Numpy SVD在连续循环下不收敛于线性最小二乘
当运行以下python代码时，它运行时不会出错。然而，当相同的数字从物联网传感器输入展平功率时，即在循环中连续运行，我得到错误“SVD未以线性最小二乘收敛”。以下数组中的数字是从给定错误“SVD未以线性最小二乘收敛”时复制和粘贴的。Numpy SVD在连续循环下不收敛于线性最小二乘,numpy,scipy,numpy-ndarray,Numpy,Scipy,Numpy Ndarray,当运行以下python代码时，它运行时不会出错。然而，当相同的数字从物联网传感器输入展平功率时，即在循环中连续运行，我得到错误“SVD未以线性最小二乘收敛”。以下数组中的数字是从给定错误“SVD未以线性最小二乘收敛”时复制和粘贴的。 在候机楼的窗口我看到 输入DLASCLS时，参数编号4的值非法 输入DLASCLS时，参数编号4的值非法“ from scipy import signal import numpy as np flatten_power = np.array([ 23.16,
在候机楼的窗口我看到 输入DLASCLS时，参数编号4的值非法 输入DLASCLS时，参数编号4的值非法“
from scipy import signal
import numpy as np
flatten_power = np.array([ 23.16, 22.46, 22.57, 25.27, 21.29, 22.78, 23.69,
22.82, 21.3 , 23.45, 23.99, 22.07, 22.54, 22.78,
21.57, 23.27, 22.88, 24.06, 23.95, 20.61, 22.62,
25.06, 22.94, 24.31, 22.83, 23.74, 22.1 , 23.39,
22.6 , 25.08, 23.43, 22.09, 23.73, 23.35, 23.52,
21.71, 22.72, 21.2 , 23.34, 22.04, 21.82, 24.89,
22.19, 24.13, 23.56, 22.53, 21.81, 28.48, 23.63,
22.3 , 22.46, 23.58, 23.02, 23.13, 24.33, 22.49,
24.6 , 23.72, 21.27, 23.25, 22.94, 24.45, 24.61,
23.75, 22.96, 22.11, 22.84, 23.44, 23.11, 21.19,
22.02, 23.22, 23.72, 20.9 , 23.76, 22.86, 22.04,
22.19, 22.68, 23.24, 23.5 , 21.58, 23.92, 24.67,
22.64, 24.35, 22.33, 21.35, 21.15, 24.52, 23.26,
20.41, 22.13, 22.22, 22.47, 22.72, 21.35, 23.22,
25.18, 21.6 , 24.16, 25.02, 23.68, 25.23, 23.14,
25.26, 25.96, 23.74, 25.14, 25.43, 24.25, 28.33,
26.07, 34.77, 23.77, 26.13, 25.05, 23.5 , 24.67,
24.05, 23.38, 27.03, 27.13, 23.64, 25.36, 25.71,
26.04, 25.3 , 24.62, 23.78, 24.26, 28.86, 23.62,
26.85, 25.39, 24.84, 27.19, 26.29, 24.53, 25.82,
25.91, 25.61, 26.35, 23.22, 24.91, 22.39, 25.66,
28.78, 23.64, 22.91, 25.6 , 22.96, 22.49, 21.91,
22.41, 22.4 , 22.97, 24.75, 23.35, 23.38, 24.9 ,
21.94, 21.57, 23.3 , 22.83, 23.61, 22.85, 23.74,
22.95, 23.64, 22.96, 23.32, 22.29, 21.88, 22.35,
25.28, 22.62, 23.29, 22.85, 23.79, 24.46, 21.79,
22.23, 21.79, 22.84, 24.61, 23.52, 22.82, 22.99,
22.91, 24.56, 23.11, 23.76, 22.85, 22.06, 21.99,
24.47, 22.67, 22.64, 22.46, 24.66, 22.14, 25.58,
23.11, 23. , 22.65, 22.48, 24.96, 22.64, 22.16,
621.04, 269.5 , 29.33, 1035.99, 170.67, 673.22, 181.29,
216.2 , 844.08, 115.34, 133.18, 96.98, 98.93, 278.49,
104.94, 311.92, 1037.68, 322.75, 561.8 , 989.76, 652.98,
574.07, 676.87, 660.16, 604.62, 689.59, 653.65, 753.52,
681.86, 701.36, 679.6 , 698.15, 638.34, 714.32, 662.22,
634.62, 668.27, 702.85, 667.87, 750.7 , 746.33, 590.96,
646.18, 712.75, 650.15, 671.42, 737.9 , 635.75, 672.51,
682.16, 612.88, 696.04, 685.16, 655.46, 666.21, 654.82,
718.76, 661.24, 468.6 , 485.03, 439.47, 511.13, 457.96,
554.79, 481.19, 442.89, 530.47, 391.72, 524.2 , 582.09,
372.63])
smoothed_power = signal.savgol_filter(flatten_power, window_length=101, polyorder=2)