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Diffstat (limited to 'test/minitest/test_minitest_benchmark.rb')
-rw-r--r-- | test/minitest/test_minitest_benchmark.rb | 104 |
1 files changed, 0 insertions, 104 deletions
diff --git a/test/minitest/test_minitest_benchmark.rb b/test/minitest/test_minitest_benchmark.rb deleted file mode 100644 index 089d0b3ce0..0000000000 --- a/test/minitest/test_minitest_benchmark.rb +++ /dev/null @@ -1,104 +0,0 @@ -############################################################ -# This file is imported from a different project. -# DO NOT make modifications in this repo. -# File a patch instead and assign it to Ryan Davis -############################################################ - -require 'minitest/autorun' -require 'minitest/benchmark' - -## -# Used to verify data: -# http://www.wolframalpha.com/examples/RegressionAnalysis.html - -class TestMiniTestBenchmark < MiniTest::Unit::TestCase - def test_cls_bench_exp - assert_equal [2, 4, 8, 16, 32], self.class.bench_exp(2, 32, 2) - end - - def test_cls_bench_linear - assert_equal [2, 4, 6, 8, 10], self.class.bench_linear(2, 10, 2) - end - - def test_cls_benchmark_methods - assert_equal [], self.class.benchmark_methods - - c = Class.new(MiniTest::Unit::TestCase) do - def bench_blah - end - end - - assert_equal ["bench_blah"], c.benchmark_methods - end - - def test_cls_bench_range - assert_equal [1, 10, 100, 1_000, 10_000], self.class.bench_range - end - - def test_fit_exponential_clean - x = [1.0, 2.0, 3.0, 4.0, 5.0] - y = x.map { |n| 1.1 * Math.exp(2.1 * n) } - - assert_fit :exponential, x, y, 1.0, 1.1, 2.1 - end - - def test_fit_exponential_noisy - x = [1.0, 1.9, 2.6, 3.4, 5.0] - y = [12, 10, 8.2, 6.9, 5.9] - - # verified with Numbers and R - assert_fit :exponential, x, y, 0.95, 13.81148, -0.1820 - end - - def test_fit_linear_clean - # y = m * x + b where m = 2.2, b = 3.1 - x = (1..5).to_a - y = x.map { |n| 2.2 * n + 3.1 } - - assert_fit :linear, x, y, 1.0, 3.1, 2.2 - end - - def test_fit_linear_noisy - x = [ 60, 61, 62, 63, 65] - y = [3.1, 3.6, 3.8, 4.0, 4.1] - - # verified in numbers and R - assert_fit :linear, x, y, 0.8315, -7.9635, 0.1878 - end - - def test_fit_power_clean - # y = A x ** B, where B = b and A = e ** a - # if, A = 1, B = 2, then - - x = [1.0, 2.0, 3.0, 4.0, 5.0] - y = [1.0, 4.0, 9.0, 16.0, 25.0] - - assert_fit :power, x, y, 1.0, 1.0, 2.0 - end - - def test_fit_power_noisy - # from www.engr.uidaho.edu/thompson/courses/ME330/lecture/least_squares.html - x = [10, 12, 15, 17, 20, 22, 25, 27, 30, 32, 35] - y = [95, 105, 125, 141, 173, 200, 253, 298, 385, 459, 602] - - # verified in numbers - assert_fit :power, x, y, 0.90, 2.6217, 1.4556 - - # income to % of households below income amount - # http://library.wolfram.com/infocenter/Conferences/6461/PowerLaws.nb - x = [15000, 25000, 35000, 50000, 75000, 100000] - y = [0.154, 0.283, 0.402, 0.55, 0.733, 0.843] - - # verified in numbers - assert_fit :power, x, y, 0.96, 3.119e-5, 0.8959 - end - - def assert_fit msg, x, y, fit, exp_a, exp_b - a, b, rr = send "fit_#{msg}", x, y - - assert_operator rr, :>=, fit - assert_in_delta exp_a, a - assert_in_delta exp_b, b - end -end - |