//
// Created by 14727 on 2022/11/7.
//

#include <utility>

#include "NurbsEvaluator.cuh"
#include "cstdio"
#include "utils.h"
//#include "NurbsBasis.cuh"

__device__ void normalization(float &a, float &b, float &c) {
    float sumA = a * a;
    float sumB = b * b;
    float sumC = c * c;
    float sum = sumA + sumB + sumC;
    a = sqrt(sumA / sum);
    b = sqrt(sumB / sum);
    c = sqrt(sumC / sum);
}

//extern __device__ void NurbsBasis::d_basisFunction(float *N_Texture, const float *knots, float u, int degree, int d_knotsCnt) {};

__host__ NurbsSurface::Evaluator::Evaluator(std::vector<std::vector<std::vector<float>>> controlPoints,
                                            std::vector<float> knots_u, std::vector<float> knots_v) {
    this->knots_u = std::move(knots_u);
    this->knots_v = std::move(knots_v);
    this->controlPoints = std::move(controlPoints);
    recordTime = false;
    d_nTexture_u = nullptr;
    d_nTexture_v = nullptr;
    d_nTexture1_u = nullptr;
    d_nTexture1_v = nullptr;
    d_knots_u = nullptr;
    d_knots_v = nullptr;
    d_points = nullptr;
    d_derivatives = nullptr;
}

__host__ std::vector<std::map<std::pair<float, float>, std::vector<float>>>
NurbsSurface::Evaluator::evaluate(int sampleCnt_u, int sampleCnt_v) {
    if (POINT_SIZE != controlPoints[0][0].size()) {
        printf("Error! Nurbs控制点应表示为长度为4的齐次坐标\n");
        return {};
    }

    // 构造指向device的controlPoints
    const int pointsCnt_u = controlPoints.size(), pointsCnt_v = controlPoints[0].size();
    const int pointsBytes = pointsCnt_u * pointsCnt_v * POINT_SIZE * sizeof(float);
    auto *h_points = (float *) malloc(pointsBytes);
    for (int i = 0; i < pointsCnt_u; i++) {
        for (int j = 0; j < pointsCnt_v; j++) {
            for (int k = 0; k < POINT_SIZE; k++) {
                h_points[(i * pointsCnt_v + j) * POINT_SIZE + k] = controlPoints[i][j][k];
            }
        }
    }
    cudaMalloc((void **) &d_points, pointsBytes);
    cudaMemcpy(d_points, h_points, pointsBytes, cudaMemcpyHostToDevice);

    // 构造指向device的knots
    const int knotsCnt_u = knots_u.size(), knotsCnt_v = knots_v.size();
    const int knotsBytes_u = knotsCnt_u * sizeof(float), knotsBytes_v = knotsCnt_v * sizeof(float);
    auto *h_knots_u = (float *) malloc(knotsBytes_u), *h_knots_v = (float *) malloc(knotsBytes_v);
    for (int i = 0; i < knotsCnt_u; i++) h_knots_u[i] = knots_u[i];
    for (int i = 0; i < knotsCnt_v; i++) h_knots_v[i] = knots_v[i];

    cudaMalloc((void **) &d_knots_u, knotsBytes_u);
    cudaMalloc((void **) &d_knots_v, knotsBytes_v);
    cudaMemcpy(d_knots_u, h_knots_u, knotsBytes_u, cudaMemcpyHostToDevice);
    cudaMemcpy(d_knots_v, h_knots_v, knotsBytes_v, cudaMemcpyHostToDevice);

    // 构造nTexture
    cudaMalloc((void **) &d_nTexture_u,
               sampleCnt_u * pointsCnt_u * sizeof(float)); // 注意nTexture的大小，在算梯度时用得到i=pointsCnt + 1的基函数值
    cudaMalloc((void **) &d_nTexture_v, sampleCnt_v * pointsCnt_v * sizeof(float));

    // 构造nTexture1
    cudaMalloc((void **) &d_nTexture1_u, sampleCnt_u * (pointsCnt_u + 1) * sizeof(float));
    cudaMalloc((void **) &d_nTexture1_v, sampleCnt_v * (pointsCnt_v + 1) * sizeof(float));

    // 构造g_basisTexture线程层级
    dim3 blockBasis(512);
    dim3 gridBasis_u((sampleCnt_u + blockBasis.x - 1) / blockBasis.x);
    dim3 gridBasis_v((sampleCnt_v + blockBasis.x - 1) / blockBasis.x);

    // 构造线程层级，调用核函数
    dim3 block(32, 32);
    dim3 grid((sampleCnt_u + block.x - 1) / block.x, (sampleCnt_v + block.y - 1) / block.y);
    // 记录用时
    double time_cost_device;
    g_basisTexture<<<gridBasis_u, blockBasis>>>(d_nTexture_u, d_nTexture1_u, d_knots_u, pointsCnt_u, knotsCnt_u,
                                                sampleCnt_u);
    cudaDeviceSynchronize();
    g_basisTexture<<<gridBasis_v, blockBasis>>>(d_nTexture_v, d_nTexture1_v, d_knots_v, pointsCnt_v, knotsCnt_v,
                                                sampleCnt_v);
    cudaDeviceSynchronize();

    if (recordTime) time_cost_device = utils::get_time_windows();
    g_evaluate <<<grid, block>>>(d_nTexture_u, d_nTexture_v, d_points, pointsCnt_u, pointsCnt_v, POINT_SIZE,
                                 knots_u[knotsCnt_u - 1], knots_v[knotsCnt_v - 1], sampleCnt_u, sampleCnt_v);
    cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用
    if (recordTime) {
        time_cost_device = utils::get_time_windows() - time_cost_device;
        printf("GPU time cost of surface evaluation for %d samples: %lf\n", sampleCnt_u * sampleCnt_v,
               time_cost_device);
    }

