Conversion Among Various Object Classes
as.mefa.RdThese functions coerce into class 'mefa' or 'stcs'; or converts 'mefa' or 'stcs' obects into a 'data.frame', 'matrix', 'array', 'list'.
Usage
as.stcs(x, ...)
# S3 method for default
as.stcs(x, ...)
as.mefa(x, ...)
as.Mefa(x, ...)
as.Xtab(x, ...)
# S3 method for default
as.mefa(x, samp, taxa, ...)
# S3 method for array
as.mefa(x, ...)
# S3 method for list
as.mefa(x, ...)
# S3 method for mefa
as.matrix(x, ...)
# S3 method for mefa
as.array(x, ...)
# S3 method for mefa
as.list(x, ...)
# S3 method for stcs
as.data.frame(x, ...)
# S3 method for mefa
as.data.frame(x, ..., fun, name, make.unique = FALSE)
mss(x, name, make.unique = FALSE, ...)
msr(x, name, make.unique = FALSE, ...)
mts(x, name, make.unique = FALSE, ...)
mtr(x, name, make.unique = FALSE, ...)Arguments
- x
an object of class 'mefa'.
- samp
a data frame containing rows for samples, or
NULL. See argumentxtab.fixedand details for sample matching options.- taxa
a data frame containing rows for taxa, or
NULL. See argumentxtab.fixedand details for taxa matching options.- fun
a function to determine what to return, see details. It has no default, because the choice is not trivial.
- name
optional character vector, names to return if not all possible elements are needed, see details.
- make.unique
logical, useful to use
make.unique = TRUEif names to return are non-unique, see details.- ...
other arguments passed to the generic function
as.data.frame.
Details
The usage of most of these coercion methods is trivial. Arrays and lists can be coerced into 'mefa' objects as if those were the segm element of it (either nested, or non nested). The reverse is true, when coercing an object of class 'mefa' into list or array, the segm element is used.
Coercing among object classes 'matrix' and 'mefa' is done via using the xtab element.
By as.data.frame.mefa, four kinds of data frames can be returned, depending on the function used as the fun argument:
mss returns summary statistics for samples (richness and abundance) and x$samp;
msr returns raw data (x$xtab) and x$samp;
mts returns summary statistics for taxa (occurrence and abundance) and x$taxa;
mtr returns raw data (t(x$xtab)) and x$taxa.
The name can be used if only a subset of the summary statistics, or raw data should be returned. The character vector should contain names of elements to return (see examples).
It might (rarely) occur, that names of the summary statistics, or the raw data and the column names of the sample/taxa table overlap (contains names that are common in the two set). In this case, the make.unique = TRUE can be used to resolve non-uniqueness and avoid the error message produced otherwise.
The functions supplied as the fun argument can be used separately. Although the usage of the as.data.frame method is more transparent.
Value
