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Optionally evaluate code chunks that use DiagrammeR #603

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Jan 16, 2024
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Optionally evaluate code chunks that use DiagrammeR #603

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8 changes: 5 additions & 3 deletions vignettes/get_started.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,8 @@ if (!file.exists("figures"))

file.copy("../man/figures/plotlegend.png",
"figures/plotlegend.png")

diagrammer_installed <- requireNamespace("DiagrammeR", quietly = TRUE)
```

## Installation
Expand Down Expand Up @@ -384,7 +386,7 @@ greta provides a plot function for greta models to help you visualise and check
```{r plot, eval = FALSE}
plot(m)
```
```{r plot_hidden, echo = FALSE}
```{r plot_hidden, echo = FALSE, eval = diagrammer_installed}
gr <- plot(m)
DiagrammeR::export_graph(attr(gr, "dgr_graph"),
file_name = "figures/full_graph.png",
Expand All @@ -405,7 +407,7 @@ The fourth type of node (diamonds) represents probability distributions. These h

For example, a plot of just the prior distribution over `coef` (defined as `coef <- normal(0, 3)`) shows the parameters as data leading into the normal distribution, and a dashed arrow leading out to the distribution's value, the variable `coef`:

```{r plot_coef, echo = FALSE}
```{r plot_coef, echo = FALSE, eval = diagrammer_installed}
coef <- normal(0, 3)
m_coef <- model(coef)
gr <- plot(m_coef)
Expand All @@ -419,7 +421,7 @@ DiagrammeR::export_graph(attr(gr, "dgr_graph"),

It's the same for the model likelihood, but this time the distribution's parameters are a variable (`sd`) and the result of an operation (`mean`), and the distribution's value is given by data (the observed sepal lengths `y`):

```{r plot_likelihood, echo = FALSE}
```{r plot_likelihood, echo = FALSE, eval = diagrammer_installed}
sd <- variable()
y <- as_data(iris$Sepal.Length)
mean <- ones(150)
Expand Down
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