Matplotlib.pyplot.sci() in Python

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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.sci() Function

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

Syntax: matplotlib.pyplot.sci(im)

Parameters:

im: This image will be the target of colormap functions.

Returns: This method does not return any value.

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

Example 1:

import matplotlib.pyplot as plt 
from matplotlib.collections import LineCollection 
from matplotlib import colors as mcolors 
  
import numpy as np 
  
N = 50
x = np.arange(N) 
   
ys = [x + i for i in x] 
   
fig, ax = plt.subplots() 
ax.set_xlim(0, 20) 
ax.set_ylim(0, 20) 
   
line_segments = LineCollection([np.column_stack([x, y]) for y in ys], 
                               linewidths =(0.5, 1, 1.5, 2), 
                               linestyles ='dashed', color ="#eeffdd") 
  
line_segments.set_array(1/(x + 1)) 
ax.add_collection(line_segments) 
line_segments.set_array(x) 
  
plt.sci(line_segments)   
plt.title('matplotlib.pyplot.sci() Example') 
  
plt.show() 

Output:

Example 2:

import matplotlib.pyplot as plt 
from matplotlib.collections import EventCollection 
from matplotlib.collections import LineCollection 
import numpy as np 
   
np.random.seed(19680801) 
xvalue = np.random.random([2, 10]) 
xvalue1 = xvalue[0, :] 
xvalue2 = xvalue[1, :] 
xvalue1.sort() 
xvalue2.sort() 
   
yvalue1 = xvalue1 ** 4
yvalue2 = 1 - xvalue2 ** 6
   
fig = plt.figure() 
ax = fig.add_subplot(1, 1, 1) 
ax.plot(xvalue1, yvalue1, color ='tab:blue') 
ax.plot(xvalue2, yvalue2, color ='tab:green') 
   
xresult1 = EventCollection(xvalue1, color ='tab:blue') 
yresult1 = EventCollection(yvalue1, color ='tab:blue', 
                           orientation ='vertical') 
ax.add_collection(xresult1) 
ax.add_collection(yresult1) 
  
plt.sci(xresult1)   
plt.title('matplotlib.pyplot.sci() Example') 
  
plt.show() 