An object of class 'stcs', 'mefa', 'matrix', 'array', 'list' or 'data.frame', depending on the method used.
References
S\'olymos P. (2008) mefa: an R package for handling and reporting count data. Community Ecology 9, 125--127.
S\'olymos P. (2009) Processing ecological data in R with the mefa package. Journal of Statistical Software 29(8), 1--28. doi:10.18637/jss.v029.i08
Author
P\'eter S\'olymos, solymos@ualberta.ca
Examples
data(dol.count, dol.samp, dol.taxa)
x <- mefa(stcs(dol.count), dol.samp, dol.taxa)
## These two are equivalent
as.data.frame(x, fun = mss)
#> s.rich s.abu microhab method
#> DQ1 5 18 dead.wood quadrat
#> DQ2 7 39 dead.wood quadrat
#> DQ3 4 9 dead.wood quadrat
#> DT1 7 11 dead.wood time
#> DT2 10 13 dead.wood time
#> DT3 5 13 dead.wood time
#> LQ1 5 34 litter quadrat
#> LQ2 5 17 litter quadrat
#> LQ3 7 82 litter quadrat
#> LT1 0 0 litter time
#> LT2 2 2 litter time
#> LT3 5 10 litter time
#> RQ1 10 23 rock quadrat
#> RQ2 16 97 rock quadrat
#> RQ3 13 63 rock quadrat
#> RT1 11 44 rock time
#> RT2 15 47 rock time
#> RT3 10 30 rock time
#> WQ1 9 48 live.wood quadrat
#> WQ2 10 90 live.wood quadrat
#> WQ3 8 24 live.wood quadrat
#> WT1 5 5 live.wood time
#> WT2 4 6 live.wood time
#> WT3 3 6 live.wood time
mss(x)
#> s.rich s.abu microhab method
#> DQ1 5 18 dead.wood quadrat
#> DQ2 7 39 dead.wood quadrat
#> DQ3 4 9 dead.wood quadrat
#> DT1 7 11 dead.wood time
#> DT2 10 13 dead.wood time
#> DT3 5 13 dead.wood time
#> LQ1 5 34 litter quadrat
#> LQ2 5 17 litter quadrat
#> LQ3 7 82 litter quadrat
#> LT1 0 0 litter time
#> LT2 2 2 litter time
#> LT3 5 10 litter time
#> RQ1 10 23 rock quadrat
#> RQ2 16 97 rock quadrat
#> RQ3 13 63 rock quadrat
#> RT1 11 44 rock time
#> RT2 15 47 rock time
#> RT3 10 30 rock time
#> WQ1 9 48 live.wood quadrat
#> WQ2 10 90 live.wood quadrat
#> WQ3 8 24 live.wood quadrat
#> WT1 5 5 live.wood time
#> WT2 4 6 live.wood time
#> WT3 3 6 live.wood time
## Return only two species
as.data.frame(x, fun = msr, c("iiso", "ppyg"))
#> aacu amin apur bbip bcan ccer clam cort ctri dbre dper druf eful estr ffau
#> DQ1 0 4 0 0 0 0 0 0 2 0 2 0 0 1 0
#> DQ2 0 4 1 0 0 0 0 0 20 0 2 2 0 0 0
#> DQ3 0 3 1 0 0 0 0 0 0 0 0 0 0 0 0
#> DT1 0 1 0 0 1 0 0 0 0 0 1 0 0 1 0
#> DT2 0 2 1 1 0 0 2 0 0 0 1 1 0 1 0
#> DT3 0 3 0 1 0 0 0 0 0 0 0 0 0 0 0
#> LQ1 1 3 0 0 0 0 0 0 0 0 1 0 0 0 1
#> LQ2 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0
#> LQ3 0 2 1 1 0 1 0 0 0 0 7 0 0 0 0
#> LT1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> LT2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> LT3 0 5 0 0 0 0 0 0 0 0 1 0 0 0 0
#> RQ1 0 3 0 0 0 1 1 1 0 0 3 0 0 0 2
#> RQ2 0 7 0 4 0 0 0 0 7 1 6 0 0 3 2
#> RQ3 2 13 0 1 0 0 0 0 10 3 6 0 2 0 2
#> RT1 0 4 0 3 0 2 0 1 0 0 1 0 0 0 7
#> RT2 0 1 2 3 1 0 0 1 1 0 2 0 0 4 12
#> RT3 0 5 1 5 0 0 1 0 0 0 0 0 0 0 6
#> WQ1 0 3 0 1 1 0 0 3 0 0 0 0 0 0 0
#> WQ2 0 4 0 1 0 1 0 0 0 0 20 0 0 2 0
#> WQ3 0 10 0 3 0 0 0 0 0 0 0 0 0 1 2