    // 释放内存
    free(h_points);
    free(h_knots_u);
    free(h_knots_v);
    printf("First derivatives and normal vectors calculated by GPU:\n");
    return {};
}


__host__ std::vector<std::map<float, std::vector<float>>>
NurbsCurve::Evaluator::evaluate(int sampleCnt) {

    if (POINT_SIZE != controlPoints[0].size()) {
        printf("Error! Nurbs控制点应表示为长度为4的齐次坐标\n");
        return {};
    }
    // 构造指向device的controlPoints
    const int pointsCnt = controlPoints.size();
    const int pointsBytes = pointsCnt * POINT_SIZE * sizeof(float);
    auto *h_points = (float *) malloc(pointsBytes);
    for (int i = 0; i < pointsCnt; i++) {
        for (int j = 0; j < POINT_SIZE; j++) {
            h_points[i * POINT_SIZE + j] = controlPoints[i][j];
        }
    }
    myCudaFree(d_points);  // 注意内存管理
    cudaMalloc((void **) &d_points, pointsBytes);
    cudaMemcpy(d_points, h_points, pointsBytes, cudaMemcpyHostToDevice);

    // 构造指向device的knots
    const int knotsCnt = knots.size();
    const int knotsBytes = knotsCnt * sizeof(float);
    auto *h_knots = (float *) malloc(knotsBytes);
    for (int i = 0; i < knotsCnt; i++) h_knots[i] = knots[i];
    myCudaFree(d_knots);  // 注意内存管理
    cudaMalloc((void **) &d_knots, knotsBytes);
    cudaMemcpy(d_knots, h_knots, knotsBytes, cudaMemcpyHostToDevice);

    // 分配nTexture的内存。只需要GPU内存
//    float *d_nTexture = nullptr;
    myCudaFree(d_nTexture);  // 注意内存管理
    cudaMalloc((void **) &d_nTexture,
               sampleCnt * pointsCnt * sizeof(float)); // 注意nTexture的大小，在算梯度时用得到i=pointsCnt + 1的基函数值

    // 分配nTexture1的内存。只需要GPU内存
//    float *d_nTexture1 = nullptr;
    myCudaFree(d_nTexture1);  // 注意内存管理
    cudaMalloc((void **) &d_nTexture1, sampleCnt * (pointsCnt + 1) * sizeof(float));

    // 构造g_basisTexture线程层级
    dim3 blockBasis(512);
    dim3 gridBasis((sampleCnt + blockBasis.x - 1) / blockBasis.x);

    // 构造线程层级
    dim3 block(32, 32);
    dim3 grid((sampleCnt + block.x * block.y - 1) / (block.x * block.y));
    // 记录用时
    double time_cost_device;
    if (recordTime) time_cost_device = utils::get_time_windows();
    printf("there..\n");
    g_basisTexture <<<gridBasis, blockBasis>>>(d_nTexture, d_nTexture1, d_knots, pointsCnt, knotsCnt, sampleCnt);
//    cudaMemcpy(d_nTextureCpy, d_nTexture, nTextureBytes, cudaMemcpyDeviceToDevice); // 有同步功能
    cudaDeviceSynchronize();
    printf("here..\n");
    g_evaluate <<<grid, block>>>(d_nTexture, d_points, pointsCnt, POINT_SIZE, knots[knotsCnt - 1], sampleCnt);
//    g_test<<<1,6>>>(d_nTextureCpy);
    cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用
    if (recordTime) {
        time_cost_device = utils::get_time_windows() - time_cost_device;
        printf("GPU time cost of curve evaluation for %d samples: %lf\n", sampleCnt, time_cost_device);
    }
    free(h_points);
    free(h_knots);
    return {};
}

__host__ void NurbsSurface::Evaluator::derivative(int sampleCnt_u, int sampleCnt_v) {
    // 先完成evaluation
    evaluate(sampleCnt_u, sampleCnt_v);

    if (POINT_SIZE != controlPoints[0][0].size()) {
        printf("Error! Nurbs控制点应表示为长度为4的齐次坐标\n");
        return;
    }

    float *d_derTexture_u = nullptr;
    float *d_derTexture_v = nullptr;
    const int pointsCnt_u = controlPoints.size(), pointsCnt_v = controlPoints[0].size();
    const int knotsCnt_u = knots_u.size(), knotsCnt_v = knots_v.size();
    cudaMalloc((void **) &d_derTexture_u, sampleCnt_u * pointsCnt_u * sizeof(float));
    cudaMalloc((void **) &d_derTexture_v, sampleCnt_v * pointsCnt_v * sizeof(float));

    // 构造切向量计算结果
    myCudaFree(d_derivatives);
    cudaMalloc((void **) &d_derivatives,
               sampleCnt_v * sampleCnt_u * 6 * sizeof(float)); // 每个采用所求的切向量是一个六元向量，前三位是对u的偏导、后三位是对v的偏导

