def remove_ghost_particles(last_phase_xml, output_file_name, sigma=1.0):
# Remove all the ghost particles from the morphology for the final output
final_morphology = hf.load_morphology_xml(last_phase_xml)
# Determine the atomIDs for each particle beginning with the letters 'X'
# or 'R' - these are the ghost particles
atom_IDs_to_remove = []
for atom_ID, atom_type in enumerate(final_morphology["type"]):
if (atom_type[0] == "X") or (atom_type[0] == "R"):
# This is a ghost particle
atom_IDs_to_remove.append(atom_ID)
# Reverse sorting trick so that the location indices don't change as we
# delete particles from the system
atom_IDs_to_remove.sort(reverse=True)
# Now delete the atoms from the morphology
atom_attribs = ["position", "image", "type", "mass", "diameter", "body", "charge"]
for atom_ID in atom_IDs_to_remove:
for key in atom_attribs:
final_morphology[key].pop(atom_ID)
final_morphology["natoms"] -= len(atom_IDs_to_remove)
# Delete any constraints associated with those atoms that have been removed
atom_constraints = ["bond", "angle", "dihedral", "improper"]
for key in atom_constraints:
constraints_to_remove = []
for constraint_no, constraint in enumerate(final_morphology[key]):
for atom_ID in constraint[1:]:
if (atom_ID in atom_IDs_to_remove) and (
constraint_no not in constraints_to_remove
):
constraints_to_remove.append(constraint_no)
constraints_to_remove.sort(reverse=True)
for constraint_no in constraints_to_remove:
final_morphology[key].pop(constraint_no)
# Output the final morphology
hf.write_morphology_xml(final_morphology, output_file_name, sigma)
def test_check_morphology(self, run_simulation):
output_morph_dir = run_simulation["output_parameter_dict"][
"output_morph_dir"]
input_morph_dir = run_simulation["output_parameter_dict"][
"input_morph_dir"]
morphology = run_simulation["output_parameter_dict"]["morphology"]
morph_dir = os.path.join(output_morph_dir,
os.path.splitext(morphology)[0], "morphology")
output_morphology = hf.load_morphology_xml(
os.path.join(morph_dir, morphology))
expected_morphology = hf.load_morphology_xml(
os.path.join(
input_morph_dir,
"FG",
morphology.replace(".xml", "_post_fine_graining.xml"),
))
self.compare_equal(expected_morphology, response=output_morphology)
def test_check_morphology_final_output_pickle(self, run_simulation):
output_morph_dir = run_simulation["output_parameter_dict"][
"output_morph_dir"]
morphology = run_simulation["output_parameter_dict"]["morphology"]
morph_dir = os.path.join(output_morph_dir,
os.path.splitext(morphology)[0], "morphology")
final_MD_output = hf.load_morphology_xml(
os.path.join(morph_dir, "final_" + morphology))
self.compare_equal(
final_MD_output,
response=run_simulation["output_AA_morphology_dict"])
def main():
list_of_files = sys.argv[1:]
if len(list_of_files) < 1:
print("No files requested to convert!")
exit()
for file_name in list_of_files:
print("Fixing the images for {:s}...".format(file_name))
morphology = hf.load_morphology_xml(file_name)
morphology = zero_out_images(morphology)
bond_dict = get_bond_dict(morphology)
morphology = check_bonds(morphology, bond_dict)
file_directory, split_file_name = os.path.split(file_name)
hf.write_morphology_xml(
morphology,
os.path.join(file_directory, "".join(["image_fix_", split_file_name])),
)
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
"-m",
"--molecule_source",
required=False,
help="""Specify the source of the add_hydrogens dictionary and sigma value.
