[ Identification | Description | Examples | Input parameters | Links ]

The `KDSource` Component

Distributional source, based on a MCPL-format particle list, on which the Kernel Density Estimation (KDE) method is applied.

Identification

Site:
Author: O.I.Abbate, N.S.Schmidt, updates for McStas by T.Kittelmann and P.Willendrup
Origin: Instituto Balseiro
Date: Dec 2022 / May 2026

Description

Distributional source, based on a MCPL-format particle list, on which
the Kernel Density Estimation (KDE) method is applied.

It allows sampling more particles than the number present in a virtual,
previously generated virtual source, without repeating samples, controlled via the nloop
input parameter.

To function, this component requires a KDSource installation v.2.0.2 or later, as
distributed on conda-forge and pypi and included with (conda-based) McStas 3.7.0 or later.

As inputs the component needs access to all of:

The original MPCL file
Outputs of a KDSource-analyzed / optimized KDE source:

An XML parameter-file containing the needed configuration
A "bandwidth" file (source_bws)


For information on performing KDSource analysis, please refer to the KDSource example
notebooks and the KDSource online documentation (links below).

Examples

(Test cases in bold)

Input parameters

Parameters in boldface are required; the others are optional.

Name	Unit	Description	Default
filename	str	Name of the XML parameters file containing KDSource definition.	0
Emin	meV	Lower energy bound. Particles found in the MCPL-file below the limit are skipped.	0
Emax	meV	Upper energy bound. Particles found in the MCPL-file above the limit are skipped.	FLT_MAX
nloop	int	Number of times to loop through the file.	1

AT (	,	,		) RELATIVE
ROTATED (	,	,		) RELATIVE

The KDSource Component

Identification

Description

Examples

Input parameters

Links

The `KDSource` Component