Kdtree2_r_nearest_around_point

Like Kdtree2_r_nearest, but around a point 'idxin' already existing in the data set.

note

Results are NOT sorted unless tree was created with sort option.

Interface

Interface

SUBROUTINE Kdtree2_r_nearest_around_point(tp, idxin, correltime, r2, &
                                          nfound, nalloc, results)
  TYPE(Kdtree2_), POINTER :: tp
  INTEGER, INTENT(In) :: idxin, correltime, nalloc
  REAL(kdkind), INTENT(in) :: r2
  INTEGER, INTENT(out) :: nfound
  TYPE(Kdtree2Result_), TARGET :: results(:)
END SUBROUTINE Kdtree2_r_nearest_around_point

example

PROGRAM main
USE GlobalData, ONLY: I4B, LGT, DFP
USE Display_Method
USE ReallocateUtility
USE Kdtree2_Module
USE CPUTime_Class
IMPLICIT NONE

INTEGER(I4B), PARAMETER :: n = 1000000, d = 3, num_run = 50
TYPE(kdtree2), POINTER :: kd1
TYPE(kdtree2_result), ALLOCATABLE :: res_tree(:)
INTEGER(I4B) :: ii, indx, nn
REAL(DFP) :: areal, ttime
LOGICAL(LGT) :: problem
REAL(DFP), ALLOCATABLE :: input_data(:, :), qv(:)
TYPE(CPUTime_) :: ctime

CALL Reallocate(input_data, d, n)
CALL RANDOM_NUMBER(input_data)

!! qv is query vector
CALL Reallocate(qv, d)
!! We will select qv randomly from input_data

kd1 => kdtree2_create(input_data, sort=.FALSE., rearrange=.TRUE.)

ALLOCATE (res_tree(n))

ttime = 0
DO ii = 1, num_run
  CALL RANDOM_NUMBER(areal)
  indx = FLOOR(areal * n) + 1
  qv = input_data(1:d, indx)
  res_tree(:)%idx = -666

  CALL ctime%SetStartTime()
  ! nn = kdtree2_r_count(tp=kd1, qv=qv, r2=0.1_DFP)
  CALL Kdtree2_r_nearest_around_point(tp=kd1, idxin=indx, &
           correltime=-1, r2=0.1_DFP, nfound=indx, nalloc=n, results=res_tree)
  CALL ctime%SetEndTime()

  ttime = ttime + ctime%GetTime()

  CALL Display(ctime%GetTime(), "time in each run: ")

END DO

CALL Display(ttime / REAL(num_run, DFP), "average time : ")

CALL kdtree2_destroy(kd1)

END PROGRAM main

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