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.matshow() Function
The Axes.matshow() function in axes module of matplotlib library is also used to plot the values of a 2D matrix or array as color-coded image.
Syntax:
Axes.matshow(self, Z, **kwargs)Parameters: This method accept the following parameters that are described below:
- z: This parameter contains the matrix which is to be displayed.
Returns: This returns the following:
- image : This returns the AxesImage
Below examples illustrate the matplotlib.axes.Axes.imshow() function in matplotlib.axes:
Example-1:
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np from matplotlib.colors import LogNorm dx, dy = 0.015 , 0.05 y, x = np.mgrid[ slice ( - 4 , 4 + dy, dy), slice ( - 4 , 4 + dx, dx)] z = ( 1 - x / 3. + x * * 5 + y * * 5 ) * np.exp( - x * * 2 - y * * 2 ) z = z[: - 1 , : - 1 ] z_min, z_max = - np. abs (z). max (), np. abs (z). max () fig, ax = plt.subplots() c = ax.matshow(z, cmap = 'Greens' , vmin = z_min, vmax = z_max, extent = [x. min (), x. max (), y. min (), y. max ()], interpolation = 'nearest' , origin = 'lower' ) fig.colorbar(c, ax = ax) ax.set_title( 'matplotlib.axes.Axes.matshow() Examples\n' ) plt.show() |
Output:
Example-2:
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np def samplemat(dims): """Make a matrix with all zeros and increasing elements on the diagonal""" aa = np.zeros(dims) for i in range ( min (dims)): aa[i, i] = np.sin(i * * 3 ) * * 2 + i * * 3 return aa # Display matrix fig, ax = plt.subplots() ax.matshow(samplemat(( 9 , 9 )), cmap = "Accent" ) ax.set_title( 'matplotlib.axes.Axes.matshow() Examples\n' ) plt.show() |
Output: