SweetSpotSimilarity.cs

using Lucene.Net.Index;
using Lucene.Net.Search.Similarities;
using System;

namespace Lucene.Net.Misc
{
    /*
     * 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.
     */

    /// <summary>
    /// <para>
    /// A similarity with a lengthNorm that provides for a "plateau" of
    /// equally good lengths, and tf helper functions.
    /// </para>
    /// <para>
    /// For lengthNorm, A min/max can be specified to define the
    /// plateau of lengths that should all have a norm of 1.0.
    /// Below the min, and above the max the lengthNorm drops off in a
    /// sqrt function.
    /// </para>
    /// <para>
    /// For tf, baselineTf and hyperbolicTf functions are provided, which
    /// subclasses can choose between.
    /// </para>
    /// </summary>
    /// <a href="doc-files/ss.gnuplot">A Gnuplot file used to generate some of the visualizations refrenced from each function.</a>
    public class SweetSpotSimilarity : DefaultSimilarity
    {
        private int ln_min = 1;
        private int ln_max = 1;
        private float ln_steep = 0.5f;

        private float tf_base = 0.0f;
        private float tf_min = 0.0f;

        private float tf_hyper_min = 0.0f;
        private float tf_hyper_max = 2.0f;
        private double tf_hyper_base = 1.3d;
        private float tf_hyper_xoffset = 10.0f;

        public SweetSpotSimilarity()
              : base()
        {
        }

        /// <summary>
        /// Sets the baseline and minimum function variables for baselineTf
        /// </summary>
        /// <seealso cref="BaselineTf(float)"/>
        public virtual void SetBaselineTfFactors(float @base, float min)
        {
            tf_min = min;
            tf_base = @base;
        }

        /// <summary>
        /// Sets the function variables for the hyperbolicTf functions
        /// </summary>
        /// <param name="min"> the minimum tf value to ever be returned (default: 0.0) </param>
        /// <param name="max"> the maximum tf value to ever be returned (default: 2.0) </param>
        /// <param name="base"> the base value to be used in the exponential for the hyperbolic function (default: 1.3) </param>
        /// <param name="xoffset"> the midpoint of the hyperbolic function (default: 10.0) </param>
        /// <seealso cref="HyperbolicTf(float)"/>
        public virtual void SetHyperbolicTfFactors(float min, float max, double @base, float xoffset)
        {
            tf_hyper_min = min;
            tf_hyper_max = max;
            tf_hyper_base = @base;
            tf_hyper_xoffset = xoffset;
        }

        /// <summary>
        /// Sets the default function variables used by lengthNorm when no field
        /// specific variables have been set.
        /// </summary>
        /// <seealso cref="ComputeLengthNorm(int)"/>
        public virtual void SetLengthNormFactors(int min, int max, float steepness, bool discountOverlaps)
        {
            this.ln_min = min;
            this.ln_max = max;
            this.ln_steep = steepness;
            this.DiscountOverlaps = discountOverlaps;
        }

        /// <summary>
        /// Implemented as 
        /// <c>
        /// state.Boost * ComputeLengthNorm(numTokens) 
        /// </c> 
        /// where numTokens does not count overlap tokens if
        /// discountOverlaps is true by default or true for this
        /// specific field. 
        /// </summary>
        public override float LengthNorm(FieldInvertState state)
        {
            int numTokens;

            if (DiscountOverlaps)
            {
                numTokens = state.Length - state.NumOverlap;
            }
            else
            {
                numTokens = state.Length;
            }

            return state.Boost * ComputeLengthNorm(numTokens);
        }

        /// <summary>
        /// Implemented as:
        /// <code>
        /// 1/sqrt( steepness * (Math.Abs(x-min) + Math.Abs(x-max) - (max-min)) + 1 )
        /// </code>.
        /// 
        /// <para>
        /// This degrades to <code>1/Math.Sqrt(x)</code> when min and max are both 1 and
        /// steepness is 0.5
        /// </para>
        /// 
        /// <para>
        /// :TODO: potential optimization is to just flat out return 1.0f if numTerms
        /// is between min and max.
        /// </para>
        /// </summary>
        /// <seealso cref="SetLengthNormFactors(int, int, float, bool)"/>
        /// <a href="doc-files/ss.computeLengthNorm.svg">An SVG visualization of this function</a>
        public virtual float ComputeLengthNorm(int numTerms)
        {
            int l = ln_min;
            int h = ln_max;
            float s = ln_steep;

            return (float)(1.0f / Math.Sqrt((s * (float)(Math.Abs(numTerms - l) + Math.Abs(numTerms - h) - (h - l))) + 1.0f));
        }

        /// <summary>
        /// Delegates to baselineTf
        /// </summary>
        /// <seealso cref="BaselineTf(float)"/>
        public override float Tf(float freq)
        {
            return BaselineTf(freq);
        }

        /// <summary>
        /// Implemented as:
        /// <code>
        ///  (x &lt;= min) &#63; base : Math.Sqrt(x+(base**2)-min)
        /// </code>
        /// ...but with a special case check for 0.
        /// <para>
        /// This degrates to <code>Math.Sqrt(x)</code> when min and base are both 0
        /// </para>
        /// </summary>
        /// <seealso cref="SetBaselineTfFactors(float, float)"/>
        /// <a href="doc-files/ss.baselineTf.svg">An SVG visualization of this function</a>
        public virtual float BaselineTf(float freq)
        {
            if (0.0f == freq)
            {
                return 0.0f;
            }

            return (freq <= tf_min) ? tf_base : (float)Math.Sqrt(freq + (tf_base * tf_base) - tf_min);
        }

        /// <summary>
        /// Uses a hyperbolic tangent function that allows for a hard max...
        /// 
        /// <code>
        /// tf(x)=min+(max-min)/2*(((base**(x-xoffset)-base**-(x-xoffset))/(base**(x-xoffset)+base**-(x-xoffset)))+1)
        /// </code>
        /// 
        /// <para>
        /// This code is provided as a convenience for subclasses that want
        /// to use a hyperbolic tf function.
        /// </para>
        /// </summary>
        /// <seealso cref="SetHyperbolicTfFactors(float, float, double, float)"/>
        /// <a href="doc-files/ss.hyperbolicTf.svg">An SVG visualization of this function</a>
        public virtual float HyperbolicTf(float freq)
        {
            if (0.0f == freq)
            {
                return 0.0f;
            }

            float min = tf_hyper_min;
            float max = tf_hyper_max;
            double @base = tf_hyper_base;
            float xoffset = tf_hyper_xoffset;
            double x = (double)(freq - xoffset);

            float result = min + (float)((max - min) / 2.0f * (((Math.Pow(@base, x) - Math.Pow(@base, -x)) / (Math.Pow(@base, x) + Math.Pow(@base, -x))) + 1.0d));

            return float.IsNaN(result) ? max : result;
        }
    }
}