Java Double Convert to convertDoubleValuesFromNetcdf(double[] netcdfData, double missingValue, double scaleFactor, double offSet)

Description

Converts the raw values from a netcdf file to the real values using the given missingValue, scaleFactor and offset.

License

Open Source License

Parameter

Parameter	Description
netcdfData	a parameter
missingValue	a parameter
scaleFactor	a parameter
offSet	a parameter

Declaration

private static void convertDoubleValuesFromNetcdf(double[] netcdfData, double missingValue, double scaleFactor,
        double offSet) 

Method Source Code

//package com.java2s;
/* MOD_V2.0/*from www  .ja va 2  s  . c o m*/
* Copyright (c) 2012 OpenDA Association
* All rights reserved.
*
* This file is part of OpenDA.
*
* OpenDA is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation, either version 3 of
* the License, or (at your option) any later version.
*
* OpenDA is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with OpenDA.  If not, see <http://www.gnu.org/licenses/>.
*/

public class Main {
    /**
     * Converts the raw values from a netcdf file to the real values using the given
     * missingValue, scaleFactor and offset.
     *
     * @param netcdfData
     * @param missingValue
     * @param scaleFactor
     * @param offSet
     */
    private static void convertDoubleValuesFromNetcdf(double[] netcdfData, double missingValue, double scaleFactor,
            double offSet) {
        //according to the CF-convention:
        //see http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.6/cf-conventions.html#missing-data
        //"Applications that process variables that have attributes to indicate both a transformation (via a scale and/or offset)
        //and missing values should first check that a data value is valid, and then apply the transformation."
        //see http://cf-pcmdi.llnl.gov/documents/cf-conventions/1.6/cf-conventions.html#packed-data
        //"After the data values of a variable have been read, they are to be multiplied by the scale_factor,
        //and have add_offset added to them. If both attributes are present, the data are scaled before the offset is added."

        //apply scale factor and offset and replace missing values with Double.NaN.
        if (scaleFactor == 1d && offSet == 0d) {
            //in this case no need to apply the scaleFactor and offset.
            if (!Double.isNaN(missingValue)) {
                for (int i = 0; i < netcdfData.length; i++) {
                    if (Double.compare(netcdfData[i], missingValue) == 0) {
                        netcdfData[i] = Double.NaN;
                    }
                }
            } else {//if missingValue is Double.NaN, then missing values in netcdfData array are already equal to Double.NaN.
                //do nothing.
            }
        } else {
            for (int i = 0; i < netcdfData.length; i++) {
                if (Double.compare(netcdfData[i], missingValue) == 0) {
                    netcdfData[i] = Double.NaN;
                } else {
                    netcdfData[i] = netcdfData[i] * scaleFactor + offSet;
                }
            }
        }
    }
}

Related

1. convertdoubleToDouble(double[][] dbleArray)
2. convertDoubleToFloat(final double[][] doubleSeries)
3. convertDoubleToLong(Double value)
4. convertDoubleToPercentage(double doub)
5. convertDoubleToShort(double value)
6. double2Arr(double var, byte[] arrayBytes, int startIndex)
7. double2array(int sz, double seed)
8. double2bin(double d)
9. double2bipolar(final double d[])