/** * if val is missing data, see VariableDS.isMissingData() */ public boolean isMissingData(double val) { return vs.isMissing(val); }
/** * if val is missing data, see VariableDS.isMissingData() */ public boolean isMissingData(double val) { return vs.isMissing(val); }
/** * if val is missing data, see VariableDS.isMissingData() */ public boolean isMissingData(double val) { return vs.isMissing(val); }
@Override public boolean isMissing(double val) { return (vds != null) && vds.isMissing(val); }
/** * if val is missing data, see VariableDS.isMissingData() */ public boolean isMissingData(double val) { return vs.isMissing(val); }
@Override public boolean isMissing(double val) { return (vds != null) && vds.isMissing(val); }
public boolean isMissing(double val) { return vs.isMissing(val); }
public boolean isMissing(double val) { return vs.isMissing(val); }
public boolean isMissing(double val) { return vs.isMissing(val); }
public boolean isMissing(double val) { return vs.isMissing(val); }
/** * Convert (in place) all values in the given array that are considered * as "missing" to Float.NaN, according to isMissingData(val). * * @param values input array * @return input array, with missing values converted to NaNs. */ public float[] setMissingToNaN(float[] values) { if (!vs.hasMissing()) return values; final int length = values.length; for (int i = 0; i < length; i++) { double value = values[i]; if (vs.isMissing(value)) values[i] = Float.NaN; } return values; }
/** * Convert (in place) all values in the given array that are considered * as "missing" to Float.NaN, according to isMissingData(val). * * @param values input array * @return input array, with missing values converted to NaNs. */ public float[] setMissingToNaN(float[] values) { if (!vs.hasMissing()) return values; final int length = values.length; for (int i = 0; i < length; i++) { double value = values[i]; if (vs.isMissing(value)) values[i] = Float.NaN; } return values; }
/** * Convert (in place) all values in the given array that are considered * as "missing" to Float.NaN, according to isMissingData(val). * * @param values input array * @return input array, with missing values converted to NaNs. */ public float[] setMissingToNaN(float[] values) { if (!vs.hasMissing()) return values; final int length = values.length; for (int i = 0; i < length; i++) { double value = values[i]; if (vs.isMissing(value)) values[i] = Float.NaN; } return values; }
public boolean isMissing(StructureData sdata) { if (isString()) return false; double val = getCoordValue(sdata); return varTop.isMissing(val); } }
@Override public boolean isMissing(StructureData sdata) { if (isString()) return false; double val = getCoordValue(sdata); return varTop.isMissing(val); } }
public boolean isMissing(StructureData sdata) { if (isString()) return false; double val = getCoordValue(sdata); return varTop.isMissing(val); } }
@Test public void testScaling2() throws Exception { DatasetUrl durl = DatasetUrl.findDatasetUrl(location+"fine.ncml"); NetcdfFile ncfile = NetcdfDataset.acquireFile(durl, null); // make sure that scaling is applied VariableDS vs = (VariableDS) ncfile.findVariable("hs"); Array data = vs.read("0,1,:,:)"); while (data.hasNext()) { float val = data.nextFloat(); if (!vs.isMissing(val)) assert (val < 10.0) : val; //System.out.printf("%f %n",val); } ncfile.close(); }