def get_param_values(self, model_info=None, sim_index=None):
"""Return a vector of parameter values.
@keyword model_info: The model information from model_loop(). This is unused.
@type model_info: None
@keyword sim_index: The Monte Carlo simulation index.
@type sim_index: int
@return: The vector of parameter values.
@rtype: list of str
"""
# Assemble the values and return it.
return assemble_param_vector(sim_index=sim_index)
def get_param_values(self, model_info=None, sim_index=None):
"""Return a vector of parameter values.
@keyword model_info: The model information from model_loop(). This is unused.
@type model_info: None
@keyword sim_index: The Monte Carlo simulation index.
@type sim_index: int
@return: The vector of parameter values.
@rtype: list of str
"""
# Assemble the values and return it.
return assemble_param_vector(sim_index=sim_index)
def distribute(file="distribution.pdb.bz2", dir=None, atom_id=None, total=1000, max_rotations=100000, model=1, force=True):
"""Create a uniform distribution of structures for the frame order motions.
@keyword file: The PDB file for storing the frame order motional distribution. The compression is determined automatically by the file extensions '*.pdb', '*.pdb.gz', and '*.pdb.bz2'.
@type file: str
@keyword dir: The directory name to place the file into.
@type dir: str or None
@keyword atom_id: The atom identification string to allow the distribution to be a subset of all atoms.
@type atom_id: None or str
@keyword total: The total number of states/model/structures in the distribution.
@type total: int
@keyword max_rotations: The maximum number of rotations to generate the distribution from. This prevents an execution for an infinite amount of time when a frame order amplitude parameter is close to zero so that the subset of all rotations within the distribution is close to zero.
@type max_rotations: int
@keyword model: Only one model from an analysed ensemble of structures can be used for the distribution, as the corresponding PDB file consists of one model per state.
@type model: int
@keyword force: A flag which, if set to True, will overwrite the any pre-existing file.
@type force: bool
"""
# Printout.
print("Uniform distribution of structures representing the frame order motions.")
# Check the total.
if total > 9999:
raise RelaxError("A maximum of 9999 models is allowed in the PDB format.")
# Checks.
check_pipe()
check_model()
check_domain()
check_parameters()
check_pivot()
# Skip the rigid model.
if cdp.model == MODEL_RIGID:
print("Skipping the rigid model.")
return
# Open the output file.
file = open_write_file(file_name=file, dir=dir, force=force)
# The parameter values.
values = assemble_param_vector()
params = {}
i = 0
for name in cdp.params:
params[name] = values[i]
i += 1
# The structure.
structure = deepcopy(cdp.structure)
if structure.num_models() > 1:
structure.collapse_ensemble(model_num=model)
# The pivot points.
num_states = 1
if cdp.model == MODEL_DOUBLE_ROTOR:
num_states = 2
pivot = zeros((num_states, 3), float64)
for i in range(num_states):
pivot[i] = generate_pivot(order=i+1, pdb_limit=True)
# Shift to the average position.
average_position(structure=structure, models=[None])
# The motional eigenframe.
frame = generate_axis_system()
# Only work with a subset.
if atom_id:
# The inverted selection.
selection = structure.selection(atom_id=atom_id, inv=True)
# Delete the data.
structure.delete(selection=selection, verbosity=0)
# Create the distribution.
uniform_distribution(file=file, model=cdp.model, structure=structure, parameters=params, eigenframe=frame, pivot=pivot, atom_id=domain_moving(), total=total, max_rotations=max_rotations)
# Close the file.
file.close()
def simulate(file="simulation.pdb.bz2", dir=None, step_size=2.0, snapshot=10, total=1000, model=1, force=True):
"""Pseudo-Brownian dynamics simulation of the frame order motions.
@keyword file: The PDB file for storing the frame order pseudo-Brownian dynamics simulation. The compression is determined automatically by the file extensions '*.pdb', '*.pdb.gz', and '*.pdb.bz2'.
@type file: str
@keyword dir: The directory name to place the file into.
@type dir: str or None
@keyword step_size: The rotation will be of a random direction but with this fixed angle. The value is in degrees.
@type step_size: float
@keyword snapshot: The number of steps in the simulation when snapshots will be taken.
@type snapshot: int
@keyword total: The total number of snapshots to take before stopping the simulation.
@type total: int
@keyword model: Only one model from an analysed ensemble of structures can be used for the pseudo-Brownian simulation, as the simulation and corresponding PDB file consists of one model per simulation.
@type model: int
@keyword force: A flag which, if set to True, will overwrite the any pre-existing file.
@type force: bool
"""
# Printout.
print("Pseudo-Brownian dynamics simulation of the frame order motions.")
# Checks.
check_pipe()
check_model()
check_domain()
check_parameters()
check_pivot()
# Skip the rigid model.
if cdp.model == MODEL_RIGID:
print("Skipping the rigid model.")
return
# Open the output file.
file = open_write_file(file_name=file, dir=dir, force=force)
# The parameter values.
values = assemble_param_vector()
params = {}
i = 0
for name in cdp.params:
params[name] = values[i]
i += 1
# The structure.
structure = deepcopy(cdp.structure)
if structure.num_models() > 1:
structure.collapse_ensemble(model_num=model)
# The pivot points.
num_states = 1
if cdp.model == MODEL_DOUBLE_ROTOR:
num_states = 2
pivot = zeros((num_states, 3), float64)
for i in range(num_states):
pivot[i] = generate_pivot(order=i+1, pdb_limit=True)
# Shift to the average position.
average_position(structure=structure, models=[None])
# The motional eigenframe.
frame = generate_axis_system()
# Create the distribution.
brownian(file=file, model=cdp.model, structure=structure, parameters=params, eigenframe=frame, pivot=pivot, atom_id=domain_moving(), step_size=step_size, snapshot=snapshot, total=total)
# Close the file.
file.close()
def simulate(file="simulation.pdb.bz2",
dir=None,
step_size=2.0,
snapshot=10,
total=1000,
model=1,
force=True):
"""Pseudo-Brownian dynamics simulation of the frame order motions.
