The GONG DowNStream Pipeline (DNSPIPE)

Ed Anderson


Global Oscillation Network Group****
National Solar Observatory
National Optical Astronomy Observatories
This document was written in 1994. The text has not been updated.


This document presents the requirements for, and the detailed design of, the downstream pipeline processing of site-day calibrated velocity images to site-day l-nu diagrams.


Table of Contents

1. Introduction

2. Requirements
2.1. Software Functional Requirements
2.2. Software Performance Requirements
2.3. Input Data Specifications
2.3.1. Input Images
2.3.2. Input PLMTRIM Data
2.4. Output Data Specifications
2.4.1. Time Series
2.4.2. Power Spectra
2.4.3. l-nu Diagrams
2.5. Disk Space

3. Detailed Design
3.1. Schematic Program Flow
3.2. Algorithm and Design Considerations
3.2.1. Apodization
3.2.2. Remapping to Heliographic Coordinates
3.2.2.1. The Angles [equation] and [equation]
3.2.3. Temporal Filtering
3.2.4. Spherical Harmonic Transform
3.2.5. SHT Output

4. Algorithm Verification
4.1. Apodization
4.2. Heliographic Remapping
4.2.1. [equation] Correction Tests
4.2.2. P-angle Correction Tests
4.2.3. Offset Angle Correction Test
4.2.4. Elliptical Image Tests
4.3. Temporal Filtering
4.3.1. dnspipe.filter = 1
4.3.2. dnspipe.filter = 2
4.3.3. dnspipe.filter = block_filter_length
4.3.4. dnspipe.filter = filter_file_name
4.4. Spherical Harmonic Transform

5. Timing Results

Appendix I Software Installation
Appendix II DMAC Operator Instructions

1.  Introduction

      The most useful quality assessment diagnostics of the GONG pipeline are the l-nu diagrams which are produced during the last stage of the pipeline processing. Therefore, each site-day of data is to be processed through to l-nu diagrams in order to evaluate the quality of the data for that particular day of observation. Assuming that the l-nu diagrams indicate no problems, then the time series (which are the required science data products) will be archived in the DSDS.

2.  Requirements

2.1.  Software Functional Requirements

The requirements for the downstream pipeline processing are as follows:

1)
To process site-day calibrated velocity images through to l-nu diagrams. This involves remapping the velocity images into heliographic coordinates, filtering the remapped images to remove low frequency velocity gradients (i.e., isolate the p-mode signal), apodization, performing a Spherical Harmonic Transform (SHT) on the apodized detrended remapped images, creating the site day time series of spherical harmonic coefficients, gapfilling the time series, creating the site day power spectra, and creating the site-day l-nu diagrams.
2)
To archive the site-day time series in the DSDS tape library.
3)
To archive the site-day l-nu diagrams in the DSDS online library.
4)
To operate as part of the GONG Reduction and Analysis Software Package (GRASP) of IRAF.

2.2.  Software Performance Requirements

      The single performance requirement for this software is one of speed.

1)
The downstream pipeline software must process 10 site-days per working day.

This requirement is to be achieved by a combination of efficient software and multiple processors.

2.3.  Input Data Specifications

2.3.1.  Input Images

      The downstream processing code accepts as input 2-dimensional images (normally calibrated velocities) for which the following header keywords must be used.

[picture]

2.3.2.  Input PLMTRIM Data

      The PLMTRIM data file is an ASCII file generated by the GRASP task suntrans.plm_trim and used by many of the other SUNTRANS tasks. This file contains the heliographic remapping parameters, and a series of precomputed limits to be used by the SHT subroutine.

      A DMAC version of this file is to be stored in GRASP (grasplib) and will be referenced via a hidden task parameter. Users of GRASP will be able to change this parameter to refer to their own files should they desire different remapping parameters or L-max (the maximum value of the spherical harmonic degree l).

