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Diffstat (limited to 'src/pal/tests/palsuite/c_runtime/powf/test1/test1.c')
-rw-r--r-- | src/pal/tests/palsuite/c_runtime/powf/test1/test1.c | 229 |
1 files changed, 229 insertions, 0 deletions
diff --git a/src/pal/tests/palsuite/c_runtime/powf/test1/test1.c b/src/pal/tests/palsuite/c_runtime/powf/test1/test1.c new file mode 100644 index 0000000000..ca738e8c8d --- /dev/null +++ b/src/pal/tests/palsuite/c_runtime/powf/test1/test1.c @@ -0,0 +1,229 @@ +// Licensed to the .NET Foundation under one or more agreements. +// The .NET Foundation licenses this file to you under the MIT license. +// See the LICENSE file in the project root for more information. + +/*===================================================================== +** +** Source: test1.c +** +** Purpose: Tests that atan2f returns correct values for a subset of values. +** Tests with positive and negative values of x and y to ensure +** atan2f is returning results from the correct quadrant. +** +**===================================================================*/ + +#include <palsuite.h> + +// binary32 (float) has a machine epsilon of 2^-23 (approx. 1.19e-07). However, this +// is slightly too accurate when writing tests meant to run against libm implementations +// for various platforms. 2^-21 (approx. 4.76e-07) seems to be as accurate as we can get. +// +// The tests themselves will take PAL_EPSILON and adjust it according to the expected result +// so that the delta used for comparison will compare the most significant digits and ignore +// any digits that are outside the double precision range (6-9 digits). + +// For example, a test with an expect result in the format of 0.xxxxxxxxx will use PAL_EPSILON +// for the variance, while an expected result in the format of 0.0xxxxxxxxx will use +// PAL_EPSILON / 10 and and expected result in the format of x.xxxxxx will use PAL_EPSILON * 10. +#define PAL_EPSILON 4.76837158e-07 + +#define PAL_NAN sqrtf(-1.0f) +#define PAL_POSINF -logf(0.0f) +#define PAL_NEGINF logf(0.0f) + +/** + * Helper test structure + */ +struct test +{ + float x; /* first component of the value to test the function with */ + float y; /* second component of the value to test the function with */ + float expected; /* expected result */ + float variance; /* maximum delta between the expected and actual result */ +}; + +/** + * validate + * + * test validation function + */ +void __cdecl validate(float x, float y, float expected, float variance) +{ + float result = powf(x, y); + + /* + * The test is valid when the difference between result + * and expected is less than or equal to variance + */ + float delta = fabsf(result - expected); + + if (delta > variance) + { + Fail("powf(%g, %g) returned %10.9g when it should have returned %10.9g", + x, y, result, expected); + } +} + +/** + * validate + * + * test validation function for values returning NaN + */ +void __cdecl validate_isnan(float x, float y) +{ + float result = powf(x, y); + + if (!