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# Copyright 2019-22 by Robert T. Miller. All rights reserved.
# This file is part of the Biopython distribution and governed by your
# choice of the "Biopython License Agreement" or the "BSD 3-Clause License".
# Please see the LICENSE file that should have been included as part of this
# package.
"""Classes to support internal coordinates for protein structures.
Internal coordinates comprise Psi, Omega and Phi dihedral angles along the
protein backbone, Chi angles along the sidechains, and all 3-atom angles and
bond lengths defining a protein chain. These routines can compute internal
coordinates from atom XYZ coordinates, and compute atom XYZ coordinates from
internal coordinates.
Secondary benefits include the ability to align and compare residue
environments in 3D structures, support for 2D atom distance plots, converting a
distance plot plus chirality information to a structure, generating an OpenSCAD
description of a structure for 3D printing, and reading/writing structures as
internal coordinate data files.
**Usage:**
::
from Bio.PDB.PDBParser import PDBParser
from Bio.PDB.Chain import Chain
from Bio.PDB.internal_coords import *
from Bio.PDB.PICIO import write_PIC, read_PIC, read_PIC_seq
from Bio.PDB.ic_rebuild import write_PDB, IC_duplicate, structure_rebuild_test
from Bio.PDB.SCADIO import write_SCAD
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
from Bio.PDB.PDBIO import PDBIO
import numpy as np
# load a structure as normal, get first chain
parser = PDBParser()
myProtein = parser.get_structure("7rsa", "pdb7rsa.ent")
myChain = myProtein[0]["A"]
# compute bond lengths, angles, dihedral angles
myChain.atom_to_internal_coordinates(verbose=True)
# check myChain makes sense (can get angles and rebuild same structure)
resultDict = structure_rebuild_test(myChain)
assert resultDict['pass'] == True
# get residue 1 chi2 angle
r1 = next(myChain.get_residues())
r1chi2 = r1.internal_coord.get_angle("chi2")
# rotate residue 1 chi2 angle by 120 degrees (loops w/in +/-180)
r1.internal_coord.set_angle("chi2", r1chi2 + 120.0)
# update myChain XYZ coordinates with chi2 changed
myChain.internal_to_atom_coordinates()
# write new conformation with PDBIO
write_PDB(myProtein, "myChain.pdb")
# or just the ATOM records without headers:
io = PDBIO()
io.set_structure(myProtein)
io.save("myChain2.pdb")
# write chain as 'protein internal coordinates' (.pic) file
write_PIC(myProtein, "myChain.pic")
# read .pic file
myProtein2 = read_PIC("myChain.pic")
# create default structure for random sequence by reading as .pic file
myProtein3 = read_PIC_seq(
SeqRecord(
Seq("GAVLIMFPSTCNQYWDEHKR"),
id="1RND",
description="my random sequence",
)
)
myProtein3.internal_to_atom_coordinates()
write_PDB(myProtein3, "myRandom.pdb")
# access the all-dihedrals array for the chain, e.g. residue 1 chi2 angle:
r1chi2_obj = r1.internal_coord.pick_angle("chi2")
# or same thing: r1chi2_obj = r1.internal_coord.pick_angle("CA:CB:CG:CD")
r1chi2_key = r1chi2_obj.atomkeys
# r1chi2_key is tuple of AtomKeys (1_K_CA, 1_K_CB, 1_K_CG, 1_K_CD)
r1chi2_index = myChain.internal_coord.dihedraNdx[r1chi2_key]
# or same thing: r1chi2_index = r1chi2_obj.ndx
r1chi2_value = myChain.internal_coord.dihedraAngle[r1chi2_index]
# also true: r1chi2_obj == myChain.internal_coord.dihedra[r1chi2_index]
# access the array of all atoms for the chain, e.g. residue 1 C-beta
r1_cBeta_index = myChain.internal_coord.atomArrayIndex[AtomKey("1_K_CB")]
r1_cBeta_coords = myChain.internal_coord.atomArray[r1_cBeta_index]
# r1_cBeta_coords = [ x, y, z, 1.0 ]
# the Biopython Atom coord array is now a view into atomArray, so
assert r1_cBeta_coords[1] == r1["CB"].coord[1]
r1_cBeta_coords[1] += 1.0 # change the Y coord 1 angstrom
assert r1_cBeta_coords[1] == r1["CB"].coord[1]
# they are always the same (they share the same memory)
r1_cBeta_coords[1] -= 1.0 # restore
# create a selector to filter just the C-alpha atoms from the all atom array
atmNameNdx = AtomKey.fields.atm
atomArrayIndex = myChain.internal_coord.atomArrayIndex
CaSelect = [
atomArrayIndex.get(k) for k in atomArrayIndex.keys() if k.akl[atmNameNdx] == "CA"
]
# now the ordered array of C-alpha atom coordinates is:
CA_coords = myChain.internal_coord.atomArray[CaSelect]
# note this uses Numpy fancy indexing, so CA_coords is a new copy
# create a C-alpha distance plot
caDistances = myChain.internal_coord.distance_plot(CaSelect)
# display with e.g. MatPlotLib:
# import matplotlib.pyplot as plt
# plt.imshow(caDistances, cmap="hot", interpolation="nearest")
# plt.show()
# build structure from distance plot:
## create the all-atom distance plot
distances = myChain.internal_coord.distance_plot()
## get the sign of the dihedral angles
chirality = myChain.internal_coord.dihedral_signs()
## get new, empty data structure : copy data structure from myChain
myChain2 = IC_duplicate(myChain)[0]["A"]
cic2 = myChain2.internal_coord
## clear the new atomArray and di/hedra value arrays, just for proof
cic2.atomArray = np.zeros((cic2.AAsiz, 4), dtype=np.float64)
cic2.dihedraAngle[:] = 0.0
cic2.hedraAngle[:] = 0.0
cic2.hedraL12[:] = 0.0
cic2.hedraL23[:] = 0.0
## copy just the first N-Ca-C coords so structures will superimpose:
cic2.copy_initNCaCs(myChain.internal_coord)
## copy distances to chain arrays:
cic2.distplot_to_dh_arrays(distances, chirality)
## compute angles and dihedral angles from distances:
cic2.distance_to_internal_coordinates()
## generate XYZ coordinates from internal coordinates:
myChain2.internal_to_atom_coordinates()
## confirm result atomArray matches original structure:
assert np.allclose(cic2.atomArray, myChain.internal_coord.atomArray)
# superimpose all phe-phe pairs - quick hack just to demonstrate concept
# for analyzing pairwise residue interactions. Generates PDB ATOM records
# placing each PHE at origin and showing all other PHEs in environment
## shorthand for key variables:
cic = myChain.internal_coord
resNameNdx = AtomKey.fields.resname
aaNdx = cic.atomArrayIndex
## select just PHE atoms:
pheAtomSelect = [aaNdx.get(k) for k in aaNdx.keys() if k.akl[resNameNdx] == "F"]
aaF = cic.atomArray[ pheAtomSelect ] # numpy fancy indexing makes COPY not view
for ric in cic.ordered_aa_ic_list: # internal_coords version of get_residues()
if ric.rbase[2] == "F": # if PHE, get transform matrices for chi1 dihedral
chi1 = ric.pick_angle("N:CA:CB:CG") # chi1 space has C-alpha at origin
cst = np.transpose(chi1.cst) # transform TO chi1 space
# rcst = np.transpose(chi1.rcst) # transform FROM chi1 space
cic.atomArray[pheAtomSelect] = aaF.dot(cst) # transform just the PHEs
for res in myChain.get_residues(): # print PHEs in new coordinate space
if res.resname in ["PHE"]:
print(res.internal_coord.pdb_residue_string())
cic.atomArray[pheAtomSelect] = aaF # restore coordinate space from copy
# write OpenSCAD program of spheres and cylinders to 3d print myChain backbone
## set atom load filter to accept backbone only:
IC_Residue.accept_atoms = IC_Residue.accept_backbone
## delete existing data to force re-read of all atoms:
myChain.internal_coord = None
write_SCAD(myChain, "myChain.scad", scale=10.0)
See the `''Internal coordinates module''` section of the `Biopython Tutorial
and Cookbook` for further discussion.
**Terms and key data structures:**
Internal coordinates are defined on sequences of atoms which span
residues or follow accepted nomenclature along sidechains. To manage these
sequences and support Biopython's disorder mechanisms, :class:`AtomKey`
specifiers are implemented to capture residue, atom and variant identification
in a single object. A :class:`Hedron` object is specified as three sequential
AtomKeys, comprising two bond lengths and the bond angle between them. A
:class:`Dihedron` consists of four sequential AtomKeys, linking two Hedra with
a dihedral angle between them.
**Algorithmic overview:**
The Internal Coordinates module combines a specification of connected atoms as
hedra and dihedra in the :mod:`.ic_data` file with routines here to transform
XYZ coordinates of these atom sets between a local coordinate system and the
world coordinates supplied in e.g. a PDB or mmCif data file. The local
coordinate system places the center atom of a hedron at the origin (0,0,0), one
leg on the +Z axis, and the other leg on the XZ plane (see :class:`Hedron`).
Measurement and creation or manipulation of hedra and dihedra in the local
coordinate space is straightforward, and the calculated transformation matrices
enable assembling these subunits into a protein chain starting from supplied
(PDB) coordinates for the initial N-Ca-C atoms.
Psi and Phi angles are defined on atoms from adjacent residues in a protein
chain, see e.g. :meth:`.pick_angle` and :mod:`.ic_data` for the relevant
mapping between residues and backbone dihedral angles.
Transforms to and from the dihedron local coordinate space described above are
accessible via :data:`IC_Chain.dCoordSpace` and :class:`Dihedron` attributes
.cst and .rcst, and may be applied in the alignment and comparison of residues
and their environments with code along the lines of::
chi1 = ric0.pick_angle("chi1") # chi1 space defined with CA at origin
cst = np.transpose(chi1.cst) # transform TO chi1 local space
newAtomCoords = oldAtomCoords.dot(cst)
The core algorithms were developed independently during 1993-4 for
`''Development and Application of a Three-dimensional Description of Amino Acid
Environments in Protein,'' Miller, Douthart, and Dunker, Advances in Molecular
Bioinformatics, IOS Press, 1994, ISBN 90 5199 172 x, pp. 9-30.
<https://www.google.com/books/edition/Advances_in_Molecular_Bioinformatics/VmFSNNm7k6cC?gbpv=1>`_
A Protein Internal Coordinate (.pic) file format is defined to capture
sufficient detail to reproduce a PDB file from chain starting coordinates
(first residue N, Ca, C XYZ coordinates) and remaining internal coordinates.
These files are used internally to verify that a given structure can be
regenerated from its internal coordinates. See :mod:`.PICIO` for reading and
writing .pic files and :func:`.structure_rebuild_test` to determine if a
specific PDB or mmCif datafile has sufficient information to interconvert
between cartesian and internal coordinates.
Internal coordinates may also be exported as `OpenSCAD <https://www.openscad.org>`_
data arrays for generating 3D printed protein models. OpenSCAD software is
provided as a starting point and proof-of-concept for generating such models.
See :mod:`.SCADIO` and this `Thingiverse project <https://www.thingiverse.com/thing:3957471>`_
for a more advanced example.
Refer to :meth:`.distance_plot` and :meth:`.distance_to_internal_coordinates`
for converting structure data to/from 2D distance plots.
The following classes comprise the core functionality for processing internal
coordinates and are sufficiently related and coupled to place them together in
this module:
:class:`IC_Chain`: Extends Biopython Chain on .internal_coord attribute.
Manages connected sequence of residues and chain breaks; holds numpy arrays
for all atom coordinates and bond geometries. For 'parallel' processing
IC_Chain methods operate on these arrays with single numpy commands.
:class:`IC_Residue`: Extends Biopython Residue on .internal_coord attribute.
Access for per residue views on internal coordinates and methods for serial
(residue by residue) assembly.
:class:`Dihedron`: four joined atoms forming a dihedral angle.
Dihedral angle, homogeneous atom coordinates in local coordinate space,
references to relevant Hedra and IC_Residue. Getter methods for
residue dihedral angles, bond angles and bond lengths.
:class:`Hedron`: three joined atoms forming a plane.
Contains homogeneous atom coordinates in local coordinate space as well as
bond lengths and angle between them.
:class:`Edron`: base class for Hedron and Dihedron classes.
Tuple of AtomKeys comprising child, string ID, mainchain membership boolean
and other routines common for both Hedra and Dihedra. Implements rich
comparison.
:class:`AtomKey`: keys (dictionary and string) for referencing atom sequences.
Capture residue and disorder/occupancy information, provides a
no-whitespace key for .pic files, and implements rich comparison.
Custom exception classes: :class:`HedronMatchError` and
:class:`MissingAtomError`
""" # noqa
import re
from collections import deque, namedtuple
import copy
# from numpy import floor, ndarray
from numbers import Integral
try:
import numpy as np # type: ignore
except ImportError:
from Bio import MissingPythonDependencyError
raise MissingPythonDependencyError(
"Install numpy to build proteins from internal coordinates."
)
from Bio.PDB.Atom import Atom, DisorderedAtom
from Bio.Data.PDBData import protein_letters_3to1
from Bio.PDB.vectors import multi_coord_space, multi_rot_Z
from Bio.PDB.vectors import coord_space
from Bio.PDB.ic_data import ic_data_backbone, ic_data_sidechains
from Bio.PDB.ic_data import primary_angles
from Bio.PDB.ic_data import ic_data_sidechain_extras, residue_atom_bond_state
from Bio.PDB.ic_data import dihedra_primary_defaults, hedra_defaults
# for type checking only
from typing import (
List,
Dict,
Set,
TextIO,
Union,
Tuple,
cast,
TYPE_CHECKING,
Optional,
)
if TYPE_CHECKING:
from Bio.PDB.Residue import Residue
from Bio.PDB.Chain import Chain
HKT = Tuple["AtomKey", "AtomKey", "AtomKey"] # Hedron key tuple
DKT = Tuple["AtomKey", "AtomKey", "AtomKey", "AtomKey"] # Dihedron Key Tuple
EKT = Union[HKT, DKT] # Edron Key Tuple
BKT = Tuple["AtomKey", "AtomKey"] # Bond Key Tuple
# HACS = Tuple[np.array, np.array, np.array] # Hedron Atom Coord Set
HACS = np.array # Hedron Atom Coord Set
DACS = Tuple[np.array, np.array, np.array, np.array] # Dihedron Atom Coord Set
class IC_Chain:
"""Class to extend Biopython Chain with internal coordinate data.
Attributes
----------
chain: object reference
The Biopython :class:`Bio.PDB.Chain.Chain` object this extends
MaxPeptideBond: float
**Class** attribute to detect chain breaks.
Override for fully contiguous chains with some very long bonds - e.g.
for 3D printing (OpenSCAD output) a structure with missing residues.
:data:`MaxPeptideBond`
ParallelAssembleResidues: bool
**Class** attribute affecting internal_to_atom_coords.
Short (50 residue and less) chains are faster to assemble without the
overhead of creating numpy arrays, and the algorithm is easier to
understand and trace processing a single residue at a time. Clearing
(set to False) this flag will switch to the serial algorithm
ordered_aa_ic_list: list
IC_Residue objects internal_coords algorithms can process (e.g. no
waters)
initNCaC: List of N, Ca, C AtomKey tuples (NCaCKeys).
NCaCKeys start chain segments (first residue or after chain break).
These 3 atoms define the coordinate space for a contiguous chain
segment, as initially specified by PDB or mmCIF file.
AAsiz = int
AtomArray size, number of atoms in this chain
atomArray: numpy array
homogeneous atom coords ([x,, y, z, 1.0]) for every atom in chain
atomArrayIndex: dict
maps AtomKeys to atomArray indexes
hedra: dict
Hedra forming residues in this chain; indexed by 3-tuples of AtomKeys.
hedraLen: int
length of hedra dict
hedraNdx: dict
maps hedra AtomKeys to numeric index into hedra data arrays e.g.
hedraL12 below
a2ha_map: [hedraLen x 3]
atom indexes in hedraNdx order
dihedra: dict
Dihedra forming residues in this chain; indexed by 4-tuples of AtomKeys.
dihedraLen: int
length of dihedra dict
dihedraNdx: dict
maps dihedra AtomKeys to dihedra data arrays e.g. dihedraAngle
a2da_map : [dihedraLen x 4]
AtomNdx's in dihedraNdx order
d2a_map : [dihedraLen x [4]]
AtomNdx's for each dihedron (reshaped a2da_map)
Numpy arrays for vector processing of chain di/hedra:
hedraL12: numpy array
bond length between hedron 1st and 2nd atom
hedraAngle: numpy array
bond angle for each hedron, in degrees
hedraL23: numpy array
bond length between hedron 2nd and 3rd atom
id3_dh_index: dict
maps hedron key to list of dihedra starting with hedron, used by
assemble and bond_rotate to find dihedra with h1 key
id32_dh_index: dict
like id3_dh_index, find dihedra from h2 key
hAtoms: numpy array
homogeneous atom coordinates (3x4) of hedra, central atom at origin
hAtomsR: numpy array
hAtoms in reverse orientation
hAtoms_needs_update: numpy array of bool
indicates whether hAtoms represent hedraL12/A/L23
dihedraAngle: numpy array
dihedral angles (degrees) for each dihedron
dAtoms: numpy array
homogeneous atom coordinates (4x4) of dihedra, second atom at origin
dAtoms_needs_update: numpy array of bool
indicates whether dAtoms represent dihedraAngle
dCoordSpace: numpy array
forward and reverse transform matrices standardising positions of first
hedron. See :data:`dCoordSpace`.
dcsValid: bool
indicates dCoordSpace up to date
See also attributes generated by :meth:`build_edraArrays` for indexing
di/hedra data elements.
Methods
-------
internal_to_atom_coordinates:
Process ic data to Residue/Atom coordinates; calls assemble_residues()
assemble_residues:
Generate IC_Chain atom coords from internal coordinates (parallel)
assemble_residues_ser:
Generate IC_Residue atom coords from internal coordinates (serial)
atom_to_internal_coordinates:
Calculate dihedrals, angles, bond lengths (internal coordinates) for
Atom data
write_SCAD:
Write OpenSCAD matrices for internal coordinate data comprising chain;
this is a support routine, see :func:`.SCADIO.write_SCAD` to generate
OpenSCAD description of a protein chain.
distance_plot:
Generate 2D plot of interatomic distances with optional filter
distance_to_internal_coordinates:
Compute internal coordinates from distance plot and array of dihedral
angle signs.
"""
# Class globals
MaxPeptideBond = 1.4
"""Larger C-N distance than this will be chain break"""
ParallelAssembleResidues = True
"""Enable parallel internal_to_atom algorithm, is slower for short chains"""
AAsiz = 0
"""Number of atoms in this chain (size of atomArray)"""
atomArray: np.array = None
"""AAsiz x [4] of float np.float64 homogeneous atom coordinates, all atoms
in chain."""
dCoordSpace = None
"""[2][dihedraLen][4][4] : 2 arrays of 4x4 coordinate space transforms for
each dihedron. The first [0] converts TO standard space with first atom on
the XZ plane, the second atom at the origin, the third on the +Z axis, and
the fourth placed according to the dihedral angle. The second [1] transform
returns FROM the standard space to world coordinates (PDB file input or
whatever is current). Also accessible as .cst (forward
transform) and .rcst (reverse transform) in :class:`Dihedron`."""
dcsValid = None
"""True if dCoordSpace is up to date. Use :meth:`.update_dCoordSpace`
if needed."""
# for assemble_residues
_dihedraSelect = np.array([True, True, True, False])
_dihedraOK = np.array([True, True, True, True])
def __init__(self, parent: "Chain", verbose: bool = False) -> None:
"""Initialize IC_Chain object, with or without residue/Atom data.
