plotnine.scale_shape_identity

scale_shape_identity(
    *,
    name=None,
    breaks=True,
    limits=None,
    labels=True,
    expand=None,
    guide="legend",
    na_value=np.nan,
    aesthetics=(),
    drop=True,
    na_translate=True
)

No shape scaling

Parameter Attributes

name: str | None = None

The name of the scale. It is used as the label of the axis or the title of the guide. Suitable defaults are chosen depending on the type of scale.

breaks: DiscreteBreaksUser = True

List of major break points. Or a callable that takes a tuple of limits and returns a list of breaks. If True, automatically calculate the breaks.

limits: DiscreteLimitsUser = None

Limits of the scale. These are the categories (unique values) of the variables. If is only a subset of the values, those that are left out will be treated as missing data and represented with a na_value.

labels: ScaleLabelsUser = True

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

expand: (
    tuple[float, float]
    | tuple[float, float, float, float]
    | None
) = None

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.

guide: Literal["legend"] | None = "legend"

na_value: Any = np.nan

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.

aesthetics: Sequence[ScaledAestheticsName] = ()

Aesthetics affected by this scale. These are defined by each scale and the user should probably not change them. Have fun.

drop: bool = True

Whether to drop unused categories from the scale

na_translate: bool = True

If True translate missing values and show them. If False remove missing values.

Examples

from plotnine import (
    aes,
    annotate,
    coord_equal,
    element_rect,
    element_text,
    facet_wrap,
    geom_point,
    geom_segment,
    geom_text,
    geom_tile,
    ggplot,
    lims,
    scale_shape_identity,
    theme,
    theme_void,
)

import polars as pl
import numpy as np

Scatter Plot Shapes

List the shapes and prepare dataframe with what is required to display them.

filled_shapes = (
    "o",  # circle
    "^",  # triangle up
    "s",  # square
    "D",  # Diamond
    "v",  # triangle down
    "*",  # star
    "p",  # pentagon
    "8",  # octagon
    "<",  # triangle left
    "h",  # hexagon1
    ">",  # triangle right
    "H",  # hexagon1
    "d",  # thin diamond
)

unfilled_shapes = (
    "+",  # plus
    "x",  # x
    ".",  # point
    "1",  # tri_down
    "2",  # tri_up
    "3",  # tri_left
    "4",  # tri_right
    ",",  # pixel
    "_",  # hline
    "|",  # vline
    0,  # tickleft
    1,  # tickright
    2,  # tickup
    3,  # tickdown
    4,  # caretleft
    5,  # caretright
    6,  # caretup
    7,  # caretdown
)

n1 = len(filled_shapes)
n2 = len(unfilled_shapes)
ncols = 10
shapes = filled_shapes + unfilled_shapes

df = pl.DataFrame({
    "x": np.hstack([np.arange(n1) % ncols, np.arange(n2) % ncols]),
    "y": 4 - 1.5 * np.hstack([np.arange(n1) // ncols, np.arange(n2) // ncols]),
    "shape": pl.Series(shapes, dtype=object),
    "shape_kind": np.repeat(["Filled Shapes", "Unfilled Shapes"], (n1, n2))
})

df

shape: (31, 4)

x	y	shape	shape_kind
i64	f64	object	str
0	4.0	o	"Filled Shapes"
1	4.0	^	"Filled Shapes"
2	4.0	s	"Filled Shapes"
3	4.0	D	"Filled Shapes"
4	4.0	v	"Filled Shapes"
…	…	…	…
3	2.5	3	"Unfilled Shapes"
4	2.5	4	"Unfilled Shapes"
5	2.5	5	"Unfilled Shapes"
6	2.5	6	"Unfilled Shapes"
7	2.5	7	"Unfilled Shapes"

# Gallery, points

def double_quote_strings(series):
    return [
        '"{}"'.format(s) if isinstance(s, str) else "{}".format(s)
        for s in series
    ]

(
    ggplot(df, aes("x", "y"))
    
    # Background
    + geom_tile(aes(width=0.9, height=0.9), fill="#F8F8F8")
    
    # Cross-grid to help see the centering of the shapes
    + geom_segment(aes(x="x-0.45", xend="x+0.45", yend="y"), color="Crimson", alpha=0.05)
    + geom_segment(aes(xend="x", y="y-0.45", yend="y+0.45"), color="Crimson", alpha=0.05)
    
    # The shape
    + geom_point(aes(shape="shape"), fill="#E5C8D6", size=8)

    # Specification value for the shape
    + geom_text(
        aes(y="y+.5", label="double_quote_strings(shape)"),
        color="darkblue",
        va="bottom",
    )

    # Separate the shapes by their kind
    + facet_wrap("shape_kind", ncol=1)

    # Make things pretty
    + lims(y=(2, 5))
    + scale_shape_identity()
    + coord_equal()
    + theme_void()
    + theme(
        plot_background=element_rect(fill="white"),
        strip_text=element_text(size=12)
    )
)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
File ~/.uvenv/plotnine/lib/python3.13/site-packages/IPython/core/formatters.py:984, in IPythonDisplayFormatter.__call__(self, obj)
    982 method = get_real_method(obj, self.print_method)
    983 if method is not None:
--> 984     method()
    985     return True

