Adjacent matrix from igraph package to be used for autologistic model in ngspatial package in R
I am interested on running an autologistic model in ngspatial package in R. My data objects are polygones. Usually, adjacency matrices for polygones are built up based on the coordinates of the polygones centroids. However, i have define my adjacency (0/1) based on a minimum distance criterium between polygones, measured from and to the border of each polygone. I have done this in arcmap, and then with igraph package i generated the Adjacency matrix:
g<-graph_from_data_frame(My data)
A<-as_adjacency_matrix(g, attr="Dist")
A
42 x 42 sparse Matrix of class "dgCMatrix"
[[ suppressing 42 column names ‘1’, ‘2’, ‘3’ ... ]]
My matrix is just 0 and 1 values, totally symmetric (42 x 42).
However, when i try to use it in a autologistic model in ngspatial i get an error messege:
ms_autolog<-autologistic(Occupancy~Area, A=A )
'You must supply a numeric and symmetric adjacency matrix'.
I supposed that dgCMatrix is just not compatible with ngspatial, but havent found how to convert it. I have also tried directly to shape my data.csv file as a matrix, read it as a matrix, but still it cannot be read by the autologistic model.
Does anybody has any idea how can i solve this?
Many thanks in advance!
Ana María.
r igraph adjacency-list
asked Nov 20 at 17:29
Ana Prieto
134
add a comment |
I am interested on running an autologistic model in ngspatial package in R. My data objects are polygones. Usually, adjacency matrices for polygones are built up based on the coordinates of the polygones centroids. However, i have define my adjacency (0/1) based on a minimum distance criterium between polygones, measured from and to the border of each polygone. I have done this in arcmap, and then with igraph package i generated the Adjacency matrix:
g<-graph_from_data_frame(My data)
A<-as_adjacency_matrix(g, attr="Dist")
A
42 x 42 sparse Matrix of class "dgCMatrix"
[[ suppressing 42 column names ‘1’, ‘2’, ‘3’ ... ]]
My matrix is just 0 and 1 values, totally symmetric (42 x 42).
However, when i try to use it in a autologistic model in ngspatial i get an error messege:
ms_autolog<-autologistic(Occupancy~Area, A=A )
'You must supply a numeric and symmetric adjacency matrix'.
I supposed that dgCMatrix is just not compatible with ngspatial, but havent found how to convert it. I have also tried directly to shape my data.csv file as a matrix, read it as a matrix, but still it cannot be read by the autologistic model.
Does anybody has any idea how can i solve this?
Many thanks in advance!
Ana María.
r igraph adjacency-list
asked Nov 20 at 17:29
Ana Prieto
134
add a comment |
I am interested on running an autologistic model in ngspatial package in R. My data objects are polygones. Usually, adjacency matrices for polygones are built up based on the coordinates of the polygones centroids. However, i have define my adjacency (0/1) based on a minimum distance criterium between polygones, measured from and to the border of each polygone. I have done this in arcmap, and then with igraph package i generated the Adjacency matrix:
g<-graph_from_data_frame(My data)
A<-as_adjacency_matrix(g, attr="Dist")
A
42 x 42 sparse Matrix of class "dgCMatrix"
[[ suppressing 42 column names ‘1’, ‘2’, ‘3’ ... ]]
My matrix is just 0 and 1 values, totally symmetric (42 x 42).
However, when i try to use it in a autologistic model in ngspatial i get an error messege:
ms_autolog<-autologistic(Occupancy~Area, A=A )
'You must supply a numeric and symmetric adjacency matrix'.
I supposed that dgCMatrix is just not compatible with ngspatial, but havent found how to convert it. I have also tried directly to shape my data.csv file as a matrix, read it as a matrix, but still it cannot be read by the autologistic model.
Does anybody has any idea how can i solve this?
Many thanks in advance!
Ana María.
r igraph adjacency-list
asked Nov 20 at 17:29
Ana Prieto
134
I am interested on running an autologistic model in ngspatial package in R. My data objects are polygones. Usually, adjacency matrices for polygones are built up based on the coordinates of the polygones centroids. However, i have define my adjacency (0/1) based on a minimum distance criterium between polygones, measured from and to the border of each polygone. I have done this in arcmap, and then with igraph package i generated the Adjacency matrix:
g<-graph_from_data_frame(My data)
A<-as_adjacency_matrix(g, attr="Dist")
A
42 x 42 sparse Matrix of class "dgCMatrix"
[[ suppressing 42 column names ‘1’, ‘2’, ‘3’ ... ]]
My matrix is just 0 and 1 values, totally symmetric (42 x 42).