2.4.  Output Data Specifications

2.4.1.  Time Series

      The output time series images (which are archived) are to be assembled according to the scheme presented in the document GRASP Database Specifications (Anderson, 1988), (3-dimensional images, one image per l-value, with the x-axis being the time axis, the y-axis being m-value, band 1 holding the real part of the SHT and band 2 holding the imaginary part of the SHT) with the following header keywords.

[picture]

2.4.2.  Power Spectra

      The output power spectra images (which are not to be archived) are to be assembled according to the scheme presented in the document GRASP Database Specifications (Anderson, 1988), (3-dimensional images, one image per l-value, with the x-axis being frequency axis, the y-axis being m-value, band 1 holding the power spectrum and band 2 holding the phase spectrum) with the following header keywords.

[picture]

2.4.3.  l-nu Diagrams

      The output l-nu images (which are to be put in the online archive) are to be assembled according to the scheme presented in the document GRASP Database Specifications (Anderson, 1988), (2-dimensional images, with the x-axis being l-value, the y-axis being frequency) with the following header keywords.

[picture]

2.5.  Disk Space

      A single site-day will contain a maximum of 12 hours of data. This means that there could be a many as 720 images to be processed. The minimum amount of diskspace necessary to process these images is 643 MB (L-max=250).

[picture]

      In addition, 186 MB of disk space will be required to hold the FITS format time series images (assuming 32-bit FITS) for each site-day processed until the DSDS archive tape is written. Since the logical processing step would be to process a site-week, 1.3GB of disk is required to hold the FITS files waiting to be written to tape.

      Thus, the minimum amount of disk required to efficiently process a site-week of data is 1.94 GB.


3.  Detailed Design

      This section presents the detailed design of DNSPIPE. Many of the routines that DNSPIPE uses are modelled after tasks in the SUNTRANS package of GRASP. Therefore, algorithm descriptions of the spherical harmonic transform, heliographic interpolation and remapping will not be given in this document. What is discussed in this section is the overall schematic flow of the program and important specific design considerations to optimize efficiency.

3.1.  Schematic Program Flow

      The parameters for the task dnspipe are the following:

pi> lpar dnspipe
input =                 Input files
(trim_file = "pipeline$lib/plm250.sinlat") PLMTRIM's output ASCII trimming file
(offset = 90.)            Camera offset angle (degrees)
(pangle_cor = no)             Solar p-angle correction required?
(coude_cor = no)             Coude correction required (i.e., breadboard dat
(turret_cor = no)             Turret correction required (i.e., rotator off)?
(filter = "pipeline$lib/w21.fltr)Filter file name, or block filter length
(interp_type = "spline3")      Interpolant (nearest,linear,poly3,poly5,spline3
(geometry = "fndlmb")       Use geometry fndlmb|hgeom
(apod_type = "cos")          Apodization type (none|cos|kb|dc|cb)
(apod_par = 2.5)            Apodization parameter for kb or dc
(apod_cbr = 0.5)            Apodization radius for cosine-bell (cb)
  (ignore_mag = yes)            Ignore Magnetograms?
     (gapfill = yes)            Gap fill time series?
   (powerspec = yes)            Output Power Spectra?
     (lnuspec = yes)            Output L-Nu diagrams?
  (interp_out = no)             Output interpolated images?
 (detrend_out = no)             Output interpolated, detrended images?
    (apod_out = no)             Output apodized, interpolated, detrended images
    (sht_size = 20)             Size of SHT hold array
 (orientation = "counter")      Input image orientation (counter|clock)
        (mode = "ql") 

The three optional output switches (interp_out, detrend_out, apod_out) are to be used for the purpose of debugging the code, and more importantly, searching for bad images should the first pass through a data set produce dubious l-nu diagrams.

  • The Schematic Flow of the Pipeline

    3.2.  Algorithm and Design Considerations

    3.2.1.  Apodization

          Apodization is used to roll off the sharp edges of a data string prior to passing that data through a Fourier Transform in order to prevent large sidelobe structures in the output transformation.

