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1   /*
2    * Licensed to the Hipparchus project 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 Hipparchus project 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    *      https://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  package org.hipparchus.special.elliptic.jacobi;
18  
19  import org.hipparchus.util.FastMath;
20  
21  /** Algorithm for computing the principal Jacobi functions for parameter m greater than 1.
22   * <p>
23   * The rules for reciprocal parameter change are given in Abramowitz and Stegun,
24   * sections 16.11 and 17.4.15.
25   * </p>
26   * @since 2.0
27   */
28  class BigParameter extends JacobiElliptic {
29  
30      /** Algorithm to use for the positive parameter. */
31      private final JacobiElliptic algorithm;
32  
33      /** Input scaling factor. */
34      private final double inputScale;
35  
36      /** output scaling factor. */
37      private final double outputScale;
38  
39      /** Simple constructor.
40       * @param m parameter of the Jacobi elliptic function (must be greater than 1 here)
41       */
42      BigParameter(final double m) {
43          super(m);
44          algorithm   = JacobiEllipticBuilder.build(1.0 / m);
45          inputScale  = FastMath.sqrt(m);
46          outputScale = 1.0 / inputScale;
47      }
48  
49      /** {@inheritDoc} */
50      @Override
51      public CopolarN valuesN(final double u) {
52          final CopolarN trioN = algorithm.valuesN(u * inputScale);
53          return new CopolarN(outputScale * trioN.sn(), trioN.dn(), trioN.cn());
54      }
55  
56  }