R/README.md

In mysteryduck/ggrdiversity: Provides plotting functions for the package rdiversity

ggrdiversity

Plotting diversity

All of these results are output as rdiv objects, which can be visualised using the plot() function. For example:

```{r} component <- norm_alpha(meta)

Normalised subcommunity alpha

sc <- subdiv(component, 0:10) plot(sc)

![](./man/figures/README-example-1.png)

```{r}
# Normalised metacommunity alpha
mc <- metadiv(component, 0:10)
plot(mc)

# All subcommunity measures
all <- subdiv(meta, 0:10)
plot(all)

The function rdiv() can be used to transform data.frame and list objects into rdiv objects ready for plotting. This function is useful when generating plots containing both the subcommunity- and metacommunity-level diversities, or when only certain measures are of interest. For example:

```{r} combine <- rbind.data.frame(sc, mc) res1 <- rdiv(combine)

or...

combine <- list(sc, mc) res1 <- rdiv(combine)

plot(res1)

![](./man/figures/README-example-4.png)

```{r}
alpha <- norm_sub_alpha(meta, 0:10)
rho <- norm_sub_rho(meta, 0:10)

res2 <- rdiv(list(alpha, rho))

plot(res2)

If diversity is calculated for q=Inf is calculated, q is transformed on a log scale. For example:

```{r} qs <- c(seq(0,1,.1),2:10, seq(20,100,10),Inf) res3 <- norm_sub_alpha(meta, qs)

plot(res3)

![](./man/figures/README-example-6.png)

Note that in the above example, *q=0*, *q=1*, *q=2*, and *q=Inf* are highlighted as important, corresponding to Species Richness, Shannon, Simpson, and Berger Parker diversity, respecively.

In some cases, it might also be useful to examine the species-level components, which is done in the following way:

  ```{r}
# Or we can look at the individual species-level components
ind <- inddiv(component, c(seq(0,1,.1),2:10, seq(20,100,10),Inf))

plot(ind)

Note that generally defined as types or any biologically meaningful unit)

mysteryduck/ggrdiversity documentation built on May 9, 2019, 2:59 p.m.