def create_cone_pdb(mol=None, cone=None, start_res=1, apex=None, axis=None, R=None, inc=None, scale=30.0, distribution='regular', file=None, dir=None, force=False, axis_flag=True):
"""Create a PDB representation of the given cone object.
@keyword mol: The molecule container.
@type mol: MolContainer instance
@keyword cone: The cone object. This should provide the limit_check() method with determines the limits of the distribution accepting two arguments, the polar angle phi and the azimuthal angle theta, and return True if the point is in the limits or False if outside. It should also provide the theta_max() method for returning the theta value for the given phi, the phi_max() method for returning the phi value for the given theta.
@type cone: class instance
@keyword start_res: The starting residue number.
@type start_res: str
@keyword apex: The apex of the cone.
@type apex: rank-1, 3D numpy array
@keyword axis: The central axis of the cone. If not supplied, the z-axis will be used.
@type axis: rank-1, 3D numpy array
@keyword R: The rotation matrix.
@type R: rank-2, 3D numpy array
@keyword inc: The increment number used to determine the number of latitude and longitude lines.
@type inc: int
@keyword scale: The scaling factor to stretch the unit cone by.
@type scale: float
@keyword distribution: The type of point distribution to use. This can be 'uniform' or 'regular'.
@type distribution: str
@keyword file: The name of the PDB file to create.
@type file: str
@keyword dir: The name of the directory to place the PDB file into.
@type dir: str
@keyword force: Flag which if set to True will overwrite any pre-existing file.
@type force: bool
@keyword axis_flag: A flag which if True will create the cone's axis.
@type axis_flag: bool
"""
# No molecule supplied.
if mol == None:
# Create the structural object.
structure = Internal()
# Add a molecule.
structure.add_molecule(name='cone')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Create the object.
cone(mol=mol, cone=cone, start_res=start_res, apex=apex, axis=axis, R=R, inc=inc, scale=scale, distribution=distribution, axis_flag=axis_flag)
# Create the PDB file.
if file != None:
print("\nGenerating the PDB file.")
pdb_file = open_write_file(file_name=file, dir=dir, force=force)
structure.write_pdb(pdb_file)
pdb_file.close()
# Add the file to the results file list.
if not hasattr(cdp, 'result_files'):
cdp.result_files = []
cdp.result_files.append(['cone_pdb', 'Cone PDB', get_file_path(file, dir)])
status.observers.result_file.notify()
def pdb(r=1.02, file_name='uniform.pdb', inc=None):
"""Create the bond vector distribution and save the PDB file."""
# Create the structural object.
structure = Internal()
# Add a molecule.
structure.add_molecule(name='dist')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Get the polar and azimuthal angles for the distribution.
phi, theta = angles_uniform(inc)
# Get the uniform vector distribution.
vectors = vect_dist_spherical_angles(inc=inc, distribution='uniform')
# Loop over the radial array of vectors (change in longitude).
atom_num = 1
new_vectors = []
for i in range(len(theta)):
# Loop over the vectors of the radial array (change in latitude).
for j in range(len(phi)):
# The index.
index = i + j*len(theta)
# The atomic positions.
pos1 = vectors[index] * 10
pos2 = pos1 + vectors[index] * r
# Store the rearranged vector (truncated as in the PDB).
trunc_vect = zeros(3, float64)
for k in range(3):
trunc_vect[k] = float("%.3f" % pos2[k]) - float("%.3f" % pos1[k])
new_vectors.append(trunc_vect)
# Residue number.
res = (atom_num + 1) / 2
# Add the vector as a N-H atom pair.
mol.atom_add(pdb_record='ATOM', atom_num=atom_num, atom_name='N', res_name=AA_TABLE[SEQ[index]].upper(), res_num=res, pos=pos1, element='N')
mol.atom_add(pdb_record='ATOM', atom_num=atom_num+1, atom_name='H', res_name=AA_TABLE[SEQ[index]].upper(), res_num=res, pos=pos2, element='H')
# Connect.
mol.atom_connect(atom_num-1, atom_num)
# Move 2 atoms forwards.
atom_num += 2
# The PDB file.
file = open_write_file(file_name, force=True)
structure.write_pdb(file)
file.close()
# Return the vectors in the diffusion frame.
return new_vectors
def create_rotor_pdb(file=None, dir=None, rotor_angle=None, axis=None, axis_pt=True, centre=None, span=2e-9, blade_length=5e-10, force=False, staggered=False):
"""Create a PDB representation of a rotor motional model.