File ~/scm/python/plotnine/plotnine/ggplot.py:149, in ggplot._ipython_display_(self)
    142 def _ipython_display_(self):
    143     """
    144     Display plot in the output of the cell
    145 
    146     This method will always be called when a ggplot object is the
    147     last in the cell.
    148     """
--> 149     self._display()

File ~/scm/python/plotnine/plotnine/ggplot.py:190, in ggplot._display(self)
    187     self.theme = self.theme.to_retina()
    189 buf = BytesIO()
--> 190 self.save(buf, "png" if format == "retina" else format, verbose=False)
    191 figure_size_px = self.theme._figure_size_px
    192 display_func = get_display_function(format, figure_size_px)

File ~/scm/python/plotnine/plotnine/ggplot.py:702, in ggplot.save(self, filename, format, path, width, height, units, dpi, limitsize, verbose, **kwargs)
    653 def save(
    654     self,
    655     filename: Optional[str | Path | BytesIO] = None,
   (...)    664     **kwargs: Any,
    665 ):
    666     """
    667     Save a ggplot object as an image file
    668 
   (...)    700         Additional arguments to pass to matplotlib `savefig()`.
    701     """
--> 702     sv = self.save_helper(
    703         filename=filename,
    704         format=format,
    705         path=path,
    706         width=width,
    707         height=height,
    708         units=units,
    709         dpi=dpi,
    710         limitsize=limitsize,
    711         verbose=verbose,
    712         **kwargs,
    713     )
    715     with plot_context(self).rc_context:
    716         sv.figure.savefig(**sv.kwargs)

File ~/scm/python/plotnine/plotnine/ggplot.py:650, in ggplot.save_helper(self, filename, format, path, width, height, units, dpi, limitsize, verbose, **kwargs)
    647 if dpi is not None:
    648     self.theme = self.theme + theme(dpi=dpi)
--> 650 figure = self.draw(show=False)
    651 return mpl_save_view(figure, fig_kwargs)

File ~/scm/python/plotnine/plotnine/ggplot.py:322, in ggplot.draw(self, show)
    319     self._create_figure()
    320 figure = self.figure
--> 322 self._build()
    324 # setup
    325 self.axs = self.facet.setup(self)

File ~/scm/python/plotnine/plotnine/ggplot.py:419, in ggplot._build(self)
    417 npscales = scales.non_position_scales()
    418 if len(npscales):
--> 419     layers.train(npscales)
    420     layers.map(npscales)
    422 # Train coordinate system

File ~/scm/python/plotnine/plotnine/layer.py:492, in Layers.train(self, scales)
    490 def train(self, scales: Scales):
    491     for l in self:
--> 492         scales.train_df(l.data)

File ~/scm/python/plotnine/plotnine/scales/scales.py:203, in Scales.train_df(self, data, drop)
    201 # Each scale trains the columns it understands
    202 for sc in self:
--> 203     sc.train_df(data)

File ~/scm/python/plotnine/plotnine/scales/scale.py:284, in scale.train_df(self, df)
    282 aesthetics = sorted(set(self.aesthetics) & set(df.columns))
    283 for ae in aesthetics:
--> 284     self.train(df[ae])

File ~/scm/python/plotnine/plotnine/scales/scale_identity.py:36, in MapTrainMixin.train(self, x, drop)
     33 if self.guide is None:  # pyright: ignore
     34     return
---> 36 return super().train(x)

File ~/scm/python/plotnine/plotnine/scales/scale_discrete.py:107, in scale_discrete.train(self, x, drop)
    104     return
    106 na_rm = not self.na_translate
--> 107 self._range.train(x, drop, na_rm=na_rm)

File ~/scm/python/plotnine/plotnine/scales/range.py:67, in RangeDiscrete.train(self, x, drop, na_rm)
     63 """
     64 Train discrete range
     65 """
     66 rng = None if self.is_empty() else self.range
---> 67 self.range = scale_discrete.train(x, rng, drop, na_rm=na_rm)

File ~/.uvenv/plotnine/lib/python3.13/site-packages/mizani/scale.py:269, in scale_discrete.train(cls, new_data, old, drop, na_rm)
    267     limits = [c for c in ordered_cats if c in all_set]
    268 else:
--> 269     new = np.unique(new_data)
    270     new.sort()
    272     limits = old + [i for i in new if (i not in old_set)]

File ~/.uvenv/plotnine/lib/python3.13/site-packages/numpy/lib/_arraysetops_impl.py:286, in unique(ar, return_index, return_inverse, return_counts, axis, equal_nan)
    284 ar = np.asanyarray(ar)
    285 if axis is None:
--> 286     ret = _unique1d(ar, return_index, return_inverse, return_counts,
    287                     equal_nan=equal_nan, inverse_shape=ar.shape, axis=None)
    288     return _unpack_tuple(ret)
    290 # axis was specified and not None

File ~/.uvenv/plotnine/lib/python3.13/site-packages/numpy/lib/_arraysetops_impl.py:353, in _unique1d(ar, return_index, return_inverse, return_counts, equal_nan, inverse_shape, axis)
    351     aux = ar[perm]
    352 else:
--> 353     ar.sort()
    354     aux = ar
    355 mask = np.empty(aux.shape, dtype=np.bool)

TypeError: '<' not supported between instances of 'int' and 'str'

<plotnine.ggplot.ggplot at 0x10acd1220>

Source: Scatter Plot Shapes