def test_nearest_neighbor_in_sorted_arrays(self):
a = np.sort(np.unique(np.random.randint(1000, size=120)))
b = np.sort(np.unique(np.random.randint(1000, size=150)))
actual = list(util.nearest_neighbor_in_sorted_arrays(a, b))
expected = [np.abs(a - x).argmin() for x in b]
assert_equal(actual, expected,
'Wrong nearest neighbor location in sorted arrays')
def calculate_genetic_positions(map_file, snps):
'''Calculate the closest genetic positions to a list of SNP bp''s on a chromosome in the
chromosomal genetic map file map_file, and update the SNP database with those positions.'''
positions = np.loadtxt(map_file, skiprows=1, usecols=[1, 3], dtype=np.float)
bp, genetic = positions[:, 0], positions[:, 1]
closest_bp = list(util.nearest_neighbor_in_sorted_arrays(bp, [x.bp for x in snps]))
for i, x in enumerate(snps): x.genetic_pos = genetic[closest_bp[i]]
snp_dao.save(snps)
def calculate_genetic_positions(map_file, snps):
'''Calculate the closest genetic positions to a list of SNP bp''s on a chromosome in the
chromosomal genetic map file map_file, and update the SNP database with those positions.'''
positions = np.loadtxt(map_file,
skiprows=1,
usecols=[1, 3],
dtype=np.float)
bp, genetic = positions[:, 0], positions[:, 1]
closest_bp = list(
util.nearest_neighbor_in_sorted_arrays(bp, [x.bp for x in snps]))
for i, x in enumerate(snps):
x.genetic_pos = genetic[closest_bp[i]]
snp_dao.save(snps)
def test_nearest_neighbor_in_sorted_arrays(self):
a = np.sort(np.unique(np.random.randint(1000, size=120)))
b = np.sort(np.unique(np.random.randint(1000, size=150)))
actual = list(util.nearest_neighbor_in_sorted_arrays(a, b))
expected = [np.abs(a - x).argmin() for x in b]
assert_equal(actual, expected, 'Wrong nearest neighbor location in sorted arrays')