:param Bio.PDB.Chain parent: Biopython Chain object
Chain object this extends
"""
# type hinting parent as Chain leads to import cycle
self.chain = parent
self.ordered_aa_ic_list: List[IC_Residue] = []
# self.initNCaC: Dict[Tuple[str], Dict["AtomKey", np.array]] = {}
self.initNCaCs = []
self.sqMaxPeptideBond = np.square(IC_Chain.MaxPeptideBond)
# need init here for _gen_edra():
self.hedra = {}
# self.hedraNdx = {}
self.dihedra = {}
# self.dihedraNdx = {}
# cache of AtomKey results for cak()
# self.akc: Dict[Tuple(IC_Residue, str), AtomKey] = {}
self.atomArrayIndex: Dict["AtomKey", int] = {}
self.bpAtomArray: List["Atom"] = [] # rtm
self._set_residues(verbose) # no effect if no residues loaded
def __deepcopy__(self, memo) -> "IC_Chain":
"""Implement deepcopy for IC_Chain."""
existing = memo.get(id(self), False)
if existing:
return existing
dup = type(self).__new__(self.__class__)
memo[id(self)] = dup
dup.chain = memo[id(self.chain)]
dup.chain.child_dict = copy.deepcopy(self.chain.child_dict, memo)
# now have all res and ic_res but ic_res not complete
dup.chain.child_list = copy.deepcopy(self.chain.child_list, memo)
dup.akset = copy.deepcopy(self.akset, memo)
dup.aktuple = copy.deepcopy(self.aktuple, memo)
# now have all ak w/.ric
dup.ordered_aa_ic_list = copy.deepcopy(self.ordered_aa_ic_list, memo)
dup.atomArrayIndex = self.atomArrayIndex.copy()
dup.atomArrayValid = self.atomArrayValid.copy()
dup.atomArray = self.atomArray.copy()
dup.hedra = copy.deepcopy(self.hedra, memo)
dup.dihedra = copy.deepcopy(self.dihedra, memo)
dup.id3_dh_index = copy.deepcopy(self.id3_dh_index, memo)
dup.id32_dh_index = copy.deepcopy(self.id32_dh_index, memo)
# update missing items in ic_residues and
# set all bp residue atom coords to be views on dup.atomArray
# [similar in build_AtomArray() but does not copy from bpAtoms
# or modify atomArrayValid, and accesses dup]
dup.AAsiz = self.AAsiz
dup.bpAtomArray = [None] * dup.AAsiz # rtm
def setAtomVw(res, atm):
ak = AtomKey(res.internal_coord, atm)
ndx = dup.atomArrayIndex[ak]
atm.coord = dup.atomArray[ndx, 0:3] # make view on atomArray
dup.bpAtomArray[ndx] = atm # rtm
def setResAtmVws(res):
for atm in res.get_atoms():
# copy not filter so ignore no_altloc
if atm.is_disordered():
for altAtom in atm.child_dict.values():
setAtomVw(res, altAtom)
else:
setAtomVw(res, atm)
for ric in dup.ordered_aa_ic_list:
setResAtmVws(ric.residue)
ric.rprev = copy.deepcopy(ric.rprev, memo)
ric.rnext = copy.deepcopy(ric.rnext, memo)
ric.ak_set = copy.deepcopy(ric.ak_set, memo)
ric.akc = copy.deepcopy(ric.akc, memo)
ric.dihedra = copy.deepcopy(ric.dihedra, memo)
ric.hedra = copy.deepcopy(ric.hedra, memo)
dup.sqMaxPeptideBond = self.sqMaxPeptideBond
dup.initNCaCs = copy.deepcopy(self.initNCaCs, memo)
dup.hedraLen = self.hedraLen
dup.hedraL12 = self.hedraL12.copy()
dup.hedraAngle = self.hedraAngle.copy()
dup.hedraL23 = self.hedraL23.copy()
dup.hedraNdx = copy.deepcopy(self.hedraNdx, memo)
dup.dihedraLen = self.dihedraLen
dup.dihedraAngle = self.dihedraAngle.copy()
dup.dihedraAngleRads = self.dihedraAngleRads.copy()
dup.dihedraNdx = copy.deepcopy(self.dihedraNdx, memo)
dup.a2da_map = self.a2da_map.copy()
dup.a2d_map = self.a2d_map.copy()
dup.d2a_map = self.d2a_map.copy()
dup.dH1ndx = self.dH1ndx.copy()
dup.dH2ndx = self.dH2ndx.copy()
dup.hAtoms = self.hAtoms.copy()
dup.hAtomsR = self.hAtomsR.copy()
dup.hAtoms_needs_update = self.hAtoms_needs_update.copy()
dup.dRev = self.dRev.copy()
dup.dFwd = self.dFwd.copy()
dup.dAtoms_needs_update = self.dAtoms_needs_update.copy()
dup.dAtoms = self.dAtoms.copy()
dup.a4_pre_rotation = self.a4_pre_rotation.copy()
dup.dCoordSpace = self.dCoordSpace.copy()
dup.dcsValid = self.dcsValid.copy()
for d in dup.dihedra.values():
d.cst = dup.dCoordSpace[0][d.ndx]
d.rcst = dup.dCoordSpace[1][d.ndx]
return dup
# return True if a0, a1 within supplied cutoff
def _atm_dist_chk(self, a0: Atom, a1: Atom, cutoff: float, sqCutoff: float) -> bool:
return sqCutoff > np.sum(np.square(a0.coord - a1.coord))
# return a string describing issue, or None if OK
def _peptide_check(self, prev: "Residue", curr: "Residue") -> Optional[str]:
if 0 == len(curr.child_dict):
# curr residue with no atoms => reading pic file, no break
return None
if (0 != len(curr.child_dict)) and (0 == len(prev.child_dict)):
# prev residue with no atoms, curr has atoms => reading pic file,
# have break
return "PIC data missing atoms"
# handle non-standard AA not marked as HETATM (1KQF, 1NTH)
if not prev.internal_coord.isAccept:
return "previous residue not standard/accepted amino acid"
# both biopython Residues have Atoms, so check distance
Natom = curr.child_dict.get("N", None)
pCatom = prev.child_dict.get("C", None)
if Natom is None or pCatom is None:
return f"missing {'previous C' if pCatom is None else 'N'} atom"
# confirm previous residue has all backbone atoms
pCAatom = prev.child_dict.get("CA", None)
pNatom = prev.child_dict.get("N", None)
if pNatom is None or pCAatom is None:
return "previous residue missing N or Ca"
if IC_Residue.no_altloc:
if Natom.is_disordered():
Natom = Natom.selected_child
if pCatom.is_disordered():
pCatom = pCatom.selected_child
if IC_Residue.no_altloc or (
not Natom.is_disordered() and not pCatom.is_disordered()
):
dc = self._atm_dist_chk(
Natom, pCatom, IC_Chain.MaxPeptideBond, self.sqMaxPeptideBond
)
if dc:
return None
else:
return f"MaxPeptideBond ({IC_Chain.MaxPeptideBond} angstroms) exceeded"
# drop through for else Natom or pCatom is disordered:
Nlist: List[Atom] = []
pClist: List[Atom] = []
if Natom.is_disordered():
Nlist.extend(Natom.child_dict.values())
else:
Nlist = [Natom]
if pCatom.is_disordered():
pClist.extend(pCatom.child_dict.values())
else:
pClist = [pCatom]
for n in Nlist:
for c in pClist:
if self._atm_dist_chk(
n, c, IC_Chain.MaxPeptideBond, self.sqMaxPeptideBond
):
return None
return f"MaxPeptideBond ({IC_Chain.MaxPeptideBond} angstroms) exceeded"
def clear_ic(self):
"""Clear residue internal_coord settings for this chain."""
for res in self.chain.get_residues():
res.internal_coord = None
def _add_residue(
self,
res: "Residue",
last_res: List,
last_ord_res: List,
verbose: bool = False,
) -> bool:
"""Set rprev, rnext, manage chain break.
Returns True for no chain break or residue has sufficient data to
restart at this position after a chain break (sets initNCaC AtomKeys
in this case). False return means insufficient data to extend chain
with this residue.
"""
# overwrite any existing .internal_coord in case re-initialising chain
# expected state here is res.internal_coord = None
res.internal_coord = IC_Residue(res)
res.internal_coord.cic = self
ric = res.internal_coord
if (
0 < len(last_res)
and last_ord_res == last_res
and self._peptide_check(last_ord_res[0].residue, res) is None
):
# no chain break
for prev in last_ord_res:
prev.rnext.append(res.internal_coord)
ric.rprev.append(prev)
return True
elif all(atm in res.child_dict for atm in ("N", "CA", "C")):
# chain break, save coords for restart
if verbose and len(last_res) != 0: # not first residue
if last_ord_res != last_res:
reason = f"disordered residues after {last_ord_res.pretty_str()}"
else:
reason = cast(
str, self._peptide_check(last_ord_res[0].residue, res)
)
print(f"chain break at {ric.pretty_str()} due to {reason}")
iNCaC = ric.split_akl(
(AtomKey(ric, "N"), AtomKey(ric, "CA"), AtomKey(ric, "C"))
)
self.initNCaCs.extend(iNCaC)
return True
# chain break but do not have N, Ca, C coords to restart from
return False
def _set_residues(self, verbose: bool = False) -> None:
"""Initialize .internal_coord for loaded Biopython Residue objects.
Add IC_Residue as .internal_coord attribute for each :class:`.Residue`
in parent :class:`Bio.PDB.Chain.Chain`; populate ordered_aa_ic_list with
:class:`IC_Residue` references for residues which can be built (amino
acids and some hetatms); set rprev and rnext on each sequential
IC_Residue, populate initNCaC at start and after chain breaks.
Generates:
self.akset : set of :class:`.AtomKey` s in this chain
"""
# ndx = 0
last_res: List["IC_Residue"] = []
last_ord_res: List["IC_Residue"] = []
# atomCoordDict = {}
akset = set()
for res in self.chain.get_residues():
# select only not hetero or accepted hetero
if res.id[0] == " " or res.id[0] in IC_Residue.accept_resnames:
this_res: List["IC_Residue"] = []
if 2 == res.is_disordered() and not IC_Residue.no_altloc:
# print('disordered res:', res.is_disordered(), res)
for r in res.child_dict.values():
if self._add_residue(r, last_res, last_ord_res, verbose):
this_res.append(r.internal_coord)
akset.update(r.internal_coord.ak_set)
else:
if self._add_residue(res, last_res, last_ord_res, verbose):
this_res.append(res.internal_coord)
akset.update(res.internal_coord.ak_set)
if 0 < len(this_res):
self.ordered_aa_ic_list.extend(this_res)
last_ord_res = this_res
last_res = this_res
self.akset = akset
self.initNCaCs = sorted(self.initNCaCs)
def build_atomArray(self) -> None:
"""Build :class:`IC_Chain` numpy coordinate array from biopython atoms.
See also :meth:`.init_edra` for more complete initialization of IC_Chain.
Inputs:
self.akset : set
:class:`AtomKey` s in this chain
Generates:
self.AAsiz : int
number of atoms in chain (len(akset))
self.aktuple : AAsiz x AtomKeys
sorted akset AtomKeys
self.atomArrayIndex : [AAsiz] of int
numerical index for each AtomKey in aktuple
self.atomArrayValid : AAsiz x bool
atomArray coordinates current with internal coordinates if True
self.atomArray : AAsiz x np.float64[4]
homogeneous atom coordinates; Biopython :class:`.Atom`
coordinates are view into this array after execution
rak_cache : dict
lookup cache for AtomKeys for each residue
"""
def setAtom(res, atm):
ak = AtomKey(res.internal_coord, atm)
try:
ndx = self.atomArrayIndex[ak]
except KeyError:
return
self.atomArray[ndx, 0:3] = atm.coord
atm.coord = self.atomArray[ndx, 0:3] # make view on atomArray
self.atomArrayValid[ndx] = True
self.bpAtomArray[ndx] = atm # rtm
def setResAtms(res):
for atm in res.get_atoms():
if atm.is_disordered():
if IC_Residue.no_altloc:
setAtom(res, atm.selected_child)
else:
for altAtom in atm.child_dict.values():
setAtom(res, altAtom)
else:
setAtom(res, atm)
self.AAsiz = len(self.akset)
# sorted(akset) needed here for pdb atom serial number and to maintain
# consistency between a2ic and i2ac
self.aktuple = tuple(sorted(self.akset))
self.atomArrayIndex = dict(zip(self.aktuple, range(self.AAsiz)))
self.atomArrayValid = np.zeros(self.AAsiz, dtype=bool)
self.atomArray = np.zeros((self.AAsiz, 4), dtype=np.float64)
self.atomArray[:, 3] = 1.0
self.bpAtomArray = [None] * self.AAsiz # rtm
for ric in self.ordered_aa_ic_list:
setResAtms(ric.residue)
if ric.akc == {}: # pic file read
ric._build_rak_cache()
def build_edraArrays(self) -> None:
"""Build chain level hedra and dihedra arrays.
Used by :meth:`init_edra` and :meth:`_hedraDict2chain`. Should be
private method but exposed for documentation.
Inputs:
self.dihedraLen : int
number of dihedra needed
self.hedraLen : int
number of hedra needed
self.AAsiz : int
length of atomArray
self.hedraNdx : dict
maps hedron keys to range(hedraLen)
self.dihedraNdx : dict
maps dihedron keys to range(dihedraLen)
self.hedra : dict
maps Hedra keys to Hedra for chain
self.atomArray : AAsiz x np.float64[4]
homogeneous atom coordinates for chain
self.atomArrayIndex : dict
maps AtomKeys to atomArray
self.atomArrayValid : AAsiz x bool
indicates coord is up-to-date
Generates:
self.dCoordSpace : [2][dihedraLen][4][4]
transforms to/from dihedron coordinate space
self.dcsValid : dihedraLen x bool
indicates dCoordSpace is current
self.hAtoms : hedraLen x 3 x np.float64[4]
atom coordinates in hCoordSpace
self.hAtomsR : hedraLen x 3 x np.float64[4]
hAtoms in reverse order (trading space for time)
self.hAtoms_needs_update : hedraLen x bool
indicates hAtoms, hAtoms current
self.a2h_map : AAsiz x [int ...]
maps atomArrayIndex to hedraNdx's with that atom
self.a2ha_map : [hedraLen x 3]
AtomNdx's in hedraNdx order
self.h2aa : hedraLen x [int ...]
maps hedraNdx to atomNdx's in hedron (reshaped later)
Hedron.ndx : int
self.hedraNdx value stored inside Hedron object
self.dRev : dihedraLen x bool
dihedron reversed if true
self.dH1ndx, dH2ndx : [dihedraLen]
hedraNdx's for 1st and 2nd hedra
self.h1d_map : hedraLen x []
hedraNdx -> [dihedra using hedron]
Dihedron.h1key, h2key : [AtomKey ...]
hedron keys for dihedron, reversed as needed
Dihedron.hedron1, hedron2 : Hedron
references inside dihedron to hedra
Dihedron.ndx : int
self.dihedraNdx info inside Dihedron object
Dihedron.cst, rcst : np.float64p4][4]
dCoordSpace references inside Dihedron
self.a2da_map : [dihedraLen x 4]
AtomNdx's in dihedraNdx order
self.d2a_map : [dihedraLen x [4]]
AtomNdx's for each dihedron (reshaped a2da_map)
self.dFwd : bool
dihedron is not Reversed if True
self.a2d_map : AAsiz x [[dihedraNdx]
[atom ndx 0-3 of atom in dihedron]], maps atom indexes to
dihedra and atoms in them
self.dAtoms_needs_update : dihedraLen x bool
atoms in h1, h2 are current if False
"""
# dihedra coord space
self.dCoordSpace: np.ndarray = np.empty(
(2, self.dihedraLen, 4, 4), dtype=np.float64
)
self.dcsValid: np.ndarray = np.zeros((self.dihedraLen), dtype=bool)
# hedra atoms
self.hAtoms: np.ndarray = np.zeros((self.hedraLen, 3, 4), dtype=np.float64)
self.hAtoms[:, :, 3] = 1.0 # homogeneous
self.hAtomsR: np.ndarray = np.copy(self.hAtoms)
self.hAtoms_needs_update = np.full(self.hedraLen, True)
# maps between hAtoms and atomArray
a2ha_map = {}
self.a2h_map = [[] for _ in range(self.AAsiz)]
h2aa = [[] for _ in range(self.hedraLen)]
for hk, hndx in self.hedraNdx.items():
hstep = hndx * 3
for i in range(3):
ndx = self.atomArrayIndex[hk[i]]
a2ha_map[hstep + i] = ndx
self.hedra[hk].ndx = hndx
for ak in self.hedra[hk].atomkeys:
akndx = self.atomArrayIndex[ak]
h2aa[hndx].append(akndx)
self.a2h_map[akndx].append(hndx)
self.a2ha_map = np.array(tuple(a2ha_map.values()))
self.h2aa = np.array(h2aa)
# dihedra atoms
self.dAtoms: np.ndarray = np.empty((self.dihedraLen, 4, 4), dtype=np.float64)
self.dAtoms[:, :, 3] = 1.0 # homogeneous
self.a4_pre_rotation = np.empty((self.dihedraLen, 4))
# maps between dAtoms and atomArray
# hedra and dihedra
# dihedra forward/reverse data
a2da_map = {}
a2d_map = [[[], []] for _ in range(self.AAsiz)]
self.dRev: np.ndarray = np.zeros((self.dihedraLen), dtype=bool)
self.dH1ndx = np.empty(self.dihedraLen, dtype=np.int64)
self.dH2ndx = np.empty(self.dihedraLen, dtype=np.int64)
self.h1d_map = [[] for _ in range(self.hedraLen)]
self.id3_dh_index = {k[0:3]: [] for k in self.dihedraNdx.keys()}
self.id32_dh_index = {k[1:4]: [] for k in self.dihedraNdx.keys()}
for dk, dndx in self.dihedraNdx.items():
# build map between atomArray and dAtoms
dstep = dndx * 4
did3 = dk[0:3]
did32 = dk[1:4]
d = self.dihedra[dk]
for i in range(4):
ndx = self.atomArrayIndex[dk[i]]
a2da_map[dstep + i] = ndx
a2d_map[ndx][0].append(dndx)
a2d_map[ndx][1].append(i)
try:
d.h1key = did3
d.h2key = did32
h1ndx = self.hedraNdx[d.h1key]
except KeyError:
d.h1key = dk[2::-1]
d.h2key = dk[3:0:-1]
h1ndx = self.hedraNdx[d.h1key]
self.dRev[dndx] = True
d.reverse = True
h2ndx = self.hedraNdx[d.h2key]
d.hedron1 = self.hedra[d.h1key]
d.hedron2 = self.hedra[d.h2key]
self.dH1ndx[dndx] = h1ndx
self.dH2ndx[dndx] = h2ndx
self.h1d_map[h1ndx].append(dndx)
d.ndx = dndx
d.cst = self.dCoordSpace[0][dndx]
d.rcst = self.dCoordSpace[1][dndx]
self.id3_dh_index[did3].append(dk)
self.id32_dh_index[did32].append(dk)
self.a2da_map = np.array(tuple(a2da_map.values()))
self.d2a_map = self.a2da_map.reshape(-1, 4)
self.dFwd = self.dRev != True # noqa: E712
# manually create np.where(atom in dihedral)
self.a2d_map = [(np.array(xi[0]), np.array(xi[1])) for xi in a2d_map]
self.dAtoms_needs_update = np.full(self.dihedraLen, True)
def _hedraDict2chain(
self,
hl12: Dict[str, float],
ha: Dict[str, float],
hl23: Dict[str, float],
da: Dict[str, float],
bfacs: Dict[str, float],
) -> None:
"""Generate chain numpy arrays from :func:`.read_PIC` dicts.
On entry:
* chain internal_coord has ordered_aa_ic_list built, akset;
* residues have rnext, rprev, ak_set and di/hedra dicts initialised
* Chain, residues do NOT have NCaC info, id3_dh_index
* Di/hedra have cic, atomkeys set
* Dihedra do NOT have valid reverse flag, h1/2 info
"""
for ric in self.ordered_aa_ic_list:
# log chain starts - beginning and after breaks
# chain starts are only atom coords in pic files
# assume valid pic files with all 3 of N, Ca, C coords
initNCaC = []
for atm in ric.residue.get_atoms(): # n.b. only few PIC spec atoms
if 2 == atm.is_disordered():
if IC_Residue.no_altloc:
initNCaC.append(AtomKey(ric, atm.selected_child))
else:
for altAtom in atm.child_dict.values():
if altAtom.coord is not None:
initNCaC.append(AtomKey(ric, altAtom))
elif atm.coord is not None:
initNCaC.append(AtomKey(ric, atm))
if initNCaC != []:
self.initNCaCs.append(tuple(initNCaC))
# next residue NCaCKeys so can do per-residue assemble()
ric.NCaCKey = []
ric.NCaCKey.extend(
ric.split_akl(
(AtomKey(ric, "N"), AtomKey(ric, "CA"), AtomKey(ric, "C"))
)
)
ric._link_dihedra()
# if STILL have no self.initNCacs, assume pic file w/o atoms and grab
# from first residue
if self.initNCaCs == []:
ric = self.ordered_aa_ic_list[0]
iNCaC = ric.split_akl(
(AtomKey(ric, "N"), AtomKey(ric, "CA"), AtomKey(ric, "C"))
)
self.initNCaCs.extend(iNCaC)
# set any supplied coordinates from biopython atoms
# just loaded pic file so only start/chain break residues
# will have atoms
self.build_atomArray()
self.initNCaCs = sorted(self.initNCaCs)
# now create all biopython atoms for parent chain, setting coords to be
# view on atomArray entry
spNdx, icNdx, resnNdx, atmNdx, altlocNdx, occNdx = AtomKey.fields
sn = None
for ak, ndx in self.atomArrayIndex.items():
res = ak.ric.residue # read_PIC inits with IC_Residue
atm, altloc = ak.akl[atmNdx], ak.akl[altlocNdx]
occ = 1.00 if ak.akl[occNdx] is None else float(ak.akl[occNdx])
bfac = bfacs.get(ak.id, 0.0)
sn = sn + 1 if sn is not None else ndx + 1
bpAtm = None
if res.has_id(atm):
bpAtm = res[atm]
if bpAtm is None or (
2 == bpAtm.is_disordered() and not bpAtm.disordered_has_id(altloc)
):
newAtom = Atom(
atm,
self.atomArray[ndx][0:3], # init as view on atomArray
bfac,
occ,
(" " if altloc is None else altloc),
atm,
sn,
atm[0],
)
if bpAtm is None:
if altloc is None:
res.add(newAtom)
else:
disordered_atom = DisorderedAtom(atm)
res.add(disordered_atom)
disordered_atom.disordered_add(newAtom)
res.flag_disordered()
else:
bpAtm.disordered_add(newAtom)
else:
if 2 == bpAtm.is_disordered() and bpAtm.disordered_has_id(altloc):
bpAtm.disordered_select(altloc)
bpAtm.set_bfactor(bfac)
bpAtm.set_occupancy(occ)
sn = bpAtm.get_serial_number()
# hedra
# dicts sorted on creation by init_edra and maintained by write_PIC
# python 3.7 minimum for Biopython as of 6 sept 2021 PR #3714
self.hedraLen = len(ha)
self.hedraL12 = np.fromiter(hl12.values(), dtype=np.float64)
self.hedraAngle = np.fromiter(ha.values(), dtype=np.float64)
self.hedraL23 = np.fromiter(hl23.values(), dtype=np.float64)
self.hedraNdx = dict(zip(sorted(ha.keys()), range(self.hedraLen)))
# dihedra
self.dihedraLen = len(da)
self.dihedraAngle = np.fromiter(da.values(), dtype=np.float64)
self.dihedraAngleRads = np.deg2rad(self.dihedraAngle)
self.dihedraNdx = dict(zip(sorted(da.keys()), range(self.dihedraLen)))
self.build_edraArrays()
# @profile
def assemble_residues(self, verbose: bool = False) -> None:
"""Generate atom coords from internal coords (vectorised).
