Matplotlib.axes.Axes.minorticks_on() in Python
Last Updated :
21 Apr, 2020
Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.
matplotlib.axes.Axes.minorticks_on() Function
The Axes.minorticks_on() function in axes module of matplotlib library is used to display minor ticks on the axes.
Syntax:
Axes.minorticks_on(self)
Below examples illustrate the matplotlib.axes.Axes.minorticks_on() function in matplotlib.axes:
Example 1:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
import matplotlib.cm as cm
from matplotlib.collections import LineCollection
from matplotlib.ticker import MultipleLocator
with cbook.get_sample_data( 's1045.ima.gz' ) as dfile:
im = np.frombuffer(dfile.read(),
np.uint16).reshape(( 256 , 256 ))
fig, ax1 = plt.subplots()
im = np.ravel(im)
im = im[np.nonzero(im)]
im = im / ( 2 * * 20 - 1 )
ax1.hist(im, bins = 40 , color = "green" )
ax1.set_yticks([])
ax1.set_xlabel( 'Intensity (a.u.)' )
ax1.set_ylabel( 'MRI density' )
ax1.minorticks_on()
fig.suptitle('matplotlib.axes.Axes.minorticks_on() \
function Example\n\n', fontweight = "bold" )
plt.show()
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Output:
Example 2:
import matplotlib.pyplot as plt
import numpy as np
x = np.arange( 0.0 , 2 , 0.01 )
y1 = np.sin( 2 * np.pi * x)
y2 = 1.2 * np.sin( 4 * np.pi * x)
fig, (ax, ax1) = plt.subplots( 1 , 2 )
ax.fill_between(x, y1, y2, color = "green" ,
alpha = 0.6 )
ax.set_title( "Without minorticks_on()" )
ax1.fill_between(x, y1, y2, color = "green" ,
alpha = 0.6 )
ax1.minorticks_on()
ax1.set_title( "With minorticks_on()" )
fig.suptitle('matplotlib.axes.Axes.minorticks_on()\
function Example\n\n', fontweight = "bold" )
plt.show()
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Output:
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