- sddsbaseline
`sddsbaseline`()sddsbaseline -- Remove baselines from column data. Example application: determining the noise level in a video signal and subtracting it from the signal. - sddschanges
`sddschanges`()sddschanges -- Analyzes changes in column data from page to page in a file, relative to a reference file or the first page. Example application: finding changes in a waveform that is acquired repeatedly, where successive waveforms are on successive pages. - sddscliptails
`sddscliptails`()sddscliptails -- Remove tails from column data, where a tail is dubious data on either side of a peak. Example application: removing halo or noise tails from video images of beam spots. - sddsderiv
`sddsderiv`()sddsderiv -- Does numerical differentiation of multiple data columns versus a single column, with optional error propogation. - sddsinteg
`sddsinteg`()sddsinteg -- Does numerical integration of multiple data columns versus a single column, with optional error propogation. Example application: finding the field integral an accelerator magnet from a longitudinal field scan. - sddsinterp
`sddsinterp`()sddsinterp -- Does interpolation of multiple data columns as a function of a single column. Example application: finding the required current to obtain a desired excitation in a magnet, or interpolating a curve at positions given in a second file. - sddsnormalize
`sddsnormalize`()sddsnormalize -- Normalizes data in multiple columns using various types of normalization factors, determined from the data. - sddspeakfind
`sddspeakfind`()sddspeakfind -- Finds values of columns at locations of peaks in a single column. Example application: finding the position and height of peaks in a power spectrum obtained from a FFT. - sddsprocess
`sddsprocess`()sddsprocess -- Probably the most-used toolkit program, excepting`sddsplot`

. Allows creating new parameters and columns with user-specified equations; filtering and matching operations; printing, editing, scanning, and subprocess operations; statistical and waveform analysis of column data to produce new parameters; and much more. - sddssmooth
`sddssmooth`()sddssmooth -- Smooths columns of data using multipass nearest-neighbor averaging. Example application: reducing noise in a frequency spectrum prior to finding peaks. - sddszerofind
`sddszerofind`()sddszerofind -- Finds values of columns at locations of interpolated zeroes in a single column. Example application: finding zeros of a tabulated function that isn't known analytically.