    // 构造线程层级
    dim3 block(32, 32);
    dim3 grid((sampleCnt_u + block.x - 1) / block.x, (sampleCnt_v + block.y - 1) / block.y);
    // 构造g_basisTexture线程层级
    dim3 blockTex(512);
    dim3 gridTex_u((sampleCnt_u + blockTex.x - 1) / blockTex.x);
    dim3 gridTex_v((sampleCnt_v + blockTex.x - 1) / blockTex.x);
    // 记录用时
    double time_cost_device;
    if (recordTime) time_cost_device = utils::get_time_windows();
    g_derTexture<<<gridTex_u, blockTex>>>(d_derTexture_u, d_nTexture1_u, d_knots_u, pointsCnt_u, knotsCnt_u,
                                          sampleCnt_u);
    g_derTexture<<<gridTex_v, blockTex>>>(d_derTexture_v, d_nTexture1_v, d_knots_v, pointsCnt_v, knotsCnt_v,
                                          sampleCnt_v);
    cudaDeviceSynchronize();
    g_derivative<<<grid, block>>>(d_derivatives, d_derTexture_u, d_derTexture_v, d_nTexture_u, d_nTexture_v, d_points,
                                  pointsCnt_u,
                                  pointsCnt_v, POINT_SIZE, knots_u[knotsCnt_u - 1], knots_v[knotsCnt_v - 1],
                                  sampleCnt_u,
                                  sampleCnt_v);
    cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用
    if (recordTime) {
        time_cost_device = utils::get_time_windows() - time_cost_device;
        printf("GPU time cost of surface first derivative calculating for %d samples: %lf\n", sampleCnt_u * sampleCnt_v,
               time_cost_device);
    }
    cudaFree(d_derTexture_u);
    cudaFree(d_derTexture_v);
}

__host__ void NurbsCurve::Evaluator::derivative(int sampleCnt) {
    // 先完成evaluation
    evaluate(sampleCnt);

    if (POINT_SIZE != controlPoints[0].size()) {
        printf("Error! Nurbs控制点应表示为长度为4的齐次坐标\n");
        return;
    }

    float *d_derTexture = nullptr;
    const int pointsCnt = controlPoints.size();
    const int knotsCnt = knots.size();
    cudaMalloc((void **) &d_derTexture, sampleCnt * pointsCnt * sizeof(float));

    // 构造线程层级
    dim3 block(32, 32);
    dim3 grid((sampleCnt + block.x * block.y - 1) / (block.x * block.y));
    // 构造g_basisTexture线程层级
    dim3 blockTex(512);
    dim3 gridTex((sampleCnt + blockTex.x - 1) / blockTex.x);


    // 构造切向量计算结果
    myCudaFree(d_derivatives);
    cudaMalloc((void **) &d_derivatives, sampleCnt * 3 * sizeof(float)); // 每个采用所求的切向量是一个三维向量

    // 记录用时
    double time_cost_device;
    if (recordTime) time_cost_device = utils::get_time_windows();
    g_derTexture<<<gridTex, blockTex>>>(d_derTexture, d_nTexture1, d_knots, pointsCnt, knotsCnt, sampleCnt);
    cudaDeviceSynchronize();
    g_derivative<<<grid, block>>>(d_derivatives, d_derTexture, d_nTexture, d_points, pointsCnt, POINT_SIZE,
                                  knots[knotsCnt - 1], sampleCnt);
    cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用
    if (recordTime) {
        time_cost_device = utils::get_time_windows() - time_cost_device;
        printf("GPU time cost of curve first derivative calculating for %d samples: %lf\n", sampleCnt,
               time_cost_device);
    }
    cudaFree(d_derTexture);
}

__host__ void NurbsSurface::Evaluator::curvature(int sampleCnt_u, int sampleCnt_v) {
    // 先计算切向量
    derivative(sampleCnt_u, sampleCnt_v);
    if (POINT_SIZE != controlPoints[0][0].size()) {
        printf("Error! Nurbs控制点应表示为长度为4的齐次坐标\n");
        return;
    }

    // 构造线程层级
    dim3 block(32, 32);
    dim3 grid((sampleCnt_u + block.x - 1) / block.x, (sampleCnt_v + block.y - 1) / block.y);

    // 记录用时
    double time_cost_device;
    if (recordTime) time_cost_device = utils::get_time_windows();
    g_curvature<<<grid, block>>>(d_derivatives, sampleCnt_u, sampleCnt_v, knots_u[knots_u.size() - 1],
                                 knots_v[knots_v.size() - 1]);
    cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用
    if (recordTime) {
        time_cost_device = utils::get_time_windows() - time_cost_device;
        printf("GPU time cost of surface second derivative calculating for %d samples: %lf\n",
               sampleCnt_u * sampleCnt_v,
               time_cost_device);
    }
}

__host__ void NurbsCurve::Evaluator::curvature(int sampleCnt) {
    // 先计算切向量
    derivative(sampleCnt);

    if (POINT_SIZE != controlPoints[0].size()) {
        printf("Error! Nurbs控制点应表示为长度为4的齐次坐标\n");
        return;
    }

    // 构造线程层级
    dim3 block(32, 32);
    dim3 grid((sampleCnt + block.x * block.y - 1) / (block.x * block.y));

    // 记录用时
    double time_cost_device;
    if (recordTime) time_cost_device = utils::get_time_windows();
    g_curvature<<<grid, block>>>(d_derivatives, sampleCnt, knots[knots.size() - 1]);
    cudaDeviceSynchronize(); // 所用线程结束后再获取结束时间。cudaThreadSynchronize()在CUDA1.0后被弃用
    if (recordTime) {
        time_cost_device = utils::get_time_windows() - time_cost_device;
        printf("GPU time cost of curve second derivative calculating for %d samples: %lf\n", sampleCnt,
               time_cost_device);
    }
}


