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# ----------------------------------------------------------------------------
# Copyright (c) 2013--, scikit-bio development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE.txt, distributed with this software.
# ----------------------------------------------------------------------------
import numpy as np
import pandas as pd
from skbio.sequence import Protein
from skbio.stats.ordination import OrdinationResults
from skbio.embedding._embedding import SequenceEmbedding, SequenceVector, _repr_helper
def _validate_protein(sequence):
if isinstance(sequence, Protein):
sequence = str(sequence)
elif isinstance(sequence, str):
if " " in sequence:
sequence = sequence.replace(" ", "")
# perform a check to make sure the sequence is a valid protein sequence
_ = Protein(sequence)
return sequence
class ProteinEmbedding(SequenceEmbedding):
r"""Embedding of a protein sequence.
Parameters
----------
embedding : array_like
The embedding of the protein sequence. Row vectors correspond to
the latent residues coordinates.
sequence : str, Protein, or 1D ndarray
Characters representing the protein sequence itself.
clip_head : bool, optional
If ``True``, then the first row of the embedding will be removed.
Some language models specify start tokens, and this parameter can
be used to account for this.
clip_tail : bool, optional
If ``True``, then the last row of the embedding will be removed.
Some language models specify end tokens, and this parameter can
be used to account for this.
See Also
--------
skbio.sequence.Protein
Examples
--------
>>> from skbio.embedding import ProteinEmbedding
>>> import numpy as np
>>> embedding = np.random.rand(10, 3)
>>> sequence = "ACDEFGHIKL"
>>> ProteinEmbedding(embedding, sequence)
ProteinEmbedding
--------------------------
Stats:
length: 10
embedding dimension: 3
has gaps: False
has degenerates: False
has definites: True
has stops: False
--------------------------
0 ACDEFGHIKL
"""
default_write_format = "embed"
def __init__(self, embedding, sequence, clip_head=False, clip_tail=False, **kwargs):
embedding = np.asarray(embedding)
if clip_head:
embedding = embedding[1:]
if clip_tail:
embedding = embedding[:-1]
sequence = _validate_protein(sequence)
super(ProteinEmbedding, self).__init__(
embedding=embedding, sequence=sequence, **kwargs
)
@property
def residues(self):
r"""Array containing underlying residue characters."""
return self._ids.view("|S1")
def __repr__(self):
r"""Return a string representation of the ProteinEmbedding object.
Returns
-------
str
String representation of the ProteinEmbedding object.
See Also
--------
skbio.sequence.Protein
"""
seq = Protein(str(self))
rstr = _repr_helper(
repr(seq),
"Protein",
"ProteinEmbedding",
"embedding",
regex_match="has gaps",
shape=self.embedding.shape[1],
)
return rstr
example_protein_embedding = ProteinEmbedding(
np.random.default_rng(0).normal(size=(62, 1024)),
"IGKEEIQQRLAQFVDHWKELKQLAAARGQRLEESLEYQQFVANVEEEEAWINEKMTLVASED",
)
class ProteinVector(SequenceVector):
r"""Vector representation for a protein sequence.
Parameters
----------
vector : 1D or 2D array_like
The vector representation of the protein sequence. Typically a 1D array. Can
also be a 2D array with only one row.
sequence : str, Sequence, or 1D ndarray
Characters representing the protein sequence itself.
See Also
--------
SequenceVector
skbio.sequence.Protein
Examples
--------
>>> from skbio.embedding import ProteinVector
>>> import numpy as np
>>> vector = np.random.rand(10)
>>> sequence = "ACDEFGHIKL"
>>> ProteinVector(vector, sequence)
ProteinVector
--------------------------
Stats:
length: 10
vector dimension: 10
has gaps: False
has degenerates: False
has definites: True
has stops: False
--------------------------
0 ACDEFGHIKL
"""
default_write_format = "embed"
def __init__(self, vector, sequence: str, **kwargs):
sequence = _validate_protein(sequence)
super(ProteinVector, self).__init__(vector, sequence=sequence, **kwargs)
def __repr__(self):
r"""Return a string representation of the ProteinVector object.
Returns
-------
str
String representation of the ProteinEmbedding object.
See Also
--------
skbio.sequence.Protein
"""
seq = Protein(str(self))
rstr = _repr_helper(
repr(seq),
"Protein",
"ProteinVector",
"vector",
regex_match="has gaps",
shape=self.embedding.shape[1],
)
return rstr
|
