annotate

named_arrays.plt.annotate(text, xy, xytext=None, components=None, ax=None, xycoords='data', textcoords=None, arrowprops=None, annotation_clip=None, **kwargs)

A thin wrapper around matplotlib.axes.Axes.annotate() for named arrays.

Parameters:

• text (str | AbstractScalarArray) – The text of the annotation

• xy (VectorT) – The point to annotate in the coordinate system of xycoords.

• xytext (None | VectorT) – The point to place the text in the coordinate system of textcoords.

• components (None | tuple[str, str]) – If xy has more than two components, use this argument to specify which components correspond to horizontal and vertical positions.

• ax (None | Axes | AbstractArray) – The matplotlib axes instance on which to plot the annotation.

• xycoords (str | Transform | AbstractScalarArray | VectorT) – The coordinate system that xy is given in.

• textcoords (None | str | Transform | AbstractScalarArray | VectorT) – The coordinate system that xytext is given in.

• arrowprops (None | dict) – The properties used to draw the arrow.

• annotation_clip (None | bool | AbstractScalarArray) – Whether to draw the annotation when the point is outside the axes limits.

• kwargs – Additional arguments passed to matplotlib.text.Text

Return type:

ScalarArray[ndarray[tuple[Any, …], dtype[Annotation]]]

Examples

Plot a single annotation

import matplotlib.pyplot as plt
import named_arrays as na

fig, ax = plt.subplots()
ann = na.plt.annotate(
    text="text",
    xy=na.Cartesian2dVectorArray(x=.5, y=.5),
    xytext=na.Cartesian2dVectorArray(x=.75, y=.75),
)

Plot annotations in a vectorized fashion

fig, ax = plt.subplots()
ann = na.plt.annotate(
    text="text",
    xy=na.Cartesian2dVectorArray(
        x=na.linspace(.25, .75, axis="x", num=3),
        y=.5,
    ),
    xytext=na.Cartesian2dVectorArray(x=.75, y=.75),
)