@keyword file: The name of the PDB file to create.
@type file: str
@keyword dir: The name of the directory to place the PDB file into.
@type dir: str
@keyword rotor_angle: The angle of the rotor motion in degrees.
@type rotor_angle: float
@keyword axis: The vector defining the rotor axis.
@type axis: numpy rank-1, 3D array
@keyword axis_pt: A point lying anywhere on the rotor axis. This is used to define the position of the axis in 3D space.
@type axis_pt: numpy rank-1, 3D array
@keyword centre: The central point of the representation. If this point is not on the rotor axis, then the closest point on the axis will be used for the centre.
@type centre: numpy rank-1, 3D array
@keyword span: The distance from the central point to the rotor blades (meters).
@type span: float
@keyword blade_length: The length of the representative rotor blades.
@type blade_length: float
@keyword force: A flag which if set will overwrite any pre-existing file.
@type force: bool
@keyword staggered: A flag which if True will cause the rotor blades to be staggered. This is used to avoid blade overlap.
@type staggered: bool
"""
# Test if the current pipe exists.
pipes.test()
# Convert the angle to radians.
rotor_angle = rotor_angle / 360.0 * 2.0 * pi
# Create the structural object.
structure = Internal()
# Generate the rotor object.
rotor_pdb(structure=structure, rotor_angle=rotor_angle, axis=axis, axis_pt=axis_pt, centre=centre, span=span, blade_length=blade_length, staggered=staggered)
# Print out.
print("\nGenerating the PDB file.")
# Open the PDB file for writing.
tensor_pdb_file = open_write_file(file, dir, force=force)
# Write the data.
structure.write_pdb(tensor_pdb_file)
# Close the file.
tensor_pdb_file.close()
# Add the file to the results file list.
if not hasattr(cdp, 'result_files'):
cdp.result_files = []
if dir == None:
dir = getcwd()
cdp.result_files.append(['rotor_pdb', 'Rotor PDB', get_file_path(file, dir)])
status.observers.result_file.notify()
def pdb(r=1.02, file_name='uniform.pdb', inc=None):
"""Create the bond vector distribution and save the PDB file."""
# Create the structural object.
structure = Internal()
# Add a molecule.
structure.add_molecule(name='dist')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Get the polar and azimuthal angles for the distribution.
phi, theta = angles_uniform(inc)
# Get the uniform vector distribution.
vectors = vect_dist_spherical_angles(inc=inc, distribution='uniform')
# Loop over the radial array of vectors (change in longitude).
atom_num = 1
new_vectors = []
for i in range(len(theta)):
# Loop over the vectors of the radial array (change in latitude).
for j in range(len(phi)):
# The index.
index = i + j * len(theta)
# The atomic positions.
pos1 = vectors[index] * 10
pos2 = pos1 + vectors[index] * r
# Store the rearranged vector (truncated as in the PDB).
trunc_vect = zeros(3, float64)
for k in range(3):
trunc_vect[k] = float("%.3f" % pos2[k]) - float(
"%.3f" % pos1[k])
new_vectors.append(trunc_vect)
# Residue number.
res = (atom_num + 1) / 2
# Add the vector as a N-H atom pair.
mol.atom_add(pdb_record='ATOM',
atom_num=atom_num,
atom_name='N',
res_name=AA_TABLE[SEQ[index]].upper(),
res_num=res,
pos=pos1,
element='N')
mol.atom_add(pdb_record='ATOM',
atom_num=atom_num + 1,
atom_name='H',
res_name=AA_TABLE[SEQ[index]].upper(),
res_num=res,
pos=pos2,
element='H')
# Connect.
mol.atom_connect(atom_num - 1, atom_num)
# Move 2 atoms forwards.
atom_num += 2
# The PDB file.
file = open_write_file(file_name, force=True)
structure.write_pdb(file)
file.close()
# Return the vectors in the diffusion frame.
return new_vectors
def cone_pdb(cone_type=None, scale=1.0, file=None, dir=None, force=False):
"""Create a PDB file containing a geometric object representing the various cone models.
Currently the only cone types supported are 'diff in cone' and 'diff on cone'.
