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"""
A module to interact with BinaryCIF-formatted files.
"""
import gzip
import sys
from collections import deque
from typing import Optional
import numpy as np
try:
import msgpack
except ImportError:
from Bio import MissingPythonDependencyError
raise MissingPythonDependencyError(
"Install msgpack to use Bio.PDB.binaryCIF (e.g. pip install msgpack)"
) from None
import Bio.PDB._bcif_helper as _bcif_helper
from Bio.PDB.Structure import Structure
from Bio.PDB.StructureBuilder import StructureBuilder
# https://github.com/ihmwg/python-ihm/blob/main/ihm/format_bcif.py
# https://numpy.org/doc/stable/reference/arrays.dtypes.html#
# The "<" tells NumPy to use little endian representation.
# BinaryCIF always uses little endian.
_dtypes = {
1: np.dtype("<i1"), # Int8
2: np.dtype("<i2"), # Int16
3: np.dtype("<i4"), # Int32
4: np.dtype("<u1"), # UInt8
5: np.dtype("<u2"), # UInt16
6: np.dtype("<u4"), # UInt32
32: np.dtype("<f4"), # Float32
33: np.dtype("<f8"), # Float64
}
def _byte_array_decoder(column):
encoding = column["data"]["encoding"][-1]
assert encoding["kind"] == "ByteArray"
dtype = _dtypes[encoding["type"]]
column["data"]["data"] = np.frombuffer(column["data"]["data"], dtype)
column["data"]["encoding"].pop()
def _fixed_point_decoder(column):
encoding = column["data"]["encoding"][-1]
assert encoding["kind"] == "FixedPoint"
dtype = _dtypes[encoding["srcType"]]
factor = encoding["factor"]
data = column["data"]["data"]
assert data.dtype.type in (np.int32, np.uint32)
decoded_data = np.divide(data, factor, dtype=dtype)
column["data"]["data"] = decoded_data
column["data"]["encoding"].pop()
def _interval_quantization_decoder(column):
encoding = column["data"]["encoding"][-1]
assert encoding["kind"] == "IntervalQuantization"
min_val = encoding["min"]
max_val = encoding["max"]
num_steps = encoding["num_steps"]
delta = max_val - min_val / (num_steps - 1)
data = column["data"]["data"]
dtype = _dtypes[encoding["srcType"]]
decoded_data = np.add(min_val, np.multiply(data, delta, dtype=dtype), dtype=dtype)
column["data"]["data"] = decoded_data
column["data"]["encoding"].pop()
def _run_length_decoder(column):
encoding = column["data"]["encoding"][-1]
assert encoding["kind"] == "RunLength"
data = column["data"]["data"]
dtype = _dtypes[encoding["srcType"]]
if sys.maxsize == 2**63 - 1:
# We're running classical 64-bit platform here.
decoded_data = np.repeat(data[::2].astype(dtype), data[1::2])
else:
# We're assuming 32-bit platform here, numpy croaks on unsafe
# type casts.
decoded_data = np.repeat(data[::2].astype('int32', casting='unsafe'),
data[1::2].astype('int32', casting='unsafe'))
assert len(decoded_data) == encoding["srcSize"]
column["data"]["data"] = decoded_data
column["data"]["encoding"].pop()
def _delta_decoder(column):
encoding = column["data"]["encoding"][-1]
assert encoding["kind"] == "Delta"
dtype = _dtypes[encoding["srcType"]]
data = column["data"]["data"]
decoded_data = data.astype(dtype, copy=False)
decoded_data[0] += encoding["origin"]
decoded_data.cumsum(out=decoded_data)
column["data"]["data"] = decoded_data
column["data"]["encoding"].pop()
def _integer_packing_decoder(column):
encoding = column["data"]["encoding"][-1]
assert encoding["kind"] == "IntegerPacking"
byte_count = encoding["byteCount"]
src_size = encoding["srcSize"]
is_unsigned = encoding["isUnsigned"]
if is_unsigned:
dtype = np.dtype("<u4")
else:
dtype = np.dtype("<i4")
data = column["data"]["data"]
assert byte_count == data.dtype.itemsize
assert np.issubdtype(data.dtype, np.unsignedinteger) == is_unsigned
decoded_data = np.empty((src_size,), dtype)
_bcif_helper.integer_unpack(data, decoded_data)
column["data"]["data"] = decoded_data
column["data"]["encoding"].pop()
def _string_array_decoder(column):
encoding = column["data"]["encoding"][-1]
assert encoding["kind"] == "StringArray"
offsets_column = {
"data": {
"data": encoding["offsets"],
"encoding": encoding["offsetEncoding"],
}
}
lookup_column = {
"data": {
"data": column["data"]["data"],
"encoding": encoding["dataEncoding"],
}
}
string_data = encoding["stringData"]
offsets = _decode(offsets_column)
unique_strings = np.empty((len(offsets) - 1,), dtype=object)
for index in range(len(unique_strings)):
unique_string = string_data[offsets[index] : offsets[index + 1]]
unique_strings[index] = unique_string
lookups = _decode(lookup_column)
column["data"]["data"] = unique_strings[lookups]
column["data"]["encoding"].pop()
_decoders = {
"ByteArray": _byte_array_decoder,
"FixedPoint": _fixed_point_decoder,
"IntervalQuantization": _interval_quantization_decoder,
"RunLength": _run_length_decoder,
"Delta": _delta_decoder,
"IntegerPacking": _integer_packing_decoder,
"StringArray": _string_array_decoder,
}
def _decode(column):
