.. algorithm:: .. summary:: .. relatedalgorithms:: .. properties:: Description ----------- |Example of RAW GEM data focused across the 5 detector banks| Given an InputWorkspace and a Grouping filename, the algorithm performs the following: #. The calibration file is read and a map of corresponding udet-group is created. #. The algorithm determine the X boundaries for each group as the upper and lower limits of all contributing detectors to this group and determine a logarithmic step that will ensure preserving the number of bins in the initial workspace. #. All histograms are read and rebinned to the new grid for their group. #. A new workspace with N histograms is created. Within the :ref:`CalFile ` any detectors with the 'select' flag can be set to zero or with a group number of 0 or -ve groups are not included in the analysis. Since the new X boundaries depend on the group and not the entire workspace, this focusing algorithm does not create overestimated X ranges for multi-group instruments. However it is important to remember that this means that this algorithm outputs a :ref:`ragged workspace `. Some 2D and 3D plots will not display the data correctly. The DiffractionFocussing algorithm uses GroupDetectors algorithm to combine data from several spectra according to GroupingFileName file which is a :ref:`CalFile `. For EventWorkspaces ################### The algorithm can be used with an :ref:`EventWorkspace ` input, and will create an EventWorkspace output if a different workspace is specified. The main difference vs. using a Workspace2D is that the event lists from all the incoming pixels are simply appended in the grouped spectra; this means that you can rebin the resulting spectra to finer bins with no loss of data. In fact, it is unnecessary to bin your incoming data at all; binning can be performed as the very last step. .. |Example of RAW GEM data focused across the 5 detector banks| image:: /images/GEM_Focused.png .. categories:: .. sourcelink::