如何使用 Python SciPy 求解循环矩阵方程？
名为scipy.linalg.solveh_banded的线性函数用于求解带状矩阵方程。在下面给出的例子中，我们将解决循环系统Cx=b-
示例
fromscipy.linalgimport solve_circulant, solve, circulant, lstsq import numpy as np c = np.array([2, 2, 4]) b = np.array([1, 2, 3]) solve_circulant(c, b)输出结果
array([ 0.75, -0.25, 0.25])
示例
让我们看一个单一的例子，它会引发一个LinAlgError-
fromscipy.linalgimport solve_circulant, solve, circulant, lstsq import numpy as np c = np.array([1, 1, 0, 0]) b = np.array([1, 2, 3, 4]) solve_circulant(c, b)输出结果
--------------------------------------------------------------------------
LinAlgError Traceback (most recent call last)
<ipython-input-6-978604ed0a97> in <module>
----> 1 solve_circulant(c, b)
~\AppData\Roaming\Python\Python37\site-packages\scipy\linalg\basic.py in
solve_circulant(c, b, singular, tol, caxis, baxis, outaxis)
865 if is_near_singular:
866 if singular == 'raise':
--> 867 raise LinAlgError("近奇异循环矩阵。")
868 else:
869 #将较小的值替换为1以避免错误
LinAlgError: 近奇异循环矩阵。现在，要消除此错误，我们需要使用选项single='lstsq'如下-
fromscipy.linalgimport solve_circulant, solve, circulant, lstsq import numpy as np c = np.array([1, 1, 0, 0]) b = np.array([1, 2, 3, 4]) solve_circulant(c, b, singular='lstsq')输出结果
array([0.25, 1.25, 2.25, 1.25])