# Major and minor ticks¶

Demonstrate how to use major and minor tickers.

The two relevant classes are Locators and Formatters. Locators determine where the ticks are, and formatters control the formatting of tick labels.

Minor ticks are off by default (using NullLocator and NullFormatter). Minor ticks can be turned on without labels by setting the minor locator. Minor tick labels can be turned on by setting the minor formatter.

MultipleLocator places ticks on multiples of some base. FormatStrFormatter uses a format string (e.g., '%d' or '%1.2f' or '%1.1f cm') to format the tick labels.

pyplot.grid changes the grid settings of the major ticks of the y and y axis together. If you want to control the grid of the minor ticks for a given axis, use for example

ax.xaxis.grid(True, which='minor')


Note that a given locator or formatter instance can only be used on a single axis (because the locator stores references to the axis data and view limits).

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,
AutoMinorLocator)

t = np.arange(0.0, 100.0, 0.1)
s = np.sin(0.1 * np.pi * t) * np.exp(-t * 0.01)

fig, ax = plt.subplots()
ax.plot(t, s)

# Make a plot with major ticks that are multiples of 20 and minor ticks that
# are multiples of 5.  Label major ticks with '%d' formatting but don't label
# minor ticks.
ax.xaxis.set_major_locator(MultipleLocator(20))
ax.xaxis.set_major_formatter(FormatStrFormatter('%d'))

# For the minor ticks, use no labels; default NullFormatter.
ax.xaxis.set_minor_locator(MultipleLocator(5))

plt.show()


Automatic tick selection for major and minor ticks.

Use interactive pan and zoom to see how the tick intervals change. There will be either 4 or 5 minor tick intervals per major interval, depending on the major interval.

One can supply an argument to AutoMinorLocator to specify a fixed number of minor intervals per major interval, e.g. AutoMinorLocator(2) would lead to a single minor tick between major ticks.

t = np.arange(0.0, 100.0, 0.01)
s = np.sin(2 * np.pi * t) * np.exp(-t * 0.01)

fig, ax = plt.subplots()
ax.plot(t, s)

ax.xaxis.set_minor_locator(AutoMinorLocator())

ax.tick_params(which='both', width=2)
ax.tick_params(which='major', length=7)
ax.tick_params(which='minor', length=4, color='r')

plt.show()


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