Derivativecolumns

Purpose

The "Derivative Columns (SavGol)" preprocessing method performs Savitzky-Golay smoothing and differentiation on columns.

Synopsis

[y_hat,cm] = savgol(y,width,order,deriv,options)

Description

DerivativeColumns performs Savitzky-Golay smoothing and differentation to the columns of an input matrix by transposing the input matrix before applying SAVGOL. See savgol for details of SAVGOL.

Options

options = a structure array with the following fields:

• useexcluded: [ {'true'} | 'false' ], governs how excluded data is handled by the algorithm.

If 'true', excluded data is used when handling data on the edges of the excluded region (unusual excluded data may influence nearby non-excluded points).

When 'false', excluded data is never used and edges of excluded regions are handled like edges of the spectrum (may introduce edge artifacts for some derivatives).

• tails: ['traditional' | {'polyinterp'} | 'weighted'], governs how edges of data and excluded regions are handled.

'traditional' is an older approach and isn't recommended.

'polyinterp' and 'weighted' provide smoother edge transitions.

'weighted' uses '1/d' window weighting. It is less affected by end-effects than 'traditional' and 'polyinterp'.

• wt: [ {' '} | '1/d' | [1xwidth] ] allows for weighted least-squares when fitting the polynomials.

' ' (empty) provides usual (unweighted) least-squares.

'1/d' weights by the inverse distance from the window center, or

a 1 by width vector with values 0<wt<=1 allows for custom weighting.

See Also

savgol