Due to the current gap in continued funding from the U.S. National Science Foundation (NSF), the NSF Unidata Program Center has temporarily paused most operations. See NSF Unidata Pause in Most Operations for details.
Due to the current gap in continued funding from the U.S. National Science Foundation (NSF), the NSF Unidata Program Center has temporarily paused most operations. See NSF Unidata Pause in Most Operations for details.
Hi, I'm writing an application that reads data from NetCDF files and produces images. I've noticed (through profiling) that a slow point in the data reading process is the unpacking of packed data (i.e. applying scale and offset) and checking for missing values. I would like to minimize the use of these calls. To cut a long post short, I would like to find a low-level function that allows me to read the packed data, exactly as they appear in the file. I can then "manually" apply the unpacking and missing-value checks only to those data points that I need to display. I'm using nj22, version 2.2.16. I've tried reading data from GeoGrid.subset() but this (of course) performs the unpacking. I then tried getting the "unenhanced" variable object through GeoGrid.getVariable().getOriginalVariable(), but (unexpectedly) this also seems to perform unpacking and missing-value checks - I expected it to give raw data. Can anyone help me to find a function for reading raw (packed) data without performing missing-value checks? Thanks in advance, Jon -- -------------------------------------------------------------- Dr Jon Blower Tel: +44 118 378 5213 (direct line) Technical Director Tel: +44 118 378 8741 (ESSC) Reading e-Science Centre Fax: +44 118 378 6413 ESSC Email: jdb@xxxxxxxxxxxxxxxxxxxx University of Reading 3 Earley Gate Reading RG6 6AL, UK -------------------------------------------------------------- ============================================================================== To unsubscribe netcdf-java, visit: http://www.unidata.ucar.edu/mailing-list-delete-form.html ==============================================================================
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