plotnine.scales.scale_alpha_manual

class plotnine.scales.scale_alpha_manual(values, **kwargs)

Custom discrete alpha scale

Parameters:

valuesarray_like | dict

Alpha values (in the [0, 1] range) that make up the palette. The values will be matched with the limits of the scale or the breaks if provided. If it is a dict then it should map data values to alpha values.

breaksarray_like or callable(), optional

Major break points. Alternatively, a callable that takes a tuple of limits and returns a list of breaks. Default is to automatically calculate the breaks.

expandtuple, optional

Multiplicative and additive expansion constants that determine how the scale is expanded. If specified must be of length 2 or 4. Specifically the values are in this order:

(mul, add)
(mul_low, add_low, mul_high, add_high)

For example,

• (0, 0) - Do not expand.

• (0, 1) - Expand lower and upper limits by 1 unit.

• (1, 0) - Expand lower and upper limits by 100%.

• (0, 0, 0, 0) - Do not expand, as (0, 0).

• (0, 0, 0, 1) - Expand upper limit by 1 unit.

• (0, 1, 0.1, 0) - Expand lower limit by 1 unit and upper limit by 10%.

• (0, 0, 0.1, 2) - Expand upper limit by 10% plus 2 units.

If not specified, suitable defaults are chosen.

namestr, optional

Name used as the label of the scale. This is what shows up as the axis label or legend title. Suitable defaults are chosen depending on the type of scale.

labelslist or callable(), optional

List of str. Labels at the breaks. Alternatively, a callable that takes an array_like of break points as input and returns a list of strings.

palettecallable(), optional

Function to map data points onto the scale. Most scales define their own palettes.

aestheticslist, optional

list of str. Aesthetics covered by the scale. These are defined by each scale and the user should probably not change them. Have fun.

limitsarray_like, optional

Limits of the scale. For scales that deal with categoricals, these may be a subset or superset of the categories. Data values that are not in the limits will be treated as missing data and represented with the na_value.

dropbool

Whether to drop unused categories from the scale

na_translatebool

If True translate missing values and show them. If False remove missing values. Default value is True

na_valueobject

If na_translate=True, what aesthetic value should be assigned to the missing values. This parameter does not apply to position scales where nan is always placed on the right.