/**
 * Copyright 2019-2023 by XGBoost contributors
 *
 * \file c-api-demo.c
 * \brief A simple example of using xgboost C API.
 */

#include <assert.h>
#include <stddef.h>
#include <stdint.h> /* uint32_t,uint64_t */
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <xgboost/c_api.h>

#define safe_xgboost(call) {                                            \
int err = (call);                                                       \
if (err != 0) {                                                         \
  fprintf(stderr, "%s:%d: error in %s: %s\n", __FILE__, __LINE__, #call, XGBGetLastError()); \
  exit(1);                                                              \
}                                                                       \
}

/* Make Json encoded array interface. */
static void MakeArrayInterface(size_t data, size_t n, char const* typestr, size_t length,
                               char* out) {
  static char const kTemplate[] =
      "{\"data\": [%lu, true], \"shape\": [%lu, %lu], \"typestr\": \"%s\", \"version\": 3}";
  memset(out, '\0', length);
  sprintf(out, kTemplate, data, n, 1ul, typestr);
}
/* Make Json encoded DMatrix configuration. */
static void MakeConfig(int n_threads, size_t length, char* out) {
  static char const kTemplate[] = "{\"missing\": NaN, \"nthread\": %d}";
  memset(out, '\0', length);
  sprintf(out, kTemplate, n_threads);
}

int main() {
  int silent = 0;
  int use_gpu = 0;  // set to 1 to use the GPU for training

  // load the data
  DMatrixHandle dtrain, dtest;
  safe_xgboost(XGDMatrixCreateFromFile("../../data/agaricus.txt.train?format=libsvm", silent, &dtrain));
  safe_xgboost(XGDMatrixCreateFromFile("../../data/agaricus.txt.test?format=libsvm", silent, &dtest));

  // create the booster
  BoosterHandle booster;
  DMatrixHandle eval_dmats[2] = {dtrain, dtest};
  safe_xgboost(XGBoosterCreate(eval_dmats, 2, &booster));

  // configure the training
  // available parameters are described here:
  //   https://xgboost.readthedocs.io/en/latest/parameter.html
  safe_xgboost(XGBoosterSetParam(booster, "device", use_gpu ? "cuda" : "cpu"));

  safe_xgboost(XGBoosterSetParam(booster, "objective", "binary:logistic"));
  safe_xgboost(XGBoosterSetParam(booster, "min_child_weight", "1"));
  safe_xgboost(XGBoosterSetParam(booster, "gamma", "0.1"));
  safe_xgboost(XGBoosterSetParam(booster, "max_depth", "3"));
  safe_xgboost(XGBoosterSetParam(booster, "verbosity", silent ? "0" : "1"));

  // train and evaluate for 10 iterations
  int n_trees = 10;
  const char* eval_names[2] = {"train", "test"};
  const char* eval_result = NULL;
  for (int i = 0; i < n_trees; ++i) {
    safe_xgboost(XGBoosterUpdateOneIter(booster, i, dtrain));
    safe_xgboost(XGBoosterEvalOneIter(booster, i, eval_dmats, eval_names, 2, &eval_result));
    printf("%s\n", eval_result);
  }

  bst_ulong num_feature = 0;
  safe_xgboost(XGBoosterGetNumFeature(booster, &num_feature));
  printf("num_feature: %lu\n", (unsigned long)(num_feature));

  // predict
  bst_ulong out_len = 0;
  int n_print = 10;

  /* Run prediction with DMatrix object. */
  char const config[] =
      "{\"training\": false, \"type\": 0, "
      "\"iteration_begin\": 0, \"iteration_end\": 0, \"strict_shape\": false}";
  /* Shape of output prediction */
  uint64_t const* out_shape;
  /* Dimension of output prediction */
  uint64_t out_dim;
  /* Pointer to a thread local contigious array, assigned in prediction function. */
  float const* out_result = NULL;
  safe_xgboost(
      XGBoosterPredictFromDMatrix(booster, dtest, config, &out_shape, &out_dim, &out_result));

  printf("y_pred: ");
  for (int i = 0; i < n_print; ++i) {
    printf("%1.4f ", out_result[i]);
  }
  printf("\n");

  // print true labels
  safe_xgboost(XGDMatrixGetFloatInfo(dtest, "label", &out_len, &out_result));
  printf("y_test: ");
  for (int i = 0; i < n_print; ++i) {
    printf("%1.4f ", out_result[i]);
  }
  printf("\n");

