scale_size_identity#

scale_size_identity(name=None, breaks=None, labels=None, lablim=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 the library 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 or dict

A list of data values specifying the positions of ticks, or a dictionary which maps the tick labels to the breaks values.

labelslist of str or dict

A list of labels on ticks, or a dictionary which maps the breaks values to the tick labels.

lablimint, default=None

The maximum label length (in characters) before trimming is applied.

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.

formatstr

Define 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 Formatting.

Returns:
FeatureSpec

Scale specification.

Notes

Input data expected: positive numeric values.

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)
 8w = np.random.choice([8, 10, 12], size=n)
 9ggplot({'x': x, 'y': y, 'w': w}, aes('x', 'y')) + \
10    geom_point(aes(size='w'), shape=21, alpha=.2) + \
11    scale_size_identity()
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