def __deepcopy__(self, memo):
"""Return a deep copy of this MSA.
Returns
-------
TabularMSA
Deep copy of this MSA.
See Also
--------
__copy__
"""
seqs = (copy.deepcopy(seq, memo) for seq in self._seqs)
# Copying index isn't necessary because pd.Index is immutable.
msa_copy = self.__class__(sequences=seqs,
index=self.index,
metadata=None,
positional_metadata=None)
msa_copy._metadata = MetadataMixin._deepcopy_(self, memo)
msa_copy._positional_metadata = \
PositionalMetadataMixin._deepcopy_(self, memo)
return msa_copy
def __copy__(self):
"""Return a shallow copy of this MSA.
Returns
-------
TabularMSA
Shallow copy of this MSA. Sequence objects will be shallow-copied.
See Also
--------
__deepcopy__
"""
seqs = (copy.copy(seq) for seq in self._seqs)
# Copying index isn't necessary because pd.Index is immutable.
msa_copy = self.__class__(sequences=seqs,
index=self.index,
metadata=None,
positional_metadata=None)
msa_copy._metadata = MetadataMixin._copy_(self)
msa_copy._positional_metadata = PositionalMetadataMixin._copy_(self)
return msa_copy
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 __deepcopy__(self, memo):
"""Return a deep copy of this MSA.
Returns
-------
TabularMSA
Deep copy of this MSA.
See Also
--------
__copy__
"""
seqs = (copy.deepcopy(seq, memo) for seq in self._seqs)
# Copying index isn't necessary because pd.Index is immutable.
msa_copy = self.__class__(sequences=seqs, index=self.index,
metadata=None, positional_metadata=None)
msa_copy._metadata = MetadataMixin._deepcopy_(self, memo)
msa_copy._positional_metadata = \
PositionalMetadataMixin._deepcopy_(self, memo)
return msa_copy
def __copy__(self):
"""Return a shallow copy of this MSA.
Returns
-------
TabularMSA
Shallow copy of this MSA. Sequence objects will be shallow-copied.
See Also
--------
__deepcopy__
"""
seqs = (copy.copy(seq) for seq in self._seqs)
# Copying index isn't necessary because pd.Index is immutable.
msa_copy = self.__class__(sequences=seqs, index=self.index,
metadata=None,
positional_metadata=None)
msa_copy._metadata = MetadataMixin._copy_(self)
msa_copy._positional_metadata = PositionalMetadataMixin._copy_(self)
return msa_copy
def __ne__(self, other):
return MetadataMixin._ne_(self, other)
def __eq__(self, other):
return MetadataMixin._eq_(self, other)
def __init__(self, metadata=None):
MetadataMixin._init_(self, metadata=metadata)
def __deepcopy__(self, memo):
copy = self.__class__(metadata=None)
copy._metadata = MetadataMixin._deepcopy_(self, memo)
return copy
def __copy__(self):
copy = self.__class__(metadata=None)
copy._metadata = MetadataMixin._copy_(self)
return copy
def __ne__(self, other):
return MetadataMixin._ne_(self, other)
def __eq__(self, other):
"""Determine if this MSA is equal to another.
``TabularMSA`` objects are equal if their sequences, index, metadata,
and positional metadata are equal.
Parameters
----------
other : TabularMSA
MSA to test for equality against.
Returns
-------
bool
Indicates whether this MSA is equal to `other`.
Examples
--------
>>> from skbio import DNA, RNA, TabularMSA
>>> msa = TabularMSA([DNA('ACG'), DNA('AC-')])
>>> msa == msa
True
MSAs with different sequence characters are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('--G')])
False
MSAs with different types of sequences (different ``dtype``) are not
equal:
>>> msa == TabularMSA([RNA('ACG'), RNA('AC-')])
False
MSAs with different sequence metadata are not equal:
>>> msa == TabularMSA([DNA('ACG', metadata={'id': 'a'}), DNA('AC-')])
False
MSAs with different index labels are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('AC-')], minter=str)
False
MSAs with different metadata are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('AC-')],
... metadata={'id': 'msa-id'})
False
MSAs with different positional metadata are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('AC-')],
... positional_metadata={'prob': [3, 2, 1]})
False
"""
if not isinstance(other, TabularMSA):
return False
if not MetadataMixin._eq_(self, other):
return False
if not PositionalMetadataMixin._eq_(self, other):
return False
return self._seqs.equals(other._seqs)
def __init__(self, metadata=None):
MetadataMixin._init_(self, metadata=metadata)
def __eq__(self, other):
"""Determine if this MSA is equal to another.
``TabularMSA`` objects are equal if their sequences, index, metadata,
and positional metadata are equal.
Parameters
----------
other : TabularMSA
MSA to test for equality against.
Returns
-------
bool
Indicates whether this MSA is equal to `other`.
Examples
--------
>>> from skbio import DNA, RNA, TabularMSA
>>> msa = TabularMSA([DNA('ACG'), DNA('AC-')])
>>> msa == msa
True
MSAs with different sequence characters are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('--G')])
False
MSAs with different types of sequences (different ``dtype``) are not
equal:
>>> msa == TabularMSA([RNA('ACG'), RNA('AC-')])
False
MSAs with different sequence metadata are not equal:
>>> msa == TabularMSA([DNA('ACG', metadata={'id': 'a'}), DNA('AC-')])
False
MSAs with different index labels are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('AC-')], minter=str)
False
MSAs with different metadata are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('AC-')],
... metadata={'id': 'msa-id'})
False
MSAs with different positional metadata are not equal:
>>> msa == TabularMSA([DNA('ACG'), DNA('AC-')],
... positional_metadata={'prob': [3, 2, 1]})
False
"""
if not isinstance(other, TabularMSA):
return False
if not MetadataMixin._eq_(self, other):
return False
if not PositionalMetadataMixin._eq_(self, other):
return False
return self._seqs.equals(other._seqs)
def __copy__(self):
copy = self.__class__(metadata=None)
copy._metadata = MetadataMixin._copy_(self)
return copy
def __deepcopy__(self, memo):
copy = self.__class__(metadata=None)
copy._metadata = MetadataMixin._deepcopy_(self, memo)
return copy
def __eq__(self, other):
return MetadataMixin._eq_(self, other)