Fortify Rényi accumulation curves

Prepares a fortified version of results from vegan::renyiaccum() objects.

Usage

# S3 method for class 'renyiaccum'
fortify(model, data, ...)

# S3 method for class 'renyiaccum'
tidy(x, data, ...)

Arguments

model, x

an object of class vegan::renyiaccum().

data

original data set. Currently ignored.

...

additional arguments passed to other methods. Ignored in this method.

Value

A data frame (tibble) is returned. What is returned depends on how vegan::renyiaccum() was called. If raw = FALSE, then a data frame with columns site, scale, mean, std_dev, min, max, q2.5, and q97.5, containing the accumulated sites, the Rényi scale, and summary statistics of the Rényi accumulation curves. An additional column collector will be present if collector = TRUE was used in the vegan::renyiaccum() call. If raw = TRUE, then a data frame with columns site, permutation, scale, and diversity, containing the site and permutation identifiers, Rényi scale, and the Rényi diversity, respectively.

Author

Gavin L. Simpson much rewritten from an original by Didzis Elferts.

Examples

library("vegan")
library("ggplot2")
data(BCI)
pool <- renyiaccum(BCI)
df <- fortify(pool)
df
#> # A tibble: 300 × 8
#>     site scale  mean std_dev   min   max  q2.5 q97.5
#>    <int> <chr> <dbl>   <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1     1 0      4.50  0.0767  4.34  4.69  4.36  4.67
#>  2     2 0      4.80  0.0641  4.63  4.92  4.65  4.91
#>  3     3 0      4.93  0.0484  4.75  5.02  4.83  5.01
#>  4     4 0      5.01  0.0387  4.90  5.09  4.93  5.08
#>  5     5 0      5.07  0.0348  4.98  5.14  4.99  5.12
#>  6     6 0      5.11  0.0324  5.02  5.18  5.04  5.16
#>  7     7 0      5.14  0.0287  5.06  5.20  5.08  5.19
#>  8     8 0      5.17  0.0279  5.09  5.24  5.11  5.21
#>  9     9 0      5.19  0.0269  5.11  5.26  5.13  5.23
#> 10    10 0      5.21  0.0258  5.14  5.28  5.15  5.25
#> # ℹ 290 more rows

ggplot(df, aes(x = site, y = mean)) +
    geom_ribbon(aes(ymin = q2.5, ymax = q97.5, x = site),
                alpha = 0.2, inherit.aes = FALSE) +
    geom_line() +
    facet_wrap(~ scale)