fluidfft

Efficient and easy Fast Fourier Transform for Python

The fft and related operators classes are in the two subpackages

fft2d 2d Fast Fourier Transform classes (fluidfft.fft2d) ============================================================
fft3d 3d Fast Fourier Transform classes (fluidfft.fft3d) ============================================================

The two commands fluidfft-bench and fluidfft-bench-analysis can be used to benchmark the classes on particular cases and computers. These commands are implemented in the following modules

bench Benchmarking of fluidfft classes (fluidfft.bench) ===========================================================
bench_analysis Load and plot benchmarks (fluidfft.bench_analysis) ============================================================

This root module provides two helper functions to import fft classes and create fft objects:

fluidfft.import_fft_class(method, raise_import_error=True)

Import a fft class.

Parameters:
method : str

Name of module or string characterizing a method. It has to correspond to a module of fluidfft. The first part “fluidfft.” of the module “path” can be omitted.

raise_import_error : {True}, False

If raise_import_error == False and if there is an import error, the function handles the error and returns None.

Returns:
The corresponding FFT class.
fluidfft.create_fft_object(method, n0, n1, n2=None)

Helper for creating fft objects.

Parameters:
method : str

Name of module or string characterizing a method. It has to correspond to a module of fluidfft. The first part “fluidfft.” of the module “path” can be omitted.

n0, n1, n2 : int

Dimensions of the real space array (in sequential).

Returns:
The corresponding FFT object.

Functions

create_fft_object(method, n0, n1[, n2]) Helper for creating fft objects.
import_fft_class(method[, raise_import_error]) Import a fft class.