```   1 /*
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4  *
5  * This code is free software; you can redistribute it and/or modify it
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11  * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License
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13  * accompanied this code).
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17  * Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
18  *
20  * or visit www.oracle.com if you need additional information or have any
21  * questions.
22  */
23
24 /*
25  * @test
26  * @bug 4851638 4939441
27  * @summary Tests for {Math, StrictMath}.hypot
28  * @author Joseph D. Darcy
29  */
30
31 public class HypotTests {
32     private HypotTests(){}
33
34     static final double infinityD = Double.POSITIVE_INFINITY;
35     static final double NaNd      = Double.NaN;
36
37     /**
38      * Given integers m and n, assuming m < n, the triple (n^2 - m^2,
39      * 2mn, and n^2 + m^2) is a Pythagorean triple with a^2 + b^2 =
40      * c^2.  This methods returns a long array holding the Pythagorean
41      * triple corresponding to the inputs.
42      */
43     static long [] pythagoreanTriple(int m, int n) {
44         long M = m;
45         long N = n;
46         long result[] = new long[3];
47
48
49         result[0] = Math.abs(M*M - N*N);
50         result[1] = Math.abs(2*M*N);
51         result[2] = Math.abs(M*M + N*N);
52
53         return result;
54     }
55
56     static int testHypot() {
57         int failures = 0;
58
59         double [][] testCases = {
60             // Special cases
61             {infinityD,         infinityD,              infinityD},
62             {infinityD,         0.0,                    infinityD},
63             {infinityD,         1.0,                    infinityD},
64             {infinityD,         NaNd,                   infinityD},
65             {NaNd,              NaNd,                   NaNd},
66             {0.0,               NaNd,                   NaNd},
67             {1.0,               NaNd,                   NaNd},
68             {Double.longBitsToDouble(0x7FF0000000000001L),      1.0,    NaNd},
69             {Double.longBitsToDouble(0xFFF0000000000001L),      1.0,    NaNd},
70             {Double.longBitsToDouble(0x7FF8555555555555L),      1.0,    NaNd},
71             {Double.longBitsToDouble(0xFFF8555555555555L),      1.0,    NaNd},
72             {Double.longBitsToDouble(0x7FFFFFFFFFFFFFFFL),      1.0,    NaNd},
73             {Double.longBitsToDouble(0xFFFFFFFFFFFFFFFFL),      1.0,    NaNd},
76             {Double.longBitsToDouble(0x7FFCafeBabe00000L),      1.0,    NaNd},
77             {Double.longBitsToDouble(0xFFFCafeBabe00000L),      1.0,    NaNd},
78         };
79
80         for(int i = 0; i < testCases.length; i++) {
81             failures += testHypotCase(testCases[i][0], testCases[i][1],
82                                       testCases[i][2]);
83         }
84
85         // Verify hypot(x, 0.0) is close to x over the entire exponent
86         // range.
87         for(int i = DoubleConsts.MIN_SUB_EXPONENT;
88             i <= Double.MAX_EXPONENT;
89             i++) {
90             double input = Math.scalb(2, i);
91             failures += testHypotCase(input, 0.0, input);
92         }
93
94
95         // Test Pythagorean triples
96
97         // Small ones
98         for(int m = 1; m < 10; m++) {
99             for(int n = m+1; n < 11; n++) {
100                 long [] result = pythagoreanTriple(m, n);
101                 failures += testHypotCase(result[0], result[1], result[2]);
102             }
103         }
104
105         // Big ones
106         for(int m = 100000; m < 100100; m++) {
107             for(int n = m+100000; n < 200200; n++) {
108                 long [] result = pythagoreanTriple(m, n);
109                 failures += testHypotCase(result[0], result[1], result[2]);
110             }
111         }
112
113         // Approaching overflow tests
114
115         /*
116          * Create a random value r with an large-ish exponent.  The
117          * result of hypot(3*r, 4*r) should be approximately 5*r. (The
118          * computation of 4*r is exact since it just changes the
119          * exponent).  While the exponent of r is less than or equal
120          * to (MAX_EXPONENT - 3), the computation should not overflow.