This can be in the form of a python script which returns a function of the
dictionary and sigma or the name of the molecule.""",
)
args, input_files = parser.parse_known_args()
hydrogens_to_add, sigma_val = find_information(args)
for input_file in input_files:
# This dictionary has keys of the atom type, and values where the first
# element is the number of bonds required for us to add a hydrogen to
# the atom and the second element of the value defines how many
# hydrogens to add to said atom.
print(
"THIS FUNCTION IS SET UP TO USE A DICTIONARY TO DEFINE HOW MANY HYDROGENS "
" TO ADD TO BONDS OF A SPECIFIC TYPE WITH A CERTAIN NUMBER OF BONDS"
)
print(hydrogens_to_add)
print(
"IF THE ABOVE DICTIONARY DOESN'T LOOK RIGHT, PLEASE TERMINATE NOW AND "
" IGNORE ANY OUTPUTS UNTIL THE DICTIONARY HAS BEEN RECTIFIED"
)
print("Additionally, we're using a sigma value of", sigma_val)
morphology_dict = hf.load_morphology_xml(input_file, sigma=sigma_val)
# We MUST fix the images first, otherwise the hydrogens will be put in
# incorrectly.
morphology_dict = fi.zero_out_images(morphology_dict)
bond_dict = fi.get_bond_dict(morphology_dict)
morphology_dict = fi.check_bonds(morphology_dict, bond_dict)
# Now we can safely obtain the unwrapped positions
morphology_dict = hf.add_unwrapped_positions(morphology_dict)
hydrogen_positions = calculate_hydrogen_positions(
morphology_dict, hydrogens_to_add
)
morphology_dict = add_hydrogens_to_morph(
morphology_dict, hydrogen_positions
)
morphology_dict = hf.add_wrapped_positions(morphology_dict)
hf.write_morphology_xml(
morphology_dict,
input_file.replace(".xml", "_AA.xml"),
check_wrapped_posns=False,
)
def __init__(self, morphology_xml, morphology_name, parameter_dict,
chromophore_list):
# Need to save the parameter_dict in full as well as its component
# values because we're going to update the parameterDict with the new
# type mappings by the end of this code module.
self.parameter_dict = parameter_dict
# Import parameters from the parXX.py
for key, value in parameter_dict.items():
self.__dict__[key] = value
self.xml_path = morphology_xml
self.morphology_name = morphology_name
# self.inputSigma is the `compression value' in Angstroms that has been
# used to scale the morphology
# E.G. the P3HT template uses sigma = 1, but the Marsh morphologies use
# sigma = 3.
self.CG_dictionary = hf.load_morphology_xml(self.xml_path,
sigma=self.input_sigma)
self.CG_dictionary = hf.add_unwrapped_positions(self.CG_dictionary)
self.chromophore_list = chromophore_list
def __init__(
self,
molecule_index,
site_IDs,
CG_dictionary,
molecule_lengths,
rolling_AA_index,
ghost_dictionary,
parameter_dict,
):
# This class sees individual molecules.
self.no_atoms_in_morphology = rolling_AA_index
self.molecule_index = molecule_index
self.molecule_lengths = molecule_lengths
self.site_IDs = site_IDs
self.CG_dictionary = CG_dictionary
# Get the dictionary of all the CG sites in this molecule
# self.CGMonomerDictionary = self.getCGMonomerDict()
# Import the parXX.py parameters
for key, value in parameter_dict.items():
self.__dict__[key] = value
self.AA_templates_dictionary = {}
# Load the template file for each CG atom
for CG_atom_type in list(self.CG_to_template_files.keys()):
template_dictionary = hf.load_morphology_xml(
os.path.join(
self.CG_to_template_dirs[CG_atom_type],
self.CG_to_template_files[CG_atom_type],
)
)
template_dictionary = self.remap_atom_types(
template_dictionary,
parameter_dict["new_type_mappings"][CG_atom_type],
)
template_dictionary = hf.add_unwrapped_positions(
template_dictionary
)
self.AA_templates_dictionary[CG_atom_type] = template_dictionary
fine_grained = self.run_fine_grainer(ghost_dictionary)
self.AA_dictionary = fine_grained[0]
self.atom_ID_lookup_table = fine_grained[1]
self.ghost_dictionary = fine_grained[2]
def main(
AA_morphology_dict,
CG_morphology_dict,
CG_to_AAID_master,
parameter_dict,
chromophore_list,
):
# Get the random seed now for all the child processes
if parameter_dict["random_seed_override"] is not None:
np.random.seed(parameter_dict["random_seed_override"])
# Main execution function for run_HOOMD that performs the required MD phases
# First, scale the input morphology based on the pair potentials such that
# the distances and energies are normalised to the strongest pair
# interaction and the diameter of the largest atom (makes it easier on
# HOOMDs calculations and ensures that T = 1.0 is an interesting temperature
# threshold)
current_files = os.listdir(
os.path.join(
parameter_dict["output_morph_dir"],
os.path.splitext(parameter_dict["morphology"])[0],
"morphology",
)
)
# sScale, eScale = obtainScaleFactors(parameterDict)
print("Under the hood eScaling and sScaling has been disabled.")
