def test_compare_to_rcode():
windows, _ = ls.parse_vcf(vcf_file, "chr1", 95)
covmat, total_variance, eigenvals, eigenvecs = ls.cov_pca(windows[0].todense(), 10, 1)
results = np.loadtxt("lostruct-results/chr1.filtered.pca.csv",
delimiter=",",
skiprows=1)
totalandvalsR = results[0][0:11]
totalandvalsPy = np.concatenate(([total_variance], eigenvals)),
# Comes out as 0.9999921929150888
assert(np.corrcoef(totalandvalsR, totalandvalsPy)[0][1] >= 0.99999)
# Squared here, because signs are often opposite between the two analyses.
eigenvecsR = np.square(results[0][11:61])
eigenvecsPy = np.square(eigenvecs[0])
# Comes out as 0.9999921929150888
assert(np.corrcoef(eigenvecsR, eigenvecsPy)[0][1] >= 0.99999)
assert(covmat.shape == (50, 50))
mds_coords = np.loadtxt("lostruct-results/mds_coords.csv",
delimiter=",", skiprows=1, usecols=[2])
result = list()
for x in windows:
result.append(ls.eigen_windows(x, 10, 1))
result = np.vstack(result)
pc_dists = ls.get_pc_dists(result)
mds = pcoa(pc_dists)
# Comes out as 0.9971509982243156
assert(np.corrcoef(mds.samples['PC1'], mds_coords)[0][1] >= 0.995)
def test_eigen_windows():
windows, _ = ls.parse_vcf(vcf_file, "chr1", 99)
covmat, total_variance, eigenvals, eigenvecs = ls.eigen_windows(windows[0], 5, 1)
assert(np.abs(np.sum(covmat) - -0.4784263654778492) <= error_tolerance)
assert(np.abs(np.sum(total_variance) - 0.9265612493057297) <= error_tolerance)
assert(np.abs(np.sum(eigenvals) - 1.735862014813605) <= error_tolerance)
assert(np.abs(np.sum(eigenvecs) - 0.13157175919284625) <= error_tolerance)
def test_get_pcs_dists():
windows, _ = ls.parse_vcf(vcf_file, "chr1", 99)
result = list()
for x in take(4, windows):
result.append(ls.eigen_windows(x, 10, 1))
result = np.vstack(result)
pc_dists = ls.get_pc_dists(result)
assert(pc_dists[0][0] == 0.0)
assert(np.abs(pc_dists[0][3] - 0.30474948474286145) <= error_tolerance)
def test_l1_norm():
windows, _ = ls.parse_vcf(vcf_file, "chr1", 99)
_, _, eigenvals, _ = ls.eigen_windows(windows[0], 5, 1)
assert(np.sum(ls.l1_norm(eigenvals)) == 5.0)
def test_parse_vcf():
windows, positions = ls.parse_vcf(vcf_file, "chr1", 99)
assert(len(windows) == 119)
assert(len(positions) == len(windows))
assert(positions[0][0] == 59864)
assert(isinstance(windows[0], sparse.COO))