          The method of apodization used by DNSPIPE follows that of Duvall's (1994) reduction of South Pole data. A unit power apodization image is created in heliographic coordinates. The remapped velocity images are multiplied by the apodization image prior to entry into the spherical harmonic transform subroutine.

          The price paid for apodizing is a broader central peak in the power spectrum. It is not yet clear which type of apodization produces the best results, or whether velocity data need to be apodized at all because there is a natural decrease in the observed velocities towards the limb of the image. Thus, DNSPIPE has five apodization options:
    

    DNSPIPE Apodization Options

    _______________________________________

    None: No apodization done.


    Cosine:
    Equal area apodization. Response has a narrow core and a high first sidelobe.


    Dolph-Chebychev
    Wider core, and low equal height sidelobes.


    Kaiser-Bessel
    Very wide core, very low sidelobes.


    Cosine Bell
    Very narrow core, but very high, ugly sidelobes. Also known as the Tukey window.



          The apodization image is calculated from a 512-square grid upon which a circular image (of value 1) is placed. All of the apodizations listed above are radially symmetric about the center of the disk image, and thus depend only on the angular distance from disk center. Consider a unit sphere projected onto the image plane to produce the observed disk image of radius Rd as shown in the figure below.

    [picture]

    The angular distance, rho, to each pixel in the disk image is given by:

    [picture]

    [picture]

    where

    [picture]

    The apodization windows are then given by:

    [picture]

    where the parameter Rcb is the fraction of the disk radius outside of which the window roll-off is to occur. The following figures are taken from Harris, et al. (1978), and show representative filter responses for the apodization window options discussed above.

    3.2.2.  Remapping to Heliographic Coordinates

          The input disk images are remapped to a heliographic latitude-longitude grid that is symmetric in latitude about the equator and symmetric in longitude about the central meridian (i.e., there are an even number of points in each grid dimension).

          The heliographic longitude grid is specified in the range [picture] The heliographic latitude grid is actually specified in colatitude, theta, (theta = 90-latitude) or sine-colatitude. The number of longitude points, longitude dispersion, number of colatitude/sine-colatitude points, colatitude/sine-colatitude dispersion, and latitude type (i.e., colatitude or sine-colatitude) are obtained from the PLM_TRIM file.

          The remapping to the heliographic grid is done using the image interpolator software of IRAF. For each point in the heliographic grid, (theta,L), the corresponding point on the input image, (x,y) must be calculated, and the value of the input image at that point is assigned to the output.

          Consider an orthogonal coordinate system with the origin at the center of the solar disk (the sub-earth point, E) of radius r0, the y-axis parallel to the solar rotation axis and increasing to the north, and the x-axis increasing to the west as shown in the diagram below.

    [equation]

    [picture]

    [equation]

    3.2.2.1. The Angles [equation] and [equation]

          The [equation] angle is determined by ephemeris calculations and depends on the time of observation. The ephemeris used by DNSPIPE was originally written by Lytle (1988) for reduction of Kitt Peak Vacuum Telescope data in the VTEL package of IRAF. This ephemeris ignores lunar and planetary perturbations.

          The angle [equation] in the equations given in the previous section is the angle (measured eastward on the sky) from the y-axis of the camera coordinate sytem to the heliographic north rotation axis. This angle is the sum of the P-angle (angle eastward between celestial north and heliographic north) and the camera offset angle which is determined by the configuration of the instrument. The configuration of the instrument depends on the type of light feed and/or camera mounting.

    GONG Breadboard Instrument (Coude Feed)

    For this instrument the camera is fixed on the observing table and is receiving light from a Heliostat light feed. The Coude angle (the angle eastward between the celestial north and the y-axis of the camera), and the P-angle are both calculated by the ephemeris program. The angle [equation] is:

    [equation]

    where the camera_offset angle is the remaining angle between celestial north and heliographic north at noon when P and Coude angles haven accounted for. This angle must be determined via from the data using the method described in the SUNTRANS User's Guide.

