# Inverse Distance Weighted (IDW) or Simple Moving Average (SMA) INTERPOLATION (Scripts) 1.0

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• Last update: 5 years ago
• Price: Free |
• Operating system: Linux, Mac OS X, Win All, BSD, Solaris
• Publisher: Giuliano Langella (3 other programs)
See full specifications

## Inverse Distance Weighted (IDW) or Simple Moving Average (SMA) INTERPOLATION (Scripts) Publisher's description

### This function computes at (Xi,Yi) unknown locations the IDW (w<0) or the SMA (w=0) predictions using r1 neighbourhood type ('n':number of points; 'r':radius) and r2 neighbourhood size from Vc measured values at (Xc,Yc) loca

This function computes at (Xi,Yi) unknown locations the IDW (w<0) or the SMA (w=0) predictions using r1 neighbourhood type ('n':number of points; 'r':radius) and r2 neighbourhood size from Vc measured values at (Xc,Yc) locations.

OUTPUTS
Vi: (mandatory) [PxQ] gIDW interpolated values
--> P=1, Q=1 yields interpolation at one
point
--> P>1, Q=1 yields interpolation at a
vector of points
--> P>1, Q>1 yields interpolation at a
(ir)regular grid of points
========================================

INPUTS
Xc: (mandatory) [Nx1] x coordinates of known points
Yc: (mandatory) [Nx1] y coordinates of known points
Vc: (mandatory) [Nx1] known values at [Xc, Yc] locations
Xi: (mandatory) [PxQ] x coordinates of points to be interpolated
Yi: (mandatory) [PxQ] y coordinates of points to be interpolated
w: (mandatory) [scalar] distance weight
--> w<0, for Inverse Distance Weighted
interpolation [IDW]
--> w=0, for Simple Moving Average (only
if neighorhood size is local and not
global) [SMA]
r1: (optional) [string] neighbourhood type
--> 'n' (default) number of neighbours
r2: (optional) [scalar] neighbourhood size
--> number of neighbours, if r1=='n'
default is length(Xc)
default is largest distance between known points
========================================

SYNTAX
--- IDW ---
all inputs:
Vi = gIDW(Xc,Yc,Vc,Xi,Yi,-2,'n',30);
6 inputs:
Vi = gIDW(Xc,Yc,Vc,Xi,Yi,-2);
--> r1='n'; r2=length(Xc);
7 inputs:
Vi = gIDW(Xc,Yc,Vc,Xi,Yi,-2,'n');
--> r2=length(Xc);
Vi = gIDW(Xc,Yc,Vc,Xi,Yi,-2,'r');
--> r2=largest distance between know points [Xi,Yi] (see D1 calculation)
--- SMA ---
Vi = gIDW(Xc,Yc,Vc,Xi,Yi,0,'n',10);
--- Spatial Map ---
Vi = gIDW(Xc,Yc,Vc,Xi,Yi,-2,'n',10);
-with Xi and Yi 2D arrays of coordinates relative to an (ir)regular
grid.
========================================

EXAMPLES
Interpolation at one point location:
Vi = gIDW([1:1:10]',[2:2:20]',rand(10,1)*100,5.5,11,-2,'n');
---
Interpolation at a regular grid of unknown points:
XYc = [1:1:10]';
Vc = rand(10,1)*100;
Xi = rand(50,50)*10;
Yi = rand(50,50)*10;
[Xi,Yi] = meshgrid(XYc);
Vi = gIDW(XYc,XYc,Vc,Xi,Yi,-2,'r',3);
hold on
mapshow(Xi,Yi,Vi,'DisplayType','surface')
colormap gray
scatter(XYc,XYc,Vc,'filled','MarkerFaceColor','g','MarkerEdgeColor','y')
axis([0,11,0,11])
hold off

#### System Requirements:

MATLAB 7.7 (R2008b)
Program Release Status: New Release
Program Install Support: Install and Uninstall

#### Inverse Distance Weighted (IDW) or Simple Moving Average (SMA) INTERPOLATION (Scripts) Tags:

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