def crop_pointcloud(data_crop, x_o, y_o, x_i, y_i, R_o, R_i, z_critical): K_o = R_o ** 2 / range_z K_i = R_i ** 2 / range_z for z in range(range_z): r_o = np.sqrt(z * K_o) data_layer = data_crop[:, :, z] d_o = np.sqrt(x_o ** 2 + y_o ** 2) d_i = np.sqrt(x_i ** 2 + y_i ** 2) if z < z_critical: r_i = 0 else: r_i = np.sqrt(z * K_i) data_crop[:, :, z] = np.where((d_o > r_o) | (d_i <= r_i), 0, data_layer) return data_crop data_crop = data[:, :, :400] print(file_path) # np.savetxt('reshape_data.txt', data_crop, delimiter=',') range_x, range_y, range_z = data_crop.shape x, y = np.meshgrid(np.arange(range_x), np.arange(range_y)) # np.savetxt('reshape_data.txt', x, delimiter=' ', fmt="%i") x_o = x - range_x / 2 y_o = y - range_y / 2 x_i = x - dx y_i = y - dy z_critical = 50 R_o = 550 R_i = 200 data_crop = crop_pointcloud(data_crop, x_o, y_o, x_i, y_i, R_o, R_i, z_critical) data_crop = data_crop[:, :, 10:] 用C++ Eigen::Tensor实现

以下是使用C++ Eigen::Tensor实现的crop_pointcloud函数的代码：

#include <iostream>
#include <Eigen/Dense>
#include <unsupported/Eigen/CXX11/Tensor>

using namespace Eigen;

template<typename Scalar>
Eigen::Tensor<Scalar, 3> crop_pointcloud(const Eigen::Tensor<Scalar, 3>& data_crop, const Eigen::Tensor<Scalar, 2>& x_o, const Eigen::Tensor<Scalar, 2>& y_o, const Eigen::Tensor<Scalar, 2>& x_i, const Eigen::Tensor<Scalar, 2>& y_i, const Scalar R_o, const Scalar R_i, const Scalar z_critical) {
    Eigen::Tensor<Scalar, 3> cropped_data = data_crop;

    Scalar K_o = R_o * R_o / cropped_data.dimension(2);
    Scalar K_i = R_i * R_i / cropped_data.dimension(2);

    for (int z = 0; z < cropped_data.dimension(2); z++) {
        Scalar r_o = std::sqrt(z * K_o);
        auto data_layer = cropped_data.chip(z, 2);
        auto d_o = (x_o.square() + y_o.square()).sqrt();
        auto d_i = (x_i.square() + y_i.square()).sqrt();

        Scalar r_i = (z < z_critical) ? 0 : std::sqrt(z * K_i);
        data_layer = data_layer * ((d_o <= r_o) && (d_i > r_i)).cast<Scalar>();
    }

    return cropped_data;
}

int main() {
    Eigen::Tensor<float, 3> data_crop; // initialize data_crop tensor
    Eigen::Tensor<float, 2> x_o, y_o, x_i, y_i; // initialize x_o, y_o, x_i, y_i tensors
    float R_o, R_i, z_critical;

    // set values for data_crop, x_o, y_o, x_i, y_i, R_o, R_i, and z_critical

    Eigen::Tensor<float, 3> cropped_data = crop_pointcloud(data_crop, x_o, y_o, x_i, y_i, R_o, R_i, z_critical);
    cropped_data = cropped_data.slice(Eigen::array<int, 3>({0, 0, 10}), Eigen::array<int, 3>({cropped_data.dimension(0), cropped_data.dimension(1), cropped_data.dimension(2) - 10}));
    // use cropped_data tensor
}

该代码使用了Eigen::Tensor库来操作tensor，其中chip函数用于获取tensor中的某一层数据，slice函数用于裁剪tensor。