Non Tabular data structure in Fortran - fortran

Question

I would like to build a data structure for non tabular data. I am not sure what is the right way to do that in (modern) Fortran.
I have a data set of houses that includes their location (lat,lon) and price. I have another data of factories that include their location (lat,lon) and the amount of pollution they produce. For each house I need to create a list of factories which are within 5km radius of the house. Not just the number of these factories but the whole (lat,lon,pollution) vectors of these factories. Each house has a different number of factories close to it ranging from zero to about eighty.
MODULE someDefinitions
IMPLICIT NONE
INTEGER, PARAMETER :: N_houses=82390, N_factories=4215
TYPE house
REAL :: lat,lon,price
! a few more fields which are not important here
END TYPE
TYPE factory
REAL :: lat,lon,pollution
! a few more fields which are not important here
END TYPE
Contains
PURE FUNCTION haversine(deglat1,deglon1,deglat2,deglon2) RESULT (dist)
! Some code for computing haversine distance in meters
END FUNCTION haversine
END MODULE someDefinitions
PROGRAM createStructure
USE someDefinitions
IMPLICIT NONE
TYPE(factory), DIMENSION(N_factories) :: factories
TYPE(house), DIMENSION(N_houses) :: houses
INTEGER :: i,j
! more variables definitions as needed
! code to read houses data from the disk
! code to read factories data from the disk
DO i=1,N_houses
DO j=1,N_factories
!here I compute the distance between houses(i) and factories(j)
! If this distance<=5000 I want to add the index j to the list of indices
! associated with house i. How? What is the right data structure to do
! that? some houses have zero factories within 5000 meters from them.
! Some houses have about 80 factories around them. It's unbalanced.
END DO !j
END DO !i
END PROGRAM createStructure
The created structure will then be used in further calculations. A matrix of N_houses x N_factories is way too large to save in memory.
Note: I know Fortran 2008 if that is helpful in any way.

Answer 1

Using too many nested derived types can become tedious. Here is an example using 2D arrays for all data except the required list. This is similar to the K-Nearest Neighbors (KNN) algorithm naively implemented. There may be better algorithms, of course, but the following can be a good start.
program NoStrucyures
implicit none
type listi
real, allocatable :: item(:,:)
end type
integer, parameter :: N_houses=82390, N_factories=4215
real :: houses(N_houses,3)
real :: factories(N_factories,3)
real :: distance(N_factories)
type(listi) :: list(N_houses)
integer :: i, j, k, within5k
! Generating dummy data
call random_number(houses)
call random_number(factories)
houses = houses * 500000
factories = factories * 500000
do i = 1, N_houses
distance = sqrt((houses(i,1)-factories(:,1))**2 + (houses(i,2)-factories(:,2))**2)
within5k = count( distance <= 5000 )
if (within5k > 0) then
allocate(list(i)%item(within5k,3))
k = 0
do j = 1, N_factories
if (distance(j) <= 5000) then
k = k + 1
list(i)%item(k,:) = factories(j,:)
end if
end do
else
list(i)%item = reshape([-1, -1, -1],[1,3])
end if
end do
do i=1,10
print *, list(i)%item
end do
end program NoStrucyures