限制绘图中的拟合

Question

我有一张数据图，并对其应用了线性拟合，但是，我不确定为什么，但拟合线与数据本身相距甚远。我将如何对这条线施加限制，使其恰好适合我的数据（最好也使数据成为图表的焦点！）

图形输出和代码如下：

plt.plot(np.log(ts), amps, "1", ms=5, label="Schmitt Analysis (Amplitude against Log(Time))")

##Plot Linear Fit
y1, r, *_ = np.polyfit(amps, np.log(ts), 1, full=True)
f1 = np.poly1d(y1)
plt.plot(amps, f1(amps), label=f"linear ($\chi^2$ = {r[0]:0.2f})")

plt.xlabel("Log(Time)")
plt.ylabel("Amplitude")
plt.title("Schmitt Analysis (Amplitude against Log(Time))")
plt.xlim(0,10)
plt.ylim(-40,80)
plt.legend()

plt.savefig('A_Schmitt.jpg')

实际使用的数据：

log(ts) = [ -inf 2.89037176 3.58351894 3.98898405 4.49980967 4.68213123 4.83628191 4.9698133 5.08759634 5.19295685 5.28826703 5.37527841 5.45532112 5.52942909 5.59842196 5.7235851 5.78074352 5.83481074 5.9348942 6.02586597 6.06842559 6.10924758 6.1484683 6.22257627 6.25766759 6.32435896 6.38687932 6.41673228 6.44571982 6.50128967 6.52795792 6.5539334 6.71901315 6.78219206]

amps = [77.78630383833547, 62.92926582239441, 63.84025706577048, 55.489066870438165, 38.60797989548756, 40.771390484048545, 14.679073842876978, 33.95959972488966, 29.41960790300141, 32.93241034391399, 30.927428194781815, 31.086396885182356, 21.52771899125612, 4.27684299160886, 6.432975528727562, 7.500376934048583, 18.730555740591637, 4.355896959987761, 11.677509915219987, 12.865482314301719, 0.6120306267606219, 12.614420497451556, 2.2025029753442404, 9.447046999592711, 4.0688197216393425, 0.546672901996845, 1.12780050608251, 2.2030852358874635, 2.202804718915858, 0.5726686031033587, 0.5465322281618783, 0.5185100682386156, 0.575055917739342, 0.5681697592593679]

注意到我犯了一个错误，我设法让图表更新了一点，但现在拟合完全失败了。

我也将上面的代码更新到新版本。

Answer 1

使用xlim和ylim

    plt.plot(np.log(ts), amps, "1", ms=5, label="Schmitt Analysis (Log(Amplitude) 
    against Time)")
    
    
    y1, r, *_ = np.polyfit(amps, ts, 1, full=True)
    f1 = np.poly1d(y1)
    plt.plot(amps, f1(amps), label=f"linear ($\chi^2$ = {r[0]:0.2f})")
    
    plt.xlabel("Log(Time)")
    plt.ylabel("Amplitude")
    plt.title("Schmitt Analysis (Amplitude against Log(Time)")
    plt.xlim(0, 10)
    plt.ylim(0, 10)
    plt.legend()
    
    plt.savefig('A_Schmitt.jpg'

)

Answer 2

这里有两个问题 - 拼写错误和存在 -inf。
首先是打字错误 - 你将 logts 和 amps 分别归因于 y 和 x，在你的适合，而它应该是相反的。
其次，-inf 在您的 log-transformed 时间数组中的存在没有被 fit 例程很好地处理。我们可以用 logts[1:].

手动排除第一个点

import numpy as np
from matplotlib import pyplot as plt

#recreating your input - seemingly log(ts) is a numpy array
logts = np.asarray([-np.inf, 2.89037176, 3.58351894, 3.98898405, 4.49980967, 4.68213123, 4.83628191, 4.9698133, 5.08759634, 5.19295685, 5.28826703, 5.37527841, 5.45532112, 5.52942909, 5.59842196, 5.7235851, 5.78074352, 5.83481074, 5.9348942, 6.02586597, 6.06842559, 6.10924758, 6.1484683, 6.22257627, 6.25766759, 6.32435896, 6.38687932, 6.41673228, 6.44571982, 6.50128967, 6.52795792, 6.5539334, 6.71901315, 6.78219206])
amps = [77.78630383833547, 62.92926582239441, 63.84025706577048, 55.489066870438165, 38.60797989548756, 40.771390484048545, 14.679073842876978, 33.95959972488966, 29.41960790300141, 32.93241034391399, 30.927428194781815, 31.086396885182356, 21.52771899125612, 4.27684299160886, 6.432975528727562, 7.500376934048583, 18.730555740591637, 4.355896959987761, 11.677509915219987, 12.865482314301719, 0.6120306267606219, 12.614420497451556, 2.2025029753442404, 9.447046999592711, 4.0688197216393425, 0.546672901996845, 1.12780050608251, 2.2030852358874635, 2.202804718915858, 0.5726686031033587, 0.5465322281618783, 0.5185100682386156, 0.575055917739342, 0.5681697592593679]

#plot raw data
plt.plot(logts, amps, "1", ms=5, label="Schmitt Analysis (Amplitude against Log(Time))")

#linear fit excluding the first point that is an outlier
y1, r, *_ = np.polyfit(logts[1:], amps[1:], 1, full=True)
f1 = np.poly1d(y1)

#get min and max of logts excluding nan and inf values
logtsmin = np.floor(np.nanmin(logts[logts != -np.inf]))
logtsmax = np.ceil(np.nanmax(logts[logts != np.inf]))
#evenly spaced x-values for the fit line plot 
xlogts = np.linspace(logtsmin, logtsmax, 1000)
plt.plot(xlogts, f1(xlogts), label=f"linear ($\chi^2$ = {r[0]:0.2f})")

plt.xlabel("Log(Time)")
plt.ylabel("Amplitude")
plt.title("Schmitt Analysis (Amplitude against Log(Time))")
plt.xlim(logtsmin, logtsmax)
plt.legend()

plt.show()

示例输出：

限制绘图中的拟合

Putting limits on a fitting in a plot

python

numpy

matplotlib

curve-fitting