#> WT1 0 1 0 0 0 0 0 1 0 0 0 0 0 1 1
#> WT2 0 2 1 1 0 0 0 0 0 0 2 0 0 0 0
#> WT3 0 4 0 0 0 0 0 0 0 0 0 0 0 0 1
#> hobv iiso mbor mobs odol ogla pinc ppyg pvic tuni vcos vicr vidi microhab
#> DQ1 0 0 0 0 0 0 0 0 0 0 0 0 9 dead.wood
#> DQ2 0 0 0 0 0 0 0 1 0 0 0 0 9 dead.wood
#> DQ3 3 0 0 0 0 0 0 0 0 0 0 0 2 dead.wood
#> DT1 1 0 5 0 0 0 0 0 1 0 0 0 0 dead.wood
#> DT2 1 0 0 0 0 0 0 0 0 1 0 0 2 dead.wood
#> DT3 6 0 0 0 0 0 0 0 1 0 0 0 2 dead.wood
#> LQ1 0 0 0 0 0 0 0 28 0 0 0 0 0 litter
#> LQ2 0 0 0 0 0 0 0 13 1 0 0 0 0 litter
#> LQ3 0 0 0 0 0 0 0 69 1 0 0 0 0 litter
#> LT1 0 0 0 0 0 0 0 0 0 0 0 0 0 litter
#> LT2 0 0 0 0 0 0 0 0 1 0 0 0 0 litter
#> LT3 0 0 0 0 0 0 1 0 1 2 0 0 0 litter
#> RQ1 2 0 0 0 0 1 0 5 0 0 0 0 4 rock
#> RQ2 9 0 0 2 13 3 0 28 1 2 2 0 7 rock
#> RQ3 2 0 0 1 0 0 0 9 1 0 0 0 11 rock
#> RT1 8 6 0 0 0 0 3 0 4 5 0 0 0 rock
#> RT2 1 8 0 0 0 0 5 0 1 3 0 0 2 rock
#> RT3 4 1 0 0 0 0 3 0 3 1 0 0 0 rock
#> WQ1 0 2 0 0 0 0 2 31 1 0 0 0 4 live.wood
#> WQ2 0 0 0 2 0 0 1 56 1 2 0 0 0 live.wood
#> WQ3 0 0 0 0 0 0 1 5 0 0 0 1 1 live.wood
#> WT1 0 0 0 0 0 0 0 0 0 1 0 0 0 live.wood
#> WT2 0 0 0 0 0 0 0 0 0 0 0 0 0 live.wood
#> WT3 0 0 0 0 0 0 0 0 0 0 0 0 1 live.wood
#> method NA
#> DQ1 quadrat iiso
#> DQ2 quadrat ppyg
#> DQ3 quadrat iiso
#> DT1 time ppyg
#> DT2 time iiso
#> DT3 time ppyg
#> LQ1 quadrat iiso
#> LQ2 quadrat ppyg
#> LQ3 quadrat iiso
#> LT1 time ppyg
#> LT2 time iiso
#> LT3 time ppyg
#> RQ1 quadrat iiso
#> RQ2 quadrat ppyg
#> RQ3 quadrat iiso
#> RT1 time ppyg
#> RT2 time iiso
#> RT3 time ppyg
#> WQ1 quadrat iiso
#> WQ2 quadrat ppyg
#> WQ3 quadrat iiso
#> WT1 time ppyg
#> WT2 time iiso
#> WT3 time ppyg
## Taxa table and summary
as.data.frame(x, fun = mts)
#> t.occ t.abu species author
#> aacu 3 4 Acanthinula aculeata (O. F. Muller, 1774)
#> amin 23 86 Aegopinella minor (Stabile, 1864)
#> apur 7 8 Aegopinella pura (Alder, 1830)
#> bbip 12 25 Balea biplicata (Montagu, 1803)
#> bcan 3 3 Bulgarica cana (Held, 1836)
#> ccer 4 5 Cochlodina cerata (Rossmassler, 1836)
#> clam 3 4 Cochlodina laminata (Montagu, 1803)
#> cort 5 7 Cochlodina orthostoma (Menke, 1830)
#> ctri 5 40 Carychium tridentatum (Risso, 1826)
#> dbre 2 4 Daudebardia brevipes (Draparnaud, 1805)
#> dper 15 56 Discus perspectivus (Megerle von Muhlfeld, 1816)
#> druf 2 3 Daudebardia rufa (Draparnaud, 1805)
#> eful 1 2 Euconulus fulvus (O. F. Muller, 1774)
#> estr 8 14 Euomphalia strigella (Draparnaud, 1801)
#> ffau 10 36 Chilostoma faustinum (Rossmassler, 1835)
#> hobv 10 37 Helicodonta obvoluta (O. F. Muller, 1774)
#> iiso 4 17 Isognomostoma isognomostomos (Schroter, 1784)
#> mbor 1 5 Macrogastra latestriata (A. Schmidt, 1857)
#> mobs 3 5 Ena obscura (O. F. Muller, 1774)
#> odol 1 13 Orcula dolium (Draparnaud, 1801)
#> ogla 2 4 Oxychilus glaber (Rossmassler, 1838)
#> pinc 7 16 Perforatella incarnata (O. F. Muller, 1774)
#> ppyg 10 245 Punctum pygmaeum (Draparnaud, 1801)
