在Python中:
>>> import numpy as np
>>> coeff = [0.708563939215852, -0.3111717537041549, -0.2151830138973625]
>>> np.roots(coeff)
array([ 0.81279407, -0.37363574])
在Matlab中:
>> coeff = [0.708563939215852, -0.3111717537041549, -0.2151830138973625]
>> roots(coeff)
ans =
0.812794068532020
-0.373635742116877
<>我在C++中用特征库尝试,但得到不同的结果:#include <unsupported/Eigen/Polynomials>
Eigen::Vector3d coeff(0.708563939215852, -0.3111717537041549, -0.2151830138973625);
Eigen::PolynomialSolver<double, Eigen::Dynamic> solver;
solver.compute(coeff);
const Eigen::PolynomialSolver<double, Eigen::Dynamic>::RootsType &r = solver.roots();
--> r[2] = {{1.2303239390096565, 0.000}, {-2.6764034787849331, 0.000}}
感谢@rafix07的注释,下面的代码给出了与NumPy和MATLAB中相同的结果。系数的顺序必须进行交换
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