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)