How to change the position of some x axis tick labels on top of the bottom x axis in matplotlib?

Question

This is my current script:

#!/usr/bin/env python3

import math
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

"""
Setup for a typical explanatory-style illustration style graph.
"""

h = 2
x = np.linspace(-np.pi, np.pi, 100)
y = 2 * np.sin(x)
rc = {
    # Tick in the middle of the axis line.
    'xtick.direction' : 'inout',
    'ytick.direction' : 'inout',

    # Bold is easier to read when we have few ticks.
    'font.weight': 'bold',
    'xtick.labelbottom': False,
    'xtick.labeltop': True,
}
with plt.rc_context(rc):
    fig, ax = plt.subplots()
    ax.plot(x, y)
    ax.set_title(
        '2 sin(x), not $\\sqrt{2\\pi}$',
        # TODO make LaTeX part bold?
        # https://stackoverflow.com/questions/14324477/bold-font-weight-for-latex-axes-label-in-matplotlib
        fontweight='bold',
        # Too close otherwise.
        # https://stackoverflow.com/questions/16419670/increase-distance-between-title-and-plot-in-matplolib/56738085
        pad=20
    )

    # Custom visible plot area.
    # ax.set_xlim(-3, 3)
    ax.set_ylim(-2.5, 2.5)

    # Axes
    # Axes on center:
    # https://stackoverflow.com/questions/31556446/how-to-draw-axis-in-the-middle-of-the-figure
    ax.spines['left'].set_position('zero')
    ax.spines['right'].set_visible(False)
    ax.spines['bottom'].set_position('zero')
    ax.spines['top'].set_visible(False)
    # Axes with arrow:
    # https://stackoverflow.com/questions/33737736/matplotlib-axis-arrow-tip
    ax.plot(1, 0, ls="", marker=">", ms=10, color="k",
            transform=ax.get_yaxis_transform(), clip_on=False)
    ax.plot(0, 1, ls="", marker="^", ms=10, color="k",
            transform=ax.get_xaxis_transform(), clip_on=False)

    # Ticks
    ax.xaxis.set_ticks_position('bottom')
    ax.yaxis.set_ticks_position('left')
    # Make ticks a bit longer.
    ax.tick_params(width=1, length=10)
    # Select tick positions
    # https://stackoverflow.com/questions/12608788/changing-the-tick-frequency-on-x-or-y-axis-in-matplotlib
    xticks = np.arange(math.ceil(min(x)),     math.floor(max(x)) + 1, 1)
    yticks = np.arange(math.ceil(min(y)) - 1, math.floor(max(y)) + 2, 1)
    # Remove 0.
    xticks = np.setdiff1d(xticks, [0])
    yticks = np.setdiff1d(yticks, [0])
    ax.xaxis.set_ticks(xticks)
    ax.yaxis.set_ticks(yticks)
    # Another approach. But because I want to be able to remove the 0,
    # anyways, I just explicitly give all ticks instead.
    # ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))
    # ax.yaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))

    # Annotations.
    ax.plot([0, np.pi/2], [h, h], '--r')
    ax.plot([np.pi/2, np.pi/2], [h, 0], '--r')
    ax.plot(np.pi/2, h, marker='o', linewidth=2, markersize=10,
        markerfacecolor='w', markeredgewidth=1.5, markeredgecolor='black')

plt.savefig(
    'main.png',
    format='png',
    bbox_inches='tight'
)
plt.clf()

And this is the output:

And this is what I want (hacked with GIMP), notice how the negative tick labels are on a different side of the axes now.

I tried adding:

    for tick in ax.xaxis.get_majorticklabels():
        tick.set_verticalalignment("bottom")

as shown in answers to: How to move a tick's label in matplotlib? but that does not move the tick labels up enough, and makes the labels show on top of the axes instead.

Tested on matplotlib 3.2.2.

Diziet Asahi · Answer 1 · 2020-10-25T10:26:16.957

The following code will adjust the vertical alignment of the ticks depending one whether they are at a negative or positive x-value. However that's not enough because the labels are actually anchored at the bottom of the tick line. I'm therefore adjusting their y-position a little bit, but you have to play with the value to get the desired output

# adjust the xticks so that they are on top when x<0 and on the bottom when x≥0
ax.spines['top'].set_visible(True)
ax.spines['top'].set_position('zero')
ax.spines['bottom'].set_visible(True)
ax.spines['bottom'].set_position('zero')
ax.xaxis.set_tick_params(which='both', top=True, labeltop=True,
                             bottom=True, labelbottom=True)
fig.canvas.draw()
for tick in ax.xaxis.get_major_ticks():
    print(tick.get_loc())
    if tick.get_loc()<0:
        tick.tick1line.set_visible(False)
        tick.label1.set_visible(False)
    else:
        tick.tick2line.set_visible(False)
        tick.label2.set_visible(False)

full code:

import math
import numpy as np
import matplotlib
import matplotlib.pyplot as plt

"""
Setup for a typical explanatory-style illustration style graph.
"""

h = 10
x = np.linspace(-np.pi, np.pi, 100)
y = h * np.sin(x)
rc = {
    # Tick in the middle of the axis line.
    'xtick.direction' : 'inout',
    'ytick.direction' : 'inout',

