lets_plot.scale_shape_identity#
- lets_plot.scale_shape_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 https://lets-plot.org/python/pages/formats.html.
- Returns:
- FeatureSpec
Scale specification.
Notes
Input data expected: numeric codes of shapes.
Examples
1from lets_plot import * 2LetsPlot.setup_html() 3n, m = 26, 6 4x = [i % m for i in range(n)] 5y = [int(i / m) for i in range(n)] 6s = list(range(n)) 7ggplot({'x': x, 'y': y, 's': s}, aes('x', 'y')) + \ 8 geom_point(aes(shape='s'), size=10, show_legend=False, \ 9 color='#2166ac', fill='#fddbc7', \ 10 tooltips=layer_tooltips().line('shape #@s')) + \ 11 scale_shape_identity()