public void testResolveType_parameterizedType() {
@SuppressWarnings("rawtypes") // trying to test raw type
Parameterized<?, ?, ?> parameterized =
new Parameterized<TypeTokenResolutionTest, Bar, String>() {};
TypeResolver typeResolver = TypeResolver.accordingTo(parameterized.getClass());
ParameterizedType resolved =
(ParameterizedType) typeResolver.resolveType(parameterized.parameterizedType());
assertEquals(TypeTokenResolutionTest.class, resolved.getOwnerType());
assertEquals(Bar.class, resolved.getRawType());
assertThat(resolved.getActualTypeArguments()).asList().contains(String.class);
}
/**
* This method will automatically populate the search space with parameters based on which
* Parameter objects return non-null distributions.<br>
* <br>
* Note, using this method with Cross Validation has the potential for over-estimating the
* accuracy of results if the data set is actually used to for parameter guessing.
*
* @param data the data set to get parameter estimates from
* @param paramsEach the number of parameters value to try for each parameter found
* @return the number of parameters added
*/
public int autoAddParameters(DataSet data, int paramsEach) {
Parameterized obj;
if (baseClassifier != null) obj = (Parameterized) baseClassifier;
else obj = (Parameterized) baseRegressor;
int totalParms = 0;
for (Parameter param : obj.getParameters()) {
Distribution dist;
if (param instanceof DoubleParameter) {
dist = ((DoubleParameter) param).getGuess(data);
if (dist != null) totalParms++;
} else if (param instanceof IntParameter) {
dist = ((IntParameter) param).getGuess(data);
if (dist != null) totalParms++;
}
}
if (totalParms < 1) return 0;
double[] quantiles = new double[paramsEach];
for (int i = 0; i < quantiles.length; i++) quantiles[i] = (i + 1.0) / (paramsEach + 1.0);
for (Parameter param : obj.getParameters()) {
Distribution dist;
if (param instanceof DoubleParameter) {
dist = ((DoubleParameter) param).getGuess(data);
if (dist == null) continue;
double[] vals = new double[paramsEach];
for (int i = 0; i < vals.length; i++) vals[i] = dist.invCdf(quantiles[i]);
addParameter((DoubleParameter) param, vals);
} else if (param instanceof IntParameter) {
dist = ((IntParameter) param).getGuess(data);
if (dist == null) continue;
int[] vals = new int[paramsEach];
for (int i = 0; i < vals.length; i++) vals[i] = (int) Math.round(dist.invCdf(quantiles[i]));
addParameter((IntParameter) param, vals);
}
}
return totalParms;
}