ztrans

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+ | ====== ztrans ====== | ||

+ | ===== Motivation ===== | ||

+ | Under certain circumstances (e.g. data that is arbitrarily scaled and comes from several sources has to be compared), one way to normalize (re-scale) the data is to apply z-transformation (setting the mean of values in the desired dimension to 0 and the standard deviation to 1). | ||

+ | |||

+ | ===== Function reference ('help ztrans') ===== | ||

+ | <file> ztrans - perform z-transformation on time course | ||

+ | |||

+ | FORMAT: [ztc, zf, zsh] = ztrans(tc [, dim [, tp]]) | ||

+ | |||

+ | Input fields: | ||

+ | |||

+ | tc time course data | ||

+ | dim temporal dimension (default: first non-singleton) | ||

+ | tp time points (indices of dim to use for normalization) | ||

+ | |||

+ | Output fields: | ||

+ | |||

+ | ztc z-transformed time course | ||

+ | zf z-transformation factor | ||

+ | zsh z-transformation shift | ||

+ | |||

+ | See also psctrans</file> | ||

+ | |||

+ | ===== Usage examples ===== | ||

+ | * z-transforming a single time-course (e.g. of a region or voxel):<code matlab>ztc = ztrans(tc);</code> | ||

+ | * z-transformation of an entire VTC (ensuring that dimension is 1):<code matlab>vtc.VTCData = ztrans(vtc.VTCData, 1);</code> | ||

+ | * z-transformation of 4D-NII VoxelData (ensuring that dimension is 4):<code matlab>nii.VoxelData = ztrans(nii.VoxelData, 4);</code> | ||

+ | * also obtaining the information about the scaling factor and shift:<code matlab>[ztc, zfactor, zshift] = ztrans(tc);</code> | ||

+ | * only using values where no experimental condition in an SDM is active:<code matlab>% find timepoints to use | ||

+ | tp = all(abs(sdm.SDMMatrix(:, 1:sdm.FirstConfoundPredictor-1)) < 0.1, 2); | ||

+ | |||

+ | % apply z-transformation with those as normalization basis | ||

+ | vtc.VTCData = ztrans(vtc.VTCData, 1, tp);</code> |

ztrans.txt ยท Last modified: 2010/06/11 02:04 by jochen