position

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position#

Positions of subplots, used with add_axes

This module was written by Matthias Cuntz while at Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany, and continued while at Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Nancy, France.

copyright:

Copyright 2009-2022 Matthias Cuntz, see AUTHORS.rst for details.

license:

MIT License, see LICENSE for details.

The following functions are provided:

position([row, col, num, left, right, ...])

Gives positions of subplots, to be used with add_axes instead of subplot
History

  • Written Aug 2009 by Matthias Cuntz (mc (at) macu (dot) de)

  • Ported to Python 3, Feb 2013, Matthias Cuntz

  • Add vspace instead of wspace, Jul 2013, Matthias Cuntz

  • Use assert instead of raise Error, Apr 2014, Matthias Cuntz

  • Added height and width, Feb 2016, Stephan Thober

  • Ported to pyjams, Nov 2021, Matthias Cuntz

  • More consistent docstrings, Jan 2022, Matthias Cuntz

position(row=1, col=1, num=1, left=0.125, right=0.9, bottom=0.1, top=0.9, hspace=0.1, vspace=0.1, width=None, height=None, sortcol=False, golden=False, inversegolden=False, figsize=(1.0, 1.0))[source]#

Gives positions of subplots, to be used with add_axes instead of subplot

All dimensions are fractions of the figure width or height. Figure and subplot spaces are the same as for figure.subplot params except for hspace and vspace, which are halved.

If the figsize keyword is given, a square section of the figure will be used.

Parameters:

  • row (int, optional) – Number of subplot rows (default: 1)

  • col (int, optional) – Number of subplot columns (default: 1)

  • num (int, optional) – Subplot number (default: 1)

  • left (float, optional) – Left border of plot (default: 0.125)

  • right (float, optional) – Right border of plot (default: 0.9)

  • bottom (float, optional) – Bottom border of plot (default: 0.1)

  • top (float, optional) – Top border of plot (default: 0.9)

  • hspace (float, optional) – Horizontal space between columns (default: 0.1)

  • vspace (float, optional) – Vertical space between rows (default: 0.1)

  • width (float, optional) – Prescribe width of plots (default: calculated col, left, etc.)

  • height (float, optional) – Prescribe height of plots (default: calculated row, top, etc.)

  • sortcol (bool, optional) – Fill columns then rows if True (default: False)

  • golden (bool, optional) – Ratio of width/height = (1+sqrt(5))/2 if True, i.e. the golden ratio (default: False)

  • inversegolden (bool, optional) – Ratio of height/width = (1+sqrt(5))/2 if True, i.e. the golden ratio (default: False). The golden keyword takes precedence over inversegolden.

  • figsize (tuple of 2 float, optional) – (width, height) of figure as given by e.g. matplotlib.rcParams[‘figure.figsize’]. Scales everything to a square section (default: (1, 1))

Returns:

[left, bottom, width, height] to be used with Matplotlib’s fig.add_axes.

Return type:

list

Examples

Use, for example, as follows

fig1 = figure(1)
sub1 = fig1.add_axes(position(2, 2, 1))
sub2 = fig1.add_axes(position(2, 2, 2))

Give figsize and set same left and right margins if you want to have true squares

figsize = matplotlib.rcParams['figure.figsize']
sub = fig1.add_axes(position(1, 1, 1, figsize=figsize, left=0.1,
                             right=0.9))

If you want to have a true golden ratio

sub = fig1.add_axes(position(1, 1, 1, golden=True))

>>> import numpy as np
>>> print(np.around(position(2, 2, 1), 3))
[0.125 0.55  0.338 0.35 ]
>>> print(np.around(position(2, 2, 1, sortcol=True), 3))
[0.125 0.55  0.338 0.35 ]
>>> print(np.around(position(2, 2, 1, golden=True), 3))
[0.125 0.409 0.338 0.209]
>>> print(np.around(position(2, 2, 1, inversegolden=True), 3))
[0.125 0.55  0.216 0.35 ]
>>> print(np.around(position(2, 2, 1, golden=True, sortcol=True), 3))
[0.125 0.409 0.338 0.209]
>>> print(np.around(position(2, 2, 1, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0.), 3))
[0.  0.5 0.5 0.5]
>>> print(np.around(position(2, 2, 2, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0.), 3))
[0.5 0.5 0.5 0.5]
>>> print(np.around(position(2, 2, 3, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0.), 3))
[0.  0.  0.5 0.5]
>>> print(np.around(position(2, 2, 4, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0.), 3))
[0.5 0.  0.5 0.5]
>>> print(np.around(position(2, 2, 1, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0., golden=True), 3))
[0.    0.309 0.5   0.309]
>>> print(np.around(position(2, 2, 2, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0., golden=True), 3))
[0.5   0.309 0.5   0.309]
>>> print(np.around(position(2, 2, 3, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0., golden=True), 3))
[0.    0.    0.5   0.309]
>>> print(np.around(position(2, 2, 4, top=1., bottom=0., left=0., right=1.,
...                          hspace=0., vspace=0., golden=True), 3))
[0.5   0.    0.5   0.309]

>>> figsize=[8, 11]
>>> print(np.around(position(2, 2, 1, golden=True, sortcol=True,
...                          figsize=figsize), 3))
[0.125 0.324 0.338 0.152]
>>> print(np.around(position(2, 2, 1, figsize=figsize, left=0.1), 3))
[0.1   0.427 0.35  0.255]
>>> print(np.around(position(2, 2, 1, figsize=figsize, left=0.1,
...                          golden=True), 3))
[0.1   0.33  0.35  0.157]
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