This is the 'Numpy parallel' version of :meth:`.assemble_residues_ser`.
Starting with dihedra already formed by :meth:`.init_atom_coords`, transform
each from dihedron local coordinate space into protein chain coordinate
space. Iterate until all dependencies satisfied.
Does not update :data:`dCoordSpace` as :meth:`assemble_residues_ser`
does. Call :meth:`.update_dCoordSpace` if needed. Faster to do in
single operation once all atom coordinates finished.
:param bool verbose: default False.
Report number of iterations to compute changed dihedra
generates:
self.dSet: AAsiz x dihedraLen x 4
maps atoms in dihedra to atomArray
self.dSetValid : [dihedraLen][4] of bool
map of valid atoms into dihedra to detect 3 or 4 atoms valid
Output coordinates written to :data:`atomArray`. Biopython
:class:`Bio.PDB.Atom` coordinates are a view on this data.
"""
# dihedron atom positions of chain atom ndxs, maps atomArray to dihedra
a2da_map = self.a2da_map # 8468 x int
# each chain atom to list of [dihedron], [dihedron_position]
a2d_map = self.a2d_map # 2000 x ([int], [int])
# every dihedron atom to chain atoms
d2a_map = self.d2a_map # 2117 x [4] ints
# all chain atoms
atomArray = self.atomArray # 2000
# bool markers for chain atoms with valid coordinates
atomArrayValid = self.atomArrayValid # 2000
# complete array of dihedra atoms
dAtoms = self.dAtoms # 2117 x [4][4] float
# coordinate space transformations optionally supplied
dCoordSpace1 = self.dCoordSpace[1]
dcsValid = self.dcsValid
# dSet is 4-atom arrays for every dihedral, multiple copies of
# many atoms as the dihedra overlap
self.dSet = atomArray[a2da_map].reshape(-1, 4, 4)
dSet = self.dSet
# dSetValid indicates accurate atom positions in each dSet dihedral
self.dSetValid = atomArrayValid[a2da_map].reshape(-1, 4)
dSetValid = self.dSetValid
# clear any transforms for dihedrals with outdated atoms
workSelector = (dSetValid == self._dihedraOK).all(axis=1)
self.dcsValid[np.logical_not(workSelector)] = False
dihedraWrk = None
if verbose:
dihedraWrk = workSelector.size - workSelector.sum()
# mask for dihedral with 3 valid atoms in dSet, ready to be processed:
targ = IC_Chain._dihedraSelect
# select the dihedrals ready for processing
workSelector = (dSetValid == targ).all(axis=1)
loopCount = 0
while np.any(workSelector):
# indexes of dihedra in dset to update
workNdxs = np.where(workSelector)
# subset of dihedra to update
workSet = dSet[workSelector]
# will update coordinates of 4th atom in each workSet dihedron
updateMap = d2a_map[workNdxs, 3][0]
# get all coordSpace transforms
if np.all(dcsValid[workSelector]):
cspace = dCoordSpace1[workSelector]
else:
cspace = multi_coord_space(workSet, np.sum(workSelector), True)[1]
# generate new coords for 4th atoms in workSet dihedra
initCoords = dAtoms[workSelector].reshape(-1, 4, 4)
atomArray[updateMap] = np.einsum("ijk,ik->ij", cspace, initCoords[:, 3])
# mark new computed atom positions as valid
atomArrayValid[updateMap] = True
# prep for next iteration
workSelector[:] = False
for a in updateMap:
# copy new atom positions into dihedra atom array
dSet[a2d_map[a]] = atomArray[a]
# build new workSelector from only updated dihedra
adlist = a2d_map[a]
for d in adlist[0]:
dvalid = atomArrayValid[d2a_map[d]]
workSelector[d] = (dvalid == targ).all()
loopCount += 1
if verbose:
cid = self.chain.full_id
print(
f"{cid[0]} {cid[2]} coordinates for {dihedraWrk} dihedra"
f" updated in {loopCount} iterations"
)
def assemble_residues_ser(
self,
verbose: bool = False,
start: Optional[int] = None,
fin: Optional[int] = None,
) -> None:
"""Generate IC_Residue atom coords from internal coordinates (serial).
See :meth:`.assemble_residues` for 'numpy parallel' version.
Filter positions between start and fin if set, find appropriate start
coordinates for each residue and pass to :meth:`.assemble`
:param bool verbose: default False.
Describe runtime problems
:param int start,fin: default None.
Sequence position for begin, end of subregion to generate coords
for.
"""
self.dcsValid[:] = False
for ric in self.ordered_aa_ic_list:
# : # clear and skip if outside start ... fin
if (fin and fin < ric.residue.id[1]) or (
start and start > ric.residue.id[1]
):
ric.ak_set = None
ric.akc = None
ric.residue.child_dict = {}
ric.residue.child_list = []
continue
atom_coords = ric.assemble(verbose=verbose)
if atom_coords:
ric.ak_set = set(atom_coords.keys())
def init_edra(self, verbose: bool = False) -> None:
"""Create chain and residue di/hedra structures, arrays, atomArray.
Inputs:
self.ordered_aa_ic_list : list of IC_Residue
Generates:
* edra objects, self.di/hedra (executes :meth:`._create_edra`)
* atomArray and support (executes :meth:`.build_atomArray`)
* self.hedraLen : number of hedra in structure
* hedraL12 : numpy arrays for lengths, angles (empty)
* hedraAngle ..
* hedraL23 ..
* self.hedraNdx : dict mapping hedrakeys to hedraL12 etc
* self.dihedraLen : number of dihedra in structure
* dihedraAngle ..
* dihedraAngleRads : np arrays for angles (empty)
* self.dihedraNdx : dict mapping dihedrakeys to dihedraAngle
"""
if self.ordered_aa_ic_list[0].hedra == {}:
for ric in self.ordered_aa_ic_list:
# build di/hedra objects in chain arrays
ric._create_edra(verbose=verbose)
if not hasattr(self, "atomArrayValid"):
self.build_atomArray() # ric.a2ic added gly CBs to akset
if not hasattr(self, "hedraLen"):
# hedra
self.hedraLen = len(self.hedra)
self.hedraL12 = np.empty((self.hedraLen), dtype=np.float64)
self.hedraAngle = np.empty((self.hedraLen), dtype=np.float64)
self.hedraL23 = np.empty((self.hedraLen), dtype=np.float64)
# python3.7 sorted dicts
self.hedraNdx = dict(zip(sorted(self.hedra.keys()), range(len(self.hedra))))
# dihedra
self.dihedraLen = len(self.dihedra)
self.dihedraAngle = np.empty(self.dihedraLen)
self.dihedraAngleRads = np.empty(self.dihedraLen)
self.dihedraNdx = dict(
zip(sorted(self.dihedra.keys()), range(self.dihedraLen))
)
if not hasattr(self, "hAtoms_needs_update"):
self.build_edraArrays()
# @profile
def init_atom_coords(self) -> None:
"""Set chain level di/hedra initial coords from angles and distances.
Initializes atom coordinates in local coordinate space for hedra and
dihedra, will be transformed appropriately later by :data:`dCoordSpace`
matrices for assembly.
"""
# dbg = True
if not np.all(self.dAtoms_needs_update):
self.dAtoms_needs_update |= (self.hAtoms_needs_update[self.dH1ndx]) | (
self.hAtoms_needs_update[self.dH2ndx]
)
self.dcsValid &= np.logical_not(self.dAtoms_needs_update)
# dihedra full size masks:
mdFwd = self.dFwd & self.dAtoms_needs_update
mdRev = self.dRev & self.dAtoms_needs_update
# update size masks
udFwd = self.dFwd[self.dAtoms_needs_update]
udRev = self.dRev[self.dAtoms_needs_update]
"""
if dbg:
print("mdFwd", mdFwd[0:10])
print("mdRev", mdRev[0:10])
print("udFwd", udFwd[0:10])
print("udRev", udRev[0:10])
"""
if np.any(self.hAtoms_needs_update):
# hedra inital coords
# sar = supplementary angle radian: angles which add to 180
sar = np.deg2rad(180.0 - self.hedraAngle[self.hAtoms_needs_update]) # angle
sinSar = np.sin(sar)
cosSarN = np.cos(sar) * -1
"""
if dbg:
print("sar", sar[0:10])
"""
# a2 is len3 up from a2 on Z axis, X=Y=0
self.hAtoms[:, 2, 2][self.hAtoms_needs_update] = self.hedraL23[
self.hAtoms_needs_update
]
# a0 X is sin( sar ) * len12
self.hAtoms[:, 0, 0][self.hAtoms_needs_update] = (
sinSar * self.hedraL12[self.hAtoms_needs_update]
)
# a0 Z is -(cos( sar ) * len12)
# (assume angle always obtuse, so a0 is in -Z)
self.hAtoms[:, 0, 2][self.hAtoms_needs_update] = (
cosSarN * self.hedraL12[self.hAtoms_needs_update]
)
"""
if dbg:
print("hAtoms_needs_update", self.hAtoms_needs_update[0:10])
print("self.hAtoms", self.hAtoms[0:10])
"""
# same again but 'reversed' : a0 on Z axis, a1 at origin, a2 in -Z
# a0r is len12 up from a1 on Z axis, X=Y=0
self.hAtomsR[:, 0, 2][self.hAtoms_needs_update] = self.hedraL12[
self.hAtoms_needs_update
]
# a2r X is sin( sar ) * len23
self.hAtomsR[:, 2, 0][self.hAtoms_needs_update] = (
sinSar * self.hedraL23[self.hAtoms_needs_update]
)
# a2r Z is -(cos( sar ) * len23)
self.hAtomsR[:, 2, 2][self.hAtoms_needs_update] = (
cosSarN * self.hedraL23[self.hAtoms_needs_update]
)
"""
if dbg:
print("self.hAtomsR", self.hAtomsR[0:10])
"""
self.hAtoms_needs_update[...] = False
# dihedra parts other than dihedral angle
dhlen = np.sum(self.dAtoms_needs_update) # self.dihedraLen
# only 4th atom takes work:
# pick 4th atom based on rev flag
self.a4_pre_rotation[mdRev] = self.hAtoms[self.dH2ndx, 0][mdRev]
self.a4_pre_rotation[mdFwd] = self.hAtomsR[self.dH2ndx, 2][mdFwd]
# numpy multiply, add operations below intermediate array but out=
# not working with masking:
self.a4_pre_rotation[:, 2][self.dAtoms_needs_update] = np.multiply(
self.a4_pre_rotation[:, 2][self.dAtoms_needs_update], -1
) # a4 to +Z
a4shift = np.empty(dhlen)
a4shift[udRev] = self.hedraL23[self.dH2ndx][mdRev] # len23
a4shift[udFwd] = self.hedraL12[self.dH2ndx][mdFwd] # len12
self.a4_pre_rotation[:, 2][self.dAtoms_needs_update] = np.add(
self.a4_pre_rotation[:, 2][self.dAtoms_needs_update],
a4shift,
) # so a2 at origin
"""
if dbg:
print("dhlen", dhlen)
print("a4shift", a4shift[0:10])
print("a4_pre_rotation", self.a4_pre_rotation[0:10])
"""
# now build dihedra initial coords
dH1atoms = self.hAtoms[self.dH1ndx] # fancy indexing so
dH1atomsR = self.hAtomsR[self.dH1ndx] # these copy not view
self.dAtoms[:, :3][mdFwd] = dH1atoms[mdFwd]
self.dAtoms[:, :3][mdRev] = dH1atomsR[:, 2::-1][mdRev]
"""
if dbg:
print("dH1atoms", dH1atoms[0:10])
print("dH1atosR", dH1atomsR[0:10])
print("dAtoms", self.dAtoms[0:10])
"""
# build rz rotation matrix for dihedral angle
"""
if dbg:
print("dangle-rads", self.dihedraAngleRads[0:10])
"""
rz = multi_rot_Z(self.dihedraAngleRads[self.dAtoms_needs_update])
a4rot = np.matmul(
rz,
self.a4_pre_rotation[self.dAtoms_needs_update][:].reshape(-1, 4, 1),
).reshape(-1, 4)
self.dAtoms[:, 3][mdFwd] = a4rot[udFwd] # [self.dFwd]
self.dAtoms[:, 3][mdRev] = a4rot[udRev] # [self.dRev]
"""
if dbg:
print("rz", rz[0:3])
print("dAtoms", self.dAtoms[0:10])
"""
self.dAtoms_needs_update[...] = False
# can't start assembly if initial NCaC is not valid, so copy from
# hAtoms if needed
"""
if dbg:
print("initNCaCs", self.initNCaCs)
"""
for iNCaC in self.initNCaCs:
invalid = True
if np.all(self.atomArrayValid[[self.atomArrayIndex[ak] for ak in iNCaC]]):
invalid = False
if invalid:
hatoms = self.hAtoms[self.hedraNdx[iNCaC]]
for i in range(3):
andx = self.atomArrayIndex[iNCaC[i]]
self.atomArray[andx] = hatoms[i]
self.atomArrayValid[andx] = True
"""
if dbg:
hatoms = self.hAtoms[self.hedraNdx[iNCaC]]
print("hedraNdx iNCaC", self.hedraNdx[iNCaC])
print("hatoms", hatoms)
"""
def update_dCoordSpace(self, workSelector: Optional[np.ndarray] = None) -> None:
"""Compute/update coordinate space transforms for chain dihedra.
Requires all atoms updated so calls :meth:`.assemble_residues`
(returns immediately if all atoms already assembled).
:param [bool] workSelector:
Optional mask to select dihedra for update
"""
if workSelector is None:
self.assemble_residues() # update atoms, fast if nothing to do
workSelector = np.logical_not(self.dcsValid)
workSet = self.dSet[workSelector]
self.dCoordSpace[:, workSelector] = multi_coord_space(
workSet, np.sum(workSelector), True
)
self.dcsValid[workSelector] = True
def propagate_changes(self) -> None:
"""Track through di/hedra to invalidate dependent atoms."""
# cs : chain segment
# csStart, csNext : AtomArray indexes for chain segment
# process each chain segment
csNdx = 0
csLen = len(self.initNCaCs)
atmNdx = AtomKey.fields.atm
posNdx = AtomKey.fields.respos
done = set()
while csNdx < csLen: # iterate over chain starts
startAK = self.initNCaCs[csNdx][0]
csStart = self.atomArrayIndex[startAK]
csnTry = csNdx + 1
# set csNext to be atomArray index of segment end
if csLen == csnTry:
csNext = self.AAsiz # last segment to end of atomArray
else: # this segment to next chain start
finAK = self.initNCaCs[csnTry][0]
csNext = self.atomArrayIndex[finAK]
for andx in range(csStart, csNext):
if not self.atomArrayValid[andx]:
ak = self.aktuple[andx]
atm = ak.akl[atmNdx]
pos = ak.akl[posNdx] # sequence position = residue number
if atm in ("N", "CA", "C"):
# backbone moved so all to next start moved
self.atomArrayValid[andx:csNext] = False
# and done with this invalid_atom_ndxs segment
break
elif pos not in done and atm != "H":
# H is terminal so ignore, not effect subsequent atoms
# O is terminal but used to locate CB
# atomArray is sorted, sidechain atoms follow backbone
for i in range(andx, csNext):
if self.aktuple[i].akl[posNdx] == pos:
self.atomArrayValid[i] = False
else:
# done with residue sidechain when find next
# seq pos so need not go to fin
break
done.add(pos)
csNdx += 1
# @profile
def internal_to_atom_coordinates(
self,
verbose: bool = False,
start: Optional[int] = None,
fin: Optional[int] = None,
) -> None:
"""Process IC data to Residue/Atom coords.
:param bool verbose: default False.
Describe runtime problems
:param int start,fin:
Optional sequence positions for begin, end of subregion
to process.
.. note::
Setting start or fin activates serial :meth:`.assemble_residues_ser`
instead of (Numpy parallel) :meth:`.assemble_residues`.
Start C-alpha will be at origin.
.. seealso::
:data:`ParallelAssembleResidues`
"""
if not hasattr(self, "dAtoms_needs_update"):
return # escape on no data to process
# if verbose:
# for ric in self.ordered_aa_ic_list:
# if not hasattr(ric, "NCaCKey"):
# print(
# f"no assembly for {ric} due to missing N, Ca"
# " and/or C atoms"
# )
if IC_Chain.ParallelAssembleResidues and not (start or fin):
self.propagate_changes()
self.init_atom_coords() # compute initial di/hedra coords
# transform init di/hedra to chain coord space
self.assemble_residues(verbose=verbose)
if verbose and not np.all(self.atomArrayValid):
dSetValid = self.atomArrayValid[self.a2da_map].reshape(-1, 4)
for ric in self.ordered_aa_ic_list:
for d in ric.dihedra.values():
if not dSetValid[d.ndx].all():
print(
"missing coordinates for chain "
f"{ric.cic.chain.id} {ric.pretty_str()} "
f"dihedral: {d.id}"
)
else:
if start: # set initNCaC tag to build from
for ric in self.ordered_aa_ic_list:
if start != ric.residue.id[1]:
continue
iNCaC = ric.split_akl(
(
AtomKey(ric, "N"),
AtomKey(ric, "CA"),
AtomKey(ric, "C"),
)
)
self.initNCaCs.extend(iNCaC)
self.init_atom_coords() # compute initial di/hedra coords
self.assemble_residues_ser(
verbose=verbose, start=start, fin=fin
) # internal to XYZ coordinates
# @profile
def atom_to_internal_coordinates(self, verbose: bool = False) -> None:
"""Calculate dihedrals, angles, bond lengths for Atom data.
Generates atomArray (through init_edra), value arrays for hedra and
dihedra, and coordinate space transforms for dihedra.
Generates Gly C-beta if specified, see :data:`IC_Residue.gly_Cbeta`
:param bool verbose: default False.
describe runtime problems
"""
if self.ordered_aa_ic_list == []:
return # escape on no data to process
self.init_edra(verbose=verbose)
if self.dihedra == {}:
return # escape if no hedra loaded for this chain
# compute all hedra parameters with law of cosines on 3 atom coords
ha = self.atomArray[self.a2ha_map].reshape(-1, 3, 4)
self.hedraL12 = np.linalg.norm(ha[:, 0] - ha[:, 1], axis=1)
self.hedraL23 = np.linalg.norm(ha[:, 1] - ha[:, 2], axis=1)
h_a0a2 = np.linalg.norm(ha[:, 0] - ha[:, 2], axis=1)
np.rad2deg(
np.arccos(
(
np.square(self.hedraL12)
+ np.square(self.hedraL23)
- np.square(h_a0a2)
)
/ (2 * self.hedraL12 * self.hedraL23)
),
out=self.hedraAngle,
)
# now process dihedra
dha = self.atomArray[self.a2da_map].reshape(-1, 4, 4)
# develop coord_space matrix for 1st 3 atoms of dihedra:
# note use of [...] to modify in place, dihedra cst, rcst remain valid
self.dCoordSpace[...] = multi_coord_space(dha, self.dihedraLen, True)
self.dcsValid[:] = True
# now put atom 4 into that coordinate space
do4 = np.matmul(self.dCoordSpace[0], dha[:, 3].reshape(-1, 4, 1)).reshape(-1, 4)
# and read dihedral as azimuth
np.arctan2(do4[:, 1], do4[:, 0], out=self.dihedraAngleRads)
np.rad2deg(self.dihedraAngleRads, out=self.dihedraAngle)
if hasattr(self, "gcb"):
self._spec_glyCB()
def _spec_glyCB(self) -> None:
"""Populate values for Gly C-beta."""
