TransformMD v1¶

TransformMD dialog.

Table of Contents

Summary
Properties
Description
- Notes
- Performance Notes
Source

Summary ¶

Scale and/or offset the coordinates of a MDWorkspace

Properties ¶

Name	Direction	Type	Default	Description
InputWorkspace	Input	IMDWorkspace	Mandatory	Any input MDWorkspace.
Scaling	Input	dbl list	1	Scaling value multiplying each coordinate. Default 1. Either a single value or a list for each dimension.
Offset	Input	dbl list	0	Offset value to add to each coordinate. Default 0. Either a single value or a list for each dimension.
OutputWorkspace	Output	IMDWorkspace	Mandatory	Name of the output MDWorkspace.

Description ¶

This algorithm applies a simple linear transformation to a MDWorkspace or MDHistoWorkspace. This could be used, for example, to scale the Energy dimension to different units.

Each coordinate is tranformed so that $x'_d = (x_d * s_d) + o_d$ where:

d : index of the dimension, from 0 to the number of dimensions
s : value of the Scaling parameter
o : value of the Offset parameter.

You can specify either a single value for Scaling and Offset, in which case the same m_scaling or m_offset are applied to each dimension; or you can specify a list with one entry for each dimension.

The relationship between the workspace and the original MDWorkspace, for example when the MDHistoWorkspace is the result of BinMD v1, is lost. This means that you cannot re-bin a transformed MDHistoWorkspace.

No units are not modified by this algorithm.

Performance Notes ¶

Performing the operation in-place (input=output) is always faster because the first step of the algorithm if NOT in-place is to clone the original workspace.
For MDHistoWorkspaces done in-place, TransformMD is very quick (no data is modified, just the coordinates).
For MDWorkspaces, every event’s coordinates gets modified, so this may take a while for large workspaces.
For file-backed MDWorkspaces, you will find much better performance if you perform the change in-place (input=output), because the data gets written out to disk twice otherwise.

Categories: Algorithms | MDAlgorithms