    GONG Prototype and Field Instrument (Alt-Alt Feed)

    In standard observing mode, the camera is mounted in a camera rotator which keeps the solar rotation axis aligned with the camera x-axis. Thus, the angle [equation] is:

    [equation]

    Should the camera rotator not be functioning for whatever reason, then

    [equation]

    where the turret_angle (the angle eastward between the celestial north and the y-axis of the camera) depends on the latitude of the observer (lat), the declination of the sun (dec) and the hour angle of sun (HA) and is given by

    [equation]

    where

    [equation]


    Taiwan Network Instrument (Equatorial Feed)

    For this type of light feed

    [equation]

    3.2.3.  Temporal Filtering

          The current thought on removing the low frequency signal from the velocity images is divided into a number of possible options. The main three are to use:

    a 21-minute block running mean, renormalized across data gaps,
    a 2-point backward difference filter,
    deterministic (i.e., modelled) detrending.
    

          dnspipe has been written in such a fashion, that it will accept for the parameter dnspipe.filter a number (positive integer), or a filename:

    dnspipe.filter = 1

    implies that the input images have already been deterministically detrended and therefore no temporal filter is required.
    dnspipe.filter = 2

    implies that a 2-point backward difference filter is to be used, where the filtered data at time slot t is given by:

    [equation]


    dnspipe.filter >= 3 (and odd)

    implies an equally weighted centered running mean filter, where the filtered data at time slot t is given by:

    [equation]


    dnspipe.filter = filter_file_name

    implies that a non-equally weighted filter is provided by the user in a text file, filter_file_name, where the first line is the number of filter elements (must be odd) and the remaining lines contain the filter weights (one per line, sum of which must equal 1.). The filtered data at time slot t is given by:

    [equation]

    3.2.4.  Spherical Harmonic Transform

          The SHT algorithm is described by Williams (1993) and won't be discussed in this document. The algorithm used by DNSPIPE is the same, although it's implementation differs slightly.

    3.2.5.  SHT Output

          The SHT subroutine processes a number of images (maximum of 20) simultaneously, holding all the data for these in memory. For each image, the output from the SHT subroutine is a complex coefficient array where ordered as follows:

    m=0                   m=1               m=l
    l=0 l=1 l=2 ... LMAX  l=1 l=2 ... LMAX  l=LMAX
    
    However, for efficient insertion into the time series files, this ordering needs to be:
    l=0 l=1     l=2           ... l=LMAX
    m=0 m=0 m=1 m=0 m=1 m=2       m=1 m=2 ... m=l
    
    This reordering is to be done in software (i.e., memory) just prior to exiting the SHT subroutine.

          For each value of l, there are (2l+1) m-elements that must be written to a single column in the time series for that value of l. Writing columns one (or several) at a time is highly inefficient. Also, most systems will only allow on the order of 60 disk files to be open at the same time, thus a lot of time would be spent opening and closing time series files each time a column is to be written.

          The solution devised for DNSPIPE is to transpose the complex coefficient array in memory and then write that array out to an intermediate disk image. These intermediate images will be 2-dimensional, complex, with the x-axis being time, and the y-axis being the l/m reordered SHT coefficient vector. The length of the x-axis is determined by the number of images that can be simultaneously worked on. Once the SHT calculation is completed for all the input images, all of the intermediate files are opened (at most 36 files open simultaneously if 20 images processed at a time) and a subroutine looping over l-values reads the appropriate data from each intermediate file and inserts that data into the time series for that l-value.

    Note:
    It may be possible to have all Lmax+1 (=251 for GONG) time series files open at one time. To do this requires a special compilation of the IRAF main. Testing of this will occur later this year when IRAF 2.10.3 is officially released. This is why the time series are created at the beginning of the execution of DNSPIPE.