Ca_Cb_Len = 1.53363
if hasattr(self, "scale"): # used for openscad output
Ca_Cb_Len *= self.scale # type: ignore
for gcbd in self.gcb.values(): # gcb dict created by _create_edra
cbak = gcbd[3]
self.atomArrayValid[self.atomArrayIndex[cbak]] = False
ric = cbak.ric
rN, rCA, rC, rO = (
ric.rak("N"),
ric.rak("CA"),
ric.rak("C"),
ric.rak("O"),
)
gCBd = self.dihedra[gcbd]
dndx = gCBd.ndx
# generated dihedron is O-Ca-C-Cb
# hedron2 is reversed: Cb-Ca-C (also h1 reversed: C-Ca-O)
h2ndx = gCBd.hedron2.ndx
self.hedraL12[h2ndx] = Ca_Cb_Len
self.hedraAngle[h2ndx] = 110.17513
self.hedraL23[h2ndx] = self.hedraL12[self.hedraNdx[(rCA, rC, rO)]]
self.hAtoms_needs_update[gCBd.hedron2.ndx] = True
for ak in gCBd.hedron2.atomkeys:
self.atomArrayValid[self.atomArrayIndex[ak]] = False
refval = self.dihedra.get((rN, rCA, rC, rO), None)
if refval:
angl = 122.68219 + self.dihedraAngle[refval.ndx]
self.dihedraAngle[dndx] = angl if (angl <= 180.0) else angl - 360.0
else:
self.dihedraAngle[dndx] = 120
@staticmethod
def _write_mtx(fp: TextIO, mtx: np.array) -> None:
fp.write("[ ")
rowsStarted = False
for row in mtx:
if rowsStarted:
fp.write(", [ ")
else:
fp.write("[ ")
rowsStarted = True
colsStarted = False
for col in row:
if colsStarted:
fp.write(", " + str(col))
else:
fp.write(str(col))
colsStarted = True
fp.write(" ]") # close row
fp.write(" ]")
@staticmethod
def _writeSCAD_dihed(
fp: TextIO, d: "Dihedron", hedraNdx: Dict, hedraSet: Set[EKT]
) -> None:
fp.write(
"[ {:9.5f}, {}, {}, {}, ".format(
d.angle,
hedraNdx[d.h1key],
hedraNdx[d.h2key],
(1 if d.reverse else 0),
)
)
fp.write(
f"{0 if d.h1key in hedraSet else 1}, "
f"{0 if d.h2key in hedraSet else 1}, "
)
fp.write(
" // {} [ {} -- {} ] {}\n".format(
d.id,
d.hedron1.id,
d.hedron2.id,
("reversed" if d.reverse else ""),
)
)
fp.write(" ")
IC_Chain._write_mtx(fp, d.rcst)
fp.write(" ]") # close residue array of dihedra entry
def _write_SCAD(self, fp: TextIO, backboneOnly: bool, start=None, fin=None) -> None:
"""Write self to file fp as OpenSCAD data matrices.
See `OpenSCAD <https://www.openscad.org>`_.
Works with :func:`.write_SCAD` and embedded OpenSCAD routines therein.
"""
fp.write(f' "{self.chain.id}", // chain id\n')
# generate dict for all hedra to eliminate redundant references
hedra = {}
for ric in self.ordered_aa_ic_list:
respos = ric.residue.id[1]
if start is not None and respos < start - 1:
# start-1 because rprev has some hedra for residue r
continue
if fin is not None and respos > fin:
continue
for k, h in ric.hedra.items():
hedra[k] = h
atomSet: Set[AtomKey] = set()
bondDict: Dict = {} # set()
hedraSet: Set[EKT] = set()
ndx = 0
hedraNdx = {}
for hk in sorted(hedra):
hedraNdx[hk] = ndx
ndx += 1
# write residue dihedra table
fp.write(" [ // residue array of dihedra")
resNdx = {}
dihedraNdx = {}
ndx = 0
chnStarted = False
for ric in self.ordered_aa_ic_list:
respos = ric.residue.id[1]
if start is not None and respos < start:
continue
if fin is not None and respos > fin:
continue
if "O" not in ric.akc:
if ric.lc != "G" and ric.lc != "A":
print(
"Unable to generate complete sidechain for "
f"{ric} {ric.lc} missing O atom"
)
resNdx[ric] = ndx
if chnStarted:
fp.write("\n ],")
else:
chnStarted = True
fp.write(
"\n [ // "
+ str(ndx)
+ " : "
+ str(ric.residue.id)
+ " "
+ ric.lc
+ " backbone\n"
)
ndx += 1
# assemble with no start position, return transform matrices
ric.clear_transforms()
# compute residue atom coords for no start position
# dump results because only want rcst
# IC_Chain.adbg = True
ric.assemble(resetLocation=True)
# IC_Chain.adbg = False
ndx2 = 0
started = False
for i in range(1 if backboneOnly else 2):
if i == 1:
cma = "," if started else ""
fp.write(
f"{cma}\n // {str(ric.residue.id)} {ric.lc}"
" sidechain\n"
)
started = False
for dk, d in sorted(ric.dihedra.items()):
if d.h2key in hedraNdx and (
(i == 0 and d.is_backbone()) or (i == 1 and not d.is_backbone())
):
if d.cic.dcsValid[d.ndx]:
if started:
fp.write(",\n")
else:
started = True
fp.write(" ")
IC_Chain._writeSCAD_dihed(fp, d, hedraNdx, hedraSet)
dihedraNdx[dk] = ndx2
hedraSet.add(d.h1key)
hedraSet.add(d.h2key)
ndx2 += 1
else:
print(
f"Atom missing for {d.id3}-{d.id32}, OpenSCAD"
f" chain may be discontiguous"
)
fp.write(" ],") # end of residue entry dihedra table
fp.write("\n ],\n") # end of all dihedra table
# write hedra table
fp.write(" [ //hedra\n")
for hk in sorted(hedra):
hed = hedra[hk]
fp.write(" [ ")
fp.write(
"{:9.5f}, {:9.5f}, {:9.5f}".format(
set_accuracy_95(hed.len12),
set_accuracy_95(hed.angle),
set_accuracy_95(hed.len23),
)
)
atom_str = "" # atom and bond state
atom_done_str = "" # create each only once
akndx = 0
for ak in hed.atomkeys:
atm = ak.akl[AtomKey.fields.atm]
res = ak.akl[AtomKey.fields.resname]
# try first for generic backbone/Cbeta atoms
ab_state_res = residue_atom_bond_state["X"]
ab_state = ab_state_res.get(atm, None)
if "H" == atm[0]:
ab_state = "Hsb"
if ab_state is None:
# not found above, must be sidechain atom
ab_state_res = residue_atom_bond_state.get(res, None)
if ab_state_res is not None:
ab_state = ab_state_res.get(atm, "")
else:
ab_state = ""
atom_str += ', "' + ab_state + '"'
if ak in atomSet:
atom_done_str += ", 0"
elif hk in hedraSet:
if (
hasattr(hed, "flex_female_1") or hasattr(hed, "flex_male_1")
) and akndx != 2:
if akndx == 0:
atom_done_str += ", 0"
elif akndx == 1:
atom_done_str += ", 1"
atomSet.add(ak)
elif (
hasattr(hed, "flex_female_2") or hasattr(hed, "flex_male_2")
) and akndx != 0:
if akndx == 2:
atom_done_str += ", 0"
elif akndx == 1:
atom_done_str += ", 1"
atomSet.add(ak)
else:
atom_done_str += ", 1"
atomSet.add(ak)
else:
atom_done_str += ", 0"
akndx += 1
fp.write(atom_str)
fp.write(atom_done_str)
# specify bond options
bond = []
bond.append(hed.atomkeys[0].id + "-" + hed.atomkeys[1].id)
bond.append(hed.atomkeys[1].id + "-" + hed.atomkeys[2].id)
b0 = True
for b in bond:
wstr = ""
if b in bondDict and bondDict[b] == "StdBond":
wstr = ", 0"
elif hk in hedraSet:
bondType = "StdBond"
if b0:
if hasattr(hed, "flex_female_1"):
bondType = "FemaleJoinBond"
elif hasattr(hed, "flex_male_1"):
bondType = "MaleJoinBond"
elif hasattr(hed, "skinny_1"):
bondType = "SkinnyBond"
elif hasattr(hed, "hbond_1"):
bondType = "HBond"
else:
if hasattr(hed, "flex_female_2"):
bondType = "FemaleJoinBond"
elif hasattr(hed, "flex_male_2"):
bondType = "MaleJoinBond"
# elif hasattr(hed, 'skinny_2'): # unused
# bondType = 'SkinnyBond'
elif hasattr(hed, "hbond_2"):
bondType = "HBond"
if b in bondDict:
bondDict[b] = "StdBond"
else:
bondDict[b] = bondType
wstr = ", " + str(bondType)
else:
wstr = ", 0"
fp.write(wstr)
b0 = False
akl = hed.atomkeys[0].akl
fp.write(
', "'
+ akl[AtomKey.fields.resname]
+ '", '
+ akl[AtomKey.fields.respos]
+ ', "'
+ hed.e_class
+ '"'
)
fp.write(" ], // " + str(hk) + "\n")
fp.write(" ],\n") # end of hedra table
# write chain table
self.atomArrayValid[:] = False
self.internal_to_atom_coordinates()
fp.write("\n[ // chain - world transform for each residue\n")
chnStarted = False
for ric in self.ordered_aa_ic_list:
# rtm handle start / end
respos = ric.residue.id[1]
if start is not None and respos < start:
continue
if fin is not None and respos > fin:
continue
for k, h in ric.hedra.items():
hedra[k] = h
for NCaCKey in sorted(ric.NCaCKey): # type: ignore
mtr = None
if 0 < len(ric.rprev):
acl = [self.atomArray[self.atomArrayIndex[ak]] for ak in NCaCKey]
mt, mtr = coord_space(acl[0], acl[1], acl[2], True)
else:
mtr = np.identity(4, dtype=np.float64)
if chnStarted:
fp.write(",\n")
else:
chnStarted = True
fp.write(" [ " + str(resNdx[ric]) + ', "' + str(ric.residue.id[1]))
fp.write(ric.lc + '", //' + str(NCaCKey) + "\n")
IC_Chain._write_mtx(fp, mtr)
fp.write(" ]")
fp.write("\n ]\n")
def distance_plot(
self, filter: Optional[Union[np.ndarray, None]] = None
) -> np.ndarray:
"""Generate 2D distance plot from atomArray.
Default is to calculate distances for all atoms. To generate the
classic C-alpha distance plot, pass a boolean mask array like::
atmNameNdx = internal_coords.AtomKey.fields.atm
CaSelect = [
atomArrayIndex.get(k)
for k in atomArrayIndex.keys()
if k.akl[atmNameNdx] == "CA"
]
plot = cic.distance_plot(CaSelect)
Alternatively, this will select all backbone atoms::
backboneSelect = [
atomArrayIndex.get(k)
for k in atomArrayIndex.keys()
if k.is_backbone()
]
:param [bool] filter: restrict atoms for calculation
.. seealso::
:meth:`.distance_to_internal_coordinates`, which requires the
default all atom distance plot.
"""
if filter is None:
atomSet = self.atomArray
else:
atomSet = self.atomArray[filter]
# create distance matrix without scipy
# see https://jbencook.com/pairwise-distance-in-numpy/
return np.linalg.norm(atomSet[:, None, :] - atomSet[None, :, :], axis=-1)
def dihedral_signs(self) -> np.ndarray:
"""Get sign array (+1/-1) for each element of chain dihedraAngle array.
Required for :meth:`.distance_to_internal_coordinates`
"""
return np.sign(self.dihedraAngle)
def distplot_to_dh_arrays(
self, distplot: np.ndarray, dihedra_signs: np.ndarray
) -> None:
"""Load di/hedra distance arays from distplot.
Fill :class:`IC_Chain` arrays hedraL12, L23, L13 and dihedraL14
distance value arrays from input distplot, dihedra_signs array from
input dihedra_signs. Distplot and di/hedra distance arrays must index
according to AtomKey mappings in :class:`IC_Chain` .hedraNdx and .dihedraNdx
(created in :meth:`IC_Chain.init_edra`)
Call :meth:`atom_to_internal_coordinates` (or at least :meth:`init_edra`)
to generate a2ha_map and d2a_map before running this.
Explcitly removed from :meth:`.distance_to_internal_coordinates` so
user may populate these chain di/hedra arrays by other
methods.
"""
ha = self.a2ha_map.reshape(-1, 3)
self.hedraL12 = distplot[ha[:, 0], ha[:, 1]]
self.hedraL23 = distplot[ha[:, 1], ha[:, 2]]
self.hedraL13 = distplot[ha[:, 0], ha[:, 2]]
da = self.d2a_map
self.dihedraL14 = distplot[da[:, 0], da[:, 3]]
self.dihedra_signs = dihedra_signs
def distance_to_internal_coordinates(
self, resetAtoms: Optional[Union[bool, None]] = True
) -> None:
"""Compute chain di/hedra from from distance and chirality data.
Distance properties on hedra L12, L23, L13 and dihedra L14 configured
by :meth:`.distplot_to_dh_arrays` or alternative loader.
dihedraAngles result is multiplied by dihedra_signs at final step
recover chirality information lost in distance plot (mirror image of
structure has same distances but opposite sign dihedral angles).
Note that chain breaks will cause errors in rebuilt structure, use
:meth:`.copy_initNCaCs` to avoid this
Based on Blue, the Hedronometer's answer to `The dihedral angles of a tetrahedron
in terms of its edge lengths <https://math.stackexchange.com/a/49340/972353>`_
on `math.stackexchange.com <https://math.stackexchange.com/>`_. See also:
`"Heron-like Hedronometric Results for Tetrahedral Volume"
<http://daylateanddollarshort.com/mathdocs/Heron-like-Results-for-Tetrahedral-Volume.pdf>`_.
Other values from that analysis included here as comments for
completeness:
* oa = hedron1 L12 if reverse else hedron1 L23
* ob = hedron1 L23 if reverse else hedron1 L12
* ac = hedron2 L12 if reverse else hedron2 L23
* ab = hedron1 L13 = law of cosines on OA, OB (hedron1 L12, L23)
* oc = hedron2 L13 = law of cosines on OA, AC (hedron2 L12, L23)
* bc = dihedron L14
target is OA, the dihedral angle along edge oa.
:param bool resetAtoms: default True.
Mark all atoms in di/hedra and atomArray for updating by
:meth:`.internal_to_atom_coordinates`. Alternatvely set this to
False and manipulate `atomArrayValid`, `dAtoms_needs_update` and
`hAtoms_needs_update` directly to reduce computation.
""" # noqa
oa = self.hedraL12[self.dH1ndx]
oa[self.dFwd] = self.hedraL23[self.dH1ndx][self.dFwd]
ob = self.hedraL23[self.dH1ndx]
ob[self.dFwd] = self.hedraL12[self.dH1ndx][self.dFwd]
ac = self.hedraL12[self.dH2ndx]
ac[self.dFwd] = self.hedraL23[self.dH2ndx][self.dFwd]
ab = self.hedraL13[self.dH1ndx]
oc = self.hedraL13[self.dH2ndx]
bc = self.dihedraL14
# Ws = (ab + ac + bc) / 2
# Xs = (ob + bc + oc) / 2
Ys = (oa + ac + oc) / 2
Zs = (oa + ob + ab) / 2
# Wsqr = Ws * (Ws - ab) * (Ws - ac) * (Ws - bc)
# Xsqr = Xs * (Xs - ob) * (Xs - bc) * (Xs - oc)
Ysqr = Ys * (Ys - oa) * (Ys - ac) * (Ys - oc)
Zsqr = Zs * (Zs - oa) * (Zs - ob) * (Zs - ab)
Hsqr = (
4 * oa * oa * bc * bc - np.square((ob * ob + ac * ac) - (oc * oc + ab * ab))
) / 16
"""
Jsqr = (
4 * ob * ob * ac * ac
- np.square((oc * oc + ab * ab) - (oa * oa + bc * bc))
) / 16
Ksqr = (
4 * oc * oc * ab * ab
- np.square((oa * oa + bc * bc) - (ob * ob + ac * ac))
) / 16
"""
Y = np.sqrt(Ysqr)
Z = np.sqrt(Zsqr)
# X = np.sqrt(Xsqr)
# W = np.sqrt(Wsqr)
cosOA = (Ysqr + Zsqr - Hsqr) / (2 * Y * Z)
# cosOB = (Zsqr + Xsqr - Jsqr) / (2 * Z * X)
# cosOC = (Xsqr + Ysqr - Ksqr) / (2 * X * Y)
# cosBC = (Wsqr + Xsqr - Hsqr) / (2 * W * X)
# cosCA = (Wsqr + Ysqr - Jsqr) / (2 * W * Y)
# cosAB = (Wsqr + Zsqr - Ksqr) / (2 * W * Z)
# OA =
# compute dihedral angles
# ensure cosOA is in range [-1,1] for arccos
cosOA[cosOA < -1.0] = -1.0
cosOA[cosOA > 1.0] = 1.0
# without np.longdouble here a few OCCACB angles lose last digit match
np.arccos(cosOA, out=self.dihedraAngleRads, dtype=np.longdouble)
self.dihedraAngleRads *= self.dihedra_signs
np.rad2deg(self.dihedraAngleRads, out=self.dihedraAngle)
# OB = np.rad2deg(np.arccos(cosOB))
# OC = np.rad2deg(np.arccos(cosOC))
# BC = np.rad2deg(np.arccos(cosBC))
# CA = np.rad2deg(np.arccos(cosCA))
# AB = np.rad2deg(np.arccos(cosAB))
# law of cosines for hedra angles
np.rad2deg(
np.arccos(
(
np.square(self.hedraL12)
+ np.square(self.hedraL23)
- np.square(self.hedraL13)
)
/ (2 * self.hedraL12 * self.hedraL23)
),
out=self.hedraAngle,
)
if resetAtoms:
self.atomArrayValid[:] = False
self.dAtoms_needs_update[:] = True
self.hAtoms_needs_update[:] = True
def copy_initNCaCs(self, other: "IC_Chain") -> None:
"""Copy atom coordinates for initNCaC atoms from other IC_Chain.
Copies the coordinates and sets atomArrayValid flags True for initial
NCaC and after any chain breaks.
Needed for :meth:`.distance_to_internal_coordinates` if target has
chain breaks (otherwise each fragment will start at origin).
Also useful if copying internal coordinates from another chain.
"""
ndx = [self.atomArrayIndex[ak] for iNCaC in other.initNCaCs for ak in iNCaC]
self.atomArray[ndx] = other.atomArray[ndx]
self.atomArrayValid[ndx] = True
class IC_Residue:
"""Class to extend Biopython Residue with internal coordinate data.
Parameters
----------
parent: biopython Residue object this class extends
Attributes
----------
no_altloc: bool default False
**Class** variable, disable processing of ALTLOC atoms if True, use
only selected atoms.
accept_atoms: tuple
**Class** variable :data:`accept_atoms`, list of PDB atom names to use
when generating internal coordinates.
Default is::
accept_atoms = accept_mainchain + accept_hydrogens
to exclude hydrogens in internal coordinates and generated PDB files,
override as::
IC_Residue.accept_atoms = IC_Residue.accept_mainchain
to get only mainchain atoms plus amide proton, use::
IC_Residue.accept_atoms = IC_Residue.accept_mainchain + ('H',)
to convert D atoms to H, set :data:`AtomKey.d2h` = True and use::
IC_Residue.accept_atoms = (
accept_mainchain + accept_hydrogens + accept_deuteriums
)
Note that `accept_mainchain = accept_backbone + accept_sidechain`.
Thus to generate sequence-agnostic conformational data for e.g.
structure alignment in dihedral angle space, use::
IC_Residue.accept_atoms = accept_backbone
or set gly_Cbeta = True and use::
IC_Residue.accept_atoms = accept_backbone + ('CB',)
Changing accept_atoms will cause the default `structure_rebuild_test` in
:mod:`.ic_rebuild` to fail if some atoms are filtered (obviously). Use
the `quick=True` option to test only the coordinates of filtered atoms
to avoid this.
