cloud.h

#pragma once

#include <ATen/ATen.h>
#include <algorithm>
#include <cmath>
#include <iomanip>
#include <iostream>
#include <map>
#include <numeric>
#include <unordered_map>
#include <vector>

#include <time.h>

template <typename scalar_t> struct PointCloud {
  std::vector<std::vector<scalar_t> *> pts;

  void set(std::vector<scalar_t> new_pts, int dim) {

    std::vector<std::vector<scalar_t> *> temp(new_pts.size() / dim);
    for (size_t i = 0; i < new_pts.size(); i++) {
      if (i % dim == 0) {
        std::vector<scalar_t> *point = new std::vector<scalar_t>(dim);

        for (size_t j = 0; j < (size_t)dim; j++) {
          (*point)[j] = new_pts[i + j];
        }
        temp[i / dim] = point;
      }
    }

    pts = temp;
  }
  void set_batch(std::vector<scalar_t> new_pts, size_t begin, long size,
                 int dim) {
    std::vector<std::vector<scalar_t> *> temp(size);
    for (size_t i = 0; i < (size_t)size; i++) {
      std::vector<scalar_t> *point = new std::vector<scalar_t>(dim);
      for (size_t j = 0; j < (size_t)dim; j++) {
        (*point)[j] = new_pts[dim * (begin + i) + j];
      }

      temp[i] = point;
    }
    pts = temp;
  }

  // Must return the number of data points.
  inline size_t kdtree_get_point_count() const { return pts.size(); }

  // Returns the dim'th component of the idx'th point in the class:
  inline scalar_t kdtree_get_pt(const size_t idx, const size_t dim) const {
    return (*pts[idx])[dim];
  }

  // Optional bounding-box computation: return false to default to a standard
  // bbox computation loop.
  // Return true if the BBOX was already computed by the class and returned in
  // "bb" so it can be avoided to redo it again. Look at bb.size() to find out
  // the expected dimensionality (e.g. 2 or 3 for point clouds)
  template <class BBOX> bool kdtree_get_bbox(BBOX & /* bb */) const {
    return false;
  }
};