121          */
122         java.util.Random rand = new java.util.Random();
123         for(int i = 0; i < 1000; i++) {
124             double d = rand.nextDouble();
125             // Scale d to have an exponent equal to MAX_EXPONENT -15
126             d = Math.scalb(d, Double.MAX_EXPONENT
127                                  -15 - Tests.ilogb(d));
128             for(int j = 0; j <= 13; j += 1) {
129                 failures += testHypotCase(3*d, 4*d, 5*d, 2.5);
130                 d *= 2.0; // increase exponent by 1
131             }
132         }
133
134         // Test for monotonicity failures.  Fix one argument and test
135         // two numbers before and two numbers after each chosen value;
136         // i.e.
137         //
138         // pcNeighbors[] =
139         // {nextDown(nextDown(pc)),
140         // nextDown(pc),
141         // pc,
142         // nextUp(pc),
143         // nextUp(nextUp(pc))}
144         //
145         // and we test that hypot(pcNeighbors[i]) <= hypot(pcNeighbors[i+1])
146         {
147             double pcNeighbors[] = new double[5];
148             double pcNeighborsHypot[] = new double[5];
149             double pcNeighborsStrictHypot[] = new double[5];
150
151
152             for(int i = -18; i <= 18; i++) {
153                 double pc = Math.scalb(1.0, i);
154
155                 pcNeighbors[2] = pc;
156                 pcNeighbors[1] = Math.nextDown(pc);
157                 pcNeighbors[0] = Math.nextDown(pcNeighbors[1]);
158                 pcNeighbors[3] = Math.nextUp(pc);
159                 pcNeighbors[4] = Math.nextUp(pcNeighbors[3]);
160
161                 for(int j = 0; j < pcNeighbors.length; j++) {
162                     pcNeighborsHypot[j]       =       Math.hypot(2.0, pcNeighbors[j]);
164                 }
165
166                 for(int j = 0; j < pcNeighborsHypot.length-1; j++) {
167                     if(pcNeighborsHypot[j] >  pcNeighborsHypot[j+1] ) {
168                         failures++;
169                         System.err.println("Monotonicity failure for Math.hypot on " +
170                                           pcNeighbors[j] + " and "  +
171                                           pcNeighbors[j+1] + "\n\treturned " +
172                                           pcNeighborsHypot[j] + " and " +
173                                           pcNeighborsHypot[j+1] );
174                     }
175
177                         failures++;
178                         System.err.println("Monotonicity failure for StrictMath.hypot on " +
179                                           pcNeighbors[j] + " and "  +
180                                           pcNeighbors[j+1] + "\n\treturned " +
181                                           pcNeighborsStrictHypot[j] + " and " +
183                     }
184
185
186                 }
187
188             }
189         }
190
191
192         return failures;
193     }
194
195     static int testHypotCase(double input1, double input2, double expected) {
196         return testHypotCase(input1,input2, expected, 1);
197     }
198
199     static int testHypotCase(double input1, double input2, double expected,
200                              double ulps) {
201         int failures = 0;
202         if (expected < 0.0) {
203             throw new AssertionError("Result of hypot must be greater than " +
204                                      "or equal to zero");
205         }
206
207         // Test Math and StrictMath methods with no inputs negated,
208         // each input negated singly, and both inputs negated.  Also
209         // test inputs in reversed order.
210
211         for(int i = -1; i <= 1; i+=2) {
212             for(int j = -1; j <= 1; j+=2) {
213                 double x = i * input1;
214                 double y = j * input2;
215                 failures += Tests.testUlpDiff("Math.hypot", x, y,
216                                               Math.hypot(x, y), expected, ulps);
217                 failures += Tests.testUlpDiff("Math.hypot", y, x,
218                                               Math.hypot(y, x ), expected, ulps);
219
220                 failures += Tests.testUlpDiff("StrictMath.hypot", x, y,
221                                               StrictMath.hypot(x, y), expected, ulps);
222                 failures += Tests.testUlpDiff("StrictMath.hypot", y, x,
223                                               StrictMath.hypot(y, x), expected, ulps);
224             }
225         }
226
227         return failures;
228     }
229
230     public static void main(String argv[]) {
231         int failures = 0;
232
233         failures += testHypot();
234
235         if (failures > 0) {
236             System.err.println("Testing the hypot incurred "
237                                + failures + " failures.");
238             throw new RuntimeException();
239         }
240     }
241
242 }
```