building a spatial matrix

PLEASE IGNORE THE PREVIOUS EMAIL, IT WAS SENT BY MISTAKE

Hello Sarah
thanks a lot for your advice.

I followed your suggestions unitil the creation of "result"

The allocation of the values of result$distance to the matrix result.m,
however ,does not seem to work: it produces a matrix with identical

corresponding to the last values of result$distance. Maybe my description

the dataset was not clear enough.

I produced the final matrix spat_dist with a loop, that I report below (it
takes about 1 hour on my macbook pro),

set_i = -1   # create a variable to store the i values already examined

for(i in unique(result$id)){

  set_i=c(set_i,i) # store the value of the i

  set_neigh = result$id_neigh[result$id==i & !result$id_neigh %in% set_i]

identify the locations connected to i. If the distance between i and j was
examined before, don't look for the distance between j and i

  for(j in set_neigh){
    if(i!=j){
      spat_dist[i,j] = result$distance[result$id==i &  result$id_neigh==j]
      spat_dist[j,i] = spat_dist[i,j]
    }
    else{
      spat_dist[i,j]=0
    }
  }
}

It is not the most elegant and efficient solution in the world, that's for
sure.

I would be grateful, if you could suggest an alternative instruction to:

result.m[factor(result$fcell), factor(result$cellneigh)] <-

so I will learn a faster procedure (I tried many times but to modify this
structure but I did not make it). I don't want to abuse of your time, so
forget it if you are busy

Thank you so much anyway,
Mario

ps I attach the data. Notice that the 1327 units in id_cell are firms,
indexed by id, located in location f_cell. Different firms can be located

the same f_cell. With respect to your suggestion, I added two columns to
"result" with the id of the firms.

On Fri, May 13, 2016 at 3:26 PM, A M Lavezzi <mario.lavezzi at unipa.it>

Hello Sarah
thanks a lot for your advice.

I followed your suggestions unitl the creation of "result"

The allocation of the values of result$distance to the matrix result.m,
however ,does not seem to work: it produces a matrix with identical

corresponding to the last values of result$distance. Maybe my

the dataset was not clear enough.

I produced the final matrix with a loop, that I report below (it takes
about 1 hour on my macbook pro),

set_i = -1   # create a variable to store the i values already examined

for(i in unique(result$id)){

  set_i=c(set_i,i) # store the value of the i

  set_neigh = result$id_neigh[result$id==i & !result$id_neigh %in% set_i]
# identify the locations connected to i. Exclude                  those

  for(j in set_neigh){
    if(i!=j){
      spat_dist[i,j] = result$distance[result$id==i &

      spat_dist[j,i] = spat_dist[i,j]
    }
    else{
      spat_dist[i,j]=0
    }
  }
}

It not the most elegant and efficient solution in the world, that's for
sure



On Thu, May 12, 2016 at 2:51 PM, Sarah Goslee <sarah.goslee at gmail.com>
wrote:

I don't see any reason why a loop is out of the question, and
answering would have been much easier if you'd included the requested
reproducible data, but what about this?

This solution is robust to pairs from idcell being absent in censDist,
and to the difference from A to B being different than the distance
from B to A, but not to A-B appearing twice. If that's possible,
you'll need to figure out how to manage it.

# create some fake data

idcell <- data.frame(
  id = seq_len(5),
  fcell = sample(1:100, 5))

censDist <- expand.grid(fcell=seq_len(100), cellneigh=seq_len(100))
censDist$distance <- runif(nrow(censDist))

# assemble the non-symmetric distance matrix
result <- subset(censDist, fcell %in% idcell$fcell & cellneigh %in%
idcell$fcell)
result.m <- matrix(NA, nrow=nrow(idcell), ncol=nrow(idcell))
result.m[factor(result$fcell), factor(result$cellneigh)] <-
result$distance

Sarah

On Thu, May 12, 2016 at 5:26 AM, A M Lavezzi <mario.lavezzi at unipa.it>
wrote:

Hello,

I have a sample of 1327  locations, each one idetified by an id and a
numerical code.

I need to build a spatial matrix, say, M, i.e. a 1327x1327 matrix
collecting distances among the locations.

M(i,i) should be 0, M(i,j) should contain the distance among location

and
j

I shoud use data organized in the following way:

1) id_cell contains the identifier (id) of each location (1...1327)

the
numerical code of the location (f_cell) (see head of id_cell below)

head(id_cell)

     id  f_cell
1    1   2120
12  2     204
22  3   2546
24  4   1327
34  5   1729
43  6   2293

2) censDist contains, for each location identified by its numerical
code,
the distance to other locations (censDist has 1.5 million rows). The
head(consist) below, for example, reads like this:

location 2924 has a distance to 2732 of 1309.7525
location 2924 has a distance to 2875 of 696.2891,
etc.

head(censDist)

  f_cell f  _cell_neigh  distance
1   2924         2732   1309.7525
2   2924         2875     696.2891
3   2924         2351   1346.0561
4   2924         2350   1296.9804
5   2924         2725   1278.1877
6   2924         2721   1346.9126


Basically, for every location in  id_cell I should pick up the

to
other locations in id_cell from censDist, and allocate it in M

I have not come up with a satisfactory vectorizion of this problem and
using a loop is out of question.

Thanks for your help
Mario