示例#1
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    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
示例#2
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    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
示例#3
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    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)
示例#4
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    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)
示例#5
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    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
示例#6
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    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
示例#7
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 def __ne__(self, other):
     return MetadataMixin._ne_(self, other)
示例#8
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 def __eq__(self, other):
     return MetadataMixin._eq_(self, other)
示例#9
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 def __init__(self, metadata=None):
     MetadataMixin._init_(self, metadata=metadata)
示例#10
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 def __deepcopy__(self, memo):
     copy = self.__class__(metadata=None)
     copy._metadata = MetadataMixin._deepcopy_(self, memo)
     return copy
示例#11
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 def __copy__(self):
     copy = self.__class__(metadata=None)
     copy._metadata = MetadataMixin._copy_(self)
     return copy
示例#12
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 def __ne__(self, other):
     return MetadataMixin._ne_(self, other)
示例#13
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    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)
示例#14
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 def __init__(self, metadata=None):
     MetadataMixin._init_(self, metadata=metadata)
示例#15
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    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)
示例#16
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 def __copy__(self):
     copy = self.__class__(metadata=None)
     copy._metadata = MetadataMixin._copy_(self)
     return copy
示例#17
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 def __deepcopy__(self, memo):
     copy = self.__class__(metadata=None)
     copy._metadata = MetadataMixin._deepcopy_(self, memo)
     return copy
示例#18
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 def __eq__(self, other):
     return MetadataMixin._eq_(self, other)