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+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.commons.math3.analysis.function;
+
+import org.apache.commons.math3.analysis.DifferentiableUnivariateFunction;
+import org.apache.commons.math3.analysis.FunctionUtils;
+import org.apache.commons.math3.analysis.ParametricUnivariateFunction;
+import org.apache.commons.math3.analysis.UnivariateFunction;
+import org.apache.commons.math3.analysis.differentiation.DerivativeStructure;
+import org.apache.commons.math3.analysis.differentiation.UnivariateDifferentiableFunction;
+import org.apache.commons.math3.exception.DimensionMismatchException;
+import org.apache.commons.math3.exception.NullArgumentException;
+import org.apache.commons.math3.exception.OutOfRangeException;
+import org.apache.commons.math3.util.FastMath;
+
+/**
+ * <a href="http://en.wikipedia.org/wiki/Logit">
+ * Logit</a> function.
+ * It is the inverse of the {@link Sigmoid sigmoid} function.
+ *
+ * @since 3.0
+ */
+public class Logit implements UnivariateDifferentiableFunction, DifferentiableUnivariateFunction {
+ /** Lower bound. */
+ private final double lo;
+ /** Higher bound. */
+ private final double hi;
+
+ /**
+ * Usual logit function, where the lower bound is 0 and the higher
+ * bound is 1.
+ */
+ public Logit() {
+ this(0, 1);
+ }
+
+ /**
+ * Logit function.
+ *
+ * @param lo Lower bound of the function domain.
+ * @param hi Higher bound of the function domain.
+ */
+ public Logit(double lo,
+ double hi) {
+ this.lo = lo;
+ this.hi = hi;
+ }
+
+ /** {@inheritDoc} */
+ public double value(double x)
+ throws OutOfRangeException {
+ return value(x, lo, hi);
+ }
+
+ /** {@inheritDoc}
+ * @deprecated as of 3.1, replaced by {@link #value(DerivativeStructure)}
+ */
+ @Deprecated
+ public UnivariateFunction derivative() {
+ return FunctionUtils.toDifferentiableUnivariateFunction(this).derivative();
+ }
+
+ /**
+ * Parametric function where the input array contains the parameters of
+ * the logit function, ordered as follows:
+ * <ul>
+ * <li>Lower bound</li>
+ * <li>Higher bound</li>
+ * </ul>
+ */
+ public static class Parametric implements ParametricUnivariateFunction {
+ /**
+ * Computes the value of the logit at {@code x}.
+ *
+ * @param x Value for which the function must be computed.
+ * @param param Values of lower bound and higher bounds.
+ * @return the value of the function.
+ * @throws NullArgumentException if {@code param} is {@code null}.
+ * @throws DimensionMismatchException if the size of {@code param} is
+ * not 2.
+ */
+ public double value(double x, double ... param)
+ throws NullArgumentException,
+ DimensionMismatchException {
+ validateParameters(param);
+ return Logit.value(x, param[0], param[1]);
+ }
+
+ /**
+ * Computes the value of the gradient at {@code x}.
+ * The components of the gradient vector are the partial
+ * derivatives of the function with respect to each of the
+ * <em>parameters</em> (lower bound and higher bound).
+ *
+ * @param x Value at which the gradient must be computed.
+ * @param param Values for lower and higher bounds.
+ * @return the gradient vector at {@code x}.
+ * @throws NullArgumentException if {@code param} is {@code null}.
+ * @throws DimensionMismatchException if the size of {@code param} is
+ * not 2.
+ */
+ public double[] gradient(double x, double ... param)
+ throws NullArgumentException,
+ DimensionMismatchException {
+ validateParameters(param);
+
+ final double lo = param[0];
+ final double hi = param[1];
+
+ return new double[] { 1 / (lo - x), 1 / (hi - x) };
+ }
+
+ /**
+ * Validates parameters to ensure they are appropriate for the evaluation of
+ * the {@link #value(double,double[])} and {@link #gradient(double,double[])}
+ * methods.
+ *
+ * @param param Values for lower and higher bounds.
+ * @throws NullArgumentException if {@code param} is {@code null}.
+ * @throws DimensionMismatchException if the size of {@code param} is
+ * not 2.
+ */
+ private void validateParameters(double[] param)
+ throws NullArgumentException,
+ DimensionMismatchException {
+ if (param == null) {
+ throw new NullArgumentException();
+ }
+ if (param.length != 2) {
+ throw new DimensionMismatchException(param.length, 2);
+ }
+ }
+ }
+
+ /**
+ * @param x Value at which to compute the logit.
+ * @param lo Lower bound.
+ * @param hi Higher bound.
+ * @return the value of the logit function at {@code x}.
+ * @throws OutOfRangeException if {@code x < lo} or {@code x > hi}.
+ */
+ private static double value(double x,
+ double lo,
+ double hi)
+ throws OutOfRangeException {
+ if (x < lo || x > hi) {
+ throw new OutOfRangeException(x, lo, hi);
+ }
+ return FastMath.log((x - lo) / (hi - x));
+ }
+
+ /** {@inheritDoc}
+ * @since 3.1
+ * @exception OutOfRangeException if parameter is outside of function domain
+ */
+ public DerivativeStructure value(final DerivativeStructure t)
+ throws OutOfRangeException {
+ final double x = t.getValue();
+ if (x < lo || x > hi) {
+ throw new OutOfRangeException(x, lo, hi);
+ }
+ double[] f = new double[t.getOrder() + 1];
+
+ // function value
+ f[0] = FastMath.log((x - lo) / (hi - x));
+
+ if (Double.isInfinite(f[0])) {
+
+ if (f.length > 1) {
+ f[1] = Double.POSITIVE_INFINITY;
+ }
+ // fill the array with infinities
+ // (for x close to lo the signs will flip between -inf and +inf,
+ // for x close to hi the signs will always be +inf)
+ // this is probably overkill, since the call to compose at the end
+ // of the method will transform most infinities into NaN ...
+ for (int i = 2; i < f.length; ++i) {
+ f[i] = f[i - 2];
+ }
+
+ } else {
+
+ // function derivatives
+ final double invL = 1.0 / (x - lo);
+ double xL = invL;
+ final double invH = 1.0 / (hi - x);
+ double xH = invH;
+ for (int i = 1; i < f.length; ++i) {
+ f[i] = xL + xH;
+ xL *= -i * invL;
+ xH *= i * invH;
+ }
+ }
+
+ return t.compose(f);
+ }
+}