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gmarsi
Asked: 2020-09-08 05:24:52 +0800 CST 2020-09-08 05:24:52 +0800 CST

Change tick size with matplotlib

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I want to change the font size of the 'ticks' of a chart. At the moment I am using the following instruction to change it only to the graph that I am going to show

plt.tick_params(labelsize = 20)

But just like with

plt.rcParams["figure.figsize"] = [20,10]

I can change the size of all the graphs that I generate, is there something similar to change the font size of the ticks of all the graphs that I generate?

python

1 Answers

  1. Best Answer

    'xtick.labelsize'You can use the rc and parameters 'ytick.labelsize':

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

# Siempre al inicio
params = {'xtick.labelsize': 20, 'ytick.labelsize': 20}
mpl.rcParams.update(params)


def f1(t):
    return np.exp(-t) * np.cos(2*np.pi*t)

def f2(t):
    return np.exp(-t) * np.sin(2*np.pi*-t)

t = np.arange(0.0, 5.0, 0.1)

fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()

ax1.plot(t, f1(t), 'bo', t, f1(t), 'k')
ax2.plot(t, f2(t), 'ro', t, f2(t), 'k')

plt.show()

    Another very useful option if you are going to modify many properties and you also intend to reuse it is to define your own style, simply create a text file to define the parameters, for example we create the file customstyle.mplstylewith the following content:

    figure.figsize: 20, 10
    xtick.labelsize : 20
    ytick.labelsize : 20

    To use it, just pass the path to plt.style.use:

    import numpy as np
import matplotlib.pyplot as plt

plt.style.use('ruta/a/customstyle.mplstyle')


def f1(t):
    return np.exp(-t) * np.cos(2*np.pi*t)

def f2(t):
    return np.exp(-t) * np.sin(2*np.pi*-t)

t = np.arange(0.0, 5.0, 0.1)

fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()

ax1.plot(t, f1(t), 'bo', t, f1(t), 'k')
ax2.plot(t, f2(t), 'ro', t, f2(t), 'k')

plt.show()

    You can also add the file to ~/.config/matplotlib/stylelibso that we can reuse the style in the future just by using its name:

    plt.style.use('customstyle')

    The directory can vary, in GNU/Linux this is usually the directory, in any case we can find it with:

    >>> import matplotlib
>>> matplotlib.get_configdir()

    and in the directory that returns us create the directory styleliband put our styles in it.

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