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1   /*
2    * Licensed to the Apache Software Foundation (ASF) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The ASF licenses this file to You under the Apache License, Version 2.0
6    * (the "License"); you may not use this file except in compliance with
7    * the License.  You may obtain a copy of the License at
8    *
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   *
11   * Unless required by applicable law or agreed to in writing, software
12   * distributed under the License is distributed on an "AS IS" BASIS,
13   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14   * See the License for the specific language governing permissions and
15   * limitations under the License.
16   */
17  
18  package org.apache.commons.numbers.combinatorics;
19  
20  import org.apache.commons.numbers.gamma.LogGamma;
21  
22  /**
23   * Class for computing the natural logarithm of the factorial of a number.
24   * It allows to allocate a cache of precomputed values.
25   * In case of cache miss, computation is performed by a call to
26   * {@link LogGamma#value(double)}.
27   */
28  public final class LogFactorial {
29      /**
30       * Size of precomputed factorials.
31       * @see Factorial
32       */
33      private static final int FACTORIALS_CACHE_SIZE = 21;
34      /**
35       * Precomputed values of the function: {@code logFactorials[i] = Math.log(i!)}.
36       */
37      private final double[] logFactorials;
38  
39      /**
40       * Creates an instance, reusing the already computed values if available.
41       *
42       * @param numValues Number of values of the function to compute.
43       * @param cache Cached values.
44       * @throw IllegalArgumentException if {@code n < 0}.
45       */
46      private LogFactorial(int numValues,
47                           double[] cache) {
48          if (numValues < 0) {
49              throw new CombinatoricsException(CombinatoricsException.NEGATIVE, numValues);
50          }
51  
52          logFactorials = new double[numValues];
53  
54          final int beginCopy = 2;
55          int endCopy;
56          if (cache == null || cache.length <= beginCopy) {
57              endCopy = beginCopy;
58          } else {
59              endCopy = Math.min(cache.length, numValues);
60          }
61  
62  
63          // Copy available values.
64          if (endCopy - beginCopy > 0) {
65              System.arraycopy(cache, beginCopy, logFactorials, beginCopy, endCopy - beginCopy);
66          }
67  
68          // Precompute.
69          for (int i = endCopy; i < numValues; i++) {
70              logFactorials[i] = logFactorials[i - 1] + Math.log(i);
71          }
72      }
73  
74      /**
75       * Creates an instance with no precomputed values.
76       * @return instance with no precomputed values
77       */
78      public static LogFactorial create() {
79          return new LogFactorial(0, null);
80      }
81  
82      /**
83       * Creates an instance with the specified cache size.
84       *
85       * @param cacheSize Number of precomputed values of the function.
86       * @return a new instance where {@code cacheSize} values have been
87       * precomputed.
88       * @throws IllegalArgumentException if {@code cacheSize < 0}.
89       */
90      public LogFactorial withCache(final int cacheSize) {
91          return new LogFactorial(cacheSize, logFactorials);
92      }
93  
94      /**
95       * Computes \( log_e(n!) \).
96       *
97       * @param n Argument.
98       * @return {@code log(n!)}.
99       * @throws IllegalArgumentException if {@code n < 0}.
100      */
101     public double value(int n) {
102         if (n < 0) {
103             throw new CombinatoricsException(CombinatoricsException.NEGATIVE, n);
104         }
105 
106         // Use cache of precomputed values.
107         if (n < logFactorials.length) {
108             return logFactorials[n];
109         }
110 
111         // Use cache of precomputed factorial values.
112         if (n < FACTORIALS_CACHE_SIZE) {
113             return Math.log(Factorial.value(n));
114         }
115 
116         // Delegate.
117         return LogGamma.value(n + 1.0);
118     }
119 }