Produces a `ggplot2`

variant of a so-called biplot for PCA (principal component analysis), but is more flexible and more appealing than the base R `biplot()`

function.

```
ggplot_pca(
x,
choices = 1:2,
scale = 1,
pc.biplot = TRUE,
labels = NULL,
labels_textsize = 3,
labels_text_placement = 1.5,
groups = NULL,
ellipse = TRUE,
ellipse_prob = 0.68,
ellipse_size = 0.5,
ellipse_alpha = 0.5,
points_size = 2,
points_alpha = 0.25,
arrows = TRUE,
arrows_colour = "darkblue",
arrows_size = 0.5,
arrows_textsize = 3,
arrows_textangled = TRUE,
arrows_alpha = 0.75,
base_textsize = 10,
...
)
```

x | an object returned by |
---|---|

choices | length 2 vector specifying the components to plot. Only the default is a biplot in the strict sense. |

scale | The variables are scaled by |

pc.biplot | If true, use what Gabriel (1971) refers to as a "principal component
biplot", with |

labels | an optional vector of labels for the observations. If set, the labels will be placed below their respective points. When using the |

labels_textsize | the size of the text used for the labels |

labels_text_placement | adjustment factor the placement of the variable names ( |

groups | an optional vector of groups for the labels, with the same length as |

ellipse | a logical to indicate whether a normal data ellipse should be drawn for each group (set with |

ellipse_prob | statistical size of the ellipse in normal probability |

ellipse_size | the size of the ellipse line |

ellipse_alpha | the alpha (transparency) of the ellipse line |

points_size | the size of the points |

points_alpha | the alpha (transparency) of the points |

arrows | a logical to indicate whether arrows should be drawn |

arrows_colour | the colour of the arrow and their text |

arrows_size | the size (thickness) of the arrow lines |

arrows_textsize | the size of the text at the end of the arrows |

arrows_textangled | a logical whether the text at the end of the arrows should be angled |

arrows_alpha | the alpha (transparency) of the arrows and their text |

base_textsize | the text size for all plot elements except the labels and arrows |

... | arguments passed on to functions |

The `ggplot_pca()`

function is based on the `ggbiplot()`

function from the `ggbiplot`

package by Vince Vu, as found on GitHub: https://github.com/vqv/ggbiplot (retrieved: 2 March 2020, their latest commit: `7325e88`

; 12 February 2015).

As per their GPL-2 licence that demands documentation of code changes, the changes made based on the source code were:

Rewritten code to remove the dependency on packages

`plyr`

,`scales`

and`grid`

Parametrised more options, like arrow and ellipse settings

Hardened all input possibilities by defining the exact type of user input for every argument

Added total amount of explained variance as a caption in the plot

Cleaned all syntax based on the

`lintr`

package, fixed grammatical errors and added integrity checksUpdated documentation

The colours for labels and points can be changed by adding another scale layer for colour, such as `scale_colour_viridis_d()`

and `scale_colour_brewer()`

.

The lifecycle of this function is **stable**. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.

If the unlying code needs breaking changes, they will occur gradually. For example, a argument will be deprecated and first continue to work, but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.

```
# `example_isolates` is a data set available in the AMR package.
# See ?example_isolates.
# See ?pca for more info about Principal Component Analysis (PCA).
# \donttest{
if (require("dplyr")) {
pca_model <- example_isolates %>%
filter(mo_genus(mo) == "Staphylococcus") %>%
group_by(species = mo_shortname(mo)) %>%
summarise_if (is.rsi, resistance) %>%
pca(FLC, AMC, CXM, GEN, TOB, TMP, SXT, CIP, TEC, TCY, ERY)
# old (base R)
biplot(pca_model)
# new
ggplot_pca(pca_model)
if (require("ggplot2")) {
ggplot_pca(pca_model) +
scale_colour_viridis_d() +
labs(title = "Title here")
}
}
# }
```