//__global__ void
//NurbsSurface::g_evaluate(const float *d_points, const float *d_knots_u, const float *d_knots_v,
//                         int d_pointsCnt_u,
//                         int d_pointsCnt_v, int d_POINT_SIZE, int d_knotsCnt_u, int d_knotsCnt_v,
//                         int d_sampleCnt_u, int d_sampleCnt_v) {
////    printf(" surface calculating... \n");
//    // 二维grid和二维的block
//    int ix = int(blockIdx.x * blockDim.x + threadIdx.x);
//    int iy = int(blockIdx.y * blockDim.y + threadIdx.y);
//
//    float d_paramCeil_u = d_knots_u[d_knotsCnt_u - 1];
//    float d_paramCeil_v = d_knots_v[d_knotsCnt_v - 1];
//
//    float u = ix * d_paramCeil_u / (d_sampleCnt_u - 1);
//    float v = iy * d_paramCeil_v / (d_sampleCnt_v - 1);
//
//    if (u > 1.0 * d_paramCeil_u || v > 1.0 * d_paramCeil_v) {
//        return;
//    }
//
//    int d_degree_u = d_knotsCnt_u - 1 - d_pointsCnt_u;
//    int d_degree_v = d_knotsCnt_v - 1 - d_pointsCnt_v;
//    // 注意，在device中，全局内存还是以malloc和free的方式分配和回收的，而不是使用cudaMalloc和cudaFree
//    auto *N_Texture_U = (float *) malloc((d_degree_u + 1) * (d_knotsCnt_u - 1) * sizeof(float));
//    auto *N_Texture_V = (float *) malloc((d_degree_v + 1) * (d_knotsCnt_v - 1) * sizeof(float));
//    d_basisFunction(N_Texture_U, d_knots_u, u, d_degree_u, d_knotsCnt_u);
//    d_basisFunction(N_Texture_V, d_knots_v, v, d_degree_v, d_knotsCnt_v);
//    float x = 0., y = 0., z = 0.;
//    for (int i = 0; i < d_pointsCnt_u; i++) {
//        for (int j = 0; j < d_pointsCnt_v; j++) {
//            float N_U = N_Texture_U[d_degree_u * (d_knotsCnt_u - 1) + i];
//            float N_V = N_Texture_V[d_degree_v * (d_knotsCnt_v - 1) + j];
//            int idx = (i * d_pointsCnt_v + j) * d_POINT_SIZE;
//            x += N_U * N_V * d_points[idx];
//            y += N_U * N_V * d_points[idx + 1];
//            z += N_U * N_V * d_points[idx + 2];
//        }
//    }
//    printf("(%g, %g)-->(%g, %g, %g)\n", u, v, x, y, z); // %g输出，舍弃无意义的0
//    free(N_Texture_U);
//    free(N_Texture_V);
//}

__global__ void
NurbsSurface::g_evaluate(const float *d_nTexture_u, const float *d_nTexture_v, const float *d_points, int d_pointsCnt_u,
                         int d_pointsCnt_v, int d_POINT_SIZE, float d_lastKnot_u, float d_lastKnot_v, int d_sampleCnt_u,
                         int d_sampleCnt_v) {

    // 二维grid和二维的block
    int ix = blockIdx.x * blockDim.x + threadIdx.x;
    int iy = blockIdx.y * blockDim.y + threadIdx.y;

    float u = ix * d_lastKnot_u / (d_sampleCnt_u - 1);
    float v = iy * d_lastKnot_v / (d_sampleCnt_v - 1);

    if (u > 1.0 * d_lastKnot_u || v > 1.0 * d_lastKnot_v) {
        return;
    }

    float x = 0., y = 0., z = 0., sumW = 0.;
    for (int i = 0; i < d_pointsCnt_u; i++) {
        float N_U = d_nTexture_u[ix * d_pointsCnt_u + i];
        for (int j = 0; j < d_pointsCnt_v; j++) {
            float N_V = d_nTexture_v[iy * d_pointsCnt_v + j];
            int idx = (i * d_pointsCnt_v + j) * d_POINT_SIZE;
            float w = d_points[idx + 3];
            x += N_U * N_V * w * d_points[idx];
            y += N_U * N_V * w * d_points[idx + 1];
            z += N_U * N_V * w * d_points[idx + 2];
            sumW += N_U * N_V * w;
        }
    }
    x = x / sumW;
    y = y / sumW;
    z = z / sumW;
//    printf("(%g, %g)-->(%g, %g, %g)\n", u, v, x, y, z); // %g输出，舍弃无意义的0
}

__global__ void
NurbsSurface::g_derivative(float *derivatives, const float *derTexture_u, const float *derTexture_v,
                           const float *nTexture_u, const float *nTexture_v, const float *d_points, int d_pointsCnt_u,
                           int d_pointsCnt_v, int d_POINT_SIZE, float d_lastKnot_u, float d_lastKnot_v,
                           int d_sampleCnt_u, int d_sampleCnt_v) {
    // 二维grid和二维的block
    int ix = blockIdx.x * blockDim.x + threadIdx.x;
    int iy = blockIdx.y * blockDim.y + threadIdx.y;

    if (ix >= d_sampleCnt_u || iy >= d_sampleCnt_v) {
        return;
    }
    float u = ix * d_lastKnot_u / (d_sampleCnt_u - 1);
    float v = iy * d_lastKnot_v / (d_sampleCnt_v - 1);

    float nubsPdx_u = 0., nubsPdy_u = 0, nubsPdz_u = 0., nubsPdw_u = 0.;
    float nubsPdx_v = 0., nubsPdy_v = 0, nubsPdz_v = 0., nubsPdw_v = 0.;

