pltutils

Collection of utility functions for matplotlib

Functions

_is_jupyter_notebook()
_is_notebook_inline_backend()
_make_style()
_reset_notebook_inline_backend()
add_margin([margin, axis, ax])	Adjust the axis length to include a margin (after autoscale)
align(x, y)	Return text alignment based on (x, y) numbers
annotate_box(s, xy[, fontcolor, ax])	Annotate with a box around the text
axes(ax)	A context manager that sets the active Axes instance to ax
backend(new_backend)	Change the backend within this context
blend_colors(color, bg, factor)	Blend color with background
cm2inch(*values)	Convert from centimeter to inch
colorbar([mappable, ax, cax, label, powerlimits])	Custom colorbar with modified style and optional label
despine([trim, ax])	Remove the top and right spines
despine_all([ax])	Remove all spines, axes labels and ticks
direct_cmap_norm(data, colors[, blend])	Colormap with direct mapping: data[i] -> colors[i]
get_palette([name, num_colors, start])	Get a color palette from matplotlib's colormap database
legend(*args[, reverse, facecolor, lw, ax])	Custom legend with modified style and option to reverse label order
plot_color(x, y, z[, ax, cmap])	Function to plot the values as changing colors in a plot.
plot_vectors(vectors[, position, name, ...])	Visualize vectors, alternative to plt.quiver()
respine([ax])	Redraw all spines, opposite of despine()
set_min_axis_length(length[, axis, ax])	Set minimum axis length
set_min_axis_ratio(ratio[, ax])	Set minimum ratio between axes limits
set_palette([name, num_colors, start, ax])	Set the active color palette
use_style([style])	Shortcut for matplotlib.style.use() with pybinding style applied by default

cm2inch(*values) → Tuple[int, int]

Convert from centimeter to inch

Parameters:

*values

Returns:

tuple

Examples

>>> cm2inch(2.54, 5.08)
(1.0, 2.0)

colorbar(mappable: ScalarMappable | None = None, ax: Axes | None = None, cax: Axes | None = None, label='', powerlimits=(0, 0), **kwargs)

Custom colorbar with modified style and optional label

Changes default pad and aspect argument values and turns on rasterization for a nicer looking colorbar with smaller size in vector formats (pdf, svg).

Parameters:

mappableOptional[ScalarMappable]

The image or contour set over which the colorbar will be drawn.

axOptional[plt.Axes]

Axis to add the colorbar to.

caxOptional[plt.Axes]

Axis to draw the colorbar in.

labelstr

Color data label.

powerlimitsTuple[int, int]

Sets size thresholds for scientific notation.

**kwargs

Forwarded to matplotlib.pyplot.colorbar().

despine(trim: bool = False, ax: Axes | None = None) → None

Remove the top and right spines

Parameters:

trimbool

Trim spines so that they don’t extend beyond the last major ticks.

axOptional[plt.Axes]

Axes to despine.

despine_all(ax: Axes | None = None) → None

Remove all spines, axes labels and ticks

Parameters:

axOptional[plt.Axes]

Axes to despine.

get_palette(name=None, num_colors=8, start=0)

Get a color palette from matplotlib’s colormap database

Parameters:

namestr, optional

Name of the palette to get. If None, get the active palette.

num_colorsint

Number of colors to retrieve.

startint

Staring from this color number.

Returns:

List[color]

legend(*args, reverse=False, facecolor='0.98', lw=0, ax: Axes | None = None, **kwargs)

Custom legend with modified style and option to reverse label order

Parameters:

reversebool

Reverse the label order.

facecolorcolor

Legend background color.

lwfloat

Frame width.

axOptional[plt.Axes]

Axis to add the legend to.

*args, **kwargs

Forwarded to matplotlib.pyplot.legend().

respine(ax: Axes | None = None) → None

Redraw all spines, opposite of despine()

Parameters:

axOptional[plt.Axes]

Axes to respine.

set_palette(name=None, num_colors=8, start=0, ax: Axes | None = None)

Set the active color palette

Parameters:

namestr, optional

Name of the palette. If None, modify the active palette.

num_colorsint

Number of colors to retrieve.

startint

Staring from this color number.

axOptional[plt.Axes]

Axis to set the palette to.

use_style(style=pb_style)

Shortcut for matplotlib.style.use() with pybinding style applied by default

Parameters:

styledict

A matplotlib style specification.