot a series of functions starting at different location on the x-axis. I'm fine with plotting them starting at the origin but varying location is causing trouble with these iteration. for instance:
我试图绘制一系列从x轴上不同位置开始的函数。我可以从原点开始绘制它们，但是不同的位置会导致这些迭代出现问题。例如：
x = [2,4,8, ..., Max]
y1=x**2 + 4
y2=x**2 + 4
...
y_m=x**2 + 4
Each plotted between:
每个绘制在：
[0, Max], [2, Max], [8, Max], .... [x_n-1, Max]
Can anyone help?
有人可以帮忙吗？
1 个解决方案
#1
1
In order to plot this left truncated function set, you may iterate over the starting index of an array slice, i.e. x[i:], which would select the complete list for i==0 and reduce the number of elements to be taken into account by one in succesive loop steps.
为了绘制这个左截断函数集，你可以遍历数组切片的起始索引，即x [i：]，它将选择i == 0的完整列表并减少要被采用的元素数量在一个成功的循环步骤中按一个帐户。
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(2,16,2)
f = lambda x: x**2 + 4
fig, ax = plt.subplots()
for i in range(len(x)-1):
ax.plot(x[i:], f(x[i:]), lw=2,label="Starting at {}".format(x[i]))
plt.legend()
plt.show()
#1
1
In order to plot this left truncated function set, you may iterate over the starting index of an array slice, i.e. x[i:], which would select the complete list for i==0 and reduce the number of elements to be taken into account by one in succesive loop steps.
为了绘制这个左截断函数集，你可以遍历数组切片的起始索引，即x [i：]，它将选择i == 0的完整列表并减少要被采用的元素数量在一个成功的循环步骤中按一个帐户。
import matplotlib.pyplot as plt
import numpy as np
x = np.arange(2,16,2)
f = lambda x: x**2 + 4
fig, ax = plt.subplots()
for i in range(len(x)-1):
ax.plot(x[i:], f(x[i:]), lw=2,label="Starting at {}".format(x[i]))
plt.legend()
plt.show()