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{{template [] |test

1. comment

inputfiles=

1. req: NCVIEW2D.DAT
2. opt: plot data stored as spreadsheet or MATLAB Timetable
3. opt: other formats such as *.jpg, *.tif, *.svg, *.pdf, *.png

}}

{{ProgramDescription name_de=NCVIEW2D name=NCVIEW2D version=March 2021 version_descr=September 2022 catchwords=oostprozessor
time series
CF-NETCDF.NCcf-netcdf.nc

shortdescription= NCVIEW2D is applied to visualize CF-NETCDF.NCcf-netcdf.nc data as time series. The following objects are within a plot:

1. plot window(s) (also subplots)
2. y-axis
3. data

A plot window can also have two y-axis with 5 individual data sets each. E. g. plot window 1 and its y-axis 1 can contain the measured and modeled water level, while plot window 2 could show measured salinity on the left y-axis and discharge on the right y-axis. Plot windows are placed from north to south. Below the lowes window, the UUID of the CF-NETCDF.NCcf-netcdf.nc data may be displayed as legend.

• File:Time series.example 1.de.pngexample 1
• File:Time series.example 2.en.pngexample 2
• File:Time series.example 3.en.pngexample 3

Remarks=

1. Variable names can be obtained via ncdump -h myData.nc
2. Measurements from BOEWRT can be converted to CF-NETCDF.NCcf-netcdf.nc using DATACONVERT or BOE2NC
3. Only the last y-label/y-limit of a figure and an axis is used for visualization
4. The maximum number of plot windows is 3.
5. This project took advantage of netCDF software developed by UCAR/Unidata (Link).

inputfiles=

1. req: NCVIEW2D.DAT

outputfiles=

1. MATLAB figure *.fig
2. DMQS metadata (stored in figure)
3. program log *.sdr
4. errors and warning *.err
5. opt: plot data stored as spreadsheet or MATLAB Timetable
6. opt: other formats such as *.jpg, *.tif, *.svg, *.pdf, *.png

methodology= This program was written in MATLAB and takes advantage of existing PROGHOME methods, such as unit conversion or i/o of BOEWRT data. The program is subdivided in the following sections:

1. blah (if requested)

1. Reading and checking the steering file
2. Testing of the existence of input data and its variables
3. Testing of the plausibility of input parameters