Matplotlib.pyplot.clim() in Python (original) (raw)

Last Updated : 19 Apr, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface. There are various plots which can be used in Pyplot are Line Plot, Contour, Histogram, Scatter, 3D Plot, etc.

Matplotlib.pyplot.clim() Function

The clim() function in pyplot module of matplotlib library is used to set the color limits of the current image.

Syntax: matplotlib.pyplot.clim(vmin=None, vmax=None)

Parameters: This method accepts only two parameters.

Below examples illustrate the matplotlib.pyplot.clim() function in matplotlib.pyplot:

Example 1:

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 ()

im = plt.imshow(z, cmap = 'Greens' ,

`` vmin = z_min,

`` vmax = z_max,

`` extent = [x. min (),

`` x. max (),

`` y. min (),

`` y. max ()],

`` interpolation = 'nearest' ,

`` origin = 'lower' )

plt.clim(vmin = 0 , vmax = 2 )

plt.title( 'matplotlib.pyplot.clim Example' )

plt.show()

Output:

Example 2:

import matplotlib.pyplot as plt

import numpy as np

from matplotlib.colors import LogNorm

dx, dy = 0.015 , 0.05

x = np.arange( - 4.0 , 4.0 , dx)

y = np.arange( - 4.0 , 4.0 , dy)

X, Y = np.meshgrid(x, y)

extent = np. min (x), np. max (x), np. min (y), np. max (y)

Z1 = np.add.outer( range ( 8 ), range ( 8 )) % 2

plt.imshow(Z1,

`` cmap = "binary_r" ,

`` interpolation = 'nearest' ,

`` extent = extent, alpha = 1 )

def geeks(x, y):

`` return ( 1 - x / 2 + x * * 5 + y * * 6 ) * np.exp( - (x * * 2 + y * * 2 ))

Z2 = geeks(X, Y)

plt.imshow(Z2, cmap = "Greens" ,

`` alpha = 0.7 ,

`` interpolation = 'bilinear' ,

`` extent = extent)

plt.clim( 0 , 2 )

plt.title( 'matplotlib.pyplot.clim Example' )

plt.show()

Output:

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