    4.  Algorithm Verification

          Algorithm verification was done for several portions of the code. In most cases, verification was accomplished by executing DNSPIPE on artificial data sets that were specifically created to produce a certain output from a particular execution of the program.

    4.1.  Apodization

          To check the apodization, a set of artificial images of size 512x512, pixel value 1, and limb parameters:

    FNDLMBXC=                 256.
    FNDLMBYC=                 256.
    FNDLMBMI=                 200.
    FNDLMBMA=                 200.
    FNDLMBAN=                   0.
    
    were created and processed using each of the four apodization options and saving the remapped, apodized images. The output apodized remapped images were examined for symmetry and then Fourier transformed. The magnitude distribution of the Fourier transforms were compared to diagrams in §3.2.1.

          The magnitude distributions are shown below. Note that response of the windows is not quite the same as in §3.2.1 (especially for the Dolph-Chebychev window) due to a combination of the window being applied to two dimensions (i.e., with radial symmetry) and the remapping not extending all the way to the limb.

    picture

    picture

    4.2.  Heliographic Remapping

          Basic tests were performed to verify the B0-angle correction, the p-angle correction, camera offset angle correction and the input image orientation. Artificial images with specified B0 and p angles were created for these tests. DNSPIPE was used to reduce these images and output remapped images which could be examined for correctness. An artificial image is shown below for B0=20 degrees, xp=0, and xoffset=90.

    [picture]

    When these images are remapped to heliographic coordinates, the grid lines should become orthogonal and symmetric about the equator and the central meridian out to the solar limb. The fiducial marks should appear at the top (i.e., heliographic north) and right (i.e., heliographic west) of the output image. The results of the tests are given in the following sections.

    4.2.1.  [equation] Correction Tests

          For the B0-angle tests, the artificial images were given large B0 values to make it easy to analyse the output. The black corners in the following images are extrapolated data from beyond the visible limb. For real data, |B0|<=6 degrees.

    [equation]

    [equation]

    [equation]

    [equation]

    4.2.2.  P-angle Correction Tests

          For the P-angle tests, the artificial images were made with xB0=0 and P=±15 degrees. For real data x|P|<=20 degrees.

    [equation]

    [equation]

    [equation]

    [equation]

    4.2.3.  Offset Angle Correction Test

          This test was conducted on an artificial data set with B0=20, xP=15, an offset angle of 90 degrees and counterclockwise orientation. Since the tests described above verify the corrections for all the possible B and xP angles as well as orientation, only a single test here is needed to demonstrate that the offset angle is correctly added to the sum of angles that define the angular distance eastward from the y-axis of the camera to the rotation axis (heliographic north) of the sun.

    [equation] Note that verification of the offset correction for GONG breadboard data, and prototype/field data taken with the camera rotator off, has been done on real data sets and will not be discussed here.

    4.2.4.  Elliptical Image Tests

          Reduction of prototype data on a regular basis has shown that we are correctly dealing with the elliptical images produced by the GONG instrument.

    4.3.  Temporal Filtering

          Constant value artificial images were used to test the four main types of temporal filters. A group of 30 artificial images (f_001 to f_030) were created each having a constant pixel value corresponding to the number of the image. These images were reduced by DNSPIPE saving the detrended, interpolated output. The mean values of the output images were then inspected and compared with prediction.

    4.3.1.  dnspipe.filter = 1

          The mean value of the output detrended images should be the same as the input images as no filtering is supposed to be done.

    [picture]

    4.3.2 dnspipe.filter = 2

    The mean of the output detrended images should be the difference of the mean values of the current input image and the image before it.

    [picture]

    4.3.3.  dnspipe.filter = block_filter_length

          The group of 30 artificial images were processed with a 21-point block running mean. The mean of the output should be zero for images 11 through 20, negative for images 1 through 10, and positive for images 21 through 31.

