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polydft

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Returns the chirped z-transform of a set of data. The polydft function is very similar to a two-dimensional czt function with the difference being that the E function does not need to be finely sampled and only providing the vertices of a polygon as input range of the function would be enough to perform the transform. The only limit however is that E is considered constant within the limits of the polygon. The polygon mesh can be created using the inpoly function.  

 

 

Supported Product: FDTD, MODE, DEVICE, INTERCONNECT

 

Syntax

Description

out = polydft(E,kx,ky);

Returns the two dimensional chirped z-transform of E. kx and ky must be linearly spaced sets of wavenumbers but can cover any range.

 

 

Example

This example demonstrates two different approaches for calculating the discrete Fourier transform (DFT) of a piecewise constant 2D function on the xy-plane. The function is defined as having the value of one inside the polygonal area specified by the vertices poly_vert. One approach uses the polydft command directly on the polygon vertices, the other approach uses a finely staircased representation of the function and the czt command.

# -------

# Inputs:

# -------

 

# xy-plane region

x_span = y_span = 5.0;

# area inside the above region where function is nonzero

poly_vert = [0.25*x_span,0.35*y_span;

             0.50*x_span,0.15*y_span;

             0.75*x_span,0.35*y_span;

             0.75*x_span,0.65*y_span;

             0.50*x_span,0.85*y_span;

             0.25*x_span,0.65*y_span];

# grid for staircasing the above polygon

Nx = Ny = 2^8;

 

# ---------

# Function:

# ---------

 

delta_x = x_span/Nx;

delta_y = y_span/Ny;

x = delta_x*linspace(0.0,Nx-1,Nx);

y = delta_y*linspace(0.0,Ny-1,Ny);

X = meshgridx(x,y);

Y = meshgridy(x,y);

poly_fun = inpoly(poly_vert,X,Y);

image(x,y,poly_fun,"x","y","staircased function");

 

# ----

# DFT:

# ----

 

# using the czt command

delta_fx = 1.0/(Nx*delta_x);

delta_fy = 1.0/(Ny*delta_y);

fx = delta_fx*linspace(-0.5*(Nx-1),0.5*(Nx-1),Nx);

kx = 2.0*pi*fx;

fy = delta_fy*linspace(-0.5*(Ny-1),0.5*(Ny-1),Ny);

ky = 2.0*pi*fy;

poly_fun_czt = czt(poly_fun,x,y,kx,ky)/(Nx*Ny);

image(kx,ky,abs(poly_fun_czt),"kx","ky","czt");

# using the polydft command

Kx = meshgridx(kx,ky);

Ky = meshgridy(kx,ky);

poly_fun_polydft = polydft(poly_vert,Kx,Ky)/(x_span*y_span);

image(x,y,abs(poly_fun_polydft),"kx","ky","polydft");

 

# ------------------------

# Function Reconstruction:

# ------------------------

 

# from czt

poly_fun_from_czt = czt(poly_fun_czt,-kx,-ky,x,y);

image(x,y,real(poly_fun_from_czt),"x","y","reconstruction from czt");

# from polydft

poly_fun_from_polydft = czt(poly_fun_polydft,-kx,-ky,x,y);

image(x,y,real(poly_fun_from_polydft),"x","y","reconstruction from polydft"); 

 

The staircased function used for transformation

The staircased function used for transformation

chirped z-transform of the function using czt

chirped z-transform of the function using czt

chirped z-transform of the function using polydft

chirped z-transform of the function using polydft

reconstructed function from czt

reconstructed function from czt

reconstructed function from polydft

reconstructed function from polydft

 

See Also

Functions, czt, inpoly, fft, fftw

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