def _ljc_bv_case1(i, z, permuted_ids, weights_i, scaling):
zx = z[:, 0]
zy = z[:, 1]
self_weight = weights_i[0]
other_weights = weights_i[1:]
zyi, zyrand = _prepare_univariate(i, zy, permuted_ids, other_weights)
return zx[i] * (zyrand @ other_weights)
def _ljc_uni(i, z, permuted_ids, weights_i, scaling):
zi, zrand = _prepare_univariate(i, z, permuted_ids, weights_i)
return zi * (zrand @ weights_i)
def _local_geary(i, z, permuted_ids, weights_i, scaling):
self_weight = weights_i[0]
other_weights = weights_i[1:]
zi, zrand = _prepare_univariate(i, z, permuted_ids, other_weights)
return (zi - zrand) ** 2 @ other_weights
def _local_geary(i, z, permuted_ids, weights_i, scaling):
zi, zrand = _prepare_univariate(i, z, permuted_ids, weights_i)
return (zi-zrand)**2 @ weights_i
def _ljc_bv_case1(i, z, permuted_ids, weights_i, scaling):
zx = z[:, 0]
zy = z[:, 1]
zyi, zyrand = _prepare_univariate(i, zy, permuted_ids, weights_i)
return zx[i] * (zyrand @ weights_i)
def _ljc_mv(i, z, permuted_ids, weights_i, scaling):
self_weight = weights_i[0]
other_weights = weights_i[1:]
zi, zrand = _prepare_univariate(i, z, permuted_ids, other_weights)
return zi * (zrand @ other_weights)