# Note that decode modifies the column.
encodings = deque(column["data"]["encoding"])
column["data"]["encoding"] = encodings
while encodings:
encoding = encodings[-1]
_decoders[encoding["kind"]](column)
return column["data"]["data"]
class BinaryCIFParser:
"""A parser for BinaryCIF files.
See the `BinaryCIF specification <https://github.com/molstar/BinaryCIF>`_.
"""
def __init__(self):
"""Initialize a BinaryCIF parser."""
self._structure_builder = StructureBuilder()
def _get_hetero_field(self, atom_group: str, component_id: str) -> str:
if atom_group == "HETATM":
hetero_field = "W" if component_id in ("HOH", "WAT") else "H"
else:
hetero_field = " "
return hetero_field
def _get_residue_ids(self, columns):
atom_groups = _decode(columns["_atom_site.group_PDB"])
component_ids = _decode(columns["_atom_site.label_comp_id"])
hetero_fields = [
self._get_hetero_field(atom_group, component_id)
for atom_group, component_id in zip(atom_groups, component_ids)
]
insertion_codes = [
code or " " for code in _decode(columns["_atom_site.pdbx_PDB_ins_code"])
]
sequence_ids = _decode(columns["_atom_site.auth_seq_id"])
return list(zip(hetero_fields, sequence_ids, insertion_codes))
def _get_atoms(self, columns):
names = _decode(columns["_atom_site.label_atom_id"])
x_list = _decode(columns["_atom_site.Cartn_x"])
y_list = _decode(columns["_atom_site.Cartn_y"])
z_list = _decode(columns["_atom_site.Cartn_z"])
coordinates_list = np.stack((x_list, y_list, z_list), axis=1)
b_factors = _decode(columns["_atom_site.B_iso_or_equiv"])
occupancies = _decode(columns["_atom_site.occupancy"])
alt_ids = [
str(alt_id or " ") for alt_id in _decode(columns["_atom_site.label_alt_id"])
]
serial_numbers = _decode(columns["_atom_site.id"])
type_symbols = _decode(columns["_atom_site.type_symbol"])
return [
{
"name": names[index],
"coord": coordinates_list[index],
"b_factor": b_factors[index],
"occupancy": occupancies[index],
"altloc": alt_ids[index],
"fullname": names[index],
"serial_number": serial_numbers[index],
"element": type_symbols[index],
}
for index in range(len(serial_numbers))
]
def get_structure(self, id: Optional[str], source: str) -> Structure:
"""Parse and return the PDB structure from a BinaryCIF file.
:param str id: the PDB code for this structure
:param str source: the path to the BinaryCIF file
:return: the PDB structure
:rtype: Bio.PDB.Structure.Structure
"""
if hasattr(source, "seek"):
# This resets the source if source is a file handle.
source.seek(0)
with (
gzip.open(source, mode="rb")
if source.endswith(".gz")
else open(source, mode="rb")
) as file:
result = msgpack.unpack(file, use_list=True)
columns = {
f"{category['name']}.{column['name']}": column
for data_block in result["dataBlocks"]
for category in data_block["categories"]
for column in category["columns"]
}
atom_model_numbers = _decode(columns["_atom_site.pdbx_PDB_model_num"])
atom_chain_ids = _decode(columns["_atom_site.label_asym_id"])
atom_residue_ids = self._get_residue_ids(columns)
atom_component_ids = _decode(columns["_atom_site.label_comp_id"])
atoms = self._get_atoms(columns)
entry_id = _decode(columns["_entry.id"])[0]
self._structure_builder.init_structure(id or entry_id)
builder_model_count = 0
builder_model_number = None
builder_chain_id = None
builder_residue_id = None
builder_component_id = None
for index in range(len(atom_model_numbers)):
model_number = atom_model_numbers[index]
chain_id = atom_chain_ids[index]
residue_id = atom_residue_ids[index]
component_id = atom_component_ids[index]
if model_number != builder_model_number:
self._structure_builder.init_model(builder_model_count, model_number)
builder_model_count += 1
builder_model_number = model_number
builder_chain_id = None
builder_residue_id = None
if chain_id != builder_chain_id:
self._structure_builder.init_chain(chain_id)
builder_chain_id = chain_id
builder_residue_id = None
if residue_id != builder_residue_id or component_id != builder_component_id:
self._structure_builder.init_residue(component_id, *residue_id)
builder_residue_id = residue_id
builder_component_id = component_id
self._structure_builder.init_atom(**atoms[index])
return self._structure_builder.get_structure()
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