    [picture]

    4.3.4.  dnspipe.filter = filter_file_name

    The group of 30 artificial images were processed with a 21-point weighted running mean filter designed by Cliff Toner. The mean of the output should be zero for images 11 through 20, negative for images 1 through 10, and positive for images 21 through 31 with the values closer to zero than similar values from the block running mean.

    [picture]

    4.4.  Spherical Harmonic Transform

          Real verification of the SHT calculation cannot be done at DMAC since all of the SHT code is related to a common source, the South Pole pipeline. Independent verification is planned for the fall of 1994, by having the SOI pipeline process a day of GONG data (and vice versa).

          The fact that we currently process prototype data and do not see anything unexpected in the power spectra leads us to believe that the SHT code does not contain any major bugs.

    5.  Timing Results

    Appendix I
    Software Installation

          As this software will be part of external IRAF package GRASP, no special installation is required, other than described in the GRASP Installation Guide for IRAF (Anderson, 1993). The mkpkg file for DNSPIPE is shown below.

    # Make DNSPIPE
    
    $call	relink
    $exit
    
    update:
    	$call	relink
    	$call	install
    	;
    
    relink:
    	$set LIBS	= "$(LIBS) -liminterp -lgrutil"
    	$update	libpkg.a
    	$omake	x_dnspipe.x
    	$link	x_dnspipe.o libpkg.a $(OBJS) $(LIBS) -o xx_dnspipe.e
    	;
    
    libpkg.a:
    	t_dnspipe.x	<imhdr.h> <imset.h> <math.h> <math/iminterp.h> \\
    			"dnspipe.h"
    	dns_apodize.x	<math.h> <mach.h> "dnspipe.h"
    	dns_dt.x
    	dns_ephem.x	<math.h>
    	dns_filter.x	"dnspipe.h"
    	dns_initsht.x	"dnspipe.h"
    	dns_interp.x	<math.h> <math/iminterp.h> "dnspipe.h"
    	dns_latlong.x	<math.h> "dnspipe.h"
    	dns_reorder.x	"dnspipe.h"
    	dns_sht.x	<math.h> "dnspipe.h"
    	dns_shtall.x	<math.h> "dnspipe.h"
    	dns_outsht.x	<math.h> "dnspipe.h"
    	dns_spigot.x	<imhdr.h> <imset.h> "dnspipe.h"
    	dns_transpose.x
    	dns_tseries.x	<imhdr.h> <imset.h> <mwset.h> "dnspipe.h"
    	dns_turret.x	<imhdr.h> <math.h>
    	dns_wwlegtran.x <math.h> "dnspipe.h"
    	dns_wwlegall.x	<math.h> "dnspipe.h"
    	Bessel_i0.x
    	Dolph_Cheby.x	<math.h>
    	fftrc.f
    	fourt.f
    	;
    
    install:
    	$move xx_dnspipe.e graspbin$x_dnspipe.e
    	;
    
    debug:
    	$set XFLAGS = "$(XFLAGS) -c -z -F -g -q"
    	$set LFLAGS = "$(LFLAGS) -z -g -q"
    	$call relink
    	;
    
    memcheck:
    	$set XFLAGS = "$(XFLAGS) -z"
    	$set LFLAGS = "$(LFLAGS) -z"
    	$set OBJS = "/lac2/iraf/extern/memcheck/memcheck.o 	/lac2/iraf/extern/memcheck/zzdbg.o 	/usr/lib/debug/malloc.o 	/usr/lib/debug/mallocmap.o"
    	$call relink
    	;
    
    listing:
    	!lpr -Pversatec t_dnspipe.x dns_*.x dnspipe.h
    	;
    

    Note:
    Dnspipe expects to have the grtools package of GRASP loaded. This will be done automatically when the PIPELINE package is loaded.

    Appendix II
    DMAC Operator Instructions

          The following is the general procedure to be followed by DMAC operators when reducing site day data.

