These functions are what underpins the ability of certain geoms to work
automatically in both directions. See the Extending ggplot2 vignette for
how they are used when implementing
has_flipped_aes( data, params = list(), main_is_orthogonal = NA, range_is_orthogonal = NA, group_has_equal = FALSE, ambiguous = FALSE, main_is_continuous = FALSE, main_is_optional = FALSE ) flip_data(data, flip = NULL) flipped_names(flip = FALSE)
The layer data
The parameters of the
Is it expected that grouped data has either a single
Is the layer ambiguous in its mapping by nature. If so, it
will only be flipped if
If there is a discrete and continuous axis, does the continuous one correspond to the main orientation?
Is the main axis aesthetic optional and, if not
given, set to
Logical. Is the layer flipped.
has_flipped_aes() is used to sniff out the orientation of the layer from
the data. It has a range of arguments that can be used to finetune the
sniffing based on what the data should look like.
flip_data() will switch
the column names of the data so that it looks like x-oriented data.
flipped_names() provides a named list of aesthetic names that corresponds
to the orientation of the layer.
TRUE if it detects a layer in the other
flip_data() will return the input
flip = FALSE and the data with flipped aesthetic names if
flip = TRUE.
flipped_names() returns a named list of strings. If
flip = FALSE the name of the element will correspond to the element, e.g.
flipped_names(FALSE)$x == "x" and if
flip = TRUE it will correspond to
the flipped name, e.g.
flipped_names(FALSE)$x == "y"
How the layer data should be interpreted depends on its specific features.
has_flipped_aes() contains a range of flags for defining what certain
features in the data correspond to:
main_is_orthogonal: This argument controls how the existence of only a
y aesthetic is understood. If
TRUE then the exisiting aesthetic
would be then secondary axis. This behaviour is present in
FALSE then the exisiting aesthetic is the main
axis as seen in e.g.
range_is_orthogonal: This argument controls whether the existance of
range-like aesthetics (e.g.
xmax) represents the main or
secondary axis. If
TRUE then the range is given for the secondary axis as
seen in e.g.
group_has_equal: This argument controls whether to test for equality of
y values inside each group and set the main axis to the one
where all is equal. This test is only performed if
TRUE, and only after
less computationally heavy tests has come up empty handed. Examples are
stat_boxplot() and stat_ydensity
ambiguous: This argument tells the function that the layer, while
bidirectional, doesn't treat each axis differently. It will circumvent any
data based guessing and only take hint from the
orientation element in
params. If this is not present it will fall back to
FALSE. Examples are
main_is_continuous: This argument controls how the test for discreteness
in the scales should be interpreted. If
TRUE then the main axis will be
the one which is not discrete-like. Conversely, if
FALSE the main axis
will be the discrete-like one. Examples of
stat_bin(), while examples of
main_is_optional: This argument controls the rare case of layers were the
main direction is an optional aesthetic. This is only seen in
x is set to
0 if not given. If
TRUE there will
be a check for whether all
x or all
y are equal to
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