@param cone_type: The type of cone model to represent.
@type cone_type: str
@param scale: The size of the geometric object is eqaul to the average pivot-CoM
vector length multiplied by this scaling factor.
@type scale: float
@param file: The name of the PDB file to create.
@type file: str
@param dir: The name of the directory to place the PDB file into.
@type dir: str
@param force: Flag which if set to True will cause any pre-existing file to be
overwritten.
@type force: int
"""
# Test if the cone models have been determined.
if cone_type == 'diff in cone':
if not hasattr(cdp, 'S_diff_in_cone'):
raise RelaxError(
"The diffusion in a cone model has not yet been determined.")
elif cone_type == 'diff on cone':
if not hasattr(cdp, 'S_diff_on_cone'):
raise RelaxError(
"The diffusion on a cone model has not yet been determined.")
else:
raise RelaxError("The cone type " + repr(cone_type) + " is unknown.")
# The number of increments for the filling of the cone objects.
inc = 20
# The rotation matrix.
R = zeros((3, 3), float64)
two_vect_to_R(array([0, 0, 1], float64),
cdp.ave_pivot_CoM / norm(cdp.ave_pivot_CoM), R)
# The isotropic cone object.
if cone_type == 'diff in cone':
angle = cdp.theta_diff_in_cone
elif cone_type == 'diff on cone':
angle = cdp.theta_diff_on_cone
cone_obj = Iso_cone(angle)
# Create the structural object.
structure = Internal()
# Add a structure.
structure.add_molecule(name='cone')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Add the pivot point.
mol.atom_add(pdb_record='HETATM',
atom_num=1,
atom_name='R',
res_name='PIV',
res_num=1,
pos=cdp.pivot_point,
element='C')
# Generate the average pivot-CoM vectors.
print("\nGenerating the average pivot-CoM vectors.")
sim_vectors = None
if hasattr(cdp, 'ave_pivot_CoM_sim'):
sim_vectors = cdp.ave_pivot_CoM_sim
res_num = generate_vector_residues(mol=mol,
vector=cdp.ave_pivot_CoM,
atom_name='Ave',
res_name_vect='AVE',
sim_vectors=sim_vectors,
res_num=2,
origin=cdp.pivot_point,
scale=scale)
# Generate the cone outer edge.
print("\nGenerating the cone outer edge.")
cap_start_atom = mol.atom_num[-1] + 1
cone_edge(mol=mol,
cone_obj=cone_obj,
res_name='CON',
res_num=3,
apex=cdp.pivot_point,
R=R,
scale=norm(cdp.pivot_CoM),
inc=inc)
# Generate the cone cap, and stitch it to the cone edge.
if cone_type == 'diff in cone':
print("\nGenerating the cone cap.")
cone_start_atom = mol.atom_num[-1] + 1
generate_vector_dist(mol=mol,
res_name='CON',
res_num=3,
centre=cdp.pivot_point,
R=R,
phi_max_fn=cone_obj.phi_max,
scale=norm(cdp.pivot_CoM),
inc=inc)
# Create the PDB file.
print("\nGenerating the PDB file.")
pdb_file = open_write_file(file, dir, force=force)
structure.write_pdb(pdb_file)
pdb_file.close()
def create_diff_tensor_pdb(scale=1.8e-6, file=None, dir=None, force=False):
"""Create the PDB representation of the diffusion tensor.
@keyword scale: The scaling factor for the diffusion tensor.
@type scale: float
@keyword file: The name of the PDB file to create.
@type file: str
@keyword dir: The name of the directory to place the PDB file into.
@type dir: str
@keyword force: Flag which if set to True will overwrite any pre-existing file.
@type force: bool
"""
# Test if the current data pipe exists.
pipes.test()
# Calculate the centre of mass.
com = pipe_centre_of_mass()
# Create the structural object.
structure = Internal()
# Create an array of data pipes to loop over (hybrid support).
if cdp.pipe_type == 'hybrid':
pipe_list = cdp.hybrid_pipes
else:
pipe_list = [pipes.cdp_name()]
# The molecule names.
if cdp.pipe_type == 'hybrid':
mol_names = []
for pipe in pipe_list:
mol_names.append('diff_tensor_' % pipe)
else:
mol_names = ['diff_tensor']
# Loop over the pipes.
for pipe_index in range(len(pipe_list)):
