Comments (1)
Rekyt
commented on May 31, 2024
For the record this is the behavior with all indices:
library("fundiversity")
site_sp_birds[, 1:2]
#> Aburria_aburri Amazona_farinosa
#> elev_250 0 1
#> elev_500 0 1
#> elev_1000 1 1
#> elev_1500 1 0
#> elev_2000 0 0
#> elev_2500 0 0
#> elev_3000 0 0
#> elev_3500 0 0
# Compute indices with only a subset of species
fd_fdis(traits_birds, site_sp_birds[, 1:2])
#> Differing number of species between trait dataset and site-species matrix
#> Taking subset of species
#> site FDis
#> 1 elev_250 0.0000
#> 2 elev_500 0.0000
#> 3 elev_1000 390.7748
#> 4 elev_1500 0.0000
#> 5 elev_2000 0.0000
#> 6 elev_2500 0.0000
#> 7 elev_3000 0.0000
#> 8 elev_3500 0.0000
fd_fdiv(traits_birds, site_sp_birds[, 1:2])
#> Differing number of species between trait dataset and site-species matrix
#> Taking subset of species
#> site FDiv
#> 1 elev_250 NaN
#> 2 elev_500 NaN
#> 3 elev_1000 1
#> 4 elev_1500 NaN
#> 5 elev_2000 0
#> 6 elev_2500 0
#> 7 elev_3000 0
#> 8 elev_3500 0
fd_feve(traits_birds, site_sp_birds[, 1:2])
#> Differing number of species between trait dataset and site-species matrix
#> Taking subset of species
#> site FEve
#> 1 elev_250 NA
#> 2 elev_500 NA
#> 3 elev_1000 NA
#> 4 elev_1500 NA
#> 5 elev_2000 NA
#> 6 elev_2500 NA
#> 7 elev_3000 NA
#> 8 elev_3500 NA
fd_fric_intersect(traits_birds, site_sp_birds[, 1:2])
#> Differing number of species between trait dataset and site-species matrix
#> Taking subset of species
#> first_site second_site FRic_intersect
#> 1 elev_250 elev_500 NA
#> 2 elev_250 elev_1000 NA
#> 3 elev_250 elev_1500 NA
#> 4 elev_250 elev_2000 NA
#> 5 elev_250 elev_2500 NA
#> 6 elev_250 elev_3000 NA
#> 7 elev_250 elev_3500 NA
#> 8 elev_500 elev_1000 NA
#> 9 elev_500 elev_1500 NA
#> 10 elev_500 elev_2000 NA
#> 11 elev_500 elev_2500 NA
#> 12 elev_500 elev_3000 NA
#> 13 elev_500 elev_3500 NA
#> 14 elev_1000 elev_1500 NA
#> 15 elev_1000 elev_2000 NA
#> 16 elev_1000 elev_2500 NA
#> 17 elev_1000 elev_3000 NA
#> 18 elev_1000 elev_3500 NA
#> 19 elev_1500 elev_2000 NA
#> 20 elev_1500 elev_2500 NA
#> 21 elev_1500 elev_3000 NA
#> 22 elev_1500 elev_3500 NA
#> 23 elev_2000 elev_2500 NA
#> 24 elev_2000 elev_3000 NA
#> 25 elev_2000 elev_3500 NA
#> 26 elev_2500 elev_3000 NA
#> 27 elev_2500 elev_3500 NA
#> 28 elev_3000 elev_3500 NA
#> 29 elev_250 elev_250 NA
#> 30 elev_500 elev_500 NA
#> 31 elev_1000 elev_1000 NA
#> 32 elev_1500 elev_1500 NA
#> 33 elev_2000 elev_2000 NA
#> 34 elev_2500 elev_2500 NA
#> 35 elev_3000 elev_3000 NA
#> 36 elev_3500 elev_3500 NA
fd_fric(traits_birds, site_sp_birds[, 1:2])
#> Differing number of species between trait dataset and site-species matrix
#> Taking subset of species
#> site FRic
#> 1 elev_250 NA
#> 2 elev_500 NA
#> 3 elev_1000 NA
#> 4 elev_1500 NA
#> 5 elev_2000 NA
#> 6 elev_2500 NA
#> 7 elev_3000 NA
#> 8 elev_3500 NA
fd_raoq(traits_birds, site_sp_birds[, 1:2])
#> Differing number of species between trait dataset and site-species matrix
#> Taking subset of species
#> site Q
#> 1 elev_250 0.0000
#> 2 elev_500 0.0000
#> 3 elev_1000 390.7748
#> 4 elev_1500 0.0000
#> 5 elev_2000 0.0000
#> 6 elev_2500 0.0000
#> 7 elev_3000 0.0000
#> 8 elev_3500 0.0000Created on 2022-11-15 with reprex v2.0.2
Session info
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.2.0 (2022-04-22 ucrt)
#> os Windows 10 x64 (build 19042)
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate fr_FR.UTF-8
#> ctype fr_FR.UTF-8
#> tz Europe/Berlin
#> date 2022-11-15
#> pandoc 2.19.2 @ C:/Program Files/RStudio/bin/quarto/bin/tools/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> abind 1.4-5 2016-07-21 [1] CRAN (R 4.2.0)
#> cachem 1.0.6 2021-08-19 [1] CRAN (R 4.2.0)
#> cli 3.4.1 2022-09-23 [1] CRAN (R 4.2.1)
#> codetools 0.2-18 2020-11-04 [1] CRAN (R 4.2.0)
#> digest 0.6.30 2022-10-18 [1] CRAN (R 4.2.0)
#> evaluate 0.18 2022-11-07 [1] CRAN (R 4.2.2)
#> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.2.0)
#> fs 1.5.2 2021-12-08 [1] CRAN (R 4.2.0)
#> fundiversity * 1.0.0.9000 2022-11-11 [1] local
