Incompatible function arguments

[wsp666]

When I used pybind11 to encapsulate goptimization.cpp as a static library that Python can call, the static library was successfully generated, but when I call it by python script test.py, the following error occurred:

optimize_graph(): incompatible function arguments. The following argument types are supported:
    1. (arg0: List[Eigen::Matrix<double, 2, 1, 0, 2, 1>], arg1: List[Eigen::Matrix<double, 2, 1, 0, 2, 1>], arg2: List[Eigen::Matrix<double, 2, 1, 0, 2, 1>], arg3: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg4: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg5: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg6: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg7: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg8: Eigen::Matrix<double, 4, 4, 0, 4, 4>) -> Tuple[Eigen::Matrix<double, 4, 4, 0, 4, 4>, Eigen::Matrix<double, 4, 4, 0, 4, 4>]

Invoked with: [array([-2.0211, -7.4957])], [array([ 0.11208, -8.2119 ])], [array([ 3.0031, -8.5468])], array([[ 0.95807, -0.28652,  0.     ,  2.5583 ],
       [ 0.28652,  0.95807,  0.     , -0.65413],
       [ 0.     ,  0.     ,  1.     ,  0.     ],
       [ 0.     ,  0.     ,  0.     ,  1.     ]]), array([[ 0.95306, -0.30279,  0.     ,  2.9053 ],
       [ 0.30279,  0.95306,  0.     , -0.44314],
       [ 0.     ,  0.     ,  1.     ,  0.     ],
       [ 0.     ,  0.     ,  0.     ,  1.     ]]), array([[ 0.9911 , -0.13312,  0.     ,  1.515  ],
       [ 0.13312,  0.9911 ,  0.     , -0.396  ],
       [-0.     ,  0.     ,  1.     ,  0.     ],
       [ 0.     ,  0.     ,  0.     ,  1.     ]]), array([[ 0.99116, -0.13269,  0.     ,  1.4875 ],
       [ 0.13269,  0.99116,  0.     , -0.40444],
       [-0.     ,  0.     ,  1.     ,  0.     ],
       [ 0.     ,  0.     ,  0.     ,  1.     ]]), array([[1., 0., 0., 0.],
       [0., 1., 0., 0.],
       [0., 0., 1., 0.],
       [0., 0., 0., 1.]]), array([[1., 0., 0., 0.],
       [0., 1., 0., 0.],
       [0., 0., 1., 0.],
       [0., 0., 0., 1.]])

here is my test.py:

import numpy as np

import goptimization

# help(goptimization)

sim_data_D = np.loadtxt('./data/data_D.txt')
sim_data_P = np.loadtxt('./data/data_P.txt')
sim_data_T = np.loadtxt('./data/data_T.txt')

P2 = sim_data_P[:,:2]
P1 = sim_data_P[:,2:4]
P = sim_data_P[:,4:]

T1 = sim_data_T[:4,:]
T2 = sim_data_T[4:,:]

D1 = sim_data_D[:4,:]
D2 = sim_data_D[4:,:]

M1 = np.identity(4)
M2 = np.identity(4)

goptimization.optimize_graph([P2[0]],
                 [P1[0]],
                 [P[0]],
                 T1,
                 T2,
                 D1,
                 D2,
                 M1,
                 M2)

here is my cpp file:

PYBIND11_MODULE(goptimization, m) {
  m.def("optimize_graph", &my_optimization, "Optimize the graph");
}

and my my_optimization function is declared:

std::pair<Eigen::Matrix4d, Eigen::Matrix4d> 
        my_optimization(std::vector<Eigen::Vector2d> P2,
                      std::vector<Eigen::Vector2d> P1,
                      std::vector<Eigen::Vector2d> P,
                      Eigen::Matrix4d T1, Eigen::Matrix4d T2,
                      Eigen::Matrix4d D1, Eigen::Matrix4d D2,
                      Eigen::Matrix4d M1, Eigen::Matrix4d M2)

Meanwhile, Multiple custom classes are used internally in the function my_optimization.
So, how to deal with it?
Thanks!

[wsp666]

In addition, the help on the function is here:

FUNCTIONS
    optimize_graph(...) method of builtins.PyCapsule instance
        optimize_graph(arg0: List[Eigen::Matrix<double, 2, 1, 0, 2, 1>], arg1: List[Eigen::Matrix<double, 2, 1, 0, 2, 1>], arg2: List[Eigen::Matrix<double, 2, 1, 0, 2, 1>], arg3: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg4: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg5: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg6: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg7: Eigen::Matrix<double, 4, 4, 0, 4, 4>, arg8: Eigen::Matrix<double, 4, 4, 0, 4, 4>) -> Tuple[Eigen::Matrix<double, 4, 4, 0, 4, 4>, Eigen::Matrix<double, 4, 4, 0, 4, 4>]