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Another fix for dummy msa feature creation

This commit is contained in:
Christina Floristean 2023-11-06 13:50:11 -05:00
parent e67d041759
commit d0f5531b0b
1 changed files with 13 additions and 8 deletions
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21
openfold/data/data_pipeline.py
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@ -272,14 +272,19 @@ def run_msa_tool(
return result return result
# Generate 1-sequence MSA features having only the input sequence def make_dummy_msa_obj(input_sequence) -> parsers.Msa:
def make_dummy_msa_feats(input_sequence) -> parsers.Msa:
deletion_matrix = [[0 for _ in input_sequence]] deletion_matrix = [[0 for _ in input_sequence]]
return parsers.Msa(sequences=input_sequence, return parsers.Msa(sequences=[input_sequence],
deletion_matrix=deletion_matrix, deletion_matrix=deletion_matrix,
descriptions=None) descriptions=None)
# Generate 1-sequence MSA features having only the input sequence
def make_dummy_msa_feats(input_sequence) -> FeatureDict:
msa_data_obj = make_dummy_msa_obj(input_sequence)
return make_msa_features([msa_data_obj])
def make_sequence_features_with_custom_template( def make_sequence_features_with_custom_template(
sequence: str, sequence: str,
mmcif_path: str, mmcif_path: str,
@ -810,7 +815,7 @@ class DataPipeline:
""" """
) )
msa_data["dummy"] = make_dummy_msa_feats(input_sequence) msa_data["dummy"] = make_dummy_msa_obj(input_sequence)
return list(msa_data.values()) return list(msa_data.values())
@ -885,7 +890,7 @@ class DataPipeline:
sequence_embedding_features = {} sequence_embedding_features = {}
# If using seqemb mode, generate a dummy MSA features using just the sequence # If using seqemb mode, generate a dummy MSA features using just the sequence
if seqemb_mode: if seqemb_mode:
msa_features = [make_dummy_msa_feats(input_sequence)] msa_features = make_dummy_msa_feats(input_sequence)
sequence_embedding_features = self._process_seqemb_features(alignment_dir) sequence_embedding_features = self._process_seqemb_features(alignment_dir)
else: else:
msa_features = self._process_msa_feats(alignment_dir, input_sequence, alignment_index) msa_features = self._process_msa_feats(alignment_dir, input_sequence, alignment_index)
@ -935,7 +940,7 @@ class DataPipeline:
sequence_embedding_features = {} sequence_embedding_features = {}
# If using seqemb mode, generate a dummy MSA features using just the sequence # If using seqemb mode, generate a dummy MSA features using just the sequence
if seqemb_mode: if seqemb_mode:
msa_features = [make_dummy_msa_feats(input_sequence)] msa_features = make_dummy_msa_feats(input_sequence)
sequence_embedding_features = self._process_seqemb_features(alignment_dir) sequence_embedding_features = self._process_seqemb_features(alignment_dir)
else: else:
msa_features = self._process_msa_feats(alignment_dir, input_sequence, alignment_index) msa_features = self._process_msa_feats(alignment_dir, input_sequence, alignment_index)
@ -992,7 +997,7 @@ class DataPipeline:
sequence_embedding_features = {} sequence_embedding_features = {}
# If in sequence embedding mode, generate dummy MSA features using just the input sequence # If in sequence embedding mode, generate dummy MSA features using just the input sequence
if seqemb_mode: if seqemb_mode:
msa_features = [make_dummy_msa_feats(input_sequence)] msa_features = make_dummy_msa_feats(input_sequence)
sequence_embedding_features = self._process_seqemb_features(alignment_dir) sequence_embedding_features = self._process_seqemb_features(alignment_dir)
else: else:
msa_features = self._process_msa_feats(alignment_dir, input_sequence, alignment_index) msa_features = self._process_msa_feats(alignment_dir, input_sequence, alignment_index)
@ -1032,7 +1037,7 @@ class DataPipeline:
sequence_embedding_features = {} sequence_embedding_features = {}
# If in sequence embedding mode, generate dummy MSA features using just the input sequence # If in sequence embedding mode, generate dummy MSA features using just the input sequence
if seqemb_mode: if seqemb_mode:
msa_features = [make_dummy_msa_feats(input_sequence)] msa_features = make_dummy_msa_feats(input_sequence)
sequence_embedding_features = self._process_seqemb_features(alignment_dir) sequence_embedding_features = self._process_seqemb_features(alignment_dir)
else: else:
msa_features = self._process_msa_feats(alignment_dir, input_sequence) msa_features = self._process_msa_feats(alignment_dir, input_sequence)