Skip to content
Related Articles

Related Articles

Improve Article
Save Article
Like Article

numpy.interp() function – Python

  • Difficulty Level : Hard
  • Last Updated : 11 Jun, 2020

numpy.interp() function returns the one-dimensional piecewise linear interpolant to a function with given discrete data points (xp, fp), evaluated at x.

Syntax : numpy.interp(x, xp, fp, left = None, right = None, period = None)

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning - Basic Level Course

Parameters :
x : [array_like] The x-coordinates at which to evaluate the interpolated values.
xp: [1-D sequence of floats] The x-coordinates of the data points, must be increasing if the argument period is not specified. Otherwise, xp is internally sorted after normalizing the periodic boundaries with xp = xp % period.
fp : [1-D sequence of float or complex] The y-coordinates of the data points, same length as xp.
left : [optional float or complex corresponding to fp] Value to return for x < xp[0], default is fp[0].
right : [optional float or complex corresponding to fp] Value to return for x > xp[-1], default is fp[-1].
period : [None or float, optional] A period for the x-coordinates. This parameter allows the proper interpolation of angular x-coordinates. Parameters left and right are ignored if the period is specified.



Return : [float or complex or ndarray] The interpolated values, same shape as x.

Code #1 :




# Python program explaining
# numpy.interp() function
       
# importing numpy as geek 
import numpy as geek 
   
x = 3.6
xp = [2, 4, 6]
fp = [1, 3, 5]
   
gfg = geek.interp(x, xp, fp)
  
print (gfg)

Output :

2.6

 
Code #2 :




# Python program explaining
# numpy.interp() function
       
# importing numpy as geek 
import numpy as geek 
   
x = [0, 1, 2.5, 2.72, 3.14]
xp = [2, 4, 6]
fp = [1, 3, 5]
   
gfg = geek.interp(x, xp, fp)
  
print (gfg)

Output :

[1.   1.   1.5  1.72 2.14]



My Personal Notes arrow_drop_up
Recommended Articles
Page :