def compress_genotypes(g, condition, axis, wrap_axes, cls, compress, **kwargs):
condition = np.asarray(condition, dtype=bool)
check_ndim(condition, 1)
_check_condition_length(g, condition, axis)
# apply compress operation on the underlying values
out = compress(condition, g.values, axis=axis, **kwargs)
if axis in wrap_axes:
out = cls(out)
if g.mask is not None:
out.mask = compress(condition, g.mask, axis=axis, **kwargs)
if g.is_phased is not None:
out.is_phased = compress(condition,
g.is_phased,
axis=axis,
**kwargs)
return out
def compress_haplotype_array(h, condition, axis, cls, compress, **kwargs):
condition = np.asarray(condition, dtype=bool)
check_ndim(condition, 1)
_check_condition_length(h, condition, axis)
out = compress(condition, h.values, axis=axis, **kwargs)
return cls(out)
def __init__(self, data):
super(GenotypeAlleleCountsChunkedArray, self).__init__(data)
check_ndim(self.values, 3)
check_integer_dtype(self.values)
def __init__(self, data):
super(HaplotypeChunkedArray, self).__init__(data)
check_ndim(self.values, 2)
check_integer_dtype(self.values)
def __init__(self, data):
super(GenotypeChunkedArray, self).__init__(data)
check_ndim(self.values, 3)
check_integer_dtype(self.values)
self._mask = None
self._is_phased = None
def __init__(self, data, chunks=None, name=None, lock=False):
super(GenotypeDaskArray, self).__init__(data,
chunks=chunks,
name=name,
lock=lock)
check_ndim(self.values, 3)
def __init__(self, data, chunks=None, name=None, lock=False):
super(GenotypeAlleleCountsDaskVector, self).__init__(data,
chunks=chunks,
name=name,
lock=lock)
check_ndim(self.values, 2)
