Parallel (sitelle.parallel)

Introduction

This module contains helper methods for parallelization of process. Because we mostly work on ndarray and DataFrame, we build three main parallelized methods:

• parallel_apply_along_axis that mimicks numpy.apply_along_axis() signature
• parallel_apply_over_frame to iterate over 2D frames of the datacubes (analyse images)
• parallel_apply_over_df that mimicks pandas.DataFrame.apply

Reference/API

sitelle.parallel Module

Functions

available_cpu_count()	Number of available virtual or physical CPUs on this system, i.e.
parallel_apply_along_axis(func1d, axis, arr, …)	Apply a function to 1-D slices along the given axis.
apply_over_frames(func2d, cube, *args, **kwargs)	Iterates over the z dimension of a cube to apply a function on each frame (i.e.
parallel_apply_over_frames(func2d, cube, …)	Iterates over the z dimension of a cube to apply a function on each frame (i.e.
parallel_apply_over_df(df, func[, axis, …])	Iterates over a pandas Dataframe to apply a function on each line, taking advantage of multiple cores.