def __init__(self,
sequences,
metadata=None,
positional_metadata=None,
minter=None,
index=None):
if isinstance(sequences, TabularMSA):
if metadata is None and sequences.has_metadata():
metadata = sequences.metadata
if (positional_metadata is None
and sequences.has_positional_metadata()):
positional_metadata = sequences.positional_metadata
if minter is None and index is None:
index = sequences.index
self._seqs = pd.Series([])
self.extend(sequences, minter=minter, index=index)
MetadataMixin._init_(self, metadata=metadata)
PositionalMetadataMixin._init_(self,
positional_metadata=positional_metadata)
def __init__(self, sequences, metadata=None, positional_metadata=None,
minter=None, index=None):
# TODO: optimize this to not append Series for each sequence.
self._seqs = pd.Series([])
for sequence in sequences:
self.append(sequence)
if minter is not None and index is not None:
raise ValueError(
"Cannot use both `minter` and `index` at the same time.")
if minter is not None:
self.reassign_index(minter=minter)
elif index is not None:
# Cast to Index to identify tuples as a MultiIndex to match
# pandas constructor. Just setting would make an index of tuples.
if not isinstance(index, pd.Index):
index = pd.Index(index)
self.index = index
MetadataMixin._init_(self, metadata=metadata)
PositionalMetadataMixin._init_(
self, positional_metadata=positional_metadata)
def __init__(self, axis_len, positional_metadata=None):
self._axis_len = axis_len
PositionalMetadataMixin._init_(
self, positional_metadata=positional_metadata)
def __init__(self, axis_len, positional_metadata=None):
self._axis_len = axis_len
PositionalMetadataMixin._init_(self, positional_metadata=positional_metadata)