There is currently no option to output internal coordinates with D
instead of H.
accept_resnames: tuple
**Class** variable :data:`accept_resnames`, list of 3-letter residue
names for HETATMs to accept when generating internal coordinates from
atoms. HETATM sidechain will be ignored, but normal backbone atoms (N,
CA, C, O, CB) will be included. Currently only CYG, YCM and UNK;
override at your own risk. To generate sidechain, add appropriate
entries to `ic_data_sidechains` in :mod:`.ic_data` and support in
:meth:`IC_Chain.atom_to_internal_coordinates`.
gly_Cbeta: bool default False
**Class** variable :data:`gly_Cbeta`, override to True to generate
internal coordinates for glycine CB atoms in
:meth:`IC_Chain.atom_to_internal_coordinates` ::
IC_Residue.gly_Cbeta = True
pic_accuracy: str default "17.13f"
**Class** variable :data:`pic_accuracy` sets accuracy for numeric values
(angles, lengths) in .pic files. Default set high to support mmCIF file
accuracy in rebuild tests. If you find rebuild tests fail with
'ERROR -COORDINATES-' and verbose=True shows only small discrepancies,
try raising this value (or lower it to 9.5 if only working with PDB
format files). ::
IC_Residue.pic_accuracy = "9.5f"
residue: Biopython Residue object reference
The :class:`.Residue` object this extends
hedra: dict indexed by 3-tuples of AtomKeys
Hedra forming this residue
dihedra: dict indexed by 4-tuples of AtomKeys
Dihedra forming (overlapping) this residue
rprev, rnext: lists of IC_Residue objects
References to adjacent (bonded, not missing, possibly disordered)
residues in chain
atom_coords: AtomKey indexed dict of numpy [4] arrays
**removed**
Use AtomKeys and atomArrayIndex to build if needed
ak_set: set of AtomKeys in dihedra
AtomKeys in all dihedra overlapping this residue (see __contains__())
alt_ids: list of char
AltLoc IDs from PDB file
bfactors: dict
AtomKey indexed B-factors as read from PDB file
NCaCKey: List of tuples of AtomKeys
List of tuples of N, Ca, C backbone atom AtomKeys; usually only 1
but more if backbone altlocs.
is20AA: bool
True if residue is one of 20 standard amino acids, based on
Residue resname
isAccept: bool
True if is20AA or in accept_resnames below
rbase: tuple
residue position, insert code or none, resname (1 letter if standard
amino acid)
cic: IC_Chain default None
parent chain :class:`IC_Chain` object
scale: optional float
used for OpenSCAD output to generate gly_Cbeta bond length
Methods
-------
assemble(atomCoordsIn, resetLocation, verbose)
Compute atom coordinates for this residue from internal coordinates
get_angle()
Return angle for passed key
get_length()
Return bond length for specified pair
pick_angle()
Find Hedron or Dihedron for passed key
pick_length()
Find hedra for passed AtomKey pair
set_angle()
Set angle for passed key (no position updates)
set_length()
Set bond length in all relevant hedra for specified pair
bond_rotate(delta)
adjusts related dihedra angles by delta, e.g. rotating psi (N-Ca-C-N)
will adjust the adjacent N-Ca-C-O by the same amount to avoid clashes
bond_set(angle)
uses bond_rotate to set specified dihedral to angle and adjust related
dihedra accordingly
rak(atom info)
cached AtomKeys for this residue
"""
accept_resnames = ("CYG", "YCM", "UNK")
"""Add 3-letter residue name here for non-standard residues with
normal backbone. CYG included for test case 4LGY (1305 residue
contiguous chain). Safe to add more names for N-CA-C-O backbones, any
more complexity will need additions to :data:`accept_atoms`,
`ic_data_sidechains` in :mod:`.ic_data` and support in
:meth:`IC_Chain.atom_to_internal_coordinates`"""
_AllBonds: bool = False
"""For OpenSCAD output, generate explicit hedra covering all bonds.
**Class** variable, whereas a PDB file just specifies atoms, OpenSCAD
output for 3D printing needs all bonds specified explicitly - otherwise
e.g. PHE rings will not be closed. This variable is managed by the
:func:`.SCADIO.write_SCAD` code."""
no_altloc: bool = False
"""Set True to filter altloc atoms on input and only work with Biopython
default Atoms"""
gly_Cbeta: bool = False
"""Create beta carbons on all Gly residues.
Setting this to True will generate internal coordinates for Gly C-beta
carbons in :meth:`atom_to_internal_coordinates`.
Data averaged from Sep 2019 Dunbrack cullpdb_pc20_res2.2_R1.0
restricted to structures with amide protons.
Please see
`PISCES: A Protein Sequence Culling Server <https://dunbrack.fccc.edu/pisces/>`_
'G. Wang and R. L. Dunbrack, Jr. PISCES: a protein sequence culling
server. Bioinformatics, 19:1589-1591, 2003.'
Ala avg rotation of OCCACB from NCACO query::
select avg(g.rslt) as avg_rslt, stddev(g.rslt) as sd_rslt, count(*)
from
(select f.d1d, f.d2d,
(case when f.rslt > 0 then f.rslt-360.0 else f.rslt end) as rslt
from (select d1.angle as d1d, d2.angle as d2d,
(d2.angle - d1.angle) as rslt from dihedron d1,
dihedron d2 where d1.re_class='AOACACAACB' and
d2.re_class='ANACAACAO' and d1.pdb=d2.pdb and d1.chn=d2.chn
and d1.res=d2.res) as f) as g
results::
| avg_rslt | sd_rslt | count |
| -122.682194862932 | 5.04403040513919 | 14098 |
"""
pic_accuracy: str = (
"17.13f" # output accuracy for angle and len values in .pic files
)
accept_backbone = (
"N",
"CA",
"C",
"O",
"OXT",
)
accept_sidechain = (
"CB",
"CG",
"CG1",
"OG1",
"OG",
"SG",
"CG2",
"CD",
"CD1",
"SD",
"OD1",
"ND1",
"CD2",
"ND2",
"CE",
"CE1",
"NE",
"OE1",
"NE1",
"CE2",
"OE2",
"NE2",
"CE3",
"CZ",
"NZ",
"CZ2",
"CZ3",
"OD2",
"OH",
"CH2",
"NH1",
"NH2",
)
accept_mainchain = accept_backbone + accept_sidechain
accept_hydrogens = (
"H",
"H1",
"H2",
"H3",
"HA",
"HA2",
"HA3",
"HB",
"HB1",
"HB2",
"HB3",
"HG2",
"HG3",
"HD2",
"HD3",
"HE2",
"HE3",
"HZ1",
"HZ2",
"HZ3",
"HG11",
"HG12",
"HG13",
"HG21",
"HG22",
"HG23",
"HZ",
"HD1",
"HE1",
"HD11",
"HD12",
"HD13",
"HG",
"HG1",
"HD21",
"HD22",
"HD23",
"NH1",
"NH2",
"HE",
"HH11",
"HH12",
"HH21",
"HH22",
"HE21",
"HE22",
"HE2",
"HH",
"HH2",
)
accept_deuteriums = (
"D",
"D1",
"D2",
"D3",
"DA",
"DA2",
"DA3",
"DB",
"DB1",
"DB2",
"DB3",
"DG2",
"DG3",
"DD2",
"DD3",
"DE2",
"DE3",
"DZ1",
"DZ2",
"DZ3",
"DG11",
"DG12",
"DG13",
"DG21",
"DG22",
"DG23",
"DZ",
"DD1",
"DE1",
"DD11",
"DD12",
"DD13",
"DG",
"DG1",
"DD21",
"DD22",
"DD23",
"ND1",
"ND2",
"DE",
"DH11",
"DH12",
"DH21",
"DH22",
"DE21",
"DE22",
"DE2",
"DH",
"DH2",
)
accept_atoms = accept_mainchain + accept_hydrogens
"""Change accept_atoms to restrict atoms processed. See :class:`IC_Residue`
for usage."""
def __init__(self, parent: "Residue") -> None:
"""Initialize IC_Residue with parent Biopython Residue.
:param Residue parent: Biopython Residue object.
The Biopython Residue this object extends
"""
self.residue = parent
self.cic: IC_Chain
# dict of hedron objects indexed by hedron keys
self.hedra: Dict[HKT, Hedron] = {}
# dict of dihedron objects indexed by dihedron keys
self.dihedra: Dict[DKT, Dihedron] = {}
# cache of AtomKey results for rak()
self.akc: Dict[Union[str, Atom], AtomKey] = {}
# set of AtomKeys involved in dihedra, used by split_akl,
# build_rak_cache. Built by __init__ for XYZ (PDB coord) input,
# _link_dihedra for PIC input
self.ak_set: Set[AtomKey] = set()
# reference to adjacent residues in chain
self.rprev: List[IC_Residue] = []
self.rnext: List[IC_Residue] = []
# bfactors copied from PDB file
self.bfactors: Dict[str, float] = {}
self.alt_ids: Union[List[str], None] = None if IC_Residue.no_altloc else []
self.is20AA = True
self.isAccept = True
# self.NCaCKey Set by _link_dihedra()
# rbase = position, insert code or none, resname (1 letter if in 20)
rid = parent.id
rbase = [rid[1], rid[2] if " " != rid[2] else None, parent.resname]
try:
rbase[2] = protein_letters_3to1[rbase[2]]
except KeyError:
self.is20AA = False
if rbase[2] not in self.accept_resnames:
self.isAccept = False
self.rbase = tuple(rbase)
self.lc = rbase[2]
if self.isAccept:
for atom in parent.get_atoms():
if hasattr(atom, "child_dict"):
if IC_Residue.no_altloc:
self._add_atom(atom.selected_child)
else:
for atm in atom.child_dict.values():
self._add_atom(atm)
else:
self._add_atom(atom)
if self.ak_set:
# only for coordinate (pdb) input, _add_atom loads
# init cache ready for atom_to_internal_coords
self._build_rak_cache()
def __deepcopy__(self, memo):
"""Deep copy implementation for IC_Residue."""
existing = memo.get(id(self), False)
if existing:
return existing
dup = type(self).__new__(self.__class__)
memo[id(self)] = dup
dup.__dict__.update(self.__dict__) # later replace what is not static
dup.cic = memo[id(self.cic)]
dup.residue = memo[id(self.residue)]
# still need to update: rnext, rprev, akc, ak_set, di/hedra
return dup
def __contains__(self, ak: "AtomKey") -> bool:
"""Return True if atomkey is in this residue."""
if ak in self.ak_set:
akl = ak.akl
if (
int(akl[0]) == self.rbase[0]
and akl[1] == self.rbase[1]
and akl[2] == self.rbase[2]
):
return True
return False
def rak(self, atm: Union[str, Atom]) -> "AtomKey":
"""Cache calls to AtomKey for this residue."""
try:
ak = self.akc[atm]
except (KeyError):
ak = self.akc[atm] = AtomKey(self, atm)
if isinstance(atm, str):
ak.missing = True
return ak
def _build_rak_cache(self) -> None:
"""Create explicit entries for for atoms so don't miss altlocs.
This ensures that self.akc (atom key cache) has an entry for selected
atom name (e.g. "CA") amongst any that have altlocs. Without this,
rak() on the other altloc atom first may result in the main atom being
missed.
"""
for ak in sorted(self.ak_set):
atmName = ak.akl[3]
if self.akc.get(atmName) is None:
self.akc[atmName] = ak
def _add_atom(self, atm: Atom) -> None:
"""Filter Biopython Atom with accept_atoms; set ak_set.
Arbitrarily renames O' and O'' to O and OXT
"""
if "O" == atm.name[0]:
if "O'" == atm.name:
atm.name = "O"
elif "O''" == atm.name:
atm.name = "OXT"
if atm.name not in self.accept_atoms:
# print('skip:', atm.name)
return
ak = self.rak(atm) # passing Atom here not string
self.ak_set.add(ak)
def __repr__(self) -> str:
"""Print string is parent Residue ID."""
return str(self.residue.full_id)
def pretty_str(self) -> str:
"""Nice string for residue ID."""
id = self.residue.id
return f"{self.residue.resname} {id[0]}{str(id[1])}{id[2]}"
def _link_dihedra(self, verbose: bool = False) -> None:
"""Housekeeping after loading all residues and dihedra.
- Link dihedra to this residue
- form id3_dh_index
- form ak_set
- set NCaCKey to be available AtomKeys
called for loading PDB / atom coords
"""
for dh in self.dihedra.values():
dh.ric = self # each dihedron can find its IC_Residue
dh.cic = self.cic # each dihedron can update chain dihedral angles
self.ak_set.update(dh.atomkeys)
for h in self.hedra.values(): # collect any atoms in orphan hedra
self.ak_set.update(h.atomkeys) # e.g. alternate CB path with no O
h.cic = self.cic # each hedron can update chain hedra
# if loaded PIC data, akc not initialised yet
if not self.akc:
self._build_rak_cache()
# initialise NCaCKey here:
self.NCaCKey = []
self.NCaCKey.extend(
self.split_akl(
(AtomKey(self, "N"), AtomKey(self, "CA"), AtomKey(self, "C"))
)
)
def set_flexible(self) -> None:
"""For OpenSCAD, mark N-CA and CA-C bonds to be flexible joints.
See :func:`.SCADIO.write_SCAD`
"""
for h in self.hedra.values():
if h.e_class == "NCAC":
h.flex_female_1 = True
h.flex_female_2 = True
elif h.e_class.endswith("NCA"):
h.flex_male_2 = True
elif h.e_class.startswith("CAC") and h.atomkeys[1].akl[3] == "C":
h.flex_male_1 = True
elif h.e_class == "CBCAC":
h.skinny_1 = True # CA-CB bond interferes with flex join
def set_hbond(self) -> None:
"""For OpenSCAD, mark H-N and C-O bonds to be hbonds (magnets).
See :func:`.SCADIO.write_SCAD`
"""
for h in self.hedra.values():
if h.e_class == "HNCA":
h.hbond_1 = True
elif h.e_class == "CACO":
h.hbond_2 = True
def _default_startpos(self) -> Dict["AtomKey", np.array]:
"""Generate default N-Ca-C coordinates to build this residue from."""
atomCoords = {}
cic = self.cic
dlist0 = [cic.id3_dh_index.get(akl, None) for akl in sorted(self.NCaCKey)]
dlist1 = [d for d in dlist0 if d is not None]
# https://stackoverflow.com/questions/11264684/flatten-list-of-lists
dlist = [cic.dihedra[val] for sublist in dlist1 for val in sublist]
# dlist = self.id3_dh_index[NCaCKey]
for d in dlist:
for i, a in enumerate(d.atomkeys):
# atomCoords[a] = d.initial_coords[i]
atomCoords[a] = cic.dAtoms[d.ndx][i]
# cic.atomArray[cic.atomArrayIndex[a]] = atomCoords[a]
# cic.atomArrayValid[cic.atomArrayIndex[a]] = True
return atomCoords
def _get_startpos(self) -> Dict["AtomKey", np.array]:
"""Find N-Ca-C coordinates to build this residue from."""
# only used by assemble()
startPos = {}
cic = self.cic
for ncac in self.NCaCKey:
if np.all(cic.atomArrayValid[[cic.atomArrayIndex[ak] for ak in ncac]]):
for ak in ncac:
startPos[ak] = cic.atomArray[cic.atomArrayIndex[ak]]
if startPos == {}:
startPos = self._default_startpos()
return startPos
def clear_transforms(self):
"""Invalidate dihedra coordinate space attributes before assemble().
Coordinate space attributes are Dihedron.cst and .rcst, and
:data:`IC_Chain.dCoordSpace`
"""
for d in self.dihedra.values():
self.cic.dcsValid[d.ndx] = False
def assemble(
self,
resetLocation: bool = False,
verbose: bool = False,
) -> Union[Dict["AtomKey", np.array], Dict[HKT, np.array], None]:
"""Compute atom coordinates for this residue from internal coordinates.
This is the IC_Residue part of the :meth:`.assemble_residues_ser` serial
version, see :meth:`.assemble_residues` for numpy vectorized approach
which works at the :class:`IC_Chain` level.
Join prepared dihedra starting from N-CA-C and N-CA-CB hedrons,
computing protein space coordinates for backbone and sidechain atoms
Sets forward and reverse transforms on each Dihedron to convert from
protein coordinates to dihedron space coordinates for first three
atoms (see :data:`IC_Chain.dCoordSpace`)
Call :meth:`.init_atom_coords` to update any modified di/hedra before
coming here, this only assembles dihedra into protein coordinate space.
**Algorithm**
Form double-ended queue, start with c-ca-n, o-c-ca, n-ca-cb, n-ca-c.
if resetLocation=True, use initial coords from generating dihedron
for n-ca-c initial positions (result in dihedron coordinate space)
while queue not empty
get 3-atom hedron key
for each dihedron starting with hedron key (1st hedron of dihedron)
if have coordinates for all 4 atoms already
add 2nd hedron key to back of queue
else if have coordinates for 1st 3 atoms
compute forward and reverse transforms to take 1st 3 atoms
to/from dihedron initial coordinate space
use reverse transform to get position of 4th atom in
current coordinates from dihedron initial coordinates
add 2nd hedron key to back of queue
else
ordering failed, put hedron key at back of queue and hope
next time we have 1st 3 atom positions (should not happen)
loop terminates (queue drains) as hedron keys which do not start any
dihedra are removed without action
:param bool resetLocation: default False.
- Option to ignore start location and orient so initial N-Ca-C
hedron at origin.
:returns:
Dict of AtomKey -> homogeneous atom coords for residue in protein
space relative to previous residue
**Also** directly updates :data:`IC_Chain.atomArray` as
:meth:`.assemble_residues` does.
"""
# debug statements below still useful, commented for performance
# dbg = False
# if hasattr(IC_Chain, "adbg"):
# dbg = IC_Chain.adbg
cic = self.cic
dcsValid = cic.dcsValid
aaValid = cic.atomArrayValid
aaNdx = cic.atomArrayIndex
aa = cic.atomArray
if not self.ak_set:
return None # give up now if no atoms to work with
NCaCKey = sorted(self.NCaCKey)
rseqpos = self.rbase[0]
# order of these startLst entries matters
startLst = self.split_akl((self.rak("C"), self.rak("CA"), self.rak("N")))
if "CB" in self.akc:
startLst.extend(
self.split_akl((self.rak("N"), self.rak("CA"), self.rak("CB")))
)
if "O" in self.akc:
startLst.extend(
self.split_akl((self.rak("O"), self.rak("C"), self.rak("CA")))
)
startLst.extend(NCaCKey)
q = deque(startLst)
# resnum = self.rbase[0]
# get initial coords from previous residue or IC_Chain info
# or default coords
if resetLocation:
# use N-CA-C initial coords from creating dihedral
atomCoords = self._default_startpos()
else:
atomCoords = self._get_startpos()
while q: # deque is not empty
"""
if dbg:
print("assemble loop start q=", q)
"""
h1k = cast(HKT, q.pop())
dihedraKeys = cic.id3_dh_index.get(h1k, None)
"""
if dbg:
print(
" h1k:",
h1k,
"len dihedra: ",
len(dihedraKeys) if dihedraKeys is not None else "None",
)
"""
if dihedraKeys is not None:
for dk in dihedraKeys:
d = cic.dihedra[dk]
dseqpos = int(d.atomkeys[0].akl[AtomKey.fields.respos])
d.initial_coords = cic.dAtoms[d.ndx]
if 4 == len(d.initial_coords) and d.initial_coords[3] is not None:
# skip incomplete dihedron if don't have 4th atom due
# to missing input data
d_h2key = d.hedron2.atomkeys
ak = d.atomkeys[3]
"""
if dbg:
print(" process", d, d_h2key, d.atomkeys)
"""
acount = len([a for a in d.atomkeys if a in atomCoords])
if 4 == acount:
# dihedron already done, queue 2nd hedron key
if dseqpos == rseqpos: # only this residue
q.appendleft(d_h2key)
"""
if dbg:
print(" 4- already done, append left")
"""
if not dcsValid[d.ndx]: # missing transform
# can happen for altloc atoms
# only needed for write_SCAD output
acs = [atomCoords[a] for a in h1k]
d.cst, d.rcst = coord_space(
acs[0], acs[1], acs[2], True
)
dcsValid[d.ndx] = True
elif 3 == acount:
"""
if dbg:
print(" 3- call coord_space")
"""
acs = np.asarray([atomCoords[a] for a in h1k])
d.cst, d.rcst = coord_space(acs[0], acs[1], acs[2], True)
dcsValid[d.ndx] = True
"""
if dbg:
print(" acs:", acs.transpose())
print("cst", d.cst)
print("rcst", d.rcst)
print(
" initial_coords[3]=",
d.initial_coords[3].transpose(),
)
"""
acak3 = d.rcst.dot(d.initial_coords[3])
"""
if dbg:
print(" acak3=", acak3.transpose())
"""
atomCoords[ak] = acak3
aa[aaNdx[ak]] = acak3
aaValid[aaNdx[ak]] = True
"""
if dbg:
print(
" 3- finished, ak:",
ak,
"coords:",
atomCoords[ak].transpose(),
)
"""
if dseqpos == rseqpos: # only this residue
q.appendleft(d_h2key)
else:
if verbose:
print("no coords to start", d)
print(
[
a
for a in d.atomkeys
if atomCoords.get(a, None) is not None
]
)
else:
if verbose:
print("no initial coords for", d)
return atomCoords
def split_akl(
self,
lst: Union[Tuple["AtomKey", ...], List["AtomKey"]],
missingOK: bool = False,
) -> List[Tuple["AtomKey", ...]]:
"""Get AtomKeys for this residue (ak_set) for generic list of AtomKeys.
