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%.COPYRIGHT (c) 1990-2005 European Southern Observatory
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%.KEYWORDS MIDAS, help files, INTERPOLATE/TI
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%.PURPOSE On-line help file for the command: INTERPOLATE/TI
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%.VERSION 1.0 29-MAY-1987 : Creation, JDP
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%----------------------------------------------------------------
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INTERPOLATE/TI 9-NOV-2005 JDP
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INTERPOLATE/TI outima intab i,d refima [s] [degree]
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interpolate Image to Image
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Spline interpolation of 1D data; table to image transformation.
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INTERPOLATE/TI outima intab i,d refima [s] [degree]
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outima = name of 1-dim output image, will be created by
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intab = name of input table
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refima = reference image;
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this image must have the desired start, step value
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in descr. START and STEP
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i = column reference for independent variable
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d = column reference for dependent variable
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s = smoothness parameter (default 1.)
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degree = degree of spline, max. 5
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(default 3, cubic splines)
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INTERPOLATE/IT, REBIN/TI, CONVERT/TABLE
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This command should be used, if the new stepsize is NOT larger
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than the current stepsize in column `i' (i.e. the difference
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between adjacent rows).
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If the stepsize is larger, the command REBIN/TI should be used
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instead, since that is doing an integration.
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Values in the column used as independent variable must be
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monotonically increasing or decreasing. Best results are obtained,
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if they are increasing.
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The parameter s controls the degree of smoothing. This parameter
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has to be chosen carefully: too small s-values will result in
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an overfitting, too large s-values will produce an underfitting
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of the data. For s very large it returns the least-squares
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The number of spline knots and their positions are determined
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automatically, taking into account the specific behaviour of
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the function underlying the data.
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Ref.: P. Dierckxx, 1982, Computer Graphics and Image Processing,
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CREATE/IMAGE refima 1,2000 0.123,0.002 NODATA
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We don't need any data in the ref. frame.
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INTERPOLATE/TI resima intab :X,:Y refima 1. 3
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Create image `resima.bdf' from column :Y of table `intab.tbl'
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corresponding to :X resampled with stepsize 0.002.
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Smoothness = 1 and we use cubic splines.
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The delta in :X between adjacent rows is assumed to be
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larger than (or equal to) 0.002 (otherwise we should have
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used REBIN/TI instead).