#> pvic 13 18 Perforatella vicina (Rossmassler, 1842)
#> tuni 8 17 Trichia unidentata (Draparnaud, 1805)
#> vcos 1 2 Vallonia costata (O. F. Muller, 1774)
#> vicr 1 1 Vitrea crystallina (O. F. Muller, 1774)
#> vidi 12 54 Vitrea diaphana (Studer, 1820)
#> familia size
#> aacu Valloniidae 2.0
#> amin Zonitidae 9.0
#> apur Zonitidae 5.0
#> bbip Clausiliidae 18.0
#> bcan Clausiliidae 18.0
#> ccer Clausiliidae 18.0
#> clam Clausiliidae 17.0
#> cort Clausiliidae 13.0
#> ctri Ellobiidae 2.3
#> dbre Zonitidae NA
#> dper Endodontidae 6.5
#> druf Zonitidae NA
#> eful Euconulidae 3.5
#> estr Helicidae 18.0
#> ffau Helicidae 20.0
#> hobv Helicidae 15.0
#> iiso Helicidae 11.0
#> mbor Clausiliidae 15.0
#> mobs Enidae 9.0
#> odol Orculidae 9.0
#> ogla Zonitidae 14.0
#> pinc Helicidae 16.0
#> ppyg Endodontidae 1.5
#> pvic Helicidae 15.5
#> tuni Helicidae 8.0
#> vcos Valloniidae 2.7
#> vicr Zonitidae 4.0
#> vidi Zonitidae 4.2
## Taxa table and raw data transpose
as.data.frame(x, fun = mtr)
#> DQ1 DQ2 DQ3 DT1 DT2 DT3 LQ1 LQ2 LQ3 LT1 LT2 LT3 RQ1 RQ2 RQ3 RT1 RT2 RT3
#> aacu 0 0 0 0 0 0 1 1 0 0 0 0 0 0 2 0 0 0
#> amin 4 4 3 1 2 3 3 1 2 0 1 5 3 7 13 4 1 5
#> apur 0 1 1 0 1 0 0 0 1 0 0 0 0 0 0 0 2 1
#> bbip 0 0 0 0 1 1 0 0 1 0 0 0 0 4 1 3 3 5
#> bcan 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0
#> ccer 0 0 0 0 0 0 0 0 1 0 0 0 1 0 0 2 0 0
#> clam 0 0 0 0 2 0 0 0 0 0 0 0 1 0 0 0 0 1
#> cort 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0
#> ctri 2 20 0 0 0 0 0 0 0 0 0 0 0 7 10 0 1 0
#> dbre 0 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0
#> dper 2 2 0 1 1 0 1 1 7 0 0 1 3 6 6 1 2 0
#> druf 0 2 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0
#> eful 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0
#> estr 1 0 0 1 1 0 0 0 0 0 0 0 0 3 0 0 4 0
#> ffau 0 0 0 0 0 0 1 0 0 0 0 0 2 2 2 7 12 6
#> hobv 0 0 3 1 1 6 0 0 0 0 0 0 2 9 2 8 1 4
#> iiso 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 8 1
#> mbor 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> mobs 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0
#> odol 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 0 0
#> ogla 0 0 0 0 0 0 0 0 0 0 0 0 1 3 0 0 0 0
#> pinc 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 3 5 3
#> ppyg 0 1 0 0 0 0 28 13 69 0 0 0 5 28 9 0 0 0
#> pvic 0 0 0 1 0 1 0 1 1 0 1 1 0 1 1 4 1 3
#> tuni 0 0 0 0 1 0 0 0 0 0 0 2 0 2 0 5 3 1
#> vcos 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0
#> vicr 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#> vidi 9 9 2 0 2 2 0 0 0 0 0 0 4 7 11 0 2 0
#> WQ1 WQ2 WQ3 WT1 WT2 WT3 species
#> aacu 0 0 0 0 0 0 Acanthinula aculeata
#> amin 3 4 10 1 2 4 Aegopinella minor
#> apur 0 0 0 0 1 0 Aegopinella pura
#> bbip 1 1 3 0 1 0 Balea biplicata
#> bcan 1 0 0 0 0 0 Bulgarica cana
#> ccer 0 1 0 0 0 0 Cochlodina cerata
#> clam 0 0 0 0 0 0 Cochlodina laminata
#> cort 3 0 0 1 0 0 Cochlodina orthostoma