@keyword file: The PDB file for storing the frame order pseudo-Brownian dynamics simulation. The compression is determined automatically by the file extensions '*.pdb', '*.pdb.gz', and '*.pdb.bz2'.
@type file: str
@keyword dir: The directory name to place the file into.
@type dir: str or None
@keyword step_size: The rotation will be of a random direction but with this fixed angle. The value is in degrees.
@type step_size: float
@keyword snapshot: The number of steps in the simulation when snapshots will be taken.
@type snapshot: int
@keyword total: The total number of snapshots to take before stopping the simulation.
@type total: int
@keyword model: Only one model from an analysed ensemble of structures can be used for the pseudo-Brownian simulation, as the simulation and corresponding PDB file consists of one model per simulation.
@type model: int
@keyword force: A flag which, if set to True, will overwrite the any pre-existing file.
@type force: bool
"""
# Printout.
print("Pseudo-Brownian dynamics simulation of the frame order motions.")
# Checks.
check_pipe()
check_model()
check_domain()
check_parameters()
check_pivot()
# Skip the rigid model.
if cdp.model == MODEL_RIGID:
print("Skipping the rigid model.")
return
# Open the output file.
file = open_write_file(file_name=file, dir=dir, force=force)
# The parameter values.
values = assemble_param_vector()
params = {}
i = 0
for name in cdp.params:
params[name] = values[i]
i += 1
# The structure.
structure = deepcopy(cdp.structure)
if structure.num_models() > 1:
structure.collapse_ensemble(model_num=model)
# The pivot points.
num_states = 1
if cdp.model == MODEL_DOUBLE_ROTOR:
num_states = 2
pivot = zeros((num_states, 3), float64)
for i in range(num_states):
pivot[i] = generate_pivot(order=i + 1, pdb_limit=True)
# Shift to the average position.
average_position(structure=structure, models=[None])
# The motional eigenframe.
frame = generate_axis_system()
# Create the distribution.
brownian(file=file,
model=cdp.model,
structure=structure,
parameters=params,
eigenframe=frame,
pivot=pivot,
atom_id=domain_moving(),
step_size=step_size,
snapshot=snapshot,
total=total)
# Close the file.
file.close()
def distribute(file="distribution.pdb.bz2",
dir=None,
atom_id=None,
total=1000,
max_rotations=100000,
model=1,
force=True):
"""Create a uniform distribution of structures for the frame order motions.
@keyword file: The PDB file for storing the frame order motional distribution. The compression is determined automatically by the file extensions '*.pdb', '*.pdb.gz', and '*.pdb.bz2'.
@type file: str
@keyword dir: The directory name to place the file into.
@type dir: str or None
@keyword atom_id: The atom identification string to allow the distribution to be a subset of all atoms.
@type atom_id: None or str
@keyword total: The total number of states/model/structures in the distribution.
@type total: int
@keyword max_rotations: The maximum number of rotations to generate the distribution from. This prevents an execution for an infinite amount of time when a frame order amplitude parameter is close to zero so that the subset of all rotations within the distribution is close to zero.
@type max_rotations: int
@keyword model: Only one model from an analysed ensemble of structures can be used for the distribution, as the corresponding PDB file consists of one model per state.
@type model: int
@keyword force: A flag which, if set to True, will overwrite the any pre-existing file.
@type force: bool
"""
# Printout.
print(
"Uniform distribution of structures representing the frame order motions."
)
# Check the total.
if total > 9999:
raise RelaxError(
"A maximum of 9999 models is allowed in the PDB format.")
# Checks.
check_pipe()
check_model()
check_domain()
check_parameters()
check_pivot()
# Skip the rigid model.
if cdp.model == MODEL_RIGID:
print("Skipping the rigid model.")
return
# Open the output file.
file = open_write_file(file_name=file, dir=dir, force=force)
# The parameter values.
values = assemble_param_vector()
params = {}
i = 0
for name in cdp.params:
params[name] = values[i]
i += 1
# The structure.
structure = deepcopy(cdp.structure)
if structure.num_models() > 1:
structure.collapse_ensemble(model_num=model)
# The pivot points.
num_states = 1
if cdp.model == MODEL_DOUBLE_ROTOR:
num_states = 2
pivot = zeros((num_states, 3), float64)
for i in range(num_states):
pivot[i] = generate_pivot(order=i + 1, pdb_limit=True)
# Shift to the average position.
average_position(structure=structure, models=[None])
# The motional eigenframe.
frame = generate_axis_system()
# Only work with a subset.
if atom_id:
# The inverted selection.
selection = structure.selection(atom_id=atom_id, inv=True)
# Delete the data.
structure.delete(selection=selection, verbosity=0)
# Create the distribution.
uniform_distribution(file=file,
model=cdp.model,
structure=structure,
parameters=params,
eigenframe=frame,
pivot=pivot,
atom_id=domain_moving(),
total=total,
max_rotations=max_rotations)
# Close the file.
file.close()
