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Second-level neighbors of large polygon (neighbors' neighbors)

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I have a large-ish set of polygons and am after identifying second-level neighbors of each, that is, the neighbors of the neighbors of each polygon (distinctly, i.e. the 2nd-level neighbors cannot contain self or 1st-level neighbors).

With a smaller number of polygons this is very easy -- owing to the "traversal" property of an adjacency matrix, we can simply square the neighbors matrix and we'll have the second-level matrix (with some minor touch-ups for the "distinctness" condition), but this doesn't extend easily to a large set of polygons:

library(sp)

library(rgeos)



dim = c(150, 150)

poly = as(GridTopology(c(0, 0), c(1, 1), dim), 'SpatialPolygons')



plot(poly[sample(prod(dim), 100), ])



neighbors = gTouches(poly, byid = TRUE)

neighbors2 = neighbors %*% neighbors

Error: cannot allocate vector of size xxx Gb

(Actually it may well compute if you've got a big-RAM machine, but anyway it will be very slow)

The problem of course is that neighbors is a huge matrix, and it's quite sparse:

format(object.size(neighbors), 'Gb')

# [1] "1.9 Gb"

mean(neighbors)

# [1] 0.0003520079

This of course is what the returnDense argument of gTouches is for, but I'm struggling to use the following output to get second-level neighbors:

neighbors = gTouches(poly, byid = TRUE)

r big-data adjacency

share

asked 8 mins ago

MichaelChiricoMichaelChirico

4151415

add a comment | 

0

I have a large-ish set of polygons and am after identifying second-level neighbors of each, that is, the neighbors of the neighbors of each polygon (distinctly, i.e. the 2nd-level neighbors cannot contain self or 1st-level neighbors).

With a smaller number of polygons this is very easy -- owing to the "traversal" property of an adjacency matrix, we can simply square the neighbors matrix and we'll have the second-level matrix (with some minor touch-ups for the "distinctness" condition), but this doesn't extend easily to a large set of polygons:

library(sp)

library(rgeos)



dim = c(150, 150)

poly = as(GridTopology(c(0, 0), c(1, 1), dim), 'SpatialPolygons')



plot(poly[sample(prod(dim), 100), ])



neighbors = gTouches(poly, byid = TRUE)

neighbors2 = neighbors %*% neighbors

Error: cannot allocate vector of size xxx Gb

(Actually it may well compute if you've got a big-RAM machine, but anyway it will be very slow)

The problem of course is that neighbors is a huge matrix, and it's quite sparse:

format(object.size(neighbors), 'Gb')

# [1] "1.9 Gb"

mean(neighbors)

# [1] 0.0003520079

This of course is what the returnDense argument of gTouches is for, but I'm struggling to use the following output to get second-level neighbors:

neighbors = gTouches(poly, byid = TRUE)

r big-data adjacency

share

asked 8 mins ago

MichaelChiricoMichaelChirico

4151415

add a comment | 

I have a large-ish set of polygons and am after identifying second-level neighbors of each, that is, the neighbors of the neighbors of each polygon (distinctly, i.e. the 2nd-level neighbors cannot contain self or 1st-level neighbors).

With a smaller number of polygons this is very easy -- owing to the "traversal" property of an adjacency matrix, we can simply square the neighbors matrix and we'll have the second-level matrix (with some minor touch-ups for the "distinctness" condition), but this doesn't extend easily to a large set of polygons:

library(sp)

library(rgeos)



dim = c(150, 150)

poly = as(GridTopology(c(0, 0), c(1, 1), dim), 'SpatialPolygons')



plot(poly[sample(prod(dim), 100), ])



neighbors = gTouches(poly, byid = TRUE)

neighbors2 = neighbors %*% neighbors

Error: cannot allocate vector of size xxx Gb

(Actually it may well compute if you've got a big-RAM machine, but anyway it will be very slow)

The problem of course is that neighbors is a huge matrix, and it's quite sparse:

format(object.size(neighbors), 'Gb')

# [1] "1.9 Gb"

mean(neighbors)

# [1] 0.0003520079

This of course is what the returnDense argument of gTouches is for, but I'm struggling to use the following output to get second-level neighbors:

neighbors = gTouches(poly, byid = TRUE)

r big-data adjacency

share

asked 8 mins ago

MichaelChiricoMichaelChirico

4151415

library(sp)

library(rgeos)



dim = c(150, 150)

poly = as(GridTopology(c(0, 0), c(1, 1), dim), 'SpatialPolygons')



plot(poly[sample(prod(dim), 100), ])



neighbors = gTouches(poly, byid = TRUE)

neighbors2 = neighbors %*% neighbors

format(object.size(neighbors), 'Gb')

# [1] "1.9 Gb"

mean(neighbors)

# [1] 0.0003520079

neighbors = gTouches(poly, byid = TRUE)

share

asked 8 mins ago

MichaelChiricoMichaelChirico

4151415

share

asked 8 mins ago

MichaelChiricoMichaelChirico

4151415

asked 8 mins ago

MichaelChiricoMichaelChirico

4151415

asked 8 mins ago

MichaelChiricoMichaelChirico

4151415