Convert similarity metrics to dissimilarity metrics
Source:R/similarity_dissimilarity_conversion.R
similarity_to_dissimilarity.RdThis function converts a data.frame of similarity metrics between sites to
dissimilarity metrics (beta diversity).
Arguments
- similarity
the output object from
similarity()ordissimilarity_to_similarity().- include_formula
a
booleanindicating if the metrics based on your own formula(s) should be converted (see Details). This argument is set toTRUEby default.
Value
A data.frame with additional class
bioregion.pairwise.metric, providing dissimilarity
metric(s) between each pair of sites based on a similarity object.
Note
The behavior of this function changes depending on column names. Columns
Site1 and Site2 are copied identically. If there are columns called
a, b, c, A, B, C they will also be copied identically. If there
are columns based on your own formula (argument formula in similarity())
or not in the original list of similarity metrics (argument metrics in
similarity()) and if the argument include_formula is set to FALSE,
they will also be copied identically. Otherwise there are going to be
converted like they other columns (default behavior).
If a column is called Euclidean, its distance will be calculated based
on the following formula:
Euclidean distance = (1 - Euclidean similarity) / Euclidean similarity
Otherwise, all other columns will be transformed into dissimilarity with the following formula:
dissimilarity = 1 - similarity
Author
Maxime Lenormand (maxime.lenormand@inrae.fr)
Boris Leroy (leroy.boris@gmail.com)
Pierre Denelle (pierre.denelle@gmail.com)
Examples
comat <- matrix(sample(0:1000, size = 50, replace = TRUE,
prob = 1 / 1:1001), 5, 10)
rownames(comat) <- paste0("Site", 1:5)
colnames(comat) <- paste0("Species", 1:10)
simil <- similarity(comat, metric = "all")
simil
#> Data.frame of similarity between sites
#> - Total number of sites: 5
#> - Total number of species: 10
#> - Number of rows: 10
#> - Number of similarity metrics: 7
#>
#>
#> Site1 Site2 Jaccard Jaccardturn Sorensen Simpson Bray Brayturn
#> 2 Site1 Site2 0.8 1.0000000 0.8888889 1.000 0.2324665 0.6427015
#> 3 Site1 Site3 0.7 0.7777778 0.8235294 0.875 0.0903852 0.1223317
#> 4 Site1 Site4 0.8 1.0000000 0.8888889 1.000 0.1058132 0.1168831
#> 5 Site1 Site5 0.8 1.0000000 0.8888889 1.000 0.2622122 0.3149022
#> 8 Site2 Site3 0.9 1.0000000 0.9473684 1.000 0.1836613 0.3355120
#> 9 Site2 Site4 1.0 1.0000000 1.0000000 1.000 0.1116717 0.3616558
#> 10 Site2 Site5 1.0 1.0000000 1.0000000 1.000 0.1307930 0.2766885
#> 14 Site3 Site4 0.9 1.0000000 0.9473684 1.000 0.4774920 0.7315271
#> 15 Site3 Site5 0.9 1.0000000 0.9473684 1.000 0.3361718 0.3727422
#> 20 Site4 Site5 1.0 1.0000000 1.0000000 1.000 0.5053790 0.6810519
#> Euclidean a b c A B C
#> 2 0.0009814101 8 0 2 295 1784 164
#> 3 0.0007215210 7 1 2 149 1930 1069
#> 4 0.0006827220 8 0 2 243 1836 2271
#> 5 0.0009173381 8 0 2 467 1612 1016
#> 8 0.0010484706 9 1 0 154 305 1064
#> 9 0.0008964378 10 0 0 166 293 2348
#> 10 0.0012192118 10 0 0 127 332 1356
#> 14 0.0011265904 9 0 1 891 327 1623
#> 15 0.0010358347 9 0 1 454 764 1029
#> 20 0.0011055029 10 0 0 1010 1504 473
dissimilarity <- similarity_to_dissimilarity(simil)
dissimilarity
#> Data.frame of dissimilarity between sites
#> - Total number of sites: 5
#> - Total number of species: 10
#> - Number of rows: 10
#> - Number of dissimilarity metrics: 7
#>
#>
#> Site1 Site2 Jaccard Jaccardturn Sorensen Simpson Bray Brayturn
#> 2 Site1 Site2 0.2 0.0000000 0.11111111 0.000 0.7675335 0.3572985
#> 3 Site1 Site3 0.3 0.2222222 0.17647059 0.125 0.9096148 0.8776683
#> 4 Site1 Site4 0.2 0.0000000 0.11111111 0.000 0.8941868 0.8831169
#> 5 Site1 Site5 0.2 0.0000000 0.11111111 0.000 0.7377878 0.6850978
#> 8 Site2 Site3 0.1 0.0000000 0.05263158 0.000 0.8163387 0.6644880
#> 9 Site2 Site4 0.0 0.0000000 0.00000000 0.000 0.8883283 0.6383442
#> 10 Site2 Site5 0.0 0.0000000 0.00000000 0.000 0.8692070 0.7233115
#> 14 Site3 Site4 0.1 0.0000000 0.05263158 0.000 0.5225080 0.2684729
#> 15 Site3 Site5 0.1 0.0000000 0.05263158 0.000 0.6638282 0.6272578
#> 20 Site4 Site5 0.0 0.0000000 0.00000000 0.000 0.4946210 0.3189481
#> Euclidean a b c A B C
#> 2 1017.9420 8 0 2 295 1784 164
#> 3 1384.9610 7 1 2 149 1930 1069
#> 4 1463.7250 8 0 2 243 1836 2271
#> 5 1089.1106 8 0 2 467 1612 1016
#> 8 952.7702 9 1 0 154 305 1064
#> 9 1114.5264 10 0 0 166 293 2348
#> 10 819.2021 10 0 0 127 332 1356
#> 14 886.6341 9 0 1 891 327 1623
#> 15 964.4050 9 0 1 454 764 1029
#> 20 903.5657 10 0 0 1010 1504 473