Changes and/or expands a list of 'generic' AtomKeys (e.g. 'N, C, C') to
be specific to this Residue's altlocs etc., e.g.
'(N-Ca_A_0.3-C, N-Ca_B_0.7-C)'
Given a list of AtomKeys for a Hedron or Dihedron,
return:
list of matching atomkeys that have id3_dh in this residue
(ak may change if occupancy != 1.00)
or
multiple lists of matching atomkeys expanded for all atom altlocs
or
empty list if any of atom_coord(ak) missing and not missingOK
:param list lst: list[3] or [4] of AtomKeys.
Non-altloc AtomKeys to match to specific AtomKeys for this residue
:param bool missingOK: default False, see above.
"""
altloc_ndx = AtomKey.fields.altloc
occ_ndx = AtomKey.fields.occ
# step 1
# given a list of AtomKeys
# form a new list of same atomkeys with coords or diheds in this residue
# plus lists of matching altloc atomkeys in coords or diheds
edraLst: List[Tuple[AtomKey, ...]] = []
altlocs = set()
posnAltlocs: Dict["AtomKey", Set[str]] = {}
akMap = {}
for ak in lst:
posnAltlocs[ak] = set()
if (
ak in self.ak_set
and ak.akl[altloc_ndx] is None
and ak.akl[occ_ndx] is None
):
# simple case no altloc and exact match in set
edraLst.append((ak,)) # tuple of ak
else:
ak2_lst = []
for ak2 in self.ak_set:
if ak.altloc_match(ak2):
# print(key)
ak2_lst.append(ak2)
akMap[ak2] = ak
altloc = ak2.akl[altloc_ndx]
if altloc is not None:
altlocs.add(altloc)
posnAltlocs[ak].add(altloc)
edraLst.append(tuple(ak2_lst))
# step 2
# check and finish for
# missing atoms
# simple case no altlocs
# else form new AtomKey lists covering all altloc permutations
maxc = 0
for akl in edraLst:
lenAKL = len(akl)
if 0 == lenAKL and not missingOK:
return [] # atom missing in atom_coords, cannot form object
elif maxc < lenAKL:
maxc = lenAKL
if 1 == maxc: # simple case no altlocs for any ak in list
newAKL = []
for akl in edraLst:
if akl: # may have empty lists if missingOK, do not append
newAKL.append(akl[0])
return [tuple(newAKL)]
else:
new_edraLst = []
for al in altlocs:
# form complete new list for each altloc
alhl = []
for akl in edraLst:
lenAKL = len(akl)
if 0 == lenAKL:
continue # ignore empty list from missingOK
if 1 == lenAKL:
alhl.append(akl[0]) # not all atoms will have altloc
# elif (lenAKL < maxc
# and al not in posnAltlocs[akMap[akl[0]]]):
elif al not in posnAltlocs[akMap[akl[0]]]:
# this position has fewer altlocs than other positions
# and this position does not have this al,
# so just grab first to form angle as could be any
alhl.append(sorted(akl)[0])
else:
for ak in akl:
if ak.akl[altloc_ndx] == al:
alhl.append(ak)
new_edraLst.append(tuple(alhl))
# print(new_edraLst)
return new_edraLst
def _gen_edra(self, lst: Union[Tuple["AtomKey", ...], List["AtomKey"]]) -> None:
"""Populate hedra/dihedra given edron ID tuple.
Given list of AtomKeys defining hedron or dihedron
convert to AtomKeys with coordinates in this residue
add appropriately to self.di/hedra, expand as needed atom altlocs
:param list lst: tuple of AtomKeys.
Specifies Hedron or Dihedron
"""
for ak in lst:
if ak.missing:
return # give up if atoms actually missing
lenLst = len(lst)
if 4 > lenLst:
cdct, dct, obj = self.cic.hedra, self.hedra, Hedron
else:
cdct, dct, obj = self.cic.dihedra, self.dihedra, Dihedron # type: ignore # noqa
if isinstance(lst, List):
tlst = tuple(lst)
else:
tlst = lst
hl = self.split_akl(tlst) # expand tlst with any altlocs
# returns list of tuples
for tnlst in hl:
# do not add edron if split_akl() made something shorter
if len(tnlst) == lenLst:
# if edron already exists, then update not replace with new
if tnlst not in cdct:
cdct[tnlst] = obj(tnlst) # type: ignore
if tnlst not in dct:
dct[tnlst] = cdct[tnlst] # type: ignore
dct[tnlst].needs_update = True # type: ignore
# @profile
def _create_edra(self, verbose: bool = False) -> None:
"""Create IC_Chain and IC_Residue di/hedra for atom coordinates.
AllBonds handled here.
:param bool verbose: default False.
Warn about missing N, Ca, C backbone atoms.
"""
# on entry we have all Biopython Atoms loaded
if not self.ak_set:
return # so give up if no atoms loaded for this residue
sN, sCA, sC = self.rak("N"), self.rak("CA"), self.rak("C")
if self.lc != "G":
sCB = self.rak("CB")
# first init di/hedra, AtomKey objects and atom_coords for di/hedra
# which extend into next residue.
if 0 < len(self.rnext) and self.rnext[0].ak_set:
# atom_coords, hedra and dihedra for backbone dihedra
# which reach into next residue
for rn in self.rnext:
nN, nCA, nC = rn.rak("N"), rn.rak("CA"), rn.rak("C")
nextNCaC = rn.split_akl((nN, nCA, nC), missingOK=True)
for tpl in nextNCaC:
for ak in tpl:
if ak in rn.ak_set:
self.ak_set.add(ak)
else:
for rn_ak in rn.ak_set:
if rn_ak.altloc_match(ak):
self.ak_set.add(rn_ak)
self._gen_edra((sN, sCA, sC, nN)) # psi
self._gen_edra((sCA, sC, nN, nCA)) # omega i+1
self._gen_edra((sC, nN, nCA, nC)) # phi i+1
self._gen_edra((sCA, sC, nN))
self._gen_edra((sC, nN, nCA))
self._gen_edra((nN, nCA, nC)) # tau i+1
# redundant next residue C-beta locator (alternate CB path)
# otherwise missing O will cause no sidechain
try:
nO = rn.akc["O"] # noqa: F841
except KeyError:
# not rn.rak here so don't trigger missing CB for Gly
nCB = rn.akc.get("CB", None)
if nCB is not None and nCB in rn.ak_set:
self.ak_set.add(nCB)
self._gen_edra((nN, nCA, nCB))
self._gen_edra((sC, nN, nCA, nCB))
# if start of chain then need to init NCaC hedron as not in previous
# residue
if 0 == len(self.rprev):
self._gen_edra((sN, sCA, sC))
# now init di/hedra for standard backbone atoms independent of
# neighbours
backbone = ic_data_backbone
for edra in backbone:
# only need to build if this residue has all the atoms in the edra
if all(atm in self.akc for atm in edra):
r_edra = [self.rak(atom) for atom in edra]
self._gen_edra(r_edra) # [4] is label on some table entries
# next init sidechain di/hedra
if self.lc is not None:
sidechain = ic_data_sidechains.get(self.lc, [])
for edraLong in sidechain:
edra = edraLong[0:4] # [4] is label on some sidechain table entries
# lots of H di/hedra can be avoided if don't have those atoms
if all(atm in self.akc for atm in edra):
r_edra = [self.rak(atom) for atom in edra]
self._gen_edra(r_edra)
if (
IC_Residue._AllBonds
): # openscad output needs all bond cylinders explicit
sidechain = ic_data_sidechain_extras.get(self.lc, [])
for edra in sidechain:
# test less useful here but avoids populating rak cache if
# possible
if all(atm in self.akc for atm in edra):
r_edra = [self.rak(atom) for atom in edra]
self._gen_edra(r_edra)
# create di/hedra for gly Cbeta if needed, populate values later
if self.gly_Cbeta and "G" == self.lc:
# add C-beta for Gly
self.ak_set.add(AtomKey(self, "CB"))
sCB = self.rak("CB")
sCB.missing = False # was True because akc cache did not have entry
self.cic.akset.add(sCB)
# main orientation comes from O-C-Ca-Cb so make Cb-Ca-C hedron
sO = self.rak("O")
htpl = (sCB, sCA, sC)
self._gen_edra(htpl)
# generate dihedral based on N-Ca-C-O offset from db query above
dtpl = (sO, sC, sCA, sCB)
self._gen_edra(dtpl)
d = self.dihedra[dtpl]
d.ric = self
d._set_hedra()
# prepare to add new Gly CB atom(s)
# in IC_Chain.atom_to_internal_coordinates()
if not hasattr(self.cic, "gcb"):
self.cic.gcb = {}
self.cic.gcb[sCB] = dtpl
# final processing of all dihedra just generated
self._link_dihedra(verbose) # re-run for new dihedra
if verbose:
# oAtom =
self.rak("O") # trigger missing flag if needed
missing = []
for akk, akv in self.akc.items():
if isinstance(akk, str) and akv.missing:
missing.append(akv)
if missing:
chn = self.residue.parent
chn_id = chn.id
chn_len = len(chn.internal_coord.ordered_aa_ic_list)
print(f"chain {chn_id} len {chn_len} missing atom(s): {missing}")
# rtm
atom_sernum = None
atom_chain = None
@staticmethod
def _pdb_atom_string(atm: Atom, cif_extend: bool = False) -> str:
"""Generate PDB ATOM record.
:param Atom atm: Biopython Atom object reference
:param IC_Residue.atom_sernum: Class variable default None.
override atom serial number if not None
:param IC_Residue.atom_chain: Class variable default None.
override atom chain id if not None
"""
if 2 == atm.is_disordered():
if IC_Residue.no_altloc:
return IC_Residue._pdb_atom_string(atm.selected_child, cif_extend)
s = ""
for a in atm.child_dict.values():
s += IC_Residue._pdb_atom_string(a, cif_extend)
return s
else:
res = atm.parent
chn = res.parent
fmt = "{:6}{:5d} {:4}{:1}{:3} {:1}{:4}{:1} {:8.3f}{:8.3f}{:8.3f}{:6.2f}{:6.2f} {:>4}\n"
if cif_extend:
fmt = "{:6}{:5d} {:4}{:1}{:3} {:1}{:4}{:1} {:10.5f}{:10.5f}{:10.5f}{:7.3f}{:6.2f} {:>4}\n"
s = (fmt).format(
"ATOM",
IC_Residue.atom_sernum
if IC_Residue.atom_sernum is not None
else atm.serial_number,
atm.fullname,
atm.altloc,
res.resname,
IC_Residue.atom_chain if IC_Residue.atom_chain is not None else chn.id,
res.id[1],
res.id[2],
atm.coord[0],
atm.coord[1],
atm.coord[2],
atm.occupancy,
atm.bfactor,
atm.element,
)
# print(s)
return s
# rtm
def pdb_residue_string(self) -> str:
"""Generate PDB ATOM records for this residue as string.
Convenience method for functionality not exposed in PDBIO.py.
Increments :data:`IC_Residue.atom_sernum` if not None
:param IC_Residue.atom_sernum: Class variable default None.
Override and increment atom serial number if not None
:param IC_Residue.atom_chain: Class variable.
Override atom chain id if not None
.. todo::
move to PDBIO
"""
str = ""
atomArrayIndex = self.cic.atomArrayIndex
bpAtomArray = self.cic.bpAtomArray
respos = self.rbase[0]
resposNdx = AtomKey.fields.respos
for ak in sorted(self.ak_set):
if int(ak.akl[resposNdx]) == respos: # skip rnext atoms
str += IC_Residue._pdb_atom_string(bpAtomArray[atomArrayIndex[ak]])
if IC_Residue.atom_sernum is not None:
IC_Residue.atom_sernum += 1
return str
@staticmethod
def _residue_string(res: "Residue") -> str:
"""Generate PIC Residue string.
Enough to create Biopython Residue object without actual Atoms.
:param Residue res: Biopython Residue object reference
"""
segid = res.get_segid()
if segid.isspace() or "" == segid:
segid = ""
else:
segid = " [" + segid + "]"
return str(res.get_full_id()) + " " + res.resname + segid + "\n"
_pfDef = namedtuple(
# general supersedes specific, so pomg + omg = omg, tau + hedra = hedra
"_pfDef",
[
"psi", # _b[0]
"omg",
"phi",
"tau", # tau hedron (N-Ca-C)
"chi1",
"chi2",
"chi3",
"chi4",
"chi5",
"pomg", # _b[9] : proline omega
"chi", # chi1 | ... | chi5
"classic_b", # psi | phi | tau | pomg
"classic", # classic_b | chi
"hedra", # _b[10] : all hedra
"primary", # _b[11] : all primary dihedra
"secondary", # _b[12] : all secondary dihedra
"all", # hedra | primary | secondary
"initAtoms", # _b[13] : XYZ coordinates of initial Tau (N-Ca-C)
"bFactors", # _b[14]
],
)
_b = [1 << i for i in range(16)]
_bChi = _b[4] | _b[5] | _b[6] | _b[7] | _b[8]
_bClassB = _b[0] | _b[2] | _b[3] | _b[9]
_bClass = _bClassB | _bChi
_bAll = _b[10] | _b[11] | _b[12]
pic_flags = _pfDef(
_b[0],
_b[1],
_b[2],
_b[3],
_b[4],
_b[5],
_b[6],
_b[7],
_b[8],
_b[9],
_bChi,
_bClassB,
_bClass,
_b[10],
_b[11],
_b[12],
_bAll,
_b[13],
_b[14],
)
"""Used by :func:`.PICIO.write_PIC` to control classes of values to be defaulted."""
picFlagsDefault = pic_flags.all | pic_flags.initAtoms | pic_flags.bFactors
"""Default is all dihedra + initial tau atoms + bFactors."""
picFlagsDict = pic_flags._asdict()
"""Dictionary of pic_flags values to use as needed."""
def _write_pic_bfac(self, atm: Atom, s: str, col: int) -> Tuple[str, int]:
ak = self.rak(atm)
if 0 == col % 5:
s += "BFAC:"
s += " " + ak.id + " " + f"{atm.get_bfactor():6.2f}"
col += 1
if 0 == col % 5:
s += "\n"
return s, col
def _write_PIC(
self,
pdbid: str = "0PDB",
chainid: str = "A",
picFlags: int = picFlagsDefault,
hCut: Optional[Union[float, None]] = None,
pCut: Optional[Union[float, None]] = None,
) -> str:
"""Write PIC format lines for this residue.
See :func:`.PICIO.write_PIC`.
:param str pdbid: PDB idcode string; default 0PDB
:param str chainid: PDB Chain ID character; default A
:param int picFlags: control details written to PIC file; see
:meth:`.PICIO.write_PIC`
:param float hCut: only write hedra with ref db angle std dev > this
value; default None
:param float pCut: only write primary dihedra with ref db angle
std dev > this value; default None
"""
pAcc = IC_Residue.pic_accuracy
if pdbid is None:
pdbid = "0PDB"
if chainid is None:
chainid = "A"
icr = IC_Residue
s = icr._residue_string(self.residue)
if (
picFlags & icr.pic_flags.initAtoms
and 0 == len(self.rprev) # no prev residue
and hasattr(self, "NCaCKey")
and self.NCaCKey is not None # have valid NCacKey
# N coords valid (e.g. not all 0.00)
and not (np.all(self.residue["N"].coord == self.residue["N"].coord[0]))
):
NCaChedron = self.pick_angle(self.NCaCKey[0]) # first tau
if NCaChedron is not None:
try:
ts = IC_Residue._pdb_atom_string(self.residue["N"], cif_extend=True)
ts += IC_Residue._pdb_atom_string(
self.residue["CA"], cif_extend=True
)
ts += IC_Residue._pdb_atom_string(
self.residue["C"], cif_extend=True
)
s += ts # only if no exception: have all 3 atoms
except KeyError:
pass
base = pdbid + " " + chainid + " "
cic = self.cic
if picFlags & icr.pic_flags.hedra or picFlags & icr.pic_flags.tau:
for h in sorted(self.hedra.values()):
if (
not picFlags & icr.pic_flags.hedra # not all hedra
and picFlags & icr.pic_flags.tau # but yes tau hedron
and h.e_class != "NCAC" # and is not tau
):
continue
if hCut is not None:
hc = h.xrh_class if hasattr(h, "xrh_class") else h.e_class
if hc in hedra_defaults and hedra_defaults[hc][1] <= hCut:
continue
hndx = h.ndx
try:
s += (
base
+ h.id
+ " "
+ f"{cic.hedraL12[hndx]:{pAcc}} {cic.hedraAngle[hndx]:{pAcc}} {cic.hedraL23[hndx]:{pAcc}}"
+ "\n"
)
except KeyError:
pass
for d in sorted(self.dihedra.values()):
if d.primary:
if not picFlags & icr.pic_flags.primary:
# primary and not primary flag so keep checking filters
# db = d.bits()
if not picFlags & d.bits():
continue
elif not picFlags & icr.pic_flags.secondary:
continue # secondary and flag not set -> skip
if pCut is not None:
if (
d.primary
and d.pclass in dihedra_primary_defaults
and dihedra_primary_defaults[d.pclass][1] <= pCut
):
continue
try:
s += base + d.id + " " + f"{cic.dihedraAngle[d.ndx]:{pAcc}}" + "\n"
except KeyError:
pass
if picFlags & icr.pic_flags.bFactors:
col = 0
for a in sorted(self.residue.get_atoms()):
if 2 == a.is_disordered():
if IC_Residue.no_altloc or self.alt_ids is None:
s, col = self._write_pic_bfac(a.selected_child, s, col)
else:
for atm in a.child_dict.values():
s, col = self._write_pic_bfac(atm, s, col)
else:
s, col = self._write_pic_bfac(a, s, col)
if 0 != col % 5:
s += "\n"
return s
def _get_ak_tuple(self, ak_str: str) -> Optional[Tuple["AtomKey", ...]]:
"""Convert atom pair string to AtomKey tuple.
:param str ak_str:
Two atom names separated by ':', e.g. 'N:CA'
Optional position specifier relative to self,
e.g. '-1C:N' for preceding peptide bond.
"""
AK = AtomKey
S = self
angle_key2 = []
akstr_list = ak_str.split(":")
lenInput = len(akstr_list)
for a in akstr_list:
m = self._relative_atom_re.match(a)
if m:
if m.group(1) == "-1":
if 0 < len(S.rprev):
angle_key2.append(AK(S.rprev[0], m.group(2)))
elif m.group(1) == "1":
if 0 < len(S.rnext):
angle_key2.append(AK(S.rnext[0], m.group(2)))
elif m.group(1) == "0":
angle_key2.append(self.rak(m.group(2)))
else:
angle_key2.append(self.rak(a))
if len(angle_key2) != lenInput:
return None
return tuple(angle_key2)
_relative_atom_re = re.compile(r"^(-?[10])([A-Z]+)$")
def _get_angle_for_tuple(
self, angle_key: EKT
) -> Optional[Union["Hedron", "Dihedron"]]:
len_mkey = len(angle_key)
rval: Optional[Union["Hedron", "Dihedron"]]
if 4 == len_mkey:
rval = self.dihedra.get(cast(DKT, angle_key), None)
elif 3 == len_mkey:
rval = self.hedra.get(cast(HKT, angle_key), None)
else:
return None
return rval
# @profile
def pick_angle(
self, angle_key: Union[EKT, str]
) -> Optional[Union["Hedron", "Dihedron"]]:
"""Get Hedron or Dihedron for angle_key.
:param angle_key:
- tuple of 3 or 4 AtomKeys
- string of atom names ('CA') separated by :'s
- string of [-1, 0, 1]<atom name> separated by ':'s. -1 is
previous residue, 0 is this residue, 1 is next residue
- psi, phi, omg, omega, chi1, chi2, chi3, chi4, chi5
- tau (N-CA-C angle) see Richardson1981
- tuples of AtomKeys is only access for alternate disordered atoms
Observe that a residue's phi and omega dihedrals, as well as the hedra
comprising them (including the N:Ca:C `tau` hedron), are stored in the
n-1 di/hedra sets; this overlap is handled here, but may be an issue if
accessing directly.
The following print commands are equivalent (except for sidechains with
non-carbon atoms for chi2)::
ric = r.internal_coord
print(
r,
ric.get_angle("psi"),
ric.get_angle("phi"),
ric.get_angle("omg"),
ric.get_angle("tau"),
ric.get_angle("chi2"),
)
print(
r,
ric.get_angle("N:CA:C:1N"),
ric.get_angle("-1C:N:CA:C"),
ric.get_angle("-1CA:-1C:N:CA"),
ric.get_angle("N:CA:C"),
ric.get_angle("CA:CB:CG:CD"),
)
See ic_data.py for detail of atoms in the enumerated sidechain angles
and the backbone angles which do not span the peptide bond. Using 's'
for current residue ('self') and 'n' for next residue, the spanning
(overlapping) angles are::
(sN, sCA, sC, nN) # psi
(sCA, sC, nN, nCA) # omega i+1
(sC, nN, nCA, nC) # phi i+1
(sCA, sC, nN)
(sC, nN, nCA)
(nN, nCA, nC) # tau i+1
:return: Matching Hedron, Dihedron, or None.
