Matplotlib.axes.Axes.clabel() in Python

01 Jul, 2022
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.
The Axes.clabel() function in axes module of matplotlib library is used to label a contour plot.
Syntax:
Axes.clabel(self, CS, *args, **kwargs)
Parameters: This method accept the following parameters that are described below:
cs : This parameter is the ContourSet to label.
fontsize : This parameter is the size in points.
gridsize : This parameter represents the number of hexagons in the x-direction or both direction.
colors : This parameter is used to color the label
inline : This parameter removes the underlying contour where the label is placed.
inline_spacing : This parameter is space in pixels to leave on each side of label when placing inline.
marginals : This parameter is used to plot the marginal density as colormapped rectangles along the bottom of the x-axis and left of the y-axis.
fmt : This parameter is the format string for the label.
manual : This parameter is used to place the contour label using mouse.
rightside_up : This parameter is used to rotate the label.
use_clabeltext : This parameter is used to create labels. ClabelText recalculates rotation angles of texts.
Returns: This returns the following:
labels:This returns the list of Text instances for the labels.
Below examples illustrate the matplotlib.axes.Axes.clabel() function in matplotlib.axes: 
Example-1: 
Python3
# Implementation of matplotlib functionimport numpy as npimport matplotlib.pyplot as pltimport matplotlib.ticker as tickerimport matplotlib delta = 2.5x = np.arange(-13.0, 13.0, delta)y = np.arange(-12.0, 12.0, delta)X, Y = np.meshgrid(x, y)Z = (np.exp(-X**2 - Y**2) - np.exp(-(X - 1)**2 - (Y - 1)**2)) * 3 fig1, ax1 = plt.subplots()CS1 = ax1.contour(X, Y, Z) fmt = {}strs = ['1', '2', '3', '4', '5', '6', '7']for l, s in zip(CS1.levels, strs):    fmt[l] = sax1.clabel(CS1, CS1.levels, inline = True,           fmt = fmt, fontsize = 10) ax1.set_title('matplotlib.axes.Axes.clabel() Example')plt.show()
Output:
  
Example-2: 
Python3
# Implementation of matplotlib functionimport matplotlibimport numpy as npimport matplotlib.cm as cmimport matplotlib.pyplot as plt delta = 0.025x = np.arange(-3.0, 3.0, delta)y = np.arange(-2.0, 2.0, delta)X, Y = np.meshgrid(x, y)Z = (np.exp(-X**2 - Y**2) - np.exp(-(X - 1)**2 - (Y - 1)**2)) * 3 fig, ax = plt.subplots()im = ax.imshow(Z, interpolation ='bilinear', origin ='lower',               cmap ="Greens", extent =(-3, 3, -2, 2)) levels = np.arange(-1.2, 1.6, 0.2)CS = ax.contour(Z, levels, origin ='lower', cmap ='spring',                linewidths = 2, extent =(-3, 3, -2, 2))zc = CS.collections[6]plt.setp(zc, linewidth = 4) ax.clabel(CS, levels[1::2], inline = 1, fmt ='% 1.1f',          fontsize = 14) CB = fig.colorbar(CS, shrink = 0.8, extend ='both')CBI = fig.colorbar(im, orientation ='horizontal',                   shrink = 0.8) ax.set_title('matplotlib.axes.Axes.clabel() Example')plt.show()
Output:
 
sidhanthnandansaaho
Python-matplotlib
Python
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