However, when i try to use it in a autologistic model in ngspatial i get an error messege:
ms_autolog<-autologistic(Occupancy~Area, A=A )
'You must supply a numeric and symmetric adjacency matrix'.
I supposed that dgCMatrix is just not compatible with ngspatial, but havent found how to convert it. I have also tried directly to shape my data.csv file as a matrix, read it as a matrix, but still it cannot be read by the autologistic model.
Does anybody has any idea how can i solve this?
Many thanks in advance!
Ana María.
r igraph adjacency-list
r igraph adjacency-list
asked Nov 20 at 17:29
Ana Prieto
134
asked Nov 20 at 17:29
Ana Prieto
134
asked Nov 20 at 17:29
Ana Prieto
134
asked Nov 20 at 17:29
Ana Prieto
134
asked Nov 20 at 17:29
Ana Prieto
134
134
add a comment |
add a comment |
1 Answer
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It's difficult to check this without a minimal working example but you could try this:
A <- as_adjacency_matrix(g, attr = "Dist", sparse = F)
This way you get a binary matrix with 0 and 1 instead of a sparse matrix.
answered Nov 20 at 17:45
Ben Nutzer
9316
1
Yes, that's how it worked! Thanks for the confirmation though. I found it finally yesterday, and was actually comming to make an update ;). It was a very easy solution, but i had assumed sparse=T because in theory an adj. matrix can be a sparse matrix.
– Ana Prieto
Nov 21 at 16:00
add a comment |
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It's difficult to check this without a minimal working example but you could try this:
A <- as_adjacency_matrix(g, attr = "Dist", sparse = F)
This way you get a binary matrix with 0 and 1 instead of a sparse matrix.
answered Nov 20 at 17:45
Ben Nutzer
9316
1
Yes, that's how it worked! Thanks for the confirmation though. I found it finally yesterday, and was actually comming to make an update ;). It was a very easy solution, but i had assumed sparse=T because in theory an adj. matrix can be a sparse matrix.
– Ana Prieto
Nov 21 at 16:00
add a comment |
It's difficult to check this without a minimal working example but you could try this:
A <- as_adjacency_matrix(g, attr = "Dist", sparse = F)
This way you get a binary matrix with 0 and 1 instead of a sparse matrix.
answered Nov 20 at 17:45
Ben Nutzer
9316
1
Yes, that's how it worked! Thanks for the confirmation though. I found it finally yesterday, and was actually comming to make an update ;). It was a very easy solution, but i had assumed sparse=T because in theory an adj. matrix can be a sparse matrix.
– Ana Prieto
Nov 21 at 16:00
add a comment |
It's difficult to check this without a minimal working example but you could try this:
A <- as_adjacency_matrix(g, attr = "Dist", sparse = F)
This way you get a binary matrix with 0 and 1 instead of a sparse matrix.
answered Nov 20 at 17:45
Ben Nutzer
9316
It's difficult to check this without a minimal working example but you could try this:
A <- as_adjacency_matrix(g, attr = "Dist", sparse = F)
This way you get a binary matrix with 0 and 1 instead of a sparse matrix.
answered Nov 20 at 17:45
Ben Nutzer
9316
answered Nov 20 at 17:45
Ben Nutzer
9316
answered Nov 20 at 17:45
Ben Nutzer
9316
answered Nov 20 at 17:45
Ben Nutzer
9316
9316
1
Yes, that's how it worked! Thanks for the confirmation though. I found it finally yesterday, and was actually comming to make an update ;). It was a very easy solution, but i had assumed sparse=T because in theory an adj. matrix can be a sparse matrix.
– Ana Prieto
Nov 21 at 16:00
add a comment |
1
Yes, that's how it worked! Thanks for the confirmation though. I found it finally yesterday, and was actually comming to make an update ;). It was a very easy solution, but i had assumed sparse=T because in theory an adj. matrix can be a sparse matrix.
– Ana Prieto
Nov 21 at 16:00
1
1
Yes, that's how it worked! Thanks for the confirmation though. I found it finally yesterday, and was actually comming to make an update ;). It was a very easy solution, but i had assumed sparse=T because in theory an adj. matrix can be a sparse matrix.
– Ana Prieto
Nov 21 at 16:00
Yes, that's how it worked! Thanks for the confirmation though. I found it finally yesterday, and was actually comming to make an update ;). It was a very easy solution, but i had assumed sparse=T because in theory an adj. matrix can be a sparse matrix.
– Ana Prieto
Nov 21 at 16:00
add a comment |
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