2. Matrix and network formats
Maxime Lenormand, Boris Leroy and Pierre Denelle
2024-11-20
Source:vignettes/a2_matrix_and_network_formats.Rmd
a2_matrix_and_network_formats.RmdLoad data
The bioregion’s package contains as example dataset the
spatial distribution of Mediterranean vegetation. This dataset has been
analyzed in this
article and contains the abundance of 3,697 species in 715 sites.
This dataset is composed of three files, vegedf
a data.frame with 460,878 rows and 3 columns (Site, Species
and Abundance),
## Site Species Abundance
## 1 35 10017 1
## 2 35 10024 18
## 3 35 10034 1
## 4 35 10035 1
## 5 35 10056 2
## 6 35 10080 3
dim(vegedf)## [1] 460878 3
sum(!duplicated(vegedf[,1]))## [1] 715
sum(!duplicated(vegedf[,2]))## [1] 3697vegemat
a co-occurrence matrix containing the same information
gathered in a matrix with 715 rows and 3,697 columns,
data(vegemat)
vegemat[1:10,1:10]## Species
## Site 10001 10002 10003 10004 10005 10006 10007 10008 10009 10010
## 35 0 0 0 0 0 0 0 0 0 0
## 36 2 0 0 0 0 0 1 12 0 0
## 37 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0 0 0 0
## 39 5 0 0 0 0 0 0 2 0 0
## 84 0 0 0 0 0 0 0 0 0 0
## 85 3 0 0 0 0 0 1 7 0 0
## 86 0 0 0 2 0 0 2 22 0 0
## 87 16 0 0 0 0 0 2 54 0 0
## 88 228 0 0 0 0 0 0 5 0 0
dim(vegemat)## [1] 715 3697and vegesf a spatial object containing the geometry of the 715 sites.
From matrix to network
The function mat_to_net
transforms a co-occurrence matrix such as
vegemat into a network represented by a
data.frame (such as vegedf in this case). If
weight = TRUE a third column is added with the values
contained in the matrix.
net <- mat_to_net(vegemat, weight = TRUE, remove_zeroes = FALSE)In line with the network format, the two first columns are named
Node1 and Node2 by default.
head(net)## Node1 Node2 Weight
## 1 35 10001 0
## 2 35 10002 0
## 3 35 10003 0
## 4 35 10004 0
## 5 35 10005 0
## 6 35 10006 0
dim(net)## [1] 2643355 3If remove_zeroes = TRUE the pairs of nodes with a weight
equal to 0 will be removed from the output.
net <- mat_to_net(vegemat, weight = TRUE, remove_zeroes = TRUE)
head(net)## Node1 Node2 Weight
## 17 35 10017 1
## 24 35 10024 18
## 34 35 10034 1
## 35 35 10035 1
## 56 35 10056 2
## 80 35 10080 3
dim(net)## [1] 460878 3From network to matrix
The function net_to_mat
does the opposite. It transforms a network represented by a two- or a
three-columns data.frame (such as vegedf) into
a co-occurrence matrix (such as vegemat in
this case).
mat <- net_to_mat(vegedf, weight = TRUE, squared = FALSE, symmetrical = FALSE, missing_value = 0)
mat[1:5,1:5]## 10017 10024 10034 10035 10056
## 35 1 18 1 1 2
## 36 252 57 72 19 75
## 37 66 1 13 23 43
## 38 17 1 5 89 27
## 39 17 17 34 3 8
dim(mat)## [1] 715 3697If squared = TRUE a squared matrix will be generated,
the rownames and colnames will correspond to the concatenation without
duplicates of the two first columns of the data.frame.
mat <- net_to_mat(vegedf, weight = TRUE, squared = TRUE, symmetrical = FALSE, missing_value = 0)
mat[1:5,1:5]## 35 36 37 38 39
## 35 0 0 0 0 0
## 36 0 0 0 0 0
## 37 0 0 0 0 0
## 38 0 0 0 0 0
## 39 0 0 0 0 0
dim(mat)## [1] 4412 4412The argument missing_value defines the value to assign
to the pairs of nodes not present in the input network. The default
value is 0 but any other numeric value can be used.
temp <- data.frame(Site=c("35","36","36","38","39"), Species=c("36","35","37","37","39"), Abundance=c(1,2,3,4,0))
net <- rbind(temp,vegedf)
mat <- net_to_mat(net, weight = TRUE, squared = TRUE, symmetrical = FALSE, missing_value = -1)
mat[1:5,1:5]## 35 36 38 39 37
## 35 -1 1 -1 -1 -1
## 36 2 -1 -1 -1 3
## 38 -1 -1 -1 -1 4
## 39 -1 -1 -1 0 -1
## 37 -1 -1 -1 -1 -1Finally, if squared = TRUE it is possible to get a
symmetrical matrix as output (symmetrical = TRUE). In this
case the resulting squared matrix will be symmetrical, except for the
symmetrical pairs of nodes already present in the input network (35
<-> 36) in the example below.
mat <- net_to_mat(net, weight = TRUE, squared = TRUE, symmetrical = TRUE, missing_value = 0)
mat[1:5,1:5]## 35 36 38 39 37
## 35 0 1 0 0 0
## 36 2 0 0 0 3
## 38 0 0 0 0 4
## 39 0 0 0 0 0
## 37 0 3 4 0 0