vector-fftw-0.1.3.7: A binding to the fftw library for one-dimensional vectors.

Numeric.FFT.Vector.Unnormalized

Description

Raw, unnormalized versions of the transforms in fftw.

Note that the forwards and backwards transforms of this module are not actually inverses. For example, run idft (run dft v) /= v in general.

Synopsis

# Creating and executing Plans

run :: (Vector v a, Vector v b, Storable a, Storable b) => Transform a b -> v a -> v b Source #

Create and run a Plan for the given transform.

plan :: (Storable a, Storable b) => Transform a b -> Int -> Plan a b Source #

Create a Plan of a specific size. This function is equivalent to planOfType Estimate.

execute :: (Vector v a, Vector v b, Storable a, Storable b) => Plan a b -> v a -> v b Source #

Run a plan on the given Vector.

If planInputSize p /= length v, then calling execute p v will throw an exception.

# Complex-to-complex transforms

A forward discrete Fourier transform. The output and input sizes are the same (n).

y_k = sum_(j=0)^(n-1) x_j e^(-2pi i j k/n)

A backward discrete Fourier transform. The output and input sizes are the same (n).

y_k = sum_(j=0)^(n-1) x_j e^(2pi i j k/n)

# Real-to-complex transforms

A forward discrete Fourier transform with real data. If the input size is n, the output size will be n div 2 + 1.

A backward discrete Fourier transform which produces real data.

This Transform behaves differently than the others:

• Calling plan dftC2R n creates a Plan whose output size is n, and whose input size is n div 2 + 1.
• If length v == n, then length (run dftC2R v) == 2*(n-1).

# Real-to-real transforms

The real-even (DCT) and real-odd (DST) transforms. The input and output sizes are the same (n).

A type-1 discrete cosine transform.

y_k = x_0 + (-1)^k x_(n-1) + 2 sum_(j=1)^(n-2) x_j cos(pi j k/(n-1))

A type-2 discrete cosine transform.

y_k = 2 sum_(j=0)^(n-1) x_j cos(pi(j+1/2)k/n)

A type-3 discrete cosine transform.

y_k = x_0 + 2 sum_(j=1)^(n-1) x_j cos(pi j(k+1/2)/n)

A type-4 discrete cosine transform.

y_k = 2 sum_(j=0)^(n-1) x_j cos(pi(j+1/2)(k+1/2)/n)

## Discrete sine transforms

A type-1 discrete sine transform.

y_k = 2 sum_(j=0)^(n-1) x_j sin(pi(j+1)(k+1)/(n+1))

A type-2 discrete sine transform.

y_k = 2 sum_(j=0)^(n-1) x_j sin(pi(j+1/2)(k+1)/n)

A type-3 discrete sine transform.

y_k = (-1)^k x_(n-1) + 2 sum_(j=0)^(n-2) x_j sin(pi(j+1)(k+1/2)/n)

A type-4 discrete sine transform.

y_k = sum_(j=0)^(n-1) x_j sin(pi(j+1/2)(k+1/2)/n)