def testSurv(self):
# if the quantities are not numeric, you can use [] but not ()
surv = Surv.from_seq(list('allen'))
self.assertAlmostEqual(surv['a'], 0.8)
self.assertAlmostEqual(surv['e'], 0.6)
self.assertAlmostEqual(surv['l'], 0.2)
self.assertAlmostEqual(surv['n'], 0)
# test unnormalized
t = [1, 2, 2, 3, 5]
surv = Surv.from_seq(t, normalize=False)
self.assertListEqual(list(surv), [4, 2, 1, 0])
res = surv([0, 1, 2, 3, 4, 5, 6])
self.assertListEqual(list(res), [5., 4., 2., 1., 1., 0., 0.])
res = surv.inverse([0, 1, 2, 3, 4, 5])
self.assertListEqual(list(res), [5, 3, 2, 2, 1, -np.inf])
# test normalized
# () uses forward to interpolate
surv = Surv.from_seq(t)
self.assertEqual(surv(0), 1)
self.assertAlmostEqual(surv(1), 0.8)
self.assertAlmostEqual(surv(2), 0.4)
self.assertAlmostEqual(surv(3), 0.2)
self.assertAlmostEqual(surv(4), 0.2)
self.assertAlmostEqual(surv(5), 0)
self.assertAlmostEqual(surv(6), 0)
xs = range(-1, 7)
ps = surv(xs)
for p1, p2 in zip(ps, [1, 1, 0.8, 0.4, 0.2, 0.2, 0, 0]):
self.assertAlmostEqual(p1, p2)
self.assertTrue(np.isnan(surv.inverse(-0.1)))
self.assertEqual(surv.inverse(0), 5)
self.assertEqual(surv.inverse(0.1), 5)
self.assertEqual(surv.inverse(0.2), 3)
self.assertEqual(surv.inverse(0.3), 3)
self.assertEqual(surv.inverse(0.4), 2)
self.assertEqual(surv.inverse(0.5), 2)
self.assertEqual(surv.inverse(0.6), 2)
self.assertEqual(surv.inverse(0.7), 2)
self.assertEqual(surv.inverse(0.8), 1)
self.assertEqual(surv.inverse(0.9), 1)
self.assertEqual(surv.inverse(1), -np.inf)
ps = [0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
qs = surv.inverse(ps)
self.assertTrue((qs == [5, 5, 3, 3, 2, 2, 2, 2, 1, 1, -np.inf]).all())
np.random.seed(42)
xs = surv.choice(7, replace=True)
self.assertListEqual(xs.tolist(), [2, 5, 3, 2, 1, 1, 1])
def testHazard(self):
t = [1, 2, 2, 3, 5]
haz = Hazard.from_seq(t)
# () uses forward to interpolate
self.assertAlmostEqual(haz(1), 0.2)
self.assertAlmostEqual(haz(2), 0.5)
self.assertAlmostEqual(haz(3), 0.5)
self.assertAlmostEqual(haz(4), 0)
self.assertAlmostEqual(haz(5), 1.0)
self.assertAlmostEqual(haz(6), 0)
xs = [0, 1, 2, 3, 4, 5, 6]
res = haz(xs)
for x, y in zip(res, [0, 0.2, 0.5, 0.5, 0, 1, 0]):
self.assertAlmostEqual(x, y)
cdf = Cdf.from_seq(t)
haz2 = cdf.make_hazard()
res = haz2(xs)
for x, y in zip(res, [0, 0.2, 0.5, 0.5, 0, 1, 0]):
self.assertAlmostEqual(x, y)
surv = Surv.from_seq(t)
haz3 = surv.make_hazard()
res = haz3(xs)
for x, y in zip(res, [0, 0.2, 0.5, 0.5, 0, 1, 0]):
self.assertAlmostEqual(x, y)
def testSurvSampling(self):
surv = Surv.from_seq([1, 2, 3, 4, 5, 6])
expected = [2, 4, 2, 1, 5, 4, 4, 4, 1, 3]
np.random.seed(17)
a = surv.choice(10)
self.assertTrue(np.all((a == expected)))
a = surv.sample(10, replace=True, random_state=17)
self.assertTrue(np.all((a == expected)))
def testSurvComparison(self):
d4 = Surv.from_seq(range(1,5))
self.assertEqual(d4.gt_dist(2), 0.5)
self.assertEqual(d4.gt_dist(d4), 0.375)
self.assertEqual(d4.lt_dist(2), 0.25)
self.assertEqual(d4.lt_dist(d4), 0.375)
self.assertEqual(d4.ge_dist(2), 0.75)
self.assertEqual(d4.ge_dist(d4), 0.625)
self.assertEqual(d4.le_dist(2), 0.5)
self.assertEqual(d4.le_dist(d4), 0.625)
self.assertEqual(d4.eq_dist(2), 0.25)
self.assertEqual(d4.eq_dist(d4), 0.25)
self.assertEqual(d4.ne_dist(2), 0.75)
self.assertEqual(d4.ne_dist(d4), 0.75)
def testConversionFunctions(self):
t = [1, 2, 2, 3, 5, 5, 7, 10]
pmf = Pmf.from_seq(t)
cdf = Cdf.from_seq(t)
surv = Surv.from_seq(t)
haz = Hazard.from_seq(t)
cdf2 = pmf.make_cdf()
self.almost_equal_dist(cdf, cdf2)
surv2 = pmf.make_surv()
self.almost_equal_dist(surv, surv2)
haz2 = pmf.make_hazard()
self.almost_equal_dist(haz, haz2)
surv3 = haz2.make_surv()
self.almost_equal_dist(surv, surv3)
cdf3 = haz2.make_cdf()
self.almost_equal_dist(cdf, cdf3)
pmf3 = haz2.make_pmf()
self.almost_equal_dist(pmf, pmf3)