Note
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Tick formatters#
Tick formatters define how the numeric value associated with a tick on an axis is formatted as a string.
This example illustrates the usage and effect of the most common formatters.
import matplotlib.pyplot as plt
from matplotlib import ticker
def setup(ax, title):
"""Set up common parameters for the Axes in the example."""
# only show the bottom spine
ax.yaxis.set_major_locator(ticker.NullLocator())
ax.spines.right.set_color('none')
ax.spines.left.set_color('none')
ax.spines.top.set_color('none')
# define tick positions
ax.xaxis.set_major_locator(ticker.MultipleLocator(1.00))
ax.xaxis.set_minor_locator(ticker.MultipleLocator(0.25))
ax.xaxis.set_ticks_position('bottom')
ax.tick_params(which='major', width=1.00, length=5)
ax.tick_params(which='minor', width=0.75, length=2.5, labelsize=10)
ax.set_xlim(0, 5)
ax.set_ylim(0, 1)
ax.text(0.0, 0.2, title, transform=ax.transAxes,
fontsize=14, fontname='Monospace', color='tab:blue')
Tick formatters can be set in one of two ways, either by passing a str
or function to set_major_formatter
or set_minor_formatter
,
or by creating an instance of one of the various Formatter
classes
and providing that to set_major_formatter
or
set_minor_formatter
.
The first two examples directly pass a str
or function.
fig0, axs0 = plt.subplots(2, 1, figsize=(8, 2))
fig0.suptitle('Simple Formatting')
# A ``str``, using format string function syntax, can be used directly as a
# formatter. The variable ``x`` is the tick value and the variable ``pos`` is
# tick position. This creates a StrMethodFormatter automatically.
setup(axs0[0], title="'{x} km'")
axs0[0].xaxis.set_major_formatter('{x} km')
# A function can also be used directly as a formatter. The function must take
# two arguments: ``x`` for the tick value and ``pos`` for the tick position,
# and must return a ``str``. This creates a FuncFormatter automatically.
setup(axs0[1], title="lambda x, pos: str(x-5)")
axs0[1].xaxis.set_major_formatter(lambda x, pos: str(x-5))
fig0.tight_layout()
The remaining examples use Formatter
objects.
fig1, axs1 = plt.subplots(7, 1, figsize=(8, 6))
fig1.suptitle('Formatter Object Formatting')
# Null formatter
setup(axs1[0], title="NullFormatter()")
axs1[0].xaxis.set_major_formatter(ticker.NullFormatter())
# StrMethod formatter
setup(axs1[1], title="StrMethodFormatter('{x:.3f}')")
axs1[1].xaxis.set_major_formatter(ticker.StrMethodFormatter("{x:.3f}"))
# FuncFormatter can be used as a decorator
@ticker.FuncFormatter
def major_formatter(x, pos):
return f'[{x:.2f}]'
setup(axs1[2], title='FuncFormatter("[{:.2f}]".format)')
axs1[2].xaxis.set_major_formatter(major_formatter)
# Fixed formatter
setup(axs1[3], title="FixedFormatter(['A', 'B', 'C', ...])")
# FixedFormatter should only be used together with FixedLocator.
# Otherwise, one cannot be sure where the labels will end up.
positions = [0, 1, 2, 3, 4, 5]
labels = ['A', 'B', 'C', 'D', 'E', 'F']
axs1[3].xaxis.set_major_locator(ticker.FixedLocator(positions))
axs1[3].xaxis.set_major_formatter(ticker.FixedFormatter(labels))
# Scalar formatter
setup(axs1[4], title="ScalarFormatter()")
axs1[4].xaxis.set_major_formatter(ticker.ScalarFormatter(useMathText=True))
# FormatStr formatter
setup(axs1[5], title="FormatStrFormatter('#%d')")
axs1[5].xaxis.set_major_formatter(ticker.FormatStrFormatter("#%d"))
# Percent formatter
setup(axs1[6], title="PercentFormatter(xmax=5)")
axs1[6].xaxis.set_major_formatter(ticker.PercentFormatter(xmax=5))
fig1.tight_layout()
plt.show()
References
The use of the following functions, methods, classes and modules is shown in this example:
Total running time of the script: ( 0 minutes 1.187 seconds)