    for (int i = 0; i < d_pointsCnt_u; i++) {
        for (int j = 0; j < d_pointsCnt_u; j++) {
            int baseIdx = (i * d_pointsCnt_v + j) * d_POINT_SIZE;
            float factor_u = derTexture_u[ix * d_pointsCnt_u + i] * nTexture_v[iy * d_pointsCnt_v + j];
            float factor_v = derTexture_v[iy * d_pointsCnt_v + j] * nTexture_u[ix * d_pointsCnt_u + i];
            float wij = d_points[baseIdx + 3];
            nubsPdx_u += factor_u * wij * d_points[baseIdx];
            nubsPdy_u += factor_u * wij * d_points[baseIdx + 1];
            nubsPdz_u += factor_u * wij * d_points[baseIdx + 2];
            nubsPdw_u += factor_u * wij;

            nubsPdx_v += factor_v * wij * d_points[baseIdx];
            nubsPdy_v += factor_v * wij * d_points[baseIdx + 1];
            nubsPdz_v += factor_v * wij * d_points[baseIdx + 2];
            nubsPdw_v += factor_v * wij;
        }
    }

    float x = 0., y = 0., z = 0., w = 0.;
    for (int i = 0; i < d_pointsCnt_u; i++) {
        float N_U = nTexture_u[ix * d_pointsCnt_u + i];
        for (int j = 0; j < d_pointsCnt_v; j++) {
            float N_V = nTexture_v[iy * d_pointsCnt_v + j];
            int idx = (i * d_pointsCnt_v + j) * d_POINT_SIZE;
            float wij = d_points[idx + 3];
            x += N_U * N_V * wij * d_points[idx];
            y += N_U * N_V * wij * d_points[idx + 1];
            z += N_U * N_V * wij * d_points[idx + 2];
            w += N_U * N_V * wij;
        }
    }

    float w2 = w * w;
    float pdx_u = (nubsPdx_u * w - x * nubsPdw_u) / w2;
    float pdy_u = (nubsPdy_u * w - y * nubsPdw_u) / w2;
    float pdz_u = (nubsPdz_u * w - z * nubsPdw_u) / w2;

    float pdx_v = (nubsPdx_v * w - x * nubsPdw_v) / w2;
    float pdy_v = (nubsPdy_v * w - y * nubsPdw_v) / w2;
    float pdz_v = (nubsPdz_v * w - z * nubsPdw_v) / w2;
//    float pdz_u = (nubsPdz_u * w - z )

    int baseIdx = (ix * d_sampleCnt_v + iy) * 6;
    derivatives[baseIdx] = pdx_u;
    derivatives[baseIdx + 1] = pdy_u;
    derivatives[baseIdx + 2] = pdz_u;
    derivatives[baseIdx + 3] = pdx_v;
    derivatives[baseIdx + 4] = pdy_v;
    derivatives[baseIdx + 5] = pdz_v;

    float x_n = pdy_u * pdz_v - pdy_v * pdz_u, y_n = pdx_v * pdz_u - pdx_u * pdz_v, z_n =
            pdx_u * pdy_v - pdx_v * pdy_u; // 叉乘得到法向量
    if((ix == 8 && iy == 9) || (ix == 7 && iy == 9) || (ix == 9 && iy == 9) || (ix == 8 && iy == 8) || (ix == 8 && iy == 10))
    printf("(%g,%g)-->u:(%g, %g, %g), v:(%g,%g,%g), normal:(%g,%g,%g)\n", u, v, pdx_u, pdy_u, pdz_u, pdx_v, pdy_v,
           pdz_v, x_n, y_n, z_n);
}

__global__ void
NurbsSurface::g_curvature(const float *derivatives, int sampleCnt_u, int sampleCnt_v, float lastKnot_u,
                          float lastKnot_v) {
    // 二维grid和二维的block
    int ix = blockIdx.x * blockDim.x + threadIdx.x;
    int iy = blockIdx.y * blockDim.y + threadIdx.y;

    if (ix >= sampleCnt_u || iy >= sampleCnt_v) {
        return;
    }


    float step_u = lastKnot_u / (sampleCnt_u - 1), step_v = lastKnot_v / (sampleCnt_v - 1);
    float u = ix * step_u, v = iy * step_v;

    int baseIdx = (ix * sampleCnt_v + iy) * 6;
    int lastBaseIdx_u = ((ix - 1) * sampleCnt_v + iy) * 6, nextBaseIdx_u = ((ix + 1) * sampleCnt_v + iy) * 6;
    int lastBaseIdx_v = (ix * sampleCnt_v + iy - 1) * 6, nextBaseIdx_v = (ix * sampleCnt_v + iy + 1) * 6;

//    printf("(%g,%g)-->u:(%g, %g, %g), v:(%g,%g,%g)\n", u, v, derivatives[baseIdx], derivatives[baseIdx + 1],
//           derivatives[baseIdx + 2], derivatives[baseIdx + 3], derivatives[baseIdx + 4], derivatives[baseIdx + 5]);

    float sndPdx_uu, sndPdy_uu, sndPdz_uu, sndPdx_vv, sndPdy_vv, sndPdz_vv;  // 二阶导
    float sndPdx_uv, sndPdy_uv, sndPdz_uv, sndPdx_vu, sndPdy_vu, sndPdz_vu;

    if (ix == 0) {
        sndPdx_uu = (derivatives[nextBaseIdx_u] - derivatives[baseIdx]) / step_u;
        sndPdy_uu = (derivatives[nextBaseIdx_u + 1] - derivatives[baseIdx + 1]) / step_u;
        sndPdz_uu = (derivatives[nextBaseIdx_u + 2] - derivatives[baseIdx + 2]) / step_u;

