File:Shepard interpolation 1 dimension.png
Summary
Category:Uploaded with en.wp upload wizard#79879489000001| Description |
English: This is a result from the shepard method applied to a 1 dimension function. |
| Date | |
| Source |
At IST (Lisbon, PT) with ubuntu+python+numpy+matplotlib |
| Author | Fmafunenga |
Licensing
I, the copyright holder of this work, hereby publish it under the following licenses:
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Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled GNU Free Documentation License. |
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Source code
The python code (numpy archive copy at the Wayback Machine, matplotlib) used to create this image:
import numpy as np
import matplotlib.pyplot as plt
def weight( pointA, pointB ):
p = 2.0 #this is the power parameter
rst = ( 1.0/( abs(pointA-pointB)**p ) )
return rst
def idw( xi, ui ):
xidw = np.arange(-4.0, 9.0, 0.01)
uidw = np.arange(-4.0, 9.0, 0.01)
for idx in range(len(xidw)):
denum = 0.0 ; num = 0.0
for i in range(len(xi)):
w = weight( xidw[idx], xi[i] )
denum += w
num += w*ui[i]
uidw[idx] = num / denum
return xidw, uidw
if __name__ == "__main__":
xi = [0.0, 1.0, 4.0, 5.0]
yi = [1.0, 2.0, 2.0, 1.0]
xidwr, yidwr = idw( xi, yi )
plt.plot( xi, yi, "ok",ms=10, lw=2, label="Samples" )
plt.plot( xidwr, yidwr, "-", label="IDW" )
plt.title( r"Shepard's interpolation in 1 dimension: $p=2$" )
plt.xlim((-4.1,9.1)) ; plt.xlabel(r"X")
plt.ylim((0.9,2.1)) ; plt.ylabel(r"U")
plt.legend() ; plt.grid() ; plt.show()
Category:Geostatistics
Category:Interpolation