# Get the pipe container.
pipe = pipes.get_pipe(pipe_list[pipe_index])
# Test if the diffusion tensor data is loaded.
if not hasattr(pipe, 'diff_tensor'):
raise RelaxNoTensorError('diffusion')
# Test if a structure has been loaded.
if not hasattr(cdp, 'structure'):
raise RelaxNoPdbError
# Add a new structure.
structure.add_molecule(name=mol_names[pipe_index])
# Alias the single molecule from the single model.
mol = structure.get_molecule(mol_names[pipe_index])
# The diffusion tensor type.
diff_type = pipe.diff_tensor.type
if diff_type == 'spheroid':
diff_type = pipe.diff_tensor.spheroid_type
# Simulation info.
sim_num = None
if hasattr(pipe.diff_tensor, 'tm_sim'):
# The number.
sim_num = len(pipe.diff_tensor.tm_sim)
# Tensor axes.
axes = []
sim_axes = []
if diff_type in ['oblate', 'prolate']:
axes.append(pipe.diff_tensor.Dpar * pipe.diff_tensor.Dpar_unit)
if sim_num != None:
sim_axes.append([])
for i in range(sim_num):
sim_axes[0].append(pipe.diff_tensor.Dpar_sim[i] * pipe.diff_tensor.Dpar_unit_sim[i])
if diff_type == 'ellipsoid':
axes.append(pipe.diff_tensor.Dx * pipe.diff_tensor.Dx_unit)
axes.append(pipe.diff_tensor.Dy * pipe.diff_tensor.Dy_unit)
axes.append(pipe.diff_tensor.Dz * pipe.diff_tensor.Dz_unit)
if sim_num != None:
sim_axes.append([])
sim_axes.append([])
sim_axes.append([])
for i in range(sim_num):
sim_axes[0].append(pipe.diff_tensor.Dx_sim[i] * pipe.diff_tensor.Dx_unit_sim[i])
sim_axes[1].append(pipe.diff_tensor.Dy_sim[i] * pipe.diff_tensor.Dy_unit_sim[i])
sim_axes[2].append(pipe.diff_tensor.Dz_sim[i] * pipe.diff_tensor.Dz_unit_sim[i])
# Create the object.
diffusion_tensor(mol=mol, tensor=pipe.diff_tensor.tensor, tensor_diag=pipe.diff_tensor.tensor_diag, diff_type=diff_type, rotation=pipe.diff_tensor.rotation, axes=axes, sim_axes=sim_axes, com=com, scale=scale)
# Create the PDB file.
######################
# Print out.
print("\nGenerating the PDB file.")
# Create the PDB file.
tensor_pdb_file = open_write_file(file, dir, force=force)
structure.write_pdb(tensor_pdb_file)
tensor_pdb_file.close()
# Add the file to the results file list.
if not hasattr(cdp, 'result_files'):
cdp.result_files = []
if dir == None:
dir = getcwd()
cdp.result_files.append(['diff_tensor_pdb', 'Diffusion tensor PDB', get_file_path(file, dir)])
status.observers.result_file.notify()
def web_of_motion(file=None, dir=None, models=None, force=False):
"""Create a PDB representation of the motion between a set of models.
This will create a PDB file containing the atoms of all models, with identical atoms links using CONECT records. This function only supports the internal structural object.
@keyword file: The name of the PDB file to write.
@type file: str
@keyword dir: The directory where the PDB file will be placed. If set to None, then the file will be placed in the current directory.
@type dir: str or None
@keyword models: The optional list of models to restrict this to.
@type models: list of int or None
@keyword force: The force flag which if True will cause the file to be overwritten.
@type force: bool
"""
# Test if the current data pipe exists.
pipes.test()
# Test if the structure exists.
if not hasattr(cdp, 'structure') or not cdp.structure.num_models() or not cdp.structure.num_molecules():
raise RelaxNoPdbError
# Validate the models.
cdp.structure.validate_models()
# Initialise the structural object.
web = Internal()
# The model list.
if models == None:
models = []
for k in range(len(cdp.structure.structural_data)):
models.append(cdp.structure.structural_data[k].num)
# Loop over the molecules.
for i in range(len(cdp.structure.structural_data[0].mol)):
# Alias the molecule of the first model.
mol1 = cdp.structure.structural_data[0].mol[i]