#> future 1.29.0 2022-11-06 [1] CRAN (R 4.2.0)
#> future.apply 1.10.0 2022-11-05 [1] CRAN (R 4.2.2)
#> geometry 0.4.6.1 2022-07-04 [1] CRAN (R 4.2.0)
#> globals 0.16.1 2022-08-28 [1] CRAN (R 4.2.1)
#> glue 1.6.2 2022-02-24 [1] CRAN (R 4.2.0)
#> highr 0.9 2021-04-16 [1] CRAN (R 4.2.0)
#> htmltools 0.5.3 2022-07-18 [1] CRAN (R 4.2.0)
#> knitr 1.40 2022-08-24 [1] CRAN (R 4.2.1)
#> lattice 0.20-45 2021-09-22 [1] CRAN (R 4.2.0)
#> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.2.1)
#> listenv 0.8.0 2019-12-05 [1] CRAN (R 4.2.0)
#> magic 1.6-0 2022-02-09 [1] CRAN (R 4.2.0)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.2.0)
#> Matrix 1.5-1 2022-09-13 [1] CRAN (R 4.2.1)
#> memoise 2.0.1 2021-11-26 [1] CRAN (R 4.2.0)
#> parallelly 1.32.1 2022-07-21 [1] CRAN (R 4.2.1)
#> purrr 0.3.5 2022-10-06 [1] CRAN (R 4.2.1)
#> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.2.1)
#> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.2.0)
#> R.oo 1.25.0 2022-06-12 [1] CRAN (R 4.2.0)
#> R.utils 2.12.2 2022-11-11 [1] CRAN (R 4.2.0)
#> Rcpp 1.0.9 2022-07-08 [1] CRAN (R 4.2.1)
#> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.2.1)
#> rlang 1.0.6.9000 2022-10-11 [1] Github (r-lib/rlang@28a40b5)
#> rmarkdown 2.18 2022-11-09 [1] CRAN (R 4.2.2)
#> rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.2.1)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.2.0)
#> stringi 1.7.8 2022-07-11 [1] CRAN (R 4.2.1)
#> stringr 1.4.1 2022-08-20 [1] CRAN (R 4.2.1)
#> styler 1.8.1 2022-11-07 [1] CRAN (R 4.2.2)
#> withr 2.5.0 2022-03-03 [1] CRAN (R 4.2.0)
#> xfun 0.34 2022-10-18 [1] CRAN (R 4.2.0)
#> yaml 2.3.6 2022-10-18 [1] CRAN (R 4.2.0)
#>
#> [1] C:/Users/ke76dimu/Documents/R/R-4.2.0/library
#>
#> ──────────────────────────────────────────────────────────────────────────────It seems the behavior isn't consistent across indices. Also it is not consistent when there is no species or not enough. What should be our choice?
Should we return NA or 0?
For FDis, having no species or only one necessarily mean an FDis of 0, but could also be NA as we can't measure any kind of dissimilarity with less than two species.
For FDiv, because we have to compute the convex hull, it's has a volume of 0 with 0 species but is not computable as soon as we have 1 species.
FEve needs at least 3 species to get a minimum spanning tree.
FRic needs convex hull estimate which is impossible with 2 species but 4 traits.
Same for FRic_intersect.
For Rao's when having no or one species it's impossible to get dissimilarity as for FDis.
Should we issue messages or warnings to the user to warn when some sites return NAs?
What about unifying outputs across functions? Should we keep them like this or try to unify how they work?
The limitations outlined above should at least be in the documentation.
from fundiversity.
Related Issues (20)
- Hex logo
- Managing error from qhull transferred to geometry::convhulln() in fd_chull()
- Error when site contains no species in fd_fdiv() and fd_feve() HOT 2
- Errors when using non-quantitative traits in fd_fric()
- Release fundiversity 0.2.1
- Specific error obtained with Qhull HOT 3
- Investigate RCGAL as a replacement of geometry HOT 4
- Simplify CI matrix by using `_R_CHECK_DEPENDS_ONLY_TESTS_` HOT 2
- fd_fdiv() returns `NaN` on datasets without rownames
- Add tip in error message because of non-continuous traits HOT 1
- Renaming the vignettes to order them logically? HOT 2
- Change title of package in DESCRIPTION as it doesn't only computes "Alpha functional diversity indices"
- fd_fdis() bugs when site-species object is a data.frame() expects a matrix. HOT 2
- Using future and memoise together HOT 2
- Add link to published paper
- Should we write a vignette for non-continuous trait data? HOT 1
- fd_dis gives error if site x species matrix does not have row names HOT 4
- Be more specific in the help with memoization HOT 2
- Have a worked through example with individual level dataset
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from fundiversity.