"""
rval: Optional[Union["Hedron", "Dihedron"]] = None
if isinstance(angle_key, tuple):
rval = self._get_angle_for_tuple(angle_key)
if rval is None and self.rprev:
rval = self.rprev[0]._get_angle_for_tuple(angle_key)
elif ":" in angle_key:
angle_key = cast(EKT, self._get_ak_tuple(cast(str, angle_key)))
if angle_key is None:
return None
rval = self._get_angle_for_tuple(angle_key)
if rval is None and self.rprev:
rval = self.rprev[0]._get_angle_for_tuple(angle_key)
elif "psi" == angle_key:
if 0 == len(self.rnext):
return None
rn = self.rnext[0]
sN, sCA, sC = self.rak("N"), self.rak("CA"), self.rak("C")
nN = rn.rak("N")
rval = self.dihedra.get((sN, sCA, sC, nN), None)
elif "phi" == angle_key:
if 0 == len(self.rprev):
return None
rp = self.rprev[0]
pC, sN, sCA = rp.rak("C"), self.rak("N"), self.rak("CA")
sC = self.rak("C")
rval = rp.dihedra.get((pC, sN, sCA, sC), None)
elif "omg" == angle_key or "omega" == angle_key:
if 0 == len(self.rprev):
return None
rp = self.rprev[0]
pCA, pC, sN = rp.rak("CA"), rp.rak("C"), self.rak("N")
sCA = self.rak("CA")
rval = rp.dihedra.get((pCA, pC, sN, sCA), None)
elif "tau" == angle_key:
sN, sCA, sC = self.rak("N"), self.rak("CA"), self.rak("C")
rval = self.hedra.get((sN, sCA, sC), None)
if rval is None and 0 != len(self.rprev):
rp = self.rprev[0] # tau in prev residue for all but first
rval = rp.hedra.get((sN, sCA, sC), None)
elif angle_key.startswith("chi"):
sclist = ic_data_sidechains.get(self.lc, None)
if sclist is None:
return None
ndx = (2 * int(angle_key[-1])) - 1
try:
akl = sclist[ndx]
if akl[4] == angle_key:
klst = [self.rak(a) for a in akl[0:4]]
tklst = cast(DKT, tuple(klst))
rval = self.dihedra.get(tklst, None)
else:
return None
except IndexError:
return None
return rval
def get_angle(self, angle_key: Union[EKT, str]) -> Optional[float]:
"""Get dihedron or hedron angle for specified key.
See :meth:`.pick_angle` for key specifications.
"""
edron = self.pick_angle(angle_key)
if edron:
return edron.angle
return None
def set_angle(self, angle_key: Union[EKT, str], v: float):
"""Set dihedron or hedron angle for specified key.
See :meth:`.pick_angle` for key specifications.
"""
edron = self.pick_angle(angle_key)
if edron is not None:
edron.angle = v
def _do_bond_rotate(self, base: "Dihedron", delta: float):
"""Find and modify related dihedra through id3_dh_index."""
try:
for dk in self.cic.id3_dh_index[base.id3]:
# change all diheds with same first hedron
dihed = self.dihedra[dk]
dihed.angle += delta # +/- 180 handled in setter
# for changed dihed, change any with reverse key 2nd hedron
# so change N-Ca-C-N will change O-Ca-C-Cb
try:
for d2rk in self.cic.id3_dh_index[dihed.id32[::-1]]:
self.dihedra[d2rk].angle += delta
except KeyError:
pass
except AttributeError:
raise RuntimeError("bond_rotate, bond_set only for dihedral angles")
def bond_rotate(self, angle_key: Union[EKT, str], delta: float):
"""Rotate set of overlapping dihedrals by delta degrees.
See :meth:`.pick_angle` for key specifications.
"""
base = self.pick_angle(angle_key)
self._do_bond_rotate(base, delta)
def bond_set(self, angle_key: Union[EKT, str], val: float):
"""Set dihedron to val, update overlapping dihedra by same amount.
See :meth:`.pick_angle` for key specifications.
"""
base = self.pick_angle(angle_key)
delta = Dihedron.angle_dif(base.angle, val)
self._do_bond_rotate(base, delta)
def pick_length(
self, ak_spec: Union[str, BKT]
) -> Tuple[Optional[List["Hedron"]], Optional[BKT]]:
"""Get list of hedra containing specified atom pair.
:param ak_spec:
- tuple of two AtomKeys
- string: two atom names separated by ':', e.g. 'N:CA' with
optional position specifier relative to self, e.g. '-1C:N' for
preceding peptide bond. Position specifiers are -1, 0, 1.
The following are equivalent::
ric = r.internal_coord
print(
r,
ric.get_length("0C:1N"),
)
print(
r,
None
if not ric.rnext
else ric.get_length((ric.rak("C"), ric.rnext[0].rak("N"))),
)
If atom not found on current residue then will look on rprev[0] to
handle cases like Gly N:CA. For finer control please access
`IC_Chain.hedra` directly.
:return: list of hedra containing specified atom pair as tuples of
AtomKeys
"""
rlst: List[Hedron] = []
# if ":" in ak_spec:
if isinstance(ak_spec, str):
ak_spec = cast(BKT, self._get_ak_tuple(ak_spec))
if ak_spec is None:
return None, None
for hed_key, hed_val in self.hedra.items():
if all(ak in hed_key for ak in ak_spec):
rlst.append(hed_val)
# handle bonds stored on rprev, e.g. set backbone, read gly N:CA
for rp in self.rprev:
for hed_key, hed_val in rp.hedra.items():
if all(ak in hed_key for ak in ak_spec):
rlst.append(hed_val)
return rlst, ak_spec
def get_length(self, ak_spec: Union[str, BKT]) -> Optional[float]:
"""Get bond length for specified atom pair.
See :meth:`.pick_length` for ak_spec and details.
"""
hed_lst, ak_spec2 = self.pick_length(ak_spec)
if hed_lst is None or ak_spec2 is None:
return None
for hed in hed_lst:
val = hed.get_length(ak_spec2)
if val is not None:
return val
return None
def set_length(self, ak_spec: Union[str, BKT], val: float) -> None:
"""Set bond length for specified atom pair.
See :meth:`.pick_length` for ak_spec.
"""
hed_lst, ak_spec2 = self.pick_length(ak_spec)
if hed_lst is not None and ak_spec2 is not None:
for hed in hed_lst:
hed.set_length(ak_spec2, val)
def applyMtx(self, mtx: np.array) -> None:
"""Apply matrix to atom_coords for this IC_Residue."""
aa = self.cic.atomArray
aai = self.cic.atomArrayIndex
rpndx = AtomKey.fields.respos
rp = str(self.rbase[0])
aselect = [aai.get(k) for k in aai.keys() if k.akl[rpndx] == rp]
aas = aa[aselect]
# numpy will broadcast the transform matrix over all points if dot()
# applied in this order
aa[aselect] = aas.dot(mtx.transpose())
"""
# slower way, one at a time
for ak in sorted(self.ak_set):
ndx = self.cic.atomArrayIndex[ak]
self.cic.atomArray[ndx] = mtx.dot(self.cic.atomArray[ndx])
"""
class Edron:
"""Base class for Hedron and Dihedron classes.
Supports rich comparison based on lists of AtomKeys.
Attributes
----------
atomkeys: tuple
3 (hedron) or 4 (dihedron) :class:`.AtomKey` s defining this di/hedron
id: str
':'-joined string of AtomKeys for this di/hedron
needs_update: bool
indicates di/hedron local atom_coords do NOT reflect current di/hedron
angle and length values in hedron local coordinate space
e_class: str
sequence of atoms (no position or residue) comprising di/hedron
for statistics
re_class: str
sequence of residue, atoms comprising di/hedron for statistics
cre_class: str
sequence of covalent radii classses comprising di/hedron for statistics
edron_re: compiled regex (Class Attribute)
A compiled regular expression matching string IDs for Hedron
and Dihedron objects
cic: IC_Chain reference
Chain internal coords object containing this hedron
ndx: int
index into IC_Chain level numpy data arrays for di/hedra.
Set in :meth:`IC_Chain.init_edra`
rc: int
number of residues involved in this edron
Methods
-------
gen_key([AtomKey, ...] or AtomKey, ...) (Static Method)
generate a ':'-joined string of AtomKey Ids
is_backbone()
Return True if all atomkeys atoms are N, Ca, C or O
"""
# regular expression to capture hedron and dihedron specifications, as in
# .pic files
edron_re = re.compile(
# pdbid and chain id
r"^(?P<pdbid>\w+)?\s(?P<chn>[\w|\s])?\s"
# 3 atom specifiers for hedron
r"(?P<a1>[\w\-\.]+):(?P<a2>[\w\-\.]+):(?P<a3>[\w\-\.]+)"
# 4th atom specifier for dihedron
r"(:(?P<a4>[\w\-\.]+))?"
r"\s+"
# len-angle-len for hedron
r"(((?P<len12>\S+)\s+(?P<angle>\S+)\s+(?P<len23>\S+)\s*$)|"
# dihedral angle for dihedron
r"((?P<dihedral>\S+)\s*$))"
)
""" A compiled regular expression matching string IDs for Hedron and
Dihedron objects"""
@staticmethod
def gen_key(lst: List["AtomKey"]) -> str:
"""Generate string of ':'-joined AtomKey strings from input.
Generate '2_A_C:3_P_N:3_P_CA' from (2_A_C, 3_P_N, 3_P_CA)
:param list lst: list of AtomKey objects
"""
if 4 == len(lst):
return f"{lst[0].id}:{lst[1].id}:{lst[2].id}:{lst[3].id}"
else:
return f"{lst[0].id}:{lst[1].id}:{lst[2].id}"
@staticmethod
def gen_tuple(akstr: str) -> Tuple:
"""Generate AtomKey tuple for ':'-joined AtomKey string.
Generate (2_A_C, 3_P_N, 3_P_CA) from '2_A_C:3_P_N:3_P_CA'
:param str akstr: string of ':'-separated AtomKey strings
"""
return tuple([AtomKey(i) for i in akstr.split(":")])
# @profile
def __init__(self, *args: Union[List["AtomKey"], EKT], **kwargs: str) -> None:
"""Initialize Edron with sequence of AtomKeys.
Acceptable input:
[ AtomKey, ... ] : list of AtomKeys
AtomKey, ... : sequence of AtomKeys as args
{'a1': str, 'a2': str, ... } : dict of AtomKeys as 'a1', 'a2' ...
"""
atomkeys: List[AtomKey] = []
for arg in args:
if isinstance(arg, list):
atomkeys = arg
elif isinstance(arg, tuple):
atomkeys = list(arg)
else:
if arg is not None:
atomkeys.append(arg)
if [] == atomkeys and all(k in kwargs for k in ("a1", "a2", "a3")):
atomkeys = [
AtomKey(kwargs["a1"]),
AtomKey(kwargs["a2"]),
AtomKey(kwargs["a3"]),
]
if "a4" in kwargs and kwargs["a4"] is not None:
atomkeys.append(AtomKey(kwargs["a4"]))
self.atomkeys = tuple(atomkeys)
self.id = Edron.gen_key(atomkeys)
self._hash = hash(self.atomkeys)
# flag indicating that atom coordinates are up to date
# (do not need to be recalculated from angle and or length values)
self.needs_update = True
# IC_Chain which contains this di/hedron
self.cic: IC_Chain # set in :meth:`IC_Residue._link_dihedra`
# no residue or position, just atoms
self.e_class = ""
# same but residue specific
self.re_class = ""
self.cre_class = ""
rset = set() # what residues this involves
atmNdx = AtomKey.fields.atm
resNdx = AtomKey.fields.resname
resPos = AtomKey.fields.respos
icode = AtomKey.fields.icode
for ak in atomkeys:
akl = ak.akl
self.e_class += akl[atmNdx]
self.re_class += akl[resNdx] + akl[atmNdx]
rset.add(akl[resPos] + (akl[icode] or ""))
self.cre_class += ak.cr_class()
self.rc = len(rset)
def __deepcopy__(self, memo):
"""Deep copy implementation for Edron."""
existing = memo.get(id(self), False)
if existing:
return existing
dup = type(self).__new__(self.__class__)
memo[id(self)] = dup
dup.__dict__.update(self.__dict__) # mostly static attribs
dup.cic = memo[id(self.cic)]
dup.atomkeys = copy.deepcopy(self.atomkeys, memo)
return dup
def __contains__(self, ak: "AtomKey") -> bool:
"""Return True if atomkey is in this edron."""
return ak in self.atomkeys
def is_backbone(self) -> bool:
"""Report True for contains only N, C, CA, O, H atoms."""
return all(ak.is_backbone() for ak in self.atomkeys)
def __repr__(self) -> str:
"""Tuple of AtomKeys is default repr string."""
return str(self.atomkeys)
def __hash__(self) -> int:
"""Hash calculated at init from atomkeys tuple."""
return self._hash
def _cmp(self, other: "Edron") -> Union[Tuple["AtomKey", "AtomKey"], bool]:
"""Comparison function ranking self vs. other; False on equal.
Priority is lowest value for sort: psi < chi1.
"""
for ak_s, ak_o in zip(self.atomkeys, other.atomkeys):
if ak_s != ak_o:
return ak_s, ak_o
return False
def __eq__(self, other: object) -> bool:
"""Test for equality."""
if not isinstance(other, type(self)):
return NotImplemented
return self.id == other.id
def __ne__(self, other: object) -> bool:
"""Test for inequality."""
if not isinstance(other, type(self)):
return NotImplemented
return self.id != other.id
def __gt__(self, other: object) -> bool:
"""Test greater than."""
if not isinstance(other, type(self)):
return NotImplemented
rslt = self._cmp(other)
if rslt:
rslt = cast(Tuple[AtomKey, AtomKey], rslt)
return rslt[0] > rslt[1]
return False
def __ge__(self, other: object) -> bool:
"""Test greater or equal."""
if not isinstance(other, type(self)):
return NotImplemented
rslt = self._cmp(other)
if rslt:
rslt = cast(Tuple[AtomKey, AtomKey], rslt)
return rslt[0] >= rslt[1]
return True
def __lt__(self, other: object) -> bool:
"""Test less than."""
if not isinstance(other, type(self)):
return NotImplemented
rslt = self._cmp(other)
if rslt:
rslt = cast(Tuple[AtomKey, AtomKey], rslt)
return rslt[0] < rslt[1]
return False
def __le__(self, other: object) -> bool:
"""Test less or equal."""
if not isinstance(other, type(self)):
return NotImplemented
rslt = self._cmp(other)
if rslt:
rslt = cast(Tuple[AtomKey, AtomKey], rslt)
return rslt[0] <= rslt[1]
return True
class Hedron(Edron):
"""Class to represent three joined atoms forming a plane.
Contains atom coordinates in local coordinate space: central atom
at origin, one terminal atom on XZ plane, and the other on the +Z axis.
Stored in two orientations, with the 3rd (forward) or first (reversed)
atom on the +Z axis. See :class:`Dihedron` for use of forward and
reverse orientations.
Attributes
----------
len12: float
distance between first and second atoms
len23: float
distance between second and third atoms
angle: float
angle (degrees) formed by three atoms in hedron
xrh_class: string
only for hedron spanning 2 residues, will have 'X' for residue
contributing only one atom
Methods
-------
get_length()
get bond length for specified atom pair
set_length()
set bond length for specified atom pair
angle(), len12(), len23()
setters for relevant attributes (angle in degrees)
"""
def __init__(self, *args: Union[List["AtomKey"], HKT], **kwargs: str) -> None:
"""Initialize Hedron with sequence of AtomKeys, kwargs.
Acceptable input:
As for Edron, plus optional 'len12', 'angle', 'len23'
keyworded values.
"""
super().__init__(*args, **kwargs)
if self.rc == 2: # hedron crosses residue boundary
resPos = AtomKey.fields.respos
icode = AtomKey.fields.icode
resNdx = AtomKey.fields.resname
atmNdx = AtomKey.fields.atm
akl0, akl1 = self.atomkeys[0].akl, self.atomkeys[1].akl
if akl0[resPos] != akl1[resPos] or akl0[icode] != akl1[icode]:
self.xrh_class = "X" + self.re_class[1:]
else:
xrhc = ""
for i in range(2):
xrhc += self.atomkeys[i].akl[resNdx] + self.atomkeys[i].akl[atmNdx]
self.xrh_class = xrhc + "X" + self.atomkeys[2].akl[atmNdx]
# __deepcopy__ covered by Edron superclass
def __repr__(self) -> str:
"""Print string for Hedron object."""
return (
f"3-{self.id} {self.re_class} {str(self.len12)} "
f"{str(self.angle)} {str(self.len23)}"
)
@property
def angle(self) -> float:
"""Get this hedron angle."""
try:
return self.cic.hedraAngle[self.ndx]
except AttributeError:
return 0.0
def _invalidate_atoms(self):
self.cic.hAtoms_needs_update[self.ndx] = True
for ak in self.atomkeys:
self.cic.atomArrayValid[self.cic.atomArrayIndex[ak]] = False
@angle.setter
def angle(self, angle_deg) -> None:
"""Set this hedron angle; sets needs_update."""
self.cic.hedraAngle[self.ndx] = angle_deg
self.cic.hAtoms_needs_update[self.ndx] = True
self.cic.atomArrayValid[self.cic.atomArrayIndex[self.atomkeys[2]]] = False
@property
def len12(self):
"""Get first length for Hedron."""
try:
return self.cic.hedraL12[self.ndx]
except AttributeError:
return 0.0
@len12.setter
def len12(self, len):
"""Set first length for Hedron; sets needs_update."""
self.cic.hedraL12[self.ndx] = len
self.cic.hAtoms_needs_update[self.ndx] = True
self.cic.atomArrayValid[self.cic.atomArrayIndex[self.atomkeys[1]]] = False
self.cic.atomArrayValid[self.cic.atomArrayIndex[self.atomkeys[2]]] = False
@property
def len23(self) -> float:
"""Get second length for Hedron."""
try:
return self.cic.hedraL23[self.ndx]
except AttributeError:
return 0.0
@len23.setter
def len23(self, len):
"""Set second length for Hedron; sets needs_update."""
self.cic.hedraL23[self.ndx] = len
self.cic.hAtoms_needs_update[self.ndx] = True
self.cic.atomArrayValid[self.cic.atomArrayIndex[self.atomkeys[2]]] = False
def get_length(self, ak_tpl: BKT) -> Optional[float]:
"""Get bond length for specified atom pair.
:param tuple ak_tpl: tuple of AtomKeys.
Pair of atoms in this Hedron
"""
if 2 > len(ak_tpl):
return None
if all(ak in self.atomkeys[:2] for ak in ak_tpl):
return self.cic.hedraL12[self.ndx]
if all(ak in self.atomkeys[1:] for ak in ak_tpl):
return self.cic.hedraL23[self.ndx]
return None
def set_length(self, ak_tpl: BKT, newLength: float):
"""Set bond length for specified atom pair; sets needs_update.
:param tuple .ak_tpl: tuple of AtomKeys
Pair of atoms in this Hedron
"""
if 2 > len(ak_tpl):
raise TypeError(f"Require exactly 2 AtomKeys: {str(ak_tpl)}")
elif all(ak in self.atomkeys[:2] for ak in ak_tpl):
self.cic.hedraL12[self.ndx] = newLength
elif all(ak in self.atomkeys[1:] for ak in ak_tpl):
self.cic.hedraL23[self.ndx] = newLength
else:
raise TypeError("%s not found in %s" % (str(ak_tpl), self))
self._invalidate_atoms()
class Dihedron(Edron):
"""Class to represent four joined atoms forming a dihedral angle.
Attributes
----------
angle: float
Measurement or specification of dihedral angle in degrees; prefer
:meth:`IC_Residue.bond_set` to set
hedron1, hedron2: Hedron object references
The two hedra which form the dihedral angle
h1key, h2key: tuples of AtomKeys
Hash keys for hedron1 and hedron2
id3,id32: tuples of AtomKeys
First 3 and second 3 atoms comprising dihedron; hxkey orders may differ
ric: IC_Residue object reference
:class:`.IC_Residue` object containing this dihedral
reverse: bool
Indicates order of atoms in dihedron is reversed from order of atoms
in hedra
primary: bool
True if this is psi, phi, omega or a sidechain chi angle
pclass: string (primary angle class)
re_class with X for adjacent residue according to nomenclature
(psi, omega, phi)
cst, rcst: numpy [4][4] arrays
transformations to (cst) and from (rcst) Dihedron coordinate space
defined with atom 2 (Hedron 1 center atom) at the origin. Views on
:data:`IC_Chain.dCoordSpace`.