  {
    printf("Dense Matrix Example (XGDMatrixCreateFromMat): ");

    const float values[] = {0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
      0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0,
      1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,
      0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0,
      1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
      1, 0, 0, 0, 0, 1, 0, 0, 0, 0};

    DMatrixHandle dmat;
    safe_xgboost(XGDMatrixCreateFromMat(values, 1, 127, 0.0, &dmat));

    const float* out_result = NULL;

    safe_xgboost(
        XGBoosterPredictFromDMatrix(booster, dmat, config, &out_shape, &out_dim, &out_result));
    assert(out_dim == 1);
    assert(out_shape[0] == 1);

    printf("%1.4f \n", out_result[0]);
    safe_xgboost(XGDMatrixFree(dmat));
  }

  {
    printf("Sparse Matrix Example (XGDMatrixCreateFromCSR): ");

    const uint64_t indptr[] = {0, 22};
    const uint32_t indices[] = {1,  9,  19, 21, 24, 34, 36, 39,  42,  53,  56,
                                65, 69, 77, 86, 88, 92, 95, 102, 106, 117, 122};
    const float data[] = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                          1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};

    DMatrixHandle dmat;
    char j_indptr[128];
    MakeArrayInterface((size_t)indptr, 2ul, "<u8", sizeof(j_indptr), j_indptr);
    char j_indices[128];
    MakeArrayInterface((size_t)indices, sizeof(indices) / sizeof(uint32_t), "<u4",
                       sizeof(j_indices), j_indices);
    char j_data[128];
    MakeArrayInterface((size_t)data, sizeof(data) / sizeof(float), "<f4", sizeof(j_data), j_data);

    char j_config[64];
    MakeConfig(0, sizeof(j_config), j_config);

    safe_xgboost(XGDMatrixCreateFromCSR(j_indptr, j_indices, j_data, 127, j_config, &dmat));

    const float* out_result = NULL;

    safe_xgboost(
        XGBoosterPredictFromDMatrix(booster, dmat, config, &out_shape, &out_dim, &out_result));
    assert(out_dim == 1);
    assert(out_shape[0] == 1);

    printf("%1.4f \n", out_result[0]);
    safe_xgboost(XGDMatrixFree(dmat));
  }

  {
    printf("Sparse Matrix Example (XGDMatrixCreateFromCSC): ");

    const uint64_t indptr[] = {
        0,  0,  1,  1,  1,  1,  1,  1,  1,  1,  2,  2,  2,  2,  2,  2,  2,  2,  2,  2,  3,  3,
        4,  4,  4,  5,  5,  5,  5,  5,  5,  5,  5,  5,  5,  6,  6,  7,  7,  7,  8,  8,  8,  9,
        9,  9,  9,  9,  9,  9,  9,  9,  9,  9,  10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11,
        12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14, 14, 14, 14, 14, 14, 14, 15,
        15, 16, 16, 16, 16, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 20, 20, 20,
        20, 20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22};

    const uint32_t indices[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};

    const float data[] = {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
                          1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0};

    char j_indptr[128];
    MakeArrayInterface((size_t)indptr, 128ul, "<u8", sizeof(j_indptr), j_indptr);
    char j_indices[128];
    MakeArrayInterface((size_t)indices, sizeof(indices) / sizeof(unsigned), "<u4",
                       sizeof(j_indices), j_indices);
    char j_data[128];
    MakeArrayInterface((size_t)data, sizeof(data) / sizeof(float), "<f4", sizeof(j_data), j_data);

    char j_config[64];
    MakeConfig(0, sizeof(j_config), j_config);

    DMatrixHandle dmat;
    safe_xgboost(XGDMatrixCreateFromCSC(j_indptr, j_indices, j_data, 1, j_config, &dmat));

    const float* out_result = NULL;

    safe_xgboost(
        XGBoosterPredictFromDMatrix(booster, dmat, config, &out_shape, &out_dim, &out_result));
    assert(out_dim == 1);
    assert(out_shape[0] == 1);

    printf("%1.4f \n", out_result[0]);
    safe_xgboost(XGDMatrixFree(dmat));
  }

  // free everything
  safe_xgboost(XGBoosterFree(booster));
  safe_xgboost(XGDMatrixFree(dtrain));
  safe_xgboost(XGDMatrixFree(dtest));
  return 0;
}