_isnanf(result)) + { + Fail("powf(%g, %g) returned %10.9g when it should have returned %10.9g", + x, y, result, PAL_NAN); + } +} + +/** + * main + * + * executable entry point + */ +int __cdecl main(int argc, char **argv) +{ + struct test tests[] = + { + /* x y expected variance */ + { PAL_NEGINF, PAL_NEGINF, 0, PAL_EPSILON }, + { PAL_NEGINF, PAL_POSINF, PAL_POSINF, 0 }, + + { -10, PAL_NEGINF, 0, PAL_EPSILON }, + { -10, -1, -0.1f, PAL_EPSILON }, + { -10, 0, 1, PAL_EPSILON * 10 }, + { -10, 1, -10, PAL_EPSILON * 100 }, + { -10, PAL_POSINF, PAL_POSINF, 0 }, + + { -2.71828183f, PAL_NEGINF, 0, PAL_EPSILON }, // x: -(e) + { -2.71828183f, -1, -0.367879441f, PAL_EPSILON }, // x: -(e) + { -2.71828183f, 0, 1, PAL_EPSILON * 10 }, // x: -(e) + { -2.71828183f, 1, -2.71828183f, PAL_EPSILON * 10 }, // x: -(e) expected: e + { -2.71828183f, PAL_POSINF, PAL_POSINF, 0 }, // x: -(e) + + { -0.0, PAL_NEGINF, PAL_POSINF, 0 }, + { -0.0, -1, PAL_NEGINF, 0 }, + { -0.0f, -0.0f, 1, PAL_EPSILON * 10 }, + { -0.0f, 0, 1, PAL_EPSILON * 10 }, + { -0.0, 1, -0.0, PAL_EPSILON }, + { -0.0, PAL_POSINF, 0, PAL_EPSILON }, + + { 0.0, PAL_NEGINF, PAL_POSINF, 0 }, + { 0.0, -1, PAL_POSINF, 0 }, + { 0, -0.0f, 1, PAL_EPSILON * 10 }, + { 0, 0, 1, PAL_EPSILON * 10 }, + { 0.0, 1, 0, PAL_EPSILON }, + { 0.0, PAL_POSINF, 0, PAL_EPSILON }, + + { 1, PAL_NEGINF, 1, PAL_EPSILON * 10 }, + { 1, PAL_POSINF, 1, PAL_EPSILON * 10 }, + + { 2.71828183f, PAL_NEGINF, 0, PAL_EPSILON }, + { 2.71828183f, -3.14159265f, 0.0432139183f, PAL_EPSILON / 10 }, // x: e y: -(pi) + { 2.71828183f, -2.71828183f, 0.0659880358f, PAL_EPSILON / 10 }, // x: e y: -(e) + { 2.71828183f, -2.30258509f, 0.1f, PAL_EPSILON }, // x: e y: -(ln(10)) + { 2.71828183f, -1.57079633f, 0.207879576f, PAL_EPSILON }, // x: e y: -(pi / 2) + { 2.71828183f, -1.44269504f, 0.236290088f, PAL_EPSILON }, // x: e y: -(logf2(e)) + { 2.71828183f, -1.41421356f, 0.243116734f, PAL_EPSILON }, // x: e y: -(sqrtf(2)) + { 2.71828183f, -1.12837917f, 0.323557264f, PAL_EPSILON }, // x: e y: -(2 / sqrtf(pi)) + { 2.71828183f, -1, 0.367879441f, PAL_EPSILON }, // x: e y: -(1) + { 2.71828183f, -0.785398163f, 0.455938128f, PAL_EPSILON }, // x: e y: -(pi / 4) + { 2.71828183f, -0.707106781f, 0.493068691f, PAL_EPSILON }, // x: e y: -(1 / sqrtf(2)) + { 2.71828183f, -0.693147181f, 0.5f, PAL_EPSILON }, // x: e y: -(ln(2)) + { 2.71828183f, -0.636619772f, 0.529077808f, PAL_EPSILON }, // x: e y: -(2 / pi) + { 2.71828183f, -0.434294482f, 0.647721485f, PAL_EPSILON }, // x: e y: -(log10f(e)) + { 2.71828183f, -0.318309886f, 0.727377349f, PAL_EPSILON }, // x: e y: -(1 / pi) + { 2.71828183f, 0, 1, PAL_EPSILON * 10 }, // x: e + { 2.71828183f, 0.318309886f, 1.37480223f, PAL_EPSILON * 10 }, // x: e y: 1 / pi + { 2.71828183f, 0.434294482f, 1.54387344f, PAL_EPSILON * 10 }, // x: e y: log10f(e) + { 2.71828183f, 0.636619772f, 1.89008116f, PAL_EPSILON * 10 }, // x: e y: 2 / pi + { 2.71828183f, 0.693147181f, 2, PAL_EPSILON * 10 }, // x: e y: ln(2) + { 2.71828183f, 0.707106781f, 2.02811498f, PAL_EPSILON * 10 }, // x: e y: 1 / sqrtf(2) + { 2.71828183f, 0.785398163f, 2.19328005f, PAL_EPSILON * 10 }, // x: e y: pi / 4 + { 2.71828183f, 1, 2.71828183f, PAL_EPSILON * 10 }, // x: e expected: e + { 2.71828183f, 1.12837917f, 3.09064302f, PAL_EPSILON * 10 }, // x: e y: 2 / sqrtf(pi) + { 2.71828183f, 1.41421356f, 4.11325038f, PAL_EPSILON * 10 }, // x: e y: sqrtf(2) + { 2.71828183f, 1.44269504f, 4.23208611f, PAL_EPSILON * 10 }, // x: e y: logf2(e) + { 2.71828183f, 1.57079633f, 4.81047738f, PAL_EPSILON * 10 }, // x: e y: pi / 2 + { 2.71828183f, 2.30258509f, 10, PAL_EPSILON * 100 }, // x: e y: ln(10) + { 2.71828183f, 2.71828183f, 15.1542622f, PAL_EPSILON * 100 }, // x: e y: e + { 2.71828183f, 3.14159265f, 23.1406926f, PAL_EPSILON * 100 }, // x: e y: pi + { 2.71828183f, PAL_POSINF, PAL_POSINF, 0 }, // x: e + + { 10, PAL_NEGINF, 0, 0 }, + { 10, -3.14159265f, 0.000721784159f, PAL_EPSILON / 1000 }, // y: -(pi) + { 10, -2.71828183f, 0.00191301410f, PAL_EPSILON / 100 }, // y: -(e) + { 10, -2.30258509f, 0.00498212830f, PAL_EPSILON / 100 }, // y: -(ln(10)) + { 10, -1.57079633f, 0.0268660410f, PAL_EPSILON / 10 }, // y: -(pi / 2) + { 10, -1.44269504f, 0.0360831928f, PAL_EPSILON / 10 }, // y: -(logf2(e)) + { 10, -1.41421356f, 0.0385288847f, PAL_EPSILON / 10 }, // y: -(sqrtf(2)) + { 10, -1.12837917f, 0.0744082059f, PAL_EPSILON / 10 }, // y: -(2 / sqrtf(pi)) + { 10, -1, 0.1f, PAL_EPSILON }, // y: -(1) + { 10, -0.785398163f, 0.163908636f, PAL_EPSILON }, // y: -(pi / 4) + { 10, -0.707106781f, 0.196287760f, PAL_EPSILON }, // y: -(1 / sqrtf(2)) + { 10, -0.693147181f, 0.202699566f, PAL_EPSILON }, // y: -(ln(2)) + { 10, -0.636619772f, 0.230876765f, PAL_EPSILON }, // y: -(2 / pi) + { 10, -0.434294482f, 0.367879441f, PAL_EPSILON }, // y: -(log10f(e)) + { 10, -0.318309886f, 0.480496373f, PAL_EPSILON }, // y: -(1 / pi) + { 10, 0, 1, PAL_EPSILON * 10 }, + { 10, 0.318309886f, 2.08118116f, PAL_EPSILON * 10 }, // y: 1 / pi + { 10, 0.434294482f, 2.71828183f, PAL_EPSILON * 10 }, // y: log10f(e) expected: e + { 10, 0.636619772f, 4.33131503f, PAL_EPSILON * 10 }, // y: 2 / pi + { 10, 0.693147181f, 4.93340967f, PAL_EPSILON * 10 }, // y: ln(2) + { 10, 0.707106781f, 5.09456117f, PAL_EPSILON * 10 }, // y: 1 / sqrtf(2) + { 10, 0.785398163f, 6.10095980f, PAL_EPSILON * 10 }, // y: pi / 4 + { 10, 1, 10, PAL_EPSILON * 100 }, + { 10, 1.12837917f, 13.4393779f, PAL_EPSILON * 100 }, // y: 2 / sqrtf(pi) + { 10, 1.41421356f, 25.9545535f, PAL_EPSILON * 100 }, // y: sqrtf(2) + { 10, 1.44269504f, 27.7137338f, PAL_EPSILON * 100 }, // y: logf2(e) + { 10, 1.57079633f, 37.2217105f, PAL_EPSILON * 100 }, // y: pi / 2 + { 10, 2.30258509f, 200.717432f, PAL_EPSILON * 1000 }, // y: ln(10) + { 10, 2.71828183f, 522.735300f, PAL_EPSILON * 1000 }, // y: e + { 10, 3.14159265f, 1385.45573f, PAL_EPSILON * 10000 }, // y: pi + { 10, PAL_POSINF, PAL_POSINF, 0 }, + + { PAL_POSINF, PAL_NEGINF, 0, PAL_EPSILON }, + { PAL_POSINF, PAL_POSINF, PAL_POSINF, 0 }, + }; + + if (PAL_Initialize(argc, argv) != 0) + { + return FAIL; + } + + for (int i = 0; i < (sizeof(tests) / sizeof(struct test)); i++) + { + validate(tests[i].x, tests[i].y, tests[i].expected, tests[i].variance); + } + + validate_isnan(-10, -1.57079633f); // y: -(pi / 2) + validate_isnan(-10, -0.785398163f); // y: -(pi / 4) + validate_isnan(-10, 0.785398163f); // y: pi / 4 + validate_isnan(-10, 1.57079633f); // y: pi / 2 + + validate_isnan(-2.71828183f, -1.57079633f); // x: -(e) y: -(pi / 2) + validate_isnan(-2.71828183f, -0.785398163f); // x: -(e) y: -(pi / 4) + validate_isnan(-2.71828183f, 0.785398163f); // x: -(e) y: pi / 4 + validate_isnan(-2.71828183f, 1.57079633f); // x: -(e) y: pi / 2 + + validate_isnan(-1, PAL_NEGINF); + validate_isnan(-1, PAL_POSINF); + + validate_isnan(PAL_NAN, -0.0); + validate_isnan(PAL_NAN, 0); + + validate_isnan(PAL_NEGINF, PAL_NAN); + validate_isnan(PAL_NAN, PAL_NEGINF); + + validate_isnan(PAL_POSINF, PAL_NAN); + validate_isnan(PAL_NAN, PAL_POSINF); + + validate_isnan(PAL_NAN, PAL_NAN); + + PAL_Terminate(); + return PASS; +} |