def test_drawing_functions(self): f = tg.uniform_int(10, 100) self.assertTrue(type(f()) == int) self.assertTrue(10 <= f() <= 100) f = tg.uniform(10, 100) self.assertTrue(type(f()) == float) self.assertTrue(10 <= f() <= 100) f = tg.uniform_choice("abcdefg") self.assertTrue(type(f()) == str) self.assertTrue('a' <= f() <= 'g') f = tg.exponential(0.1, 0.7, 0.4) self.assertTrue(type(f()) == float) self.assertTrue(0.1 <= f() <= 0.7)
def test_drawing_functions(self): f = tg.uniform_int(10, 100) self.assertTrue(type(f()) == int) self.assertTrue(10 <= f() <= 100) f = tg.uniform(10, 100) self.assertTrue(type(f()) == float) self.assertTrue(10 <= f() <= 100) f = tg.uniform_choice("abcdefg") self.assertTrue(type(f()) == str) self.assertTrue("a" <= f() <= "g") f = tg.exponential(0.1, 0.7, 0.4) self.assertTrue(type(f()) == float) self.assertTrue(0.1 <= f() <= 0.7)
pass NAMED_PERIODS = { # Named period distributions used in several UNC papers, in milliseconds. 'uni-short' : gen.uniform_int( 3, 33), 'uni-moderate' : gen.uniform_int(10, 100), 'uni-long' : gen.uniform_int(50, 250), 'log-uni-short' : gen.log_uniform_int( 3, 33), 'log-uni-moderate' : gen.log_uniform_int(10, 100), 'log-uni-long' : gen.log_uniform_int(50, 250), } NAMED_UTILIZATIONS = { # Named utilization distributions used in several UNC papers, in milliseconds. 'uni-light' : gen.uniform(0.001, 0.1), 'uni-medium' : gen.uniform(0.1 , 0.4), 'uni-heavy' : gen.uniform(0.5 , 0.9), 'exp-light' : gen.exponential(0, 1, 0.10), 'exp-medium' : gen.exponential(0, 1, 0.25), 'exp-heavy' : gen.exponential(0, 1, 0.50), 'bimo-light' : gen.multimodal([(gen.uniform(0.001, 0.5), 8), (gen.uniform(0.5 , 0.9), 1)]), 'bimo-medium' : gen.multimodal([(gen.uniform(0.001, 0.5), 6), (gen.uniform(0.5 , 0.9), 3)]), 'bimo-heavy' : gen.multimodal([(gen.uniform(0.001, 0.5), 4), (gen.uniform(0.5 , 0.9), 5)]), }
# exp-UMIN-UMAX-MEAN-PMIN-PMAX pass NAMED_PERIODS = { # Named period distributions used in several UNC papers, in milliseconds. 'uni-short': gen.uniform_int(3, 33), 'uni-moderate': gen.uniform_int(10, 100), 'uni-long': gen.uniform_int(50, 250), } NAMED_UTILIZATIONS = { # Named utilization distributions used in several UNC papers, in milliseconds. 'uni-light': gen.uniform(0.001, 0.1), 'uni-medium': gen.uniform(0.1, 0.4), 'uni-heavy': gen.uniform(0.5, 0.9), 'exp-light': gen.exponential(0, 1, 0.10), 'exp-medium': gen.exponential(0, 1, 0.25), 'exp-heavy': gen.exponential(0, 1, 0.50), 'bimo-light': gen.multimodal([(gen.uniform(0.001, 0.5), 8), (gen.uniform(0.5, 0.9), 1)]), 'bimo-medium': gen.multimodal([(gen.uniform(0.001, 0.5), 6), (gen.uniform(0.5, 0.9), 3)]), 'bimo-heavy':