lets_plot.scale_alpha_identity

lets_plot.scale_alpha_identity(name=None, breaks=None, labels=None, limits=None, na_value=None, guide='none', format=None)

Use this scale when your data has already been scaled. I.e. it already represents aesthetic values that ggplot2 can handle directly. This will not produce a legend unless you also supply the breaks and labels.

Parameters
namestr

The name of the scale - used as the axis label or the legend title.

breakslist of float

A numeric vector of positions (of ticks).

labelslist of str

A vector of labels (on ticks).

limitslist

Continuous scale: a numeric vector of length two providing limits of the scale. Discrete scale: a vector specifying the data range for the scale and the default order of their display in guides.

guide, default=’none’

Guide to use for this scale. Defaults to ‘none’.

formatstr

Defines the format for labels on the scale. The syntax resembles Python’s: ‘.2f’ -> ‘12.45’ ‘Num {}’ -> ‘Num 12.456789’ ‘TTL: {.2f}$’ -> ‘TTL: 12.45$’ For more info see https://lets-plot.org/pages/formats.html.

Returns
FeatureSpec

Scale specification.

Notes

Input data expected: numeric values in range [0, 1].

Examples

 1import numpy as np
 2from lets_plot import *
 3LetsPlot.setup_html()
 4n = 100
 5np.random.seed(42)
 6x = np.random.normal(size=n)
 7y = np.random.normal(size=n)
 8a = np.random.uniform(0, .5, size=n)
 9ggplot({'x': x, 'y': y, 'a': a}, aes('x', 'y')) + \
10    geom_point(aes(alpha='a'), shape=21, size=10) + \
11    scale_alpha_identity(limits=[.2, .5], breaks=[.2, .3, .4, .5])