通过删除下降值显示平滑曲线

问题描述

在这种情况下，是否可以通过平滑值下降的级别来显示平滑曲线？

例如，这里有两个完整的列表。

list1 = [0.02439024,0.04878049,0.07317073,0.09756098,0.12195122,0.14634146,0.17073171,0.19512195,0.2195122,0.24390244,0.26829268,0.29268293,0.31707317,0.34146341,0.36585366,0.3902439,0.41463415,0.43902439,0.46341463,0.48780488,0.51219512,0.53658537,0.56097561,0.58536585,0.6097561,0.63414634,0.65853659,0.68292683,0.70731707,0.73170732,0.75609756,0.7804878,0.80487805,0.82926829,0.85365854,0.87804878,0.90243902,0.92682927,0.95121951,0.97560976,0.97560976]

list2 = [1.,1.,0.974359,0.95,0.9268293,0.9285714,0.90697676,0.8863636,0.8666667,0.8695652,0.85106385,0.8333333,0.81632656,0.8,0.78431374,0.7692308,0.754717,0.7407407,0.72727275,0.71428573,0.7017544,0.6896552,0.6779661,0.6666667,0.6557377,0.6451613,0.63492066,0.625,0.61538464,0.6060606,0.5970149,0.5882353,0.5797101,0.5714286,0.5633803,0.5555556,0.5479452,0.5405405,0.53333336,0.5263158,0.5194805,0.51282054,0.5063291,0.5,0.49382716,0.4878049,0.48192772,0.47619048,0.47058824,0.4651163,0.4597701,0.45454547,0.4494382,0.44444445,0.43956044,0.4347826,0.43010753,0.42553192,0.42105263,0.41666666,0.41237113,0.40816328,0.4040404,0.4,0.3960396,0.39215687,0.3883495,0.3846154,0.3809524,0.3773585,0.37383178,0.37037036,0.36697248,0.36363637,0.36036035,0.35714287,0.3539823,0.3508772 ]

出现的曲线是带有 @werner 解的平滑曲线，虚线添加是我想要的最终平滑曲线。 B-spline度的变化似乎不是曲线形式。即使通过排序和删除 list2 下降的点：

new = list(zip(list1,list2))
new_ = list(dict(sorted(new)).items())
list1,list2 = list(zip(*new_))

平滑不是全部。

解决方法

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import signal

plt.ion()

df = pd.DataFrame(new,columns=['list1','list2'])
_ = signal.savgol_filter(new,21,2,axis=0)
df_ = pd.DataFrame(_,'list2'])

sns.scatterplot(data=df,x='list1',y='list2')
sns.scatterplot(data=df_,y='list2')

savgol_filter 会起作用吗？您可以根据自己的喜好稍微调整参数。