Converts an integrated co-occurrence matrix (incoma) to an integrated co-occurrence vector (incove)
get_incove(x, ordered = TRUE, repeated = TRUE, normalization = "none")
| x | A matrix - an output of the |
|---|---|
| ordered | The type of pairs considered. Either "ordered" (TRUE) or "unordered" (FALSE). The default is TRUE. See details for more explanation. |
| repeated | Should the repeated co-located co-occurrence matrices be used? Either "repeated" (TRUE) or "unrepeated" (FALSE). The default is TRUE. See details for more explanation. |
| normalization | Should the output vector be normalized? Either "none" or "pdf". The "pdf" option normalizes a vector to sum to one. The default is "none". |
An integrated co-occurrence vector
All values are kept when ordered = TRUE and repeated = TRUE.
When ordered = TRUE and repeated = FALSE all values from cocoma (but only one cocoma for each pair) and all coma values are kept.
ordered = FALSE and repeated = TRUE keeps all values from cocoma, but divides coma values by 2.
ordered = FALSE and repeated = FALSE keeps all values from cocoma (but only one cocoma for each pair), and divides coma values by 2.
library(comat) data(raster_x, package = "comat") data(raster_w, package = "comat") x = list(raster_x, raster_w, raster_x) incom = get_incoma(x) incom#> 1 2 3 2 4 6 8 9 1 2 3 #> 1 4 1 3 3 3 1 0 1 4 1 3 #> 2 1 2 2 0 2 1 1 1 1 2 2 #> 3 3 2 6 2 1 1 2 5 3 2 6 #> 2 3 0 2 2 1 1 0 1 3 0 2 #> 4 3 2 1 1 0 2 2 1 3 2 1 #> 6 1 1 1 1 2 0 0 0 1 1 1 #> 8 0 1 2 0 2 0 0 1 0 1 2 #> 9 1 1 5 1 1 0 1 4 1 1 5 #> 1 4 1 3 3 3 1 0 1 4 1 3 #> 2 1 2 2 0 2 1 1 1 1 2 2 #> 3 3 2 6 2 1 1 2 5 3 2 6 #> attr(,"no_unique") #> [1] 3 5 3incov1 = get_incove(incom) incov1#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] #> [1,] 4 1 3 1 2 2 3 2 6 3 0 2 3 2 #> [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] #> [1,] 1 1 1 1 0 1 2 1 1 5 4 1 #> [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38] #> [1,] 3 1 2 2 3 2 6 3 3 1 0 1 #> [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50] #> [1,] 0 2 1 1 1 2 1 1 2 5 2 1 #> [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62] #> [1,] 1 0 1 1 0 2 2 1 1 2 0 0 #> [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [,73] [,74] #> [1,] 0 0 2 0 0 1 1 1 0 1 4 3 #> [,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85] [,86] #> [1,] 3 1 0 1 0 2 1 1 1 2 1 1 #> [,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [,97] [,98] #> [1,] 2 5 4 1 3 1 2 2 3 2 6 3 #> [,99] [,100] [,101] [,102] [,103] [,104] [,105] [,106] [,107] [,108] #> [1,] 0 2 3 2 1 1 1 1 0 1 #> [,109] [,110] [,111] [,112] [,113] [,114] [,115] [,116] [,117] [,118] #> [1,] 2 1 1 5 4 1 3 1 2 2 #> [,119] [,120] [,121] #> [1,] 3 2 6incov2 = get_incove(incom, ordered = FALSE) incov2#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] #> [1,] 2 1 1 3 2 3 3 0 2 3 2 1 1 1 #> [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] #> [1,] 1 0 1 2 1 1 5 4 1 3 1 2 #> [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38] #> [1,] 2 3 2 6 3 3 1 0 1 0 2 1 #> [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50] #> [1,] 1 1 2 1 1 2 5 1 1 0 1 2 #> [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62] #> [1,] 0 0 2 0 0 1 1 0 1 2 3 3 #> [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [,73] [,74] #> [1,] 1 0 1 0 2 1 1 1 2 1 1 2 #> [,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85] [,86] #> [1,] 5 4 1 3 1 2 2 3 2 6 3 0 #> [,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [,97] [,98] #> [1,] 2 3 2 1 1 1 1 0 1 2 1 1 #> [,99] [,100] [,101] [,102] [,103] [,104] [,105] #> [1,] 5 2 1 1 3 2 3incov3 = get_incove(incom, ordered = FALSE, normalization = "pdf") incov3#> [,1] [,2] [,3] [,4] [,5] [,6] #> [1,] 0.01851852 0.009259259 0.009259259 0.02777778 0.01851852 0.02777778 #> [,7] [,8] [,9] [,10] [,11] [,12] [,13] #> [1,] 0.01388889 0 0.009259259 0.01388889 0.009259259 0.00462963 0.00462963 #> [,14] [,15] [,16] [,17] [,18] [,19] [,20] #> [1,] 0.00462963 0.00462963 0 0.00462963 0.009259259 0.00462963 0.00462963 #> [,21] [,22] [,23] [,24] [,25] [,26] #> [1,] 0.02314815 0.01851852 0.00462963 0.01388889 0.00462963 0.009259259 #> [,27] [,28] [,29] [,30] [,31] [,32] #> [1,] 0.009259259 0.01388889 0.009259259 0.02777778 0.01388889 0.01388889 #> [,33] [,34] [,35] [,36] [,37] [,38] [,39] #> [1,] 0.00462963 0 0.00462963 0 0.009259259 0.00462963 0.00462963 #> [,40] [,41] [,42] [,43] [,44] [,45] #> [1,] 0.00462963 0.009259259 0.00462963 0.00462963 0.009259259 0.02314815 #> [,46] [,47] [,48] [,49] [,50] [,51] [,52] #> [1,] 0.009259259 0.009259259 0 0.009259259 0.01851852 0 0 #> [,53] [,54] [,55] [,56] [,57] [,58] [,59] #> [1,] 0.01851852 0 0 0.009259259 0.009259259 0 0.009259259 #> [,60] [,61] [,62] [,63] [,64] [,65] [,66] #> [1,] 0.01851852 0.01388889 0.01388889 0.00462963 0 0.00462963 0 #> [,67] [,68] [,69] [,70] [,71] [,72] #> [1,] 0.009259259 0.00462963 0.00462963 0.00462963 0.009259259 0.00462963 #> [,73] [,74] [,75] [,76] [,77] [,78] #> [1,] 0.00462963 0.009259259 0.02314815 0.01851852 0.00462963 0.01388889 #> [,79] [,80] [,81] [,82] [,83] [,84] #> [1,] 0.00462963 0.009259259 0.009259259 0.01388889 0.009259259 0.02777778 #> [,85] [,86] [,87] [,88] [,89] [,90] [,91] #> [1,] 0.01388889 0 0.009259259 0.01388889 0.009259259 0.00462963 0.00462963 #> [,92] [,93] [,94] [,95] [,96] [,97] [,98] #> [1,] 0.00462963 0.00462963 0 0.00462963 0.009259259 0.00462963 0.00462963 #> [,99] [,100] [,101] [,102] [,103] [,104] #> [1,] 0.02314815 0.01851852 0.009259259 0.009259259 0.02777778 0.01851852 #> [,105] #> [1,] 0.02777778