        sndPdx_vu = (derivatives[nextBaseIdx_u + 3] - derivatives[baseIdx + 3]) / step_u;
        sndPdy_vu = (derivatives[nextBaseIdx_u + 4] - derivatives[baseIdx + 4]) / step_u;
        sndPdz_vu = (derivatives[nextBaseIdx_u + 5] - derivatives[baseIdx + 5]) / step_u;
    } else if (ix == sampleCnt_u - 1) {
        sndPdx_uu = (derivatives[baseIdx] - derivatives[lastBaseIdx_u]) / step_u;
        sndPdy_uu = (derivatives[baseIdx + 1] - derivatives[lastBaseIdx_u + 1]) / step_u;
        sndPdz_uu = (derivatives[baseIdx + 2] - derivatives[lastBaseIdx_u + 2]) / step_u;

        sndPdx_vu = (derivatives[baseIdx + 3] - derivatives[lastBaseIdx_u + 3]) / step_u;
        sndPdy_vu = (derivatives[baseIdx + 4] - derivatives[lastBaseIdx_u + 4]) / step_u;
        sndPdz_vu = (derivatives[baseIdx + 5] - derivatives[lastBaseIdx_u + 5]) / step_u;
    } else {
        sndPdx_uu = (derivatives[nextBaseIdx_u] - derivatives[lastBaseIdx_u]) / (2 * step_u);
        sndPdy_uu = (derivatives[nextBaseIdx_u + 1] - derivatives[lastBaseIdx_u + 1]) / (2 * step_u);
        sndPdz_uu = (derivatives[nextBaseIdx_u + 2] - derivatives[lastBaseIdx_u + 2]) / (2 * step_u);

        sndPdx_vu = (derivatives[nextBaseIdx_u + 3] - derivatives[lastBaseIdx_u + 3]) / (2 * step_u);
        sndPdy_vu = (derivatives[nextBaseIdx_u + 4] - derivatives[lastBaseIdx_u + 4]) / (2 * step_u);
        sndPdz_vu = (derivatives[nextBaseIdx_u + 5] - derivatives[lastBaseIdx_u + 5]) / (2 * step_u);
    }

    if (iy == 0) {
        sndPdx_vv = (derivatives[nextBaseIdx_v + 3] - derivatives[baseIdx + 3]) / step_v;
        sndPdy_vv = (derivatives[nextBaseIdx_v + 4] - derivatives[baseIdx + 4]) / step_v;
        sndPdz_vv = (derivatives[nextBaseIdx_v + 5] - derivatives[baseIdx + 5]) / step_v;

        sndPdx_uv = (derivatives[nextBaseIdx_v] - derivatives[baseIdx]) / step_v;
        sndPdy_uv = (derivatives[nextBaseIdx_v + 1] - derivatives[baseIdx + 1]) / step_v;
        sndPdz_uv = (derivatives[nextBaseIdx_v + 2] - derivatives[baseIdx + 2]) / step_v;
    } else if (iy == sampleCnt_v - 1) {
        sndPdx_vv = (derivatives[baseIdx + 3] - derivatives[lastBaseIdx_v + 3]) / step_v;
        sndPdy_vv = (derivatives[baseIdx + 4] - derivatives[lastBaseIdx_v + 4]) / step_v;
        sndPdz_vv = (derivatives[baseIdx + 5] - derivatives[lastBaseIdx_v + 5]) / step_v;

        sndPdx_uv = (derivatives[baseIdx] - derivatives[lastBaseIdx_v]) / step_v;
        sndPdy_uv = (derivatives[baseIdx + 1] - derivatives[lastBaseIdx_v + 1]) / step_v;
        sndPdz_uv = (derivatives[baseIdx + 2] - derivatives[lastBaseIdx_v + 2]) / step_v;
    } else {
        sndPdx_vv = (derivatives[nextBaseIdx_v + 3] - derivatives[lastBaseIdx_v + 3]) / (2 * step_v);
        sndPdy_vv = (derivatives[nextBaseIdx_v + 4] - derivatives[lastBaseIdx_v + 4]) / (2 * step_v);
        sndPdz_vv = (derivatives[nextBaseIdx_v + 5] - derivatives[lastBaseIdx_v + 5]) / (2 * step_v);

        sndPdx_uv = (derivatives[nextBaseIdx_v] - derivatives[lastBaseIdx_v]) / (2 * step_v);
        sndPdy_uv = (derivatives[nextBaseIdx_v + 1] - derivatives[lastBaseIdx_v + 1]) / (2 * step_v);
        sndPdz_uv = (derivatives[nextBaseIdx_v + 2] - derivatives[lastBaseIdx_v + 2]) / (2 * step_v);
    }

    float uvx = (sndPdx_uv + sndPdx_vu) / 2, uvy = (sndPdy_uv + sndPdy_vu) / 2, uvz = (sndPdz_uv + sndPdz_vu) / 2;
    normalization(sndPdx_uu, sndPdy_uu, sndPdz_uu);
    normalization(uvx, uvy, uvz);
    normalization(sndPdx_vv, sndPdy_vv, sndPdz_vv);


    if(ix == 8 && iy == 9)
    printf("(%g, %g) --> uu: (%g, %g, %g), uv: (%g, %g, %g), vv: (%g, %g, %g)\n", u, v, sndPdx_uu, sndPdy_uu, sndPdz_uu,
           uvx, uvy, uvz, sndPdx_vv, sndPdy_vv, sndPdz_vv);
}

