CCG_IWD1x - Combines data lines using the dispersion of the intensity-weighted co-ordinate

Description:

This routine accepts an array consisting of a series of (vectorised) lines of data and their co-ordinates. For each pixel the subroutine forms the weighted dispersion of the co-ordinate and an estimated variance along a line of data. The weights are the data values and their inverse variances. The output co-ordinate dispersions are returned in the array RESULT. The output variances in RESVAR are the standard error of RESULT.

Invocation:

CALL CCG_IWD1x( NPIX, NLINES, STACK, VARS, COORDS, MINPIX, RESULT, RESVAR, NCON, STATUS )

Arguments:

NPIX = INTEGER (Given)

The number of pixels in a line of data.

NLINES = INTEGER (Given)

The number of lines of data in the stack.

STACK( NPIX, NLINES ) = ? (Given)

The array of lines which are to be combined into a single line.

VARS( NPIX, NLINES ) = ? (Given)

The data variances.

COORDS( NPIX, NLINES ) = ? (Given)

The world co-ordinates.

MINPIX = INTEGER (Given)

The minimum number of pixels required to contribute to an output pixel.

RESULT( NPIX ) = ? (Returned)

The output line of data.

RESVAR( NPIX ) = ? (Returned)

The output variances.

NCON( NLINES ) = DOUBLE PRECISION (Returned)

The actual number of contributing pixels from each input line to the output line.

NBAD = INTEGER (Returned)

The number of bad values in the output RESULT array created while forming the statistics. It excludes those bad values whose corresponding values along the collapse axis are all bad.

STATUS = INTEGER (Given and Returned)

The global status.

Notes:

• There is a routine for each numeric data type: replace "x" in the routine name by D or R as appropriate. The STACK, VARS, COORDS, RESULT, and RESVAR arguments supplied to the routine must have the data type specified.

• It uses the corrected two-pass algorithm of Chan, T.F., Golub, G.H., & LeVeque, R.J. (1983). "Algorithms for computing the sample variance: Analysis and recommendations", American Statistician, 37(3), 242-247.