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To get started with this blank TiddlyWiki, you'll need to modify the following tiddlers:
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Your username for signing your edits. Write it as a WikiWord (eg JoeBloggs)

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----
Also see AdvancedOptions
<<importTiddlers>>
A baseline measurement is obtained by using the LISST.EXE program to collect background scatter data.

You many have several baseline measurements to choose from... the factory measurement done under pristine conditions (factory.zsc) and then others done in the lab or in the field.

You can compare your baseline measurements using comparezsc.m.  Comparezsc will require the factory file as a reference, and then allow you to select others to plot against the factory measurement.

The plot below shows several baselines.  The factory, one done in the  field with calibration spheres, two done prior to deployment after it was known  that the windows were scratched, and one done with fouled windows after deployment (Nov).  

[img[Comparative Baselines|zscplots.png]]

Fouled baselines may be useful.  Any snapshot of results during an experiment may also be used as a baseline to process the data.  The baseline should represent the status of the LISST without particles present in the sampling volume.  If the LISST was fouled most of the time, this might actually be a snapshot of the time series when there was no resuspension but fouling was present on the windows.
ProcessingSteps
# LISSTSTasc2nc.m is for settling experiments and is not finished yet.  LISST100Xasc2nc should process settling experiments as time series data, but not the settling velocity information.  We have not done enough settling tube deployments yet, and processing LISST data for settling velocity requires a different processing approach starting with LISSTST.EXE rather than LISST.EXE.
This program is from the instrument manufacturer Sequoia to communicate  and process data from LISST type 100X
LISST.INI is found in C:\WINDOWS

Instrument specific information in LISST.INI

[Instrument1172]
HK0Label=Laser Power
HK0Units=mW
HK0Scale=0.00081556
HK0Off=0
HK1Label=Battery
HK1Units=Volts
HK1Scale=0.01
HK1Off=0.0
HK2Label=External Instrument
HK2Units=Volts
HK2Scale=0
HK2Off=0
HK3Label=Laser Reference
HK3Units=mW
HK3Scale=0.00076741
HK3Off=0
HK4Label=Depth
HK4Units=meters
HK4Scale=0.01
HK4Off=0
HK5Label=Temperature
HK5Units=Deg C
HK5Scale=0.01
HK5Off=0
HK6Label=Day*100+Hour
HK6Units=
HK6Scale=1
HK6Off=0
HK7Label=Minute*100+Seconds
HK7Units=
HK7Scale=1
HK7Off=0
PreRequisites
BaselineMeasurement
ProcessingSteps
KnownIssues
# You will need the following information specific to *your* LISST:
## Thinking out what to use as a [[baseline measurement|BaselineMeasurement]] most appropriate for your experiment.
## The ring area file, names as ringarea_####.asc where #### is the LISST serial number.  This is a factory generated calibration file, and should be from the most recent calibration
## The baseline calibration file from the factory, factory_zsc_####.asc, which like the ring area file, should be from the most recent calibration
## A background scatter file, in the same format as the baseline calibration file, that has a pre-deployment [[baseline measurement|BaselineMeasurement]].
## Information in [[LISST.INI]] is up to date for each LISST instrument you own
## the volume conversion constant, found in [[instrumentdata.txt]]
# You will need MATLAB
# You will need the LISST toolbox from Sequoia
## under m_contrib/trunk/SequoiaLISST100 for LISST 100X data
## under m_contrib/trunk/SequoiaLISSTST for LISST ST settling experiments
# You will need the LISST toolbox from USGS
## If you are reading this, you got it from the toolbox directory, hopefully
# your MATLAB path should include all these toolboxes, and recursively all subdirectories contained in the toolboxes.
# Satisfy everything in PreRequisites
# Figure out which is the best [[baseline measurement|BaselineMeasurement]] to use
# Put the ringarea, factory zsc, baseline zsc and *.DAT data file all in the same working directory
# make sure [[LISST.INI]] is up do date
# run [[LISST.EXE]]
## select the instrument serial number
## open the .DAT raw data file
## in file>settings>output make sure that under processing existing raw data file build an ASCII .log and .asc file are both checked.
## click process to process the file
# set up the [[processing script file]] to process all samples using metadata.goodsamples = [1 Inf]; 
# View the data, both the raw *.cdf and calibrated *.nc with browseLISST.m
# Use this method to find the [[first and last good sample]].
# Set up the [[processing script file]] to process all samples using metadata.goodsamples = [M N]; where M is the first good sample number and N is the last good sample number.  You may wish to give this output file set a different name, such as ncroot = '8482lisstT'; where "T" designates trimmed data.
# After viewing your data, if you wish to try processing with a different [[baseline measurement|BaselineMeasurement]], you will have to begin from the beginning by first processing the binary data in [[LISST.EXE]] using the new baseline scatter file.  It is LISST.EXE which does the inversion.  These m-files simply convert to netCDF and allow viewing and trimming.

How to process LISST data in MATLAB
The trick to finding the first and last good sample....

# Open your file with browseLISST and view your data.  Determine what part is good and what part is bad.
# Use MATLAB's data tips feature:
## mark the data point where data transitions from good to bad or bad to good with a data tip, right click on the data tip and export the information to the workspace.  You will have the julian time stamp.  Then this sequence of commands will get you the sample number of that time stamp:
### Get the gregorian date string from the cursor information: datestr(cursor_info.Position(1))
### Open the netCDf file cdf = netcdf('8482lisst.cdf')
### Read in the time tj = cdf{'time'}(:)+cdf{'time2'}(:)./(1000*24*3600);
### Search for the sample number find(tj>=julian([2007,12,5,20,00,23]),1,'first') replacing 2007,12,5,20,00,23 with YYYY,MM,DD,HH,MM,SS gregorian date from your data tip.  It will return the corresponding sample number.
This is installed in c:\Program Files\sequoia\lisst100
This file contains the following constants
Serial number, type, ??, volume conversion, ??
1172, C, 529000, 45733, X
The inversion calculation from optical scatter to volume concentration is performed by [[LISST.EXE]], however Sequoia also provides a MATLAB method.  This was recently updated by Sequoia and is not yet working in this toolbox.  It is implemented by this code...

if 0,
    % do it from the binary using Sequoia code
    dvec = datevec(metadata.deployment_start);
    settings.expYear = dvec(1);
    settings.LISSTtype = metadata.type;
    settings.LISSTserial = str2double(metadata.serial);
    settings.volconv = metadata.cal.volumeconversion;
    settings.pscale = metadata.cal.pressure(1);
    settings.poffset = metadata.cal.pressure(2);
    settings.raux = 2.5/4095;

    [lisstmat, settings] = do100X(LISSTdat, metadata.zscFile, metadata.ringFile, ...
        settings, metadata.goodsamples, 0);

    save(ncroot,'lisstmat', 'metadata', 'settings');
    
end
[[metaLISSTExample.m | metaLISSTExample.m]]