Render tick marks for axes

geom_axis_ticks() renders tick marks for specified axes among the row or column factors.

geom_axis_ticks(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  subset = NULL,
  by = NULL,
  num = NULL,
  tick_length = 0.025,
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping	Set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.
data	The data to be displayed in this layer. There are three options: If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot(). A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created. A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).
stat	The statistical transformation to use on the data for this layer, as a string.
position	Position adjustment, either as a string, or the result of a call to a position adjustment function.
subset	Indices or logical vector of rows or columns for which to render elements.
by	Intervals between elements or number of elements; specify only one.
num	Intervals between elements or number of elements; specify only one.
tick_length	Numeric; the length of the tick marks, as a proportion of the minimum of the plot width and height.
...	Additional arguments passed to ggplot2::layer().
na.rm	Passed to ggplot2::layer().
show.legend	logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display.
inherit.aes	If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. borders().

Biplot layers

ggbiplot() uses ggplot2::fortify() internally to produce a single data frame with a .matrix column distinguishing the subjects ("rows") and variables ("cols"). The stat layers stat_rows() and stat_cols() simply filter the data frame to one of these two.

The geom layers geom_rows_*() and geom_cols_*() call the corresponding stat in order to render plot elements for the corresponding factor matrix. geom_dims_*() selects a default matrix based on common practice, e.g. points for rows and arrows for columns.

Aesthetics

geom_axis_ticks() understands the following aesthetics (required aesthetics are in bold):

• x

• y

• alpha

• colour

• linetype

• size

• group

• center (for un-scaling)

• scale (for un-scaling)

See also

Other geom layers: geom_axis_label(), geom_axis_text(), geom_axis(), geom_isolines_text(), geom_isolines(), geom_lineranges(), geom_origin(), geom_text_radiate(), geom_unit_circle(), geom_vector()

Examples

# Reaven & Miller overt & chemical diabetes test data and group classification
head(heplots::Diabetes)
#>   relwt glufast glutest instest sspg  group
#> 1  0.81      80     356     124   55 Normal
#> 2  0.95      97     289     117   76 Normal
#> 3  0.94     105     319     143  105 Normal
#> 4  1.04      90     356     199  108 Normal
#> 5  1.00      90     323     240  143 Normal
#> 6  0.76      86     381     157  165 Normal
# default (standardized) linear discriminant analysis of groups on tests
diabetes_lda <- MASS::lda(group ~ ., heplots::Diabetes)
# bestow 'tbl_ord' class & augment observation, centroid, and variable fields
as_tbl_ord(diabetes_lda) %>%
  augment_ord() %>%
  mutate_rows(discriminant = ifelse(! .supplement, "centroid", "case")) %>%
  print() -> diabetes_lda
#> # A tbl_ord of class 'lda': (148 x 2) x (5 x 2)'
#> # 2 coordinates: LD1 and LD2
#> # 
#> # Rows (principal): [ 148 x 2 | 6 ]
#>      LD1    LD2 |   .name    .prior .counts .grouping 
#>                 |   <chr>     <dbl>   <int> <chr>     
#> 1 -1.75   0.400 | 1 Normal    0.524      76 Normal    
#> 2  0.340 -1.38  | 2 Chemica…  0.248      36 Chemical_…
#> 3  3.66   0.580 | 3 Overt_D…  0.228      33 Overt_Dia…
#> 4 -1.72   0.663 | 4 1        NA          NA Normal    
#> 5 -2.85   1.30  | 5 2        NA          NA Normal    
#> # … with 143 more rows, and 2 more
#> #   variables: .supplement <lgl>,
#> #   discriminant <chr>
#> # 
#> # Columns (standard): [ 5 x 2 | 1 ]
#>         LD1      LD2 |   .name  
#>                      |   <chr>  
#> 1  1.36     -3.78    | 1 relwt  
#> 2 -0.0336    0.0366  | 2 glufast
#> 3  0.0126   -0.00709 | 3 glutest
#> 4 -0.000102 -0.00617 | 4 instest
#> 5  0.00424   0.00113 | 5 sspg   
# row-standard biplot
diabetes_lda %>%
  confer_inertia(1) %>%
  ggbiplot() +
  theme_bw() + theme_biplot() +
  geom_rows_point(aes(shape = .grouping, size = discriminant), alpha = .5) +
  geom_cols_axis(color = "#888888") +
  geom_cols_axis_ticks(num = 8L) +
  geom_cols_axis_text(size = 2.5, num = 8L, label_dodge = .2) +
  geom_cols_axis_label(aes(label = .name)) +
  ggtitle(
    "LDA of Reaven & Miller diabetes groups",
    "Row-standard biplot of standardized LDA"
  )
#> Warning: Ignoring unknown aesthetics: label
#> Warning: Using size for a discrete variable is not advised.
# contribution LDA of groups on tests
diabetes_lda <-
  lda_ord(group ~ ., heplots::Diabetes, axes.scale = "contribution")
# bestow 'tbl_ord' class & augment observation, centroid, and variable fields
as_tbl_ord(diabetes_lda) %>%
  augment_ord() %>%
  mutate_rows(discriminant = ifelse(! .supplement, "centroid", "case")) %>%
  print() -> diabetes_lda
#> # A tbl_ord of class 'lda_ord': (148 x 2) x (5 x 2)'
#> # 2 coordinates: LD1 and LD2
#> # 
#> # Rows (principal): [ 148 x 2 | 6 ]
#>      LD1    LD2 |   .name    .prior .counts .grouping 
#>                 |   <chr>     <dbl>   <int> <chr>     
#> 1 -1.75   0.400 | 1 Normal    0.524      76 Normal    
#> 2  0.340 -1.38  | 2 Chemica…  0.248      36 Chemical_…
#> 3  3.66   0.580 | 3 Overt_D…  0.228      33 Overt_Dia…
#> 4 -1.72   0.663 | 4 1        NA          NA Normal    
#> 5 -2.85   1.30  | 5 2        NA          NA Normal    
#> # … with 143 more rows, and 2 more
#> #   variables: .supplement <lgl>,
#> #   discriminant <chr>
#> # 
#> # Columns (standard): [ 5 x 2 | 1 ]
#>       LD1    LD2 |   .name  
#>                  |   <chr>  
#> 1  0.138  -0.384 | 1 relwt  
#> 2 -0.274   0.539 | 2 glufast
#> 3  0.861   0.288 | 3 glutest
#> 4 -0.0134 -0.666 | 4 instest
#> 5  0.388  -0.145 | 5 sspg   
# symmetric biplot
diabetes_lda %>%
  confer_inertia(.5) %>%
  ggbiplot() +
  theme_bw() + theme_biplot() +
  geom_rows_point(aes(shape = .grouping, alpha = discriminant)) +
  geom_cols_axis(color = "#888888") +
  geom_cols_axis_ticks(num = 8L) +
  geom_cols_axis_text(size = 2.5, num = 8L, label_dodge = .1) +
  ggtitle(
    "LDA of Reaven & Miller diabetes groups",
    "Symmetric biplot of contribution LDA"
  )
#> Warning: Using alpha for a discrete variable is not advised.