# Loop over the atoms.
for j in range(len(mol1.atom_name)):
# Loop over the models.
for k in range(len(cdp.structure.structural_data)):
# Skip the model.
if cdp.structure.structural_data[k].num not in models:
continue
# Alias.
mol = cdp.structure.structural_data[k].mol[i]
# Add the atom.
web.add_atom(mol_name=mol1.mol_name, atom_name=mol.atom_name[j], res_name=mol.res_name[j], res_num=mol.res_num[j], pos=[mol.x[j], mol.y[j], mol.z[j]], element=mol.element[j], chain_id=mol.chain_id[j], segment_id=mol.seg_id[j], pdb_record=mol.pdb_record[j])
# Loop over the models again, this time twice.
for k in range(len(models)):
for l in range(len(models)):
# Skip identical atoms.
if k == l:
continue
# The atom index.
index1 = j*len(models) + k
index2 = j*len(models) + l
# Connect to the previous atoms.
web.connect_atom(mol_name=mol1.mol_name, index1=index1, index2=index2)
# Append the PDB extension if needed.
if isinstance(file, str):
# The file path.
file = get_file_path(file, dir)
# Add '.pdb' to the end of the file path if it isn't there yet.
if not search(".pdb$", file):
file += '.pdb'
# Open the file for writing.
file = open_write_file(file, force=force)
# Write the structure.
web.write_pdb(file)
def create_vector_dist(length=None, symmetry=True, file=None, dir=None, force=False):
"""Create a PDB representation of the vector distribution.
@keyword length: The length to set the vectors to in the PDB file.
@type length: float
@keyword symmetry: The symmetry flag which if set will create a second PDB chain 'B' which is the same as chain 'A' but with the vectors reversed.
@type symmetry: bool
@keyword file: The name of the PDB file to create.
@type file: str
@keyword dir: The name of the directory to place the PDB file into.
@type dir: str
@keyword force: Flag which if set will overwrite any pre-existing file.
@type force: bool
"""
# Test if the current pipe exists.
pipes.test()
# Test if a structure has been loaded.
if not hasattr(cdp, 'structure') or not cdp.structure.num_models() > 0:
raise RelaxNoPdbError
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Test if unit vectors exist.
vectors = False
for interatom in interatomic_loop():
if hasattr(interatom, 'vector'):
vectors = True
break
if not vectors:
raise RelaxNoVectorsError
# Initialise.
#############
# Create the structural object.
structure = Internal()
# Add a structure.
structure.add_molecule(name='vector_dist')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Initialise the residue and atom numbers.
res_num = 1
atom_num = 1
# Centre of mass.
#################
# Calculate the centre of mass.
R = pipe_centre_of_mass()
# Increment the residue number.
res_num = res_num + 1
# The vectors.
##############
# Loop over the interatomic data containers.
for interatom in interatomic_loop():
# Get the spins.
spin1 = return_spin(interatom.spin_id1)
spin2 = return_spin(interatom.spin_id2)
# Skip deselected spin systems.
if not spin1.select or not spin2.select:
continue
# Skip containers missing vectors.
if not hasattr(interatom, 'vector'):
continue
# Scale the vector.
vector = interatom.vector * length * 1e10
# Add the first spin as the central atom.
mol.atom_add(pdb_record='ATOM', atom_num=atom_num, atom_name=spin1.name, res_name=spin1._res_name, chain_id='A', res_num=spin1._res_num, pos=R, segment_id=None, element=spin1.element)
# Add the second spin as the end atom.
mol.atom_add(pdb_record='ATOM', atom_num=atom_num+1, atom_name=spin2.name, res_name=spin2._res_name, chain_id='A', res_num=spin2._res_num, pos=R+vector, segment_id=None, element=spin2.element)
# Connect the two atoms.
mol.atom_connect(index1=atom_num-1, index2=atom_num)
# Increment the atom number.
atom_num = atom_num + 2
# Symmetry chain.
if symmetry:
# Loop over the interatomic data containers.
for interatom in interatomic_loop():
# Get the spins.
spin1 = return_spin(interatom.spin_id1)
spin2 = return_spin(interatom.spin_id2)
# Skip deselected spin systems.
if not spin1.select or not spin2.select:
continue
# Skip containers missing vectors.
if not hasattr(interatom, 'vector'):