Methods
-------
angle()
getter/setter for dihdral angle in degrees; prefer
:meth:`IC_Residue.bond_set`
bits()
return :data:`IC_Residue.pic_flags` bitmask for dihedron psi, omega, etc
"""
def __init__(self, *args: Union[List["AtomKey"], DKT], **kwargs: str) -> None:
"""Init Dihedron with sequence of AtomKeys and optional dihedral angle.
Acceptable input:
As for Edron, plus optional 'dihedral' keyworded angle value.
"""
super().__init__(*args, **kwargs)
# hedra making up this dihedron; set by self:_set_hedra()
self.hedron1: Hedron # = None
self.hedron2: Hedron # = None
self.h1key: HKT # = None
self.h2key: HKT # = None
# h1, h2key above may be reversed; id3,2 will not be
self.id3: HKT = cast(HKT, tuple(self.atomkeys[0:3]))
self.id32: HKT = cast(HKT, tuple(self.atomkeys[1:4]))
self._setPrimary()
# IC_Residue object which includes this dihedron;
# set by Residue:linkDihedra()
self.ric: IC_Residue
# order of atoms in dihedron is reversed from order of atoms in hedra
self.reverse = False # configured by :meth:`._set_hedra`
def __repr__(self) -> str:
"""Print string for Dihedron object."""
return f"4-{str(self.id)} {self.re_class} {str(self.angle)} {str(self.ric)}"
@staticmethod
def _get_hedron(ic_res: IC_Residue, id3: HKT) -> Optional[Hedron]:
"""Find specified hedron on this residue or its adjacent neighbors."""
hedron = ic_res.hedra.get(id3, None)
if not hedron and 0 < len(ic_res.rprev):
for rp in ic_res.rprev:
hedron = rp.hedra.get(id3, None)
if hedron is not None:
break
if not hedron and 0 < len(ic_res.rnext):
for rn in ic_res.rnext:
hedron = rn.hedra.get(id3, None)
if hedron is not None:
break
return hedron
def _setPrimary(self) -> bool:
"""Mark dihedra required for psi, phi, omega, chi and other angles."""
# http://www.mlb.co.jp/linux/science/garlic/doc/commands/dihedrals.html
dhc = self.e_class
if dhc == "NCACN": # psi
self.pclass = self.re_class[0:7] + "XN"
self.primary = True
elif dhc == "CACNCA": # omg
self.pclass = "XCAXC" + self.re_class[5:]
self.primary = True
elif dhc == "CNCAC": # phi
self.pclass = "XC" + self.re_class[2:]
self.primary = True
elif dhc == "CNCACB": # alternate Cbeta locator
self.altCB_class = "XC" + self.re_class[2:]
self.primary = False
elif dhc in primary_angles:
self.primary = True
self.pclass = self.re_class
else:
self.primary = False
def _set_hedra(self) -> Tuple[bool, Hedron, Hedron]:
"""Work out hedra keys and set rev flag."""
try:
return self.rev, self.hedron1, self.hedron2
except AttributeError:
pass
rev = False
res = self.ric
h1key = self.id3
hedron1 = Dihedron._get_hedron(res, h1key)
if not hedron1:
rev = True
h1key = cast(HKT, tuple(self.atomkeys[2::-1]))
hedron1 = Dihedron._get_hedron(res, h1key)
h2key = cast(HKT, tuple(self.atomkeys[3:0:-1]))
else:
h2key = self.id32
if not hedron1:
raise HedronMatchError(
f"can't find 1st hedron for key {h1key} dihedron {self}"
)
hedron2 = Dihedron._get_hedron(res, h2key)
if not hedron2:
raise HedronMatchError(
f"can't find 2nd hedron for key {h2key} dihedron {self}"
)
self.hedron1 = hedron1
self.h1key = h1key
self.hedron2 = hedron2
self.h2key = h2key
self.reverse = rev
return rev, hedron1, hedron2
@property
def angle(self) -> float:
"""Get dihedral angle."""
try:
return self.cic.dihedraAngle[self.ndx]
except AttributeError:
try:
return self._dihedral
except AttributeError:
return 360.0 # error value without type hint hassles
@angle.setter
def angle(self, dangle_deg_in: float) -> None:
"""Save new dihedral angle; sets needs_update.
Faster to modify IC_Chain level arrays directly.
This is probably not the routine you are looking for. See
:meth:`IC_Residue.bond_set` to change a dihedral angle along with its
neighbours, i.e. without clashing atoms.
N.B. dihedron (i-1)C-N-CA-CB is ignored if O exists.
C-beta is by default placed using O-C-CA-CB, but O is missing
in some PDB file residues, which means the sidechain cannot be
placed. The alternate CB path (i-1)C-N-CA-CB is provided to
circumvent this, but if this is needed then it must be adjusted in
conjunction with PHI ((i-1)C-N-CA-C) as they overlap.
:param float dangle_deg: new dihedral angle in degrees
"""
if dangle_deg_in > 180.0:
dangle_deg = dangle_deg_in - 360.0
elif dangle_deg_in < -180.0:
dangle_deg = dangle_deg_in + 360.0
else:
dangle_deg = dangle_deg_in
self._dihedral = dangle_deg
self.needs_update = True
# rtm
if True: # try:
cic = self.cic
dndx = self.ndx
cic.dihedraAngle[dndx] = dangle_deg
cic.dihedraAngleRads[dndx] = np.deg2rad(dangle_deg)
cic.dAtoms_needs_update[dndx] = True
cic.atomArrayValid[cic.atomArrayIndex[self.atomkeys[3]]] = False
@staticmethod
def angle_dif(a1: Union[float, np.ndarray], a2: Union[float, np.ndarray]):
"""Get angle difference between two +/- 180 angles.
https://stackoverflow.com/a/36001014/2783487
"""
return 180.0 - ((180.0 - a2) + a1) % 360.0
@staticmethod
def angle_avg(alst: List, in_rads: bool = False, out_rads: bool = False):
"""Get average of list of +/-180 angles.
:param List alst: list of angles to average
:param bool in_rads: input values are in radians
:param bool out_rads: report result in radians
"""
walst = alst if in_rads else np.deg2rad(alst)
ravg = np.arctan2(np.sum(np.sin(walst)), np.sum(np.cos(walst)))
return ravg if out_rads else np.rad2deg(ravg)
@staticmethod
def angle_pop_sd(alst: List, avg: float):
"""Get population standard deviation for list of +/-180 angles.
should be sample std dev but avoid len(alst)=1 -> div by 0
"""
return np.sqrt(np.sum(np.square(Dihedron.angle_dif(alst, avg))) / len(alst))
def difference(self, other: "Dihedron") -> float:
"""Get angle difference between this and other +/- 180 angles."""
return Dihedron.angle_dif(self.angle, other.angle)
def bits(self) -> int:
"""Get :data:`IC_Residue.pic_flags` bitmasks for self is psi, omg, phi, pomg, chiX."""
icr = IC_Residue
if self.e_class == "NCACN":
# i psi
return icr.pic_flags.psi
elif hasattr(self, "pclass") and self.pclass == "XCAXCPNPCA":
# i+1 is pro so i+1 omg
return icr.pic_flags.omg | icr.pic_flags.pomg
elif self.e_class == "CACNCA":
# i+1 omg
return icr.pic_flags.omg
elif self.e_class == "CNCAC":
# i+1 phi
return icr.pic_flags.phi
else:
# i chiX
atmNdx = AtomKey.fields.atm
scList = ic_data_sidechains.get(self.ric.lc)
aLst = tuple(ak.akl[atmNdx] for ak in self.atomkeys)
for e in scList:
if len(e) != 5: # only chi entries have label at [4]
continue
if aLst == e[0:4]:
return icr.pic_flags.chi1 << (int(e[4][-1]) - 1)
return 0
class AtomKey:
"""Class for dict keys to reference atom coordinates.
AtomKeys capture residue and disorder information together, and
provide a no-whitespace string key for .pic files.
Supports rich comparison and multiple ways to instantiate.
AtomKeys contain:
residue position (respos), insertion code (icode), 1 or 3 char residue
name (resname), atom name (atm), altloc (altloc), and occupancy (occ)
Use :data:`AtomKey.fields` to get the index to the component of interest by
name:
Get C-alpha atoms from IC_Chain atomArray and atomArrayIndex with
AtomKeys::
atmNameNdx = internal_coords.AtomKey.fields.atm
CaSelection = [
atomArrayIndex.get(k)
for k in atomArrayIndex.keys()
if k.akl[atmNameNdx] == "CA"
]
AtomArrayCa = atomArray[CaSelection]
Get all phenylalanine atoms in a chain::
resNameNdx = internal_coords.AtomKey.fields.resname
PheSelection = [
atomArrayIndex.get(k)
for k in atomArrayIndex.keys()
if k.akl[resNameNdx] == "F"
]
AtomArrayPhe = atomArray[PheSelection]
'resname' will be the uppercase 1-letter amino acid code if one of the 20
standard residues, otherwise the supplied 3-letter code. Supplied as input
or read from .rbase attribute of :class:`IC_Residue`.
Attributes
----------
akl: tuple
All six fields of AtomKey
fieldNames: tuple (Class Attribute)
Mapping of key index positions to names
fields: namedtuple (Class Attribute)
Mapping of field names to index positions.
id: str
'_'-joined AtomKey fields, excluding 'None' fields
atom_re: compiled regex (Class Attribute)
A compiled regular expression matching the string form of the key
d2h: bool (Class Attribute) default False
Convert D atoms to H on input if True; must also modify
:data:`IC_Residue.accept_atoms`
missing: bool default False
AtomKey __init__'d from string is probably missing, set this flag to
note the issue. Set by :meth:`.IC_Residue.rak`
ric: IC_Residue default None
*If* initialised with IC_Residue, this references the IC_residue
Methods
-------
altloc_match(other)
Returns True if this AtomKey matches other AtomKey excluding altloc
and occupancy fields
is_backbone()
Returns True if atom is N, CA, C, O or H
atm()
Returns atom name, e.g. N, CA, CB, etc.
cr_class()
Returns covalent radii class e.g. Csb
"""
atom_re = re.compile(
r"^(?P<respos>-?\d+)(?P<icode>[A-Za-z])?"
r"_(?P<resname>[a-zA-Z]+)_(?P<atm>[A-Za-z0-9]+)"
r"(?:_(?P<altloc>\w))?(?:_(?P<occ>-?\d\.\d+?))?$"
)
"""Pre-compiled regular expression to match an AtomKey string."""
_endnum_re = re.compile(r"\D+(\d+)$")
# PDB altLoc = Character = [\w ] (any non-ctrl ASCII incl space)
# PDB iCode = AChar = [A-Za-z]
fieldNames = ("respos", "icode", "resname", "atm", "altloc", "occ")
_fieldsDef = namedtuple(
"_fieldsDef", ["respos", "icode", "resname", "atm", "altloc", "occ"]
)
fields = _fieldsDef(0, 1, 2, 3, 4, 5)
"""Use this namedtuple to access AtomKey fields. See :class:`AtomKey`"""
d2h = False
"""Set True to convert D Deuterium to H Hydrogen on input."""
def __init__(
self, *args: Union[IC_Residue, Atom, List, Dict, str], **kwargs: str
) -> None:
"""Initialize AtomKey with residue and atom data.
Examples of acceptable input::
(<IC_Residue>, 'CA', ...) : IC_Residue with atom info
(<IC_Residue>, <Atom>) : IC_Residue with Biopython Atom
([52, None, 'G', 'CA', ...]) : list of ordered data fields
(52, None, 'G', 'CA', ...) : multiple ordered arguments
({respos: 52, icode: None, atm: 'CA', ...}) : dict with fieldNames
(respos: 52, icode: None, atm: 'CA', ...) : kwargs with fieldNames
52_G_CA, 52B_G_CA, 52_G_CA_0.33, 52_G_CA_B_0.33 : id strings
"""
akl: List[Optional[str]] = []
self.ric = None
for arg in args:
if isinstance(arg, str):
if "_" in arg:
# AtomKey.icd["_"] += 1
# got atom key string, recurse with regex parse
m = self.atom_re.match(arg)
if m is not None:
if akl != []: # [] != akl:
raise Exception(
"Atom Key init full key not first argument: " + arg
)
akl = list(map(m.group, AtomKey.fieldNames))
else:
akl.append(arg)
elif isinstance(arg, IC_Residue):
if akl != []:
raise Exception("Atom Key init Residue not first argument")
akl = list(arg.rbase)
self.ric = arg
elif isinstance(arg, Atom):
if 3 != len(akl):
raise Exception("Atom Key init Atom before Residue info")
akl.append(arg.name)
if not IC_Residue.no_altloc:
altloc = arg.altloc
akl.append(altloc if altloc != " " else None)
occ = float(arg.occupancy)
akl.append(str(occ) if occ != 1.00 else None)
else:
akl += [None, None]
elif isinstance(arg, list) or isinstance(arg, tuple):
akl += arg
elif isinstance(arg, dict):
for k in AtomKey.fieldNames:
akl.append(arg.get(k, None))
else:
raise Exception("Atom Key init not recognised")
# process kwargs, initialize occ and altloc to None
for i in range(len(akl), 6):
if len(akl) <= i:
fld = kwargs.get(AtomKey.fieldNames[i])
if fld is not None:
akl.append(fld)
# tweak local akl to generate id string
if isinstance(akl[0], Integral):
akl[0] = str(akl[0]) # numeric residue position to string
if self.d2h:
atmNdx = AtomKey.fields.atm
if akl[atmNdx][0] == "D":
akl[atmNdx] = re.sub("D", "H", akl[atmNdx], count=1)
self.id = "_".join(
[
"".join(filter(None, akl[:2])),
str(akl[2]), # exclude None
"_".join(filter(None, akl[3:])),
]
)
akl += [None] * (6 - len(akl))
self.akl = tuple(akl)
self._hash = hash(self.akl)
self.missing = False
def __deepcopy__(self, memo):
"""Deep copy implementation for AtomKey."""
# will fail if .ric not in memo
existing = memo.get(id(self), False)
if existing:
return existing
dup = type(self).__new__(self.__class__)
memo[id(self)] = dup
dup.__dict__.update(self.__dict__) # all static attribs except .ric
if self.ric is not None:
dup.ric = memo[id(self.ric)]
# deepcopy complete
return dup
def __repr__(self) -> str:
"""Repr string from id."""
return self.id
def __hash__(self) -> int:
"""Hash calculated at init from akl tuple."""
return self._hash
_backbone_sort_keys = {"N": 0, "CA": 1, "C": 2, "O": 3}
_sidechain_sort_keys = {
"CB": 1,
"CG": 2,
"CG1": 2,
"OG": 2,
"OG1": 2,
"SG": 2,
"CG2": 3,
"CD": 4,
"CD1": 4,
"SD": 4,
"OD1": 4,
"ND1": 4,
"CD2": 5,
"ND2": 5,
"OD2": 5,
"CE": 6,
"NE": 6,
"CE1": 6,
"OE1": 6,
"NE1": 6,
"CE2": 7,
"OE2": 7,
"NE2": 7,
"CE3": 8,
"CZ": 9,
"CZ2": 9,
"NZ": 9,
"NH1": 10,
"OH": 10,
"CZ3": 10,
"CH2": 11,
"NH2": 11,
"OXT": 12,
"H": 13,
}
_greek_sort_keys = {"A": 0, "B": 1, "G": 2, "D": 3, "E": 4, "Z": 5, "H": 6}
def altloc_match(self, other: "AtomKey") -> bool:
"""Test AtomKey match to other discounting occupancy and altloc."""
if isinstance(other, type(self)):
return self.akl[:4] == other.akl[:4]
else:
return NotImplemented
def is_backbone(self) -> bool:
"""Return True if is N, C, CA, O, or H."""
return self.akl[self.fields.atm] in ("N", "C", "CA", "O", "H")
def atm(self) -> str:
"""Return atom name : N, CA, CB, O etc."""
return self.akl[self.fields.atm]
def cr_class(self) -> Union[str, None]:
"""Return covalent radii class for atom or None."""
akl = self.akl
atmNdx = self.fields.atm
try:
return residue_atom_bond_state["X"][akl[atmNdx]]
except KeyError:
try:
resNdx = self.fields.resname
return residue_atom_bond_state[akl[resNdx]][akl[atmNdx]]
except KeyError:
return "Hsb" if akl[atmNdx][0] == "H" else None
# @profile
def _cmp(self, other: "AtomKey") -> Tuple[int, int]:
"""Comparison function ranking self vs. other.
Priority is lower value, i.e. (CA, CB) gives (0, 1) for sorting.
"""
for i in range(6):
s, o = self.akl[i], other.akl[i]
if s != o:
# insert_code, altloc can be None, deal with first
if s is None and o is not None:
# no insert code before named insert code
return 0, 1
elif o is None and s is not None:
return 1, 0
# now we know s, o not None
# s, o = cast(str, s), cast(str, o) # performance critical code
if AtomKey.fields.atm != i:
# only sorting complications at atom level, occ.
# otherwise respos, insertion code will trigger
# before residue name
if AtomKey.fields.occ == i:
oi = int(float(s) * 100)
si = int(float(o) * 100)
return si, oi # swap so higher occupancy comes first
elif AtomKey.fields.respos == i:
return int(s), int(o)
elif AtomKey.fields.resname == i:
sac, oac = (
self.akl[AtomKey.fields.altloc],
other.akl[AtomKey.fields.altloc],
)
if sac is not None:
if oac is not None:
return ord(sac), ord(oac) # altloc over resname
else: # sac has val and oac is None
return 1, 0
elif oac is not None: # oac has val and sac is None
return 0, 1
# else: # altloc
# fall through for altloc, resname with both altloc = None
return ord(s), ord(o)
# atom names from here
# backbone atoms before sidechain atoms
sb = self._backbone_sort_keys.get(s, None)
ob = self._backbone_sort_keys.get(o, None)
if sb is not None and ob is not None:
return sb, ob
elif sb is not None and ob is None:
return 0, 1
elif sb is None and ob is not None:
return 1, 0
# finished backbone and backbone vs. sidechain atoms
# sidechain vs sidechain, sidechain vs H
ss = self._sidechain_sort_keys.get(s, None)
os = self._sidechain_sort_keys.get(o, None)
if ss is not None and os is not None:
return ss, os
elif ss is not None and os is None:
return 0, 1
elif ss is None and os is not None:
return 1, 0
# amide single 'H' captured above in sidechain sort
# now 'complex'' hydrogens after sidechain
s0, s1, o0, o1 = s[0], s[1], o[0], o[1]
s1d, o1d = s1.isdigit(), o1.isdigit()
# if "H" == s0 == o0: # breaks cython
if ("H" == s0) and ("H" == o0):
if (s1 == o1) or (s1d and o1d):
enmS = self._endnum_re.findall(s)
enmO = self._endnum_re.findall(o)
if (enmS != []) and (enmO != []):
return int(enmS[0]), int(enmO[0])
elif enmS == []:
return 0, 1
else:
return 1, 0
elif s1d:
return 0, 1
elif o1d:
return 1, 0
else:
return (
self._greek_sort_keys[s1],
self._greek_sort_keys[o1],
)
return int(s), int(o) # raise exception?
return 1, 1
def __ne__(self, other: object) -> bool:
"""Test for inequality."""
if isinstance(other, type(self)):
return self.akl != other.akl
else:
return NotImplemented
def __eq__(self, other: object) -> bool: # type: ignore
"""Test for equality."""
if isinstance(other, type(self)):
return self.akl == other.akl
else:
return NotImplemented
def __gt__(self, other: object) -> bool:
"""Test greater than."""
if isinstance(other, type(self)):
rslt = self._cmp(other)
return rslt[0] > rslt[1]
else:
return NotImplemented
def __ge__(self, other: object) -> bool:
"""Test greater or equal."""
if isinstance(other, type(self)):
rslt = self._cmp(other)
return rslt[0] >= rslt[1]
else:
return NotImplemented
def __lt__(self, other: object) -> bool:
"""Test less than."""
if isinstance(other, type(self)):
rslt = self._cmp(other)
return rslt[0] < rslt[1]
else:
return NotImplemented
def __le__(self, other: object) -> bool:
"""Test less or equal."""
if isinstance(other, type(self)):
rslt = self._cmp(other)
return rslt[0] <= rslt[1]
else:
return NotImplemented
def set_accuracy_95(num: float) -> float:
"""Reduce floating point accuracy to 9.5 (xxxx.xxxxx).
Used by :class:`IC_Residue` class writing PIC and SCAD
files.
:param float num: input number
:returns: float with specified accuracy
"""
# return round(num, 5) # much slower
return float(f"{num:9.5f}")
# internal coordinates construction Exceptions
class HedronMatchError(Exception):
"""Cannot find hedron in residue for given key."""
pass
class MissingAtomError(Exception):
"""Missing atom coordinates for hedron or dihedron."""
pass
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