Streaming Polyphase Factor Decomposition / SKAT

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1 import unittest
2 import numpy as np
3 
4 from benchmark_realistic_skat import (
5     simulate_copy_ld_fixed,
6     simulate_gaussian_ld,
7     covariates,
8     process_full,
9     stream_kernel_raw,
10     spectrum_from_kernel,
11 )
12 
13 
14 class RealisticSKATTests(unittest.TestCase):
15     def test_copy_ld_is_reproducible_and_valid_genotype(self):
16         G1, maf1 = simulate_copy_ld_fixed(
17             n=120, m=300, block=30, copy_prob=0.9, seed=11
18         )
19         G2, maf2 = simulate_copy_ld_fixed(
20             n=120, m=300, block=30, copy_prob=0.9, seed=11
21         )
22         self.assertTrue(np.array_equal(G1, G2))
23         self.assertTrue(np.array_equal(maf1, maf2))
24         self.assertTrue(np.all(np.isin(G1, [0.0, 1.0, 2.0])))
25 
26     def test_streamed_raw_kernel_matches_materialized_factor(self):
27         G, maf = simulate_gaussian_ld(
28             n=140, m=500, block=25, rho=0.8, seed=12
29         )
30         _, Qx = covariates(140, seed=13)
31         _, Kfull, _, _ = process_full(G, maf, Qx)
32 
33         for bs in [17, 61, 149]:
34             Ks, _ = stream_kernel_raw(G, maf, Qx, bs)
35             rel = np.linalg.norm(Ks-Kfull) / np.linalg.norm(Kfull)
36             self.assertLess(rel, 2e-12)
37 
38     def test_spectrum_is_psd_after_kernel_construction(self):
39         G, maf = simulate_copy_ld_fixed(
40             n=100, m=250, block=25, copy_prob=0.85, seed=14
41         )
42         _, Qx = covariates(100, seed=15)
43         _, K, _, _ = process_full(G, maf, Qx)
44         lam, _, _ = spectrum_from_kernel(K)
45         self.assertTrue(np.all(lam >= 0))
46 
47 
48 if __name__ == "__main__":
49     unittest.main(verbosity=2)

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