continue
# Scale the vector.
vector = interatom.vector * length * 1e10
# Add the first spin as the central atom.
mol.atom_add(pdb_record='ATOM', atom_num=atom_num, atom_name=spin1.name, res_name=spin1._res_name, chain_id='B', res_num=spin1._res_num, pos=R, segment_id=None, element=spin1.element)
# Add the second spin as the end atom.
mol.atom_add(pdb_record='ATOM', atom_num=atom_num+1, atom_name=spin2.name, res_name=spin2._res_name, chain_id='B', res_num=spin2._res_num, pos=R-vector, segment_id=None, element=spin2.element)
# Connect the two atoms.
mol.atom_connect(index1=atom_num-1, index2=atom_num)
# Increment the atom number.
atom_num = atom_num + 2
# Create the PDB file.
######################
# Print out.
print("\nGenerating the PDB file.")
# Open the PDB file for writing.
tensor_pdb_file = open_write_file(file, dir, force=force)
# Write the data.
structure.write_pdb(tensor_pdb_file)
# Close the file.
tensor_pdb_file.close()
# Add the file to the results file list.
if not hasattr(cdp, 'result_files'):
cdp.result_files = []
if dir == None:
dir = getcwd()
cdp.result_files.append(['vector_dist_pdb', 'Vector distribution PDB', get_file_path(file, dir)])
status.observers.result_file.notify()
def create_rotor_pdb(file=None,
dir=None,
rotor_angle=None,
axis=None,
axis_pt=True,
centre=None,
span=2e-9,
blade_length=5e-10,
force=False,
staggered=False):
"""Create a PDB representation of a rotor motional model.
@keyword file: The name of the PDB file to create.
@type file: str
@keyword dir: The name of the directory to place the PDB file into.
@type dir: str
@keyword rotor_angle: The angle of the rotor motion in degrees.
@type rotor_angle: float
@keyword axis: The vector defining the rotor axis.
@type axis: numpy rank-1, 3D array
@keyword axis_pt: A point lying anywhere on the rotor axis. This is used to define the position of the axis in 3D space.
@type axis_pt: numpy rank-1, 3D array
@keyword centre: The central point of the representation. If this point is not on the rotor axis, then the closest point on the axis will be used for the centre.
@type centre: numpy rank-1, 3D array
@keyword span: The distance from the central point to the rotor blades (meters).
@type span: float
@keyword blade_length: The length of the representative rotor blades.
@type blade_length: float
@keyword force: A flag which if set will overwrite any pre-existing file.
@type force: bool
@keyword staggered: A flag which if True will cause the rotor blades to be staggered. This is used to avoid blade overlap.
@type staggered: bool
"""
# Test if the current pipe exists.
check_pipe()
# Convert the angle to radians.
rotor_angle = rotor_angle / 360.0 * 2.0 * pi
# Create the structural object.
structure = Internal()
# Generate the rotor object.
rotor(structure=structure,
rotor_angle=rotor_angle,
axis=axis,
axis_pt=axis_pt,
centre=centre,
span=span,
blade_length=blade_length,
staggered=staggered)
# Print out.
print("\nGenerating the PDB file.")
# Open the PDB file for writing.
tensor_pdb_file = open_write_file(file, dir, force=force)
# Write the data.
structure.write_pdb(tensor_pdb_file)
# Close the file.
tensor_pdb_file.close()
# Add the file to the results file list.
if not hasattr(cdp, 'result_files'):
cdp.result_files = []
if dir == None:
dir = getcwd()
cdp.result_files.append(
['rotor_pdb', 'Rotor PDB',
get_file_path(file, dir)])
status.observers.result_file.notify()
def create_vector_dist(length=None,
symmetry=True,
file=None,
dir=None,
force=False):
"""Create a PDB representation of the vector distribution.
@keyword length: The length to set the vectors to in the PDB file.
@type length: float
@keyword symmetry: The symmetry flag which if set will create a second PDB chain 'B' which is the same as chain 'A' but with the vectors reversed.
@type symmetry: bool
@keyword file: The name of the PDB file to create.
@type file: str
@keyword dir: The name of the directory to place the PDB file into.
@type dir: str
@keyword force: Flag which if set will overwrite any pre-existing file.
