def rogers_huff_r_between(gna, gnb, fill=np.nan):
"""Estimate the linkage disequilibrium parameter *r* for each pair of
variants between the two input arrays, using the method of Rogers and
Huff (2008).
Parameters
----------
gna, gnb : array_like, int8, shape (n_variants, n_samples)
Diploid genotypes at biallelic variants, coded as the number of
alternate alleles per call (i.e., 0 = hom ref, 1 = het, 2 = hom alt).
fill : float, optional
Value to use where r cannot be calculated.
Returns
-------
r : ndarray, float, shape (m_variants, n_variants )
Matrix in rectangular form.
"""
# check inputs
gna = asarray_ndim(gna, 2, dtype='i1')
gnb = asarray_ndim(gnb, 2, dtype='i1')
# compute correlation coefficients
r = gn_pairwise2_corrcoef_int8(gna, gnb, fill)
# convenience for singletons
if r.size == 1:
r = r[0, 0]
return r
def rogers_huff_r_between(gna, gnb, fill=np.nan):
"""Estimate the linkage disequilibrium parameter *r* for each pair of
variants between the two input arrays, using the method of Rogers and
Huff (2008).
Parameters
----------
gna, gnb : array_like, int8, shape (n_variants, n_samples)
Diploid genotypes at biallelic variants, coded as the number of
alternate alleles per call (i.e., 0 = hom ref, 1 = het, 2 = hom alt).
Returns
-------
r : ndarray, float, shape (m_variants, n_variants )
Matrix in rectangular form.
"""
# check inputs
gna = asarray_ndim(gna, 2, dtype='i1')
gnb = asarray_ndim(gnb, 2, dtype='i1')
# compute correlation coefficients
from allel.opt.stats import gn_pairwise2_corrcoef_int8
r = gn_pairwise2_corrcoef_int8(gna, gnb, fill)
# convenience for singletons
if r.size == 1:
r = r[0, 0]
return r