    # Bold is easier to read when we have few ticks.
    'font.weight': 'bold',
    'xtick.labelbottom': False,
    'xtick.labeltop': True,
}
with plt.rc_context(rc):
    fig, ax = plt.subplots()
    ax.plot(x, y)
    ax.set_title(
        '2 sin(x), not $\\sqrt{2\\pi}$',
        # TODO make LaTeX part bold?
        # https://stackoverflow.com/questions/14324477/bold-font-weight-for-latex-axes-label-in-matplotlib
        fontweight='bold',
        # Too close otherwise.
        # https://stackoverflow.com/questions/16419670/increase-distance-between-title-and-plot-in-matplolib/56738085
        pad=20
    )

    # Custom visible plot area.
    # ax.set_xlim(-3, 3)
    ax.set_ylim(-2.5, 2.5)

    # Axes
    # Axes on center:
    # https://stackoverflow.com/questions/31556446/how-to-draw-axis-in-the-middle-of-the-figure
    ax.spines['left'].set_position('zero')
    ax.spines['right'].set_visible(False)
    ax.spines['bottom'].set_position('zero')
    ax.spines['top'].set_visible(False)
    # Axes with arrow:
    # https://stackoverflow.com/questions/33737736/matplotlib-axis-arrow-tip
    ax.plot(1, 0, ls="", marker=">", ms=10, color="k",
            transform=ax.get_yaxis_transform(), clip_on=False)
    ax.plot(0, 1, ls="", marker="^", ms=10, color="k",
            transform=ax.get_xaxis_transform(), clip_on=False)

    # Ticks
    ax.xaxis.set_ticks_position('bottom')
    ax.yaxis.set_ticks_position('left')
    # Make ticks a bit longer.
    ax.tick_params(width=1, length=10)
    # Select tick positions
    # https://stackoverflow.com/questions/12608788/changing-the-tick-frequency-on-x-or-y-axis-in-matplotlib
    xticks = np.arange(math.ceil(min(x)),     math.floor(max(x)) + 1, 1)
    yticks = np.arange(math.ceil(min(y)) - 1, math.floor(max(y)) + 2, 1)
    # Remove 0.
    xticks = np.setdiff1d(xticks, [0])
    yticks = np.setdiff1d(yticks, [0])
    ax.xaxis.set_ticks(xticks)
    ax.yaxis.set_ticks(yticks)
    # Another approach. But because I want to be able to remove the 0,
    # anyways, I just explicitly give all ticks instead.
    # ax.xaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))
    # ax.yaxis.set_major_locator(matplotlib.ticker.MultipleLocator(1.0))
    
    for g,t in zip(ax.get_xticks(),ax.get_xticklabels()):
        if g<0:
            t.set_va('bottom')
        else:
            t.set_va('top')
        t.set_transform(ax.transData)
        t.set_position((g,0.15*-(g/abs(g))))

    # Annotations.
    ax.plot([0, np.pi/2], [h, h], '--r')
    ax.plot([np.pi/2, np.pi/2], [h, 0], '--r')
    ax.plot(np.pi/2, h, marker='o', linewidth=2, markersize=10,
        markerfacecolor='w', markeredgewidth=1.5, markeredgecolor='black')
    
    
    # adjust the xticks so that they are on top when x<0 and on the bottom when x≥0
    ax.spines['top'].set_visible(True)
    ax.spines['top'].set_position('zero')
    ax.spines['bottom'].set_visible(True)
    ax.spines['bottom'].set_position('zero')
    ax.xaxis.set_tick_params(which='both', top=True, labeltop=True,
                                 bottom=True, labelbottom=True)
    fig.canvas.draw()
    for tick in ax.xaxis.get_major_ticks():
        print(tick.get_loc())
        if tick.get_loc()<0:
            tick.tick1line.set_visible(False)
            tick.label1.set_visible(False)
        else:
            tick.tick2line.set_visible(False)
            tick.label2.set_visible(False)

I noticed later on that this solution does not scale perfectly with data size unfortunately, e.g. if I set `h = 1000`, then the numbers start touching the ticks. If I remove the added `for` loop, they don't. I'm guessing there might be a more appropriate transform to apply to the magic `0.15` such that a single number could work for any data size. — Ciro Santilli OurBigBook.com, Oct 24 '20 at 08:34
I've found a better way to manipulate the labels. I've amended my answer — Diziet Asahi, Oct 25 '20 at 10:27

How to change the position of some x axis tick labels on top of the bottom x axis in matplotlib?

1 Answers1