@type force: bool
"""
# Test if the current pipe exists.
check_pipe()
# Test if a structure has been loaded.
if not hasattr(cdp, 'structure') or not cdp.structure.num_models() > 0:
raise RelaxNoPdbError
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Test if unit vectors exist.
vectors = False
for interatom in interatomic_loop():
if hasattr(interatom, 'vector'):
vectors = True
break
if not vectors:
raise RelaxNoVectorsError
# Initialise.
#############
# Create the structural object.
structure = Internal()
# Add a structure.
structure.add_molecule(name='vector_dist')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Initialise the residue and atom numbers.
res_num = 1
atom_num = 1
# Centre of mass.
#################
# Calculate the centre of mass.
R = pipe_centre_of_mass()
# Increment the residue number.
res_num = res_num + 1
# The vectors.
##############
# Loop over the interatomic data containers.
for interatom in interatomic_loop():
# Get the spins.
spin1 = return_spin(spin_hash=interatom._spin_hash1)
spin2 = return_spin(spin_hash=interatom._spin_hash2)
# Skip deselected spin systems.
if not spin1.select or not spin2.select:
continue
# Skip containers missing vectors.
if not hasattr(interatom, 'vector'):
continue
# Scale the vector.
vector = interatom.vector * length * 1e10
# Add the first spin as the central atom.
mol.atom_add(pdb_record='ATOM',
atom_num=atom_num,
atom_name=spin1.name,
res_name=spin1._res_name,
chain_id='A',
res_num=spin1._res_num,
pos=R,
segment_id=None,
element=spin1.element)
# Add the second spin as the end atom.
mol.atom_add(pdb_record='ATOM',
atom_num=atom_num + 1,
atom_name=spin2.name,
res_name=spin2._res_name,
chain_id='A',
res_num=spin2._res_num,
pos=R + vector,
segment_id=None,
element=spin2.element)
# Connect the two atoms.
mol.atom_connect(index1=atom_num - 1, index2=atom_num)
# Increment the atom number.
atom_num = atom_num + 2
# Symmetry chain.
if symmetry:
# Loop over the interatomic data containers.
for interatom in interatomic_loop():
# Get the spins.
spin1 = return_spin(spin_hash=interatom._spin_hash1)
spin2 = return_spin(spin_hash=interatom._spin_hash2)
# Skip deselected spin systems.
if not spin1.select or not spin2.select:
continue
# Skip containers missing vectors.
if not hasattr(interatom, 'vector'):
continue
# Scale the vector.
vector = interatom.vector * length * 1e10
# Add the first spin as the central atom.
mol.atom_add(pdb_record='ATOM',
atom_num=atom_num,
atom_name=spin1.name,
res_name=spin1._res_name,
chain_id='B',
res_num=spin1._res_num,
pos=R,
segment_id=None,
element=spin1.element)
# Add the second spin as the end atom.
mol.atom_add(pdb_record='ATOM',
atom_num=atom_num + 1,
atom_name=spin2.name,
res_name=spin2._res_name,
chain_id='B',
res_num=spin2._res_num,
pos=R - vector,
segment_id=None,
element=spin2.element)
# Connect the two atoms.
mol.atom_connect(index1=atom_num - 1, index2=atom_num)
# Increment the atom number.
atom_num = atom_num + 2
# Create the PDB file.
######################
# Print out.
print("\nGenerating the PDB file.")
# Open the PDB file for writing.
tensor_pdb_file = open_write_file(file, dir, force=force)
# Write the data.
structure.write_pdb(tensor_pdb_file)
# Close the file.
tensor_pdb_file.close()
# Add the file to the results file list.
if not hasattr(cdp, 'result_files'):
cdp.result_files = []
if dir == None:
dir = getcwd()
cdp.result_files.append([
'vector_dist_pdb', 'Vector distribution PDB',
get_file_path(file, dir)
])
status.observers.result_file.notify()
def cone_pdb(cone_type=None, scale=1.0, file=None, dir=None, force=False):
"""Create a PDB file containing a geometric object representing the various cone models.
Currently the only cone types supported are 'diff in cone' and 'diff on cone'.
@param cone_type: The type of cone model to represent.
@type cone_type: str
@param scale: The size of the geometric object is eqaul to the average pivot-CoM
vector length multiplied by this scaling factor.
@type scale: float
@param file: The name of the PDB file to create.
@type file: str
@param dir: The name of the directory to place the PDB file into.