    1)
    Checkout tape of calibrated images from the DSDS.
    2)
    Load IRAF, GRASP and PIPELINE.
    % cl
    cl> grasp
    gr> pipeline
    pi>
    
    2)
    Extract the calibrated velocity images from the tape for a particular site day. If there is sufficient disk space, then extract all the site day velocity data from the tape. For example, get Big Bear site day velocity data from tape 100, using Exabyte unit st1:
    pi> !tar -vxbf 126 /dev/nrst9           # Get .toc and .lbl file 
    pi> edit v000100.toc                    # Find tape file numbers for velocity data
                                            # Normally, this data starts at file 2 and 
                                            # is sequential on tape
    pi> !mt -f /dev/rst9 rew
    pi> mkdir BByyddmm                      # Create a directory using UT date of data
    pi> cd BByyddmm                         # Go to that directory
    pi> !mt -f /dev/rst9 fsf 1              # Skip to proper file on tape
    pi> !tar -vxbf 126 /dev/nrst9           # Extract the FITS files
    pi> rfits *.fits 1 data datat=r old+    # Convert to IRAF images
    pi> delete *.fits                       # Delete the FITS files
    pi> cd ..
    pi> mkdir BByyddmm                      # Create directory for next day
    pi> !tar -vxbf 126 /dev/nrst9           # Get past EOF of last tar file
    pi> !tar -vxbf 126 /dev/nrst9           # Extract next data set
    pi> rfits *.fits 1 data datat=r old+    # Convert to IRAF images
    pi> delete *.fits                       # Delete the FITS files
    
        ...
    
    3)
    For each data set on disk:
    3a)
    Execute DNSPIPE.
    pi> cd data_directory                   # Go to data directory
    pi> files *vci*.imh > inlist        # Prepare input list for DNSPIPE
    pi> unlearn dsnpipe                 # Set DNSPIPE parameters to pipeline default
    pi> dnspipe @inlist                 # Execute
    
    Note:
    If special runs with different parameters are required, epar dnspipe prior to execution.
    3b)
    Examine l-nu diagrams using image display. If the diagrams look suspicious then contact data scientist and/or downstream programmers.
    3c)
    When the l-nu diagrams are good, then delete the input images and the power spectra, and make FITS files of time series and l-nu diagrams.
    pi> imdelete *vci*.imh,*vdp*.imh
    pi> mkdir tseries                   # make directory for time series FITS files
    pi> cd tseries
    pi> files ../*vdt*.imh > in
    pi> copy in out
    pi> !replace '../' '' out
    pi> !replace 'imh' 'fits' out
    pi> wfits @in @out
    pi> delete in,out
    pi> cd ..
    pi> mkdir lnudiagrams               # make directory for L-Nu diagram FITS files
    pi> cd lnudiagrams  
    pi> files ../*vdl*.imh > in
    pi> copy in out  
    pi> !replace '../' '' out
    pi> !replace 'imh' 'fits' out
    pi> wfits @in @out
    pi> delete in,out
    pi> cd ..
    
    3d)
    Delete the time series and l-nu diagram IRAF images.
    pi> imdelete *.imh
    
    3e)
    Use the DSDS operators menu to initiate online transfer of the l-nu diagrams.

    4)
    Return data tape to DSDS and check out a blank tape.
    5)
    Prepare a .lbl and .toc file for the blank tape, and archive the multi-day time series. Note, the out archive tapes may NOT contain data for more than one site.
    6)
    Move the .lbl and .toc files to the DSDS operator's account.
    6)
    Delete the l-nu diagram FITS files when notified by the DSDS that the on-line transfer is complete.

    Footnotes

    ****The Global Oscillation Network Group (GONG) is a community-based
    project funded principally by the National Science Foundation and administered
    by the National Solar Observatory. NSO is a division of the National Optical
    Astronomy Observatories, operated by the Association of Universities for Research
    in Astronomy, Inc. under a cooperative agreement with the National Science
    Foundation.
    ****This page was last updated by David Landy, on Jan 6, 1999.