Flucut

Purpose

Remove scatter from fluorescence EEM data.

Synopsis

Xnew = flucut(X,LowZero,LowMiss,TopZero,TopMiss,options);

Description

FLUCUT inserts a mixture of NaN and 0 values outside the data area of interest in an EEM (Excitation-Emission Matrix). FLUCUT may also be used to generate weights that can be used for deweighting scatter areas.

Inputs

• first = first input is this.

• X = X-array of EEMs. X is size IxJxK, where I is number of samples, J emissions and K excitations. X has to be a DataSet object where the axisscales contain wavelengths where X.axisscale{2} corresponds to emissions (emi) in nm and X.axisscale{3} corresponds to excitations (exci) in nm.

• LowZero = Wavelength (nm): X(emi < exci-LowZero) are set to zero. Zeros here are good for speeding up, but can lead to artifacts if the zeros are too close to the emi==exci line. Use LowMiss.
• LowMiss = Wavelength (nm): the region where emi <= exci+LowMiss(1) are set to missing (i.e., NaN) to remove scatter. If LowMiss is a 2 element vector, then only the region down to emi >= exci-LowMiss(2) are also set to missing. However, the zeros set by LowZero supercede the missing setting.
• TopZero = nm above emi==2*exci which is set to zero {default is NaN meaning no zeros (to avoid second order signal to be biased to be zero)}.
• TopMiss = Similar to LowMiss but for emi==2*exci.

NOTE: In general, for all the above, setting the input to NaN, implies that the functionality is not imposed.
NOTE: The following inputs govern how data are set to missing and zero.

LowZero and LowMiss are used to account for Rayleigh scatter, and

TopZero and TopMiss are used to accound for 2nd order scatter.

Outputs

• Xnew = New X-array with inserted NaN (for missing) and 0-values. Columns with only missing values are removed.

Options

options = a structure array with the following fields:

• plots: [ 'off' | {'on'} ], governs level of plotting.
• MakeWts: [ {'off'} | 'on' ] If 'on', weights will be given that can be used to downweight areas of scatter e.g., in PARAFAC models. The weights will be held in the output dataset field 'userdata'. {default = 'off', do not make weights}

Example

load dorrit

Xnew = flucut(EEM,20,[20 20],NaN,NaN);

See Also

parafac