こんにちは、これらの値を区分線形関数に適合させる方法を見つけようとしています。この質問を読みましたが、先に進むことができません ( Python で区分線形フィットを適用する方法は? )。この例では、2 セグメントの場合に区分関数を実装する方法を示します。ただし、図のように 3 セグメントの場合に行う必要があります。
私はこのコードを書きました：
from scipy import optimize
import matplotlib.pyplot as plt
import numpy as np
x1 = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ,11, 12, 13, 14, 15,16,17,18,19,20,21], dtype=float)
y1 = np.array([5, 7, 9, 11, 13, 15, 28.92, 42.81, 56.7, 70.59, 84.47, 98.36, 112.25, 126.14, 140.03,145,147,149,151,153,155])
x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ,11, 12, 13, 14, 15], dtype=float)
y = np.array([5, 7, 9, 11, 13, 15, 28.92, 42.81, 56.7, 70.59, 84.47, 98.36, 112.25, 126.14, 140.03])
def piecewise(x,x0,x1,y0,y1,k0,k1,k2):
return np.piecewise(x , [x <= x0, (x>= x1)] , [lambda x:k0*x + y0-k0*x0, lambda x:k1*(x-(x1+x0))-y1, lambda x:k2*x + y1-k2*x1])
p , e = optimize.curve_fit(piecewise_linear, x1, y1)
xd = np.linspace(0, 15, 100)
plt.figure()
plt.plot(x1, y1, "o")
plt.plot(xd, piecewise_linear(xd, *p))
しかし、これは出力です
なにか提案を？問題はreturn np.piecewise(x , [x <= x0, (x>= x1)] , [lambda x:k0*x + y0-k0*x0, lambda x:k1*(x-(x1+x0))-y1, lambda x:k2*x + y1-k2*x1])特に 2 番目に あると思いlambdaます。
編集1：
AL が提供するソリューションとは異なるデータを使用しようとすると、良い結果が得られません。
私はこの結果を得ます：
と
x=[ 16.01690476, 16.13801587, 14.63628571, 15.32664399,
15.8145 , 15.71507143, 15.56107143, 15.553 ,
15.08734524, 14.97275 , 15.51958333, 16.61981859,
16.36589286, 14.78708333, 14.41565476, 13.47763158,
13.42412281, 12.95551378, 13.66601504, 13.63315789,
13.21463659, 13.53464286, 14.60130952, 14.7774881 ,
13.04319048, 12.53385965, 12.65745614, 13.90535714,
14.82412281, 14.6565 , 15.09541667, 13.41434524,
13.66033333, 14.57964286, 13.55416667, 13.43041667,
13.01137566, 12.76429825, 11.55241667, 11.0634881 ,
10.92729762, 11.21625 , 10.72092857, 11.80380952,
12.55233333, 12.11307143, 11.78892857, 12.45458333,
11.05539286, 10.69214286, 10.32566667, 11.3439881 ,
9.69563492, 10.72535714, 10.26180272, 7.77272727,
6.37704082, 8.49666667, 8.5389881 , 5.68547619,
7.00616667, 8.22015873, 10.20315476, 15.35736842,
12.25158333, 11.09622153, 10.4118254 , 9.8602381 ,
10.16727273, 15.10858333, 13.82215539, 12.44719298,
10.92341667, 11.44565476, 11.43333333, 10.5045 ,
11.14357143, 10.37625 , 8.93421769, 9.48444444,
10.43483333, 10.8659881 , 10.96166667, 10.12872619,
9.64663265, 9.29979762, 9.67173469, 8.978322 ,
9.10419501, 9.45411565, 10.46411565, 7.95739229,
8.72616667, 7.03892857, 7.32547619, 7.56441667,
6.61022676, 9.09014739, 10.78141667, 10.85918367,
11.11665476, 10.141 , 9.17760771, 8.27968254,
11.02625 , 12.34809524, 11.17807018, 11.25416667,
11.29236905, 9.28357143, 9.77033333, 11.52086168,
9.8625 , 12.60281955, 12.42785714, 12.11902256,
13.1 , 13.02791667, 13.87779449, 15.09857143,
13.93935185, 13.69821429, 13.39880952, 12.45692982,
12.76921053, 13.23708333, 13.71666667, 15.39807143,
15.27916667, 14.66464286, 13.38694444, 10.97555556,
10.02191667, 11.99608333, 14.26325 , 15.40991667,
15.12908333, 15.76265476, 12.12763158, 15.01641667,
14.39602381, 12.98532143, 14.98807018, 18.30547619,
16.7564966 , 16.82982143, 19.8487013 , 19.18600907]
と
y=[ 2.36846863, 2.73722628, 2.77177583, 2.63930636, 2.80864749,
2.57066667, 2.65277287, 2.57162347, 2.76295667, 2.79835391,
2.60431154, 2.17326401, 2.67740698, 2.47138153, 2.49882574,
2.60987338, 2.69935565, 2.60755362, 2.77702029, 2.62996942,
2.45959517, 2.52750434, 2.73833005, 2.52009 , 2.80933226,
1.63807085, 2.49230099, 2.55441614, 3.19256506, 2.52609288,
1.02931596, 2.40266963, 2.3306463 , 2.69094276, 2.60779985,
2.48351648, 2.45131766, 2.40526763, 2.03952569, 1.86217009,
1.79971848, 1.91772218, 1.85895421, 2.32725731, 2.28189713,
2.11835833, 2.09636517, 2.2230303 , 1.85863317, 1.77550406,
1.68862391, 1.79187765, 1.70887476, 1.81911193, 1.74802483,
1.65776432, 1.58012849, 1.67781494, 1.62451541, 1.60555884,
1.56172214, 1.60083809, 1.65256994, 2.74794704, 2.27089627,
1.80364982, 1.51412482, 1.77738757, 1.56979564, 2.46538633,
2.37679625, 2.40389294, 2.04165763, 1.82086407, 1.90609219,
1.87480978, 1.8877854 , 1.76080074, 1.68369028, 1.57419297,
1.66470126, 1.74522552, 1.72459756, 1.65510503, 1.72131148,
1.6254417 , 1.57091907, 1.68755268, 1.70307911, 1.59445121,
1.74393783, 1.72913779, 1.66883237, 1.59859545, 1.62335831,
1.73378184, 1.62621588, 1.79532164, 1.78289992, 1.79475101,
1.7826266 , 1.68778918, 1.64484127, 1.62332696, 1.75372393,
1.99038021, 1.87268137, 1.86124502, 1.82435911, 1.62927102,
1.66443723, 1.86743516, 1.62745098, 2.20200312, 2.09641026,
2.26649111, 2.63271605, 2.18050721, 2.57138433, 2.51833359,
2.74684184, 2.57209998, 2.63762019, 2.30027877, 2.28471286,
2.40323668, 2.37103313, 2.16414489, 1.01027109, 2.64181007,
2.45467765, 2.05773672, 1.73624917, 2.05233688, 2.70820669,
2.65594222, 2.67445635, 2.37212985, 2.48221803, 2.77655216,
2.62839879, 2.26481307, 2.58005799, 2.1188172 , 2.14017268,
2.16459571, 1.95083406, 1.46224418]