__global__ void
NurbsCurve::g_evaluate(const float *NTexture, const float *d_points, const int d_pointsCnt,
                       const int d_POINT_SIZE, const float d_lastKnot, const int d_sampleCnt) {
//    printf(" curve calculating... \n");
    // 二维grid和一维的block
//    int idx = (blockIdx.y * gridDim.x + blockIdx.x) * blockDim.x + threadIdx.x;
    // 二维block和一维grid
    int idx = blockIdx.x * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x;
    float u = idx * d_lastKnot / (d_sampleCnt - 1);
    if (u > 1.0 * d_lastKnot) {
        return;
    }
//
//    int d_degree = d_knotsCnt - 1 - d_pointsCnt;
//    // 注意，在device中，全局内存还是以malloc和free的方式分配和回收的，而不是使用cudaMalloc和cudaFree
//    auto *N_dp = (float *) malloc((d_degree + 1) * (d_knotsCnt - 1) * sizeof(float));
//    d_basisFunction(N_dp, d_knots, u, d_degree, d_knotsCnt);
    float x = 0., y = 0., z = 0., sumW = 0.;
    for (int i = 0; i < d_pointsCnt; i++) {
        float N = NTexture[idx * d_pointsCnt + i];
        int baseIdx = i * d_POINT_SIZE;
        float w = d_points[baseIdx + 3];
        x += N * w * d_points[baseIdx];
        y += N * w * d_points[baseIdx + 1];
        z += N * w * d_points[baseIdx + 2];
        sumW += N * w;
    }
    x = x / sumW;
    y = y / sumW;
    z = z / sumW;
    printf("(%g)-->(%g, %g, %g)\n", u, x, y, z); // %g输出，舍弃无意义的0
}

__global__ void
NurbsCurve::g_derivative(float *derivatives, const float *derTexture, const float *nTexture, const float *d_points,
                         int d_pointsCnt, int d_POINT_SIZE,
                         float d_lastKnot, int d_sampleCnt) {
    // 二维block和一维grid
    int idx = blockIdx.x * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x;
    if (idx >= d_sampleCnt) return;
    float u = idx * d_lastKnot / (d_sampleCnt - 1);
    float nubs_dx = 0., nubs_dy = 0., nubs_dz = 0., nubs_dw = 0.;
//    printf("POINT_SIZE: %d\n", d_POINT_SIZE);

    for (int i = 0; i < d_pointsCnt; i++) {
        int baseIdx = i * d_POINT_SIZE;
        float nFactor = derTexture[idx * d_pointsCnt + i];
        float wi = d_points[baseIdx + 3];
        nubs_dx += nFactor * wi * d_points[baseIdx];
        nubs_dy += nFactor * wi * d_points[baseIdx + 1];
        nubs_dz += nFactor * wi * d_points[baseIdx + 2];
        nubs_dw += nFactor * wi;
//        printf("(x, y, z): (%g, %g, %g)\n", d_points[baseIdx], d_points[baseIdx + 1], d_points[baseIdx + 2]);
    }

    float x = 0., y = 0., z = 0., w = 0.;
    for (int i = 0; i < d_pointsCnt; i++) {
        float N = nTexture[idx * d_pointsCnt + i];
        int baseIdx = i * d_POINT_SIZE;
        float wi = d_points[baseIdx + 3];
        x += N * wi * d_points[baseIdx];
        y += N * wi * d_points[baseIdx + 1];
        z += N * wi * d_points[baseIdx + 2];
        w += N * wi;
    }
    float dx = (nubs_dx * w - x * nubs_dw) / (w * w);
    float dy = (nubs_dy * w - y * nubs_dw) / (w * w);
    float dz = (nubs_dz * w - z * nubs_dw) / (w * w);
    int baseIdx = idx * 3;
    derivatives[baseIdx] = dx;
    derivatives[baseIdx + 1] = dy;
    derivatives[baseIdx + 2] = dz;
    printf("(%g)-->(%g, %g, %g)\n", u, dx, dy, dz);
}

__global__ void NurbsCurve::g_curvature(const float *derivatives, int sampleCnt, float lastKnot) {
    // 二维block和一维grid
    int idx = blockIdx.x * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x;
    if (idx >= sampleCnt) return;
    float step = lastKnot / (sampleCnt - 1);
    float u = idx * step;
    float sndPdx, sndPdy, sndPdz;  // 二阶导
    int baseIdx = idx * 3, lastBaseIdx = (idx - 1) * 3, nextBaseIdx = (idx + 1) * 3;
    if (idx == 0) {
        sndPdx = (derivatives[nextBaseIdx] - derivatives[baseIdx]) / step;
        sndPdy = (derivatives[nextBaseIdx + 1] - derivatives[baseIdx + 1]) / step;
        sndPdz = (derivatives[nextBaseIdx + 2] - derivatives[baseIdx + 2]) / step;
    } else if (idx == sampleCnt - 1) {
        sndPdx = (derivatives[baseIdx] - derivatives[lastBaseIdx]) / step;
        sndPdy = (derivatives[baseIdx + 1] - derivatives[lastBaseIdx + 1]) / step;
        sndPdz = (derivatives[baseIdx + 2] - derivatives[lastBaseIdx + 2]) / step;
    } else {
        sndPdx = (derivatives[nextBaseIdx] - derivatives[lastBaseIdx]) / (2 * step);
        sndPdy = (derivatives[nextBaseIdx + 1] - derivatives[lastBaseIdx + 1]) / (2 * step);
        sndPdz = (derivatives[nextBaseIdx + 2] - derivatives[lastBaseIdx + 2]) / (2 * step);
    }
    printf("%g --> (%g, %g, %g)\n", u, sndPdx, sndPdy, sndPdz);
}

