用PyPlot绘制平滑线 [英] Plot smooth line with PyPlot

问题描述

我有以下简单的脚本可以绘制图形:

I've got the following simple script that plots a graph:

import matplotlib.pyplot as plt
import numpy as np

T = np.array([6, 7, 8, 9, 10, 11, 12])
power = np.array([1.53E+03, 5.92E+02, 2.04E+02, 7.24E+01, 2.72E+01, 1.10E+01, 4.70E+00])

plt.plot(T,power)
plt.show()

现在，这条线从一条直线到另一条直线看起来不错，但我认为可能会更好.我想要的是使两点之间的线变得平滑.在Gnuplot中，我会使用smooth cplines进行绘制.

As it is now, the line goes straight from point to point which looks ok, but could be better in my opinion. What I want is to smooth the line between the points. In Gnuplot I would have plotted with smooth cplines.

在PyPlot中有一种简单的方法吗?我已经找到了一些教程，但是它们看起来都相当复杂.

Is there an easy way to do this in PyPlot? I've found some tutorials, but they all seem rather complex.

推荐答案

您可以使用scipy.interpolate.spline自己整理数据:

You could use scipy.interpolate.spline to smooth out your data yourself:

from scipy.interpolate import spline

# 300 represents number of points to make between T.min and T.max
xnew = np.linspace(T.min(), T.max(), 300)  

power_smooth = spline(T, power, xnew)

plt.plot(xnew,power_smooth)
plt.show()

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scipy 0.19.0中已弃用

spline，请改用BSpline类.

spline is deprecated in scipy 0.19.0, use BSpline class instead.

从spline切换到BSpline并不是简单的复制/粘贴操作，需要进行一些调整:

Switching from spline to BSpline isn't a straightforward copy/paste and requires a little tweaking:

from scipy.interpolate import make_interp_spline, BSpline

# 300 represents number of points to make between T.min and T.max
xnew = np.linspace(T.min(), T.max(), 300) 

spl = make_interp_spline(T, power, k=3)  # type: BSpline
power_smooth = spl(xnew)

plt.plot(xnew, power_smooth)
plt.show()

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