@type dir: str
@param force: Flag which if set to True will cause any pre-existing file to be
overwritten.
@type force: int
"""
# Test if the cone models have been determined.
if cone_type == 'diff in cone':
if not hasattr(cdp, 'S_diff_in_cone'):
raise RelaxError("The diffusion in a cone model has not yet been determined.")
elif cone_type == 'diff on cone':
if not hasattr(cdp, 'S_diff_on_cone'):
raise RelaxError("The diffusion on a cone model has not yet been determined.")
else:
raise RelaxError("The cone type " + repr(cone_type) + " is unknown.")
# The number of increments for the filling of the cone objects.
inc = 20
# The rotation matrix.
R = zeros((3, 3), float64)
two_vect_to_R(array([0, 0, 1], float64), cdp.ave_pivot_CoM/norm(cdp.ave_pivot_CoM), R)
# The isotropic cone object.
if cone_type == 'diff in cone':
angle = cdp.theta_diff_in_cone
elif cone_type == 'diff on cone':
angle = cdp.theta_diff_on_cone
cone_obj = Iso_cone(angle)
# Create the structural object.
structure = Internal()
# Add a structure.
structure.add_molecule(name='cone')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Add the pivot point.
mol.atom_add(pdb_record='HETATM', atom_num=1, atom_name='R', res_name='PIV', res_num=1, pos=cdp.pivot_point, element='C')
# Generate the average pivot-CoM vectors.
print("\nGenerating the average pivot-CoM vectors.")
sim_vectors = None
if hasattr(cdp, 'ave_pivot_CoM_sim'):
sim_vectors = cdp.ave_pivot_CoM_sim
res_num = generate_vector_residues(mol=mol, vector=cdp.ave_pivot_CoM, atom_name='Ave', res_name_vect='AVE', sim_vectors=sim_vectors, res_num=2, origin=cdp.pivot_point, scale=scale)
# Generate the cone outer edge.
print("\nGenerating the cone outer edge.")
cap_start_atom = mol.atom_num[-1]+1
cone_edge(mol=mol, cone_obj=cone_obj, res_name='CON', res_num=3, apex=cdp.pivot_point, R=R, scale=norm(cdp.pivot_CoM), inc=inc)
# Generate the cone cap, and stitch it to the cone edge.
if cone_type == 'diff in cone':
print("\nGenerating the cone cap.")
cone_start_atom = mol.atom_num[-1]+1
generate_vector_dist(mol=mol, res_name='CON', res_num=3, centre=cdp.pivot_point, R=R, phi_max_fn=cone_obj.phi_max, scale=norm(cdp.pivot_CoM), inc=inc)
# Create the PDB file.
print("\nGenerating the PDB file.")
pdb_file = open_write_file(file, dir, force=force)
structure.write_pdb(pdb_file)
pdb_file.close()
from lib.io import open_write_file
from lib.structure.internal.object import Internal
# Create the structural object.
structure = Internal()
# Add a molecule.
structure.add_molecule(name='piv')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Add the original pivot.
mol.atom_add(atom_name='N',
res_name='PIV',
res_num=1,
pos=[37.254, 0.5, 16.7465],
element='N')
# Add the shifted pivot.
mol.atom_add(atom_name='N',
res_name='SFT',
res_num=2,
pos=[38.968163825736738, 2.6192628972111, 13.499077238576398],
element='N')
# Save as a PDB file.
file = open_write_file('pivot_point.pdb', force=True)
structure.write_pdb(file)
file.close()
# Create a PDB representation for the real pivot point used to generate the data.
# relax module imports.
from lib.io import open_write_file
from lib.structure.internal.object import Internal
# Create the structural object.
structure = Internal()
# Add a molecule.
structure.add_molecule(name='piv')
# Alias the single molecule from the single model.
mol = structure.structural_data[0].mol[0]
# Add the original pivot.
mol.atom_add(atom_name='N', res_name='PIV', res_num=1, pos=[ 37.254, 0.5, 16.7465], element='N')
# Add the shifted pivot.
mol.atom_add(atom_name='N', res_name='SFT', res_num=2, pos=[ 38.968163825736738, 2.6192628972111, 13.499077238576398], element='N')
# Save as a PDB file.
file = open_write_file('pivot_point.pdb', force=True)
structure.write_pdb(file)
file.close()