__global__ void g_basisTexture(float *nTexture, float *nTexture1, const float *d_knots, int d_pointsCnt, int d_knotsCnt,
                               int d_sampleCnt) {
    // 一维grid和一维block
    int idx = blockIdx.x * blockDim.x + threadIdx.x;  // 采样点编号
    float d_paramCeil = d_knots[d_knotsCnt - 1];
    float u = idx * d_paramCeil / (d_sampleCnt - 1);
    if (u > 1.0 * d_paramCeil) {
        return;
    }
    int d_degree = d_knotsCnt - 1 - d_pointsCnt;
    auto *N_dp = (float *) malloc((d_degree + 1) * (d_knotsCnt - 1) * sizeof(float));
    d_basisFunction(N_dp, d_knots, u, d_degree, d_knotsCnt);
    for (int i = 0; i < d_pointsCnt; i++) {
        nTexture[idx * d_pointsCnt + i] = N_dp[d_degree * (d_knotsCnt - 1) + i];
        nTexture1[idx * (d_pointsCnt + 1) + i] = N_dp[(d_degree - 1) * (d_knotsCnt - 1) + i];
//        printf("nTexture1: %g ", nTexture1[idx * (d_pointsCnt + 1) + i]);
    }
    nTexture1[idx * (d_pointsCnt + 1) + d_pointsCnt] = N_dp[(d_degree - 1) * (d_knotsCnt - 1) +
                                                            d_pointsCnt]; // nTexture1多记录一列数据
    free(N_dp);
}


__global__ void
g_derTexture(float *derTexture, const float *nTexture1, const float *d_knots, int d_pointsCnt, int d_knotsCnt,
             int d_sampleCnt) {
    // 一维grid和一维block
    int idx = blockIdx.x * blockDim.x + threadIdx.x;  // 采样点编号
    if (idx >= d_sampleCnt) {
        return;
    }
    int degree = d_knotsCnt - 1 - d_pointsCnt;

//    printf("degree: %d\n", degree);
    for (int i = 0; i < d_pointsCnt; i++) {
        float left = d_floatEqual(d_knots[i + degree], d_knots[i]) ? 0 :
                     nTexture1[idx * (d_pointsCnt + 1) + i] * (degree - 1) / (d_knots[i + degree] - d_knots[i]);
        float right = d_floatEqual(d_knots[i + degree + 1], d_knots[i + 1]) ? 0 :
                      nTexture1[idx * (d_pointsCnt + 1) + i + 1] * (degree - 1) /
                      (d_knots[i + degree + 1] - d_knots[i + 1]);
        derTexture[idx * d_pointsCnt + i] = left - right;
//        printf("<%d, %d> -- %g \n", idx, i, left - right);
//        printf("nTex1: %g \n", nTexture1[idx * (d_pointsCnt + 1) + i]);
    }
}

__host__ NurbsCurve::Evaluator::Evaluator(std::vector<std::vector<float>> controlPoints,
                                          std::vector<float> knots) {
    this->knots = std::move(knots);
    this->controlPoints = std::move(controlPoints);
    recordTime = false;
    d_nTexture = nullptr;
    d_nTexture1 = nullptr;
    d_points = nullptr;
    d_knots = nullptr;
    d_derivatives = nullptr;
}


__device__ void d_basisFunction(float *N_Texture, const float *knots, float u, int degree, int d_knotsCnt) {
    int m = d_knotsCnt - 1;
    for (int p = 0; p <= degree; p++) {
        for (int i = 0; i + p <= m - 1; i++) {
            if (p == 0) {
                if ((u > knots[i] || d_floatEqual(u, knots[i])) && (u < knots[i + 1])
                    ||
                    d_floatEqual(u, knots[i + 1]) && d_floatEqual(u, knots[m])) {
                    N_Texture[p * m + i] = 1.0;
                } else {
                    N_Texture[p * m + i] = 0.0;
                }
            } else {
                float Nip_1 = N_Texture[(p - 1) * m + i];
                float Ni1p_1 = N_Texture[(p - 1) * m + i + 1];
                float left = d_floatEqual(knots[i + p], knots[i]) ? 0 : (u - knots[i]) * Nip_1 /
                                                                        (knots[i + p] - knots[i]);
                float right = d_floatEqual(knots[i + p + 1], knots[i + 1]) ? 0 : (knots[i + p + 1] - u) * Ni1p_1 /
                                                                                 (knots[i + p + 1] - knots[i + 1]);
                N_Texture[p * m + i] = left + right;
            }
        }
    }
}

__device__ bool d_floatEqual(float a, float b) {
    return abs(a - b) < 0.00001;
}

__host__ void myCudaFree(float *&p) {
    if (p != nullptr) {
        cudaFree(p);
        p = nullptr;
    }
}


void NurbsCurve::Evaluator::setRecordTime(bool r) {
    recordTime = r;
}

void NurbsSurface::Evaluator::setRecordTime(bool r) {
    recordTime = r;
}

NurbsSurface::Evaluator::~Evaluator() {
    myCudaFree(d_nTexture_u);
    myCudaFree(d_nTexture_v);
    myCudaFree(d_nTexture1_u);
    myCudaFree(d_nTexture1_v);
    myCudaFree(d_points);
    myCudaFree(d_knots_u);
    myCudaFree(d_knots_v);
    cudaDeviceReset();
}

NurbsCurve::Evaluator::~Evaluator() {
    myCudaFree(d_nTexture);
    myCudaFree(d_nTexture1);
    myCudaFree(d_points);
    myCudaFree(d_knots);
    cudaDeviceReset();
}