Class TestLRPath

test/com/winvector/logistic/TestLRPath.java:46–207

public class TestLRPath {
	
	public static void copyResourceToFile(final String resourceName, final File dest) throws IOException {
		final InputStream is = TestRoundTrip.class.getClassLoader().getResourceAsStream(resourceName);
		final FileOutputStream os = new FileOutputStream(dest);
		int c = -1;
		while((c=is.read())>=0) {
			os.write(c);
		}
		os.close();
		is.close(); 
	}
	
	public static ArrayList<BurstMap> readBurstFromResource(final String resourceName) throws IOException {
		final ArrayList<BurstMap> r = new ArrayList<BurstMap>();
		final InputStream is = TestRoundTrip.class.getClassLoader().getResourceAsStream(resourceName);
		final Iterator<BurstMap> it = new TrivialIterator(new LineNumberReader(new InputStreamReader(is)),Pattern.compile("\t"),false,true,"res:"+resourceName);
		while(it.hasNext()) {
			final BurstMap row = it.next();
			r.add(row);
		}
		return r;
	}
	
	private double relDiff(double a, double b) {
		final double diff = Math.abs(a-b);
		if(diff<=0.0) {
			return 0.0;
		} else {
			return 2.0*diff/(Math.abs(a)+Math.abs(b));
		}
	}
	
	/** 
	 * essentially the same loop structure as VariableEncodings.formatSoln.  So double calculating here confirms
	 * the results are coming out correctly.
	 * @param trainSource
	 * @param adapter
	 * @param sigmoidLoss
	 * @param x
	 */
	private <T extends ExampleRow> void confirmEffectCalc(final Iterable<BurstMap> trainSource, final VariableEncodings adapter, 
			final DModel<T> sigmoidLoss, final double[] x) {
		// confirm effects work like we think
		for(final BurstMap row: trainSource) {
			// score the standard way
			final SparseSemiVec vec = adapter.vector(row);
			if(null!=vec) {
				//final String resStr = row.getAsString(adapter.def().resultColumn);
				//final int category = adapter.category(resStr);
				final Datum ei = new SparseExampleRow(vec,1.0,-1);
				final double[] pred = sigmoidLoss.predict(x,ei);
				// score via effects
				final double[] predE = new double[adapter.outcomeCategories.entrySet().size()];
				for(final Map.Entry<String,Integer> mc: adapter.outcomeCategories.entrySet()) {
					//final String outcome = mc.getKey();
					final int cati = mc.getValue();
					final int base = cati*adapter.vdim;