#> ctri 0 0 0 0 0 0 Carychium tridentatum
#> dbre 0 0 0 0 0 0 Daudebardia brevipes
#> dper 0 20 0 0 2 0 Discus perspectivus
#> druf 0 0 0 0 0 0 Daudebardia rufa
#> eful 0 0 0 0 0 0 Euconulus fulvus
#> estr 0 2 1 1 0 0 Euomphalia strigella
#> ffau 0 0 2 1 0 1 Chilostoma faustinum
#> hobv 0 0 0 0 0 0 Helicodonta obvoluta
#> iiso 2 0 0 0 0 0 Isognomostoma isognomostomos
#> mbor 0 0 0 0 0 0 Macrogastra latestriata
#> mobs 0 2 0 0 0 0 Ena obscura
#> odol 0 0 0 0 0 0 Orcula dolium
#> ogla 0 0 0 0 0 0 Oxychilus glaber
#> pinc 2 1 1 0 0 0 Perforatella incarnata
#> ppyg 31 56 5 0 0 0 Punctum pygmaeum
#> pvic 1 1 0 0 0 0 Perforatella vicina
#> tuni 0 2 0 1 0 0 Trichia unidentata
#> vcos 0 0 0 0 0 0 Vallonia costata
#> vicr 0 0 1 0 0 0 Vitrea crystallina
#> vidi 4 0 1 0 0 1 Vitrea diaphana
#> author familia size
#> aacu (O. F. Muller, 1774) Valloniidae 2.0
#> amin (Stabile, 1864) Zonitidae 9.0
#> apur (Alder, 1830) Zonitidae 5.0
#> bbip (Montagu, 1803) Clausiliidae 18.0
#> bcan (Held, 1836) Clausiliidae 18.0
#> ccer (Rossmassler, 1836) Clausiliidae 18.0
#> clam (Montagu, 1803) Clausiliidae 17.0
#> cort (Menke, 1830) Clausiliidae 13.0
#> ctri (Risso, 1826) Ellobiidae 2.3
#> dbre (Draparnaud, 1805) Zonitidae NA
#> dper (Megerle von Muhlfeld, 1816) Endodontidae 6.5
#> druf (Draparnaud, 1805) Zonitidae NA
#> eful (O. F. Muller, 1774) Euconulidae 3.5
#> estr (Draparnaud, 1801) Helicidae 18.0
#> ffau (Rossmassler, 1835) Helicidae 20.0
#> hobv (O. F. Muller, 1774) Helicidae 15.0
#> iiso (Schroter, 1784) Helicidae 11.0
#> mbor (A. Schmidt, 1857) Clausiliidae 15.0
#> mobs (O. F. Muller, 1774) Enidae 9.0
#> odol (Draparnaud, 1801) Orculidae 9.0
#> ogla (Rossmassler, 1838) Zonitidae 14.0
#> pinc (O. F. Muller, 1774) Helicidae 16.0
#> ppyg (Draparnaud, 1801) Endodontidae 1.5
#> pvic (Rossmassler, 1842) Helicidae 15.5
#> tuni (Draparnaud, 1805) Helicidae 8.0
#> vcos (O. F. Muller, 1774) Valloniidae 2.7
#> vicr (O. F. Muller, 1774) Zonitidae 4.0
#> vidi (Studer, 1820) Zonitidae 4.2
## Why is it useful?
## Instead of
glm(x$xtab[,"amin"] ~ microhab + method, data = x$samp, family = poisson)
#>
#> Call: glm(formula = x$xtab[, "amin"] ~ microhab + method, family = poisson,
#> data = x$samp)
#>
#> Coefficients:
#> (Intercept) microhablitter microhablive.wood microhabrock
#> 0.6475 -0.3483 0.3448 0.6633
#> methodquadrat
#> 0.6758
#>
#> Degrees of Freedom: 23 Total (i.e. Null); 19 Residual
#> Null Deviance: 49.38
#> Residual Deviance: 28.51 AIC: 107
## it is more convenient to use
glm(amin ~ microhab + method, data = msr(x), family = poisson)
#>
#> Call: glm(formula = amin ~ microhab + method, family = poisson, data = msr(x))
#>
#> Coefficients:
#> (Intercept) microhablitter microhablive.wood microhabrock
#> 0.6475 -0.3483 0.3448 0.6633
#> methodquadrat
#> 0.6758
#>
#> Degrees of Freedom: 23 Total (i.e. Null); 19 Residual
#> Null Deviance: 49.38
#> Residual Deviance: 28.51 AIC: 107