s_scale = 1.0
e_scale = 1.0
# Only scale the morphology if it hasn't been already
if (parameter_dict["overwrite_current_data"] is False) and (
"".join(["phase0_", parameter_dict["morphology"]]) in current_files
):
pass
else:
scale_morphology(AA_morphology_dict, parameter_dict, s_scale, e_scale)
# Reset logfile
try:
os.remove(
os.path.join(
parameter_dict["output_morph_dir"],
os.path.splitext(parameter_dict["morphology"])[0],
"morphology",
"".join(
[
"energies_",
os.path.splitext(parameter_dict["morphology"])[0],
".log",
]
),
)
)
except OSError:
pass
# Perform each molecular dynamics phase as specified in the parXX.py
for phase_no in range(parameter_dict["number_of_phases"]):
input_file = "phase{0:d}_{1:s}".format(phase_no, parameter_dict["morphology"])
output_file = "phase{0:d}_{1:s}".format(
phase_no + 1, parameter_dict["morphology"]
)
if output_file in current_files:
if parameter_dict["overwrite_current_data"] is False:
print(output_file, "already exists. Skipping...")
continue
md_phase(
AA_morphology_dict,
CG_morphology_dict,
CG_to_AAID_master,
parameter_dict,
phase_no,
os.path.join(
parameter_dict["output_morph_dir"],
os.path.splitext(parameter_dict["morphology"])[0],
"morphology",
input_file,
),
os.path.join(
parameter_dict["output_morph_dir"],
os.path.splitext(parameter_dict["morphology"])[0],
"morphology",
output_file,
),
s_scale,
e_scale,
).optimise_structure()
final_xml_name = os.path.join(
parameter_dict["output_morph_dir"],
os.path.splitext(parameter_dict["morphology"])[0],
"morphology",
"".join(["final_", parameter_dict["morphology"]]),
)
if "".join(["final_", parameter_dict["morphology"]]) not in current_files:
# Now all phases are complete, remove the ghost particles from the
# system
print("Removing ghost particles to create final output...")
remove_ghost_particles(
os.path.join(
parameter_dict["output_morph_dir"],
os.path.splitext(parameter_dict["morphology"])[0],
"morphology",
output_file,
),
final_xml_name,
sigma=s_scale,
)
# Finally, update the pickle file with the most recent and realistic
# AAMorphologyDict so that we can load it again further along the pipeline
AA_morphology_dict = hf.load_morphology_xml(final_xml_name)
# Now that we've obtained the final fine-grained morphology, we need to fix
# the images to prevent issues with obtaining the chromophores and running
# them through the ZINDO/S calculations later...
AA_morphology_dict = hf.fix_images(AA_morphology_dict)
# ...add in the unwrapped positions...
AA_morphology_dict = hf.add_unwrapped_positions(AA_morphology_dict)
# ...rewrite the final morphology xml...
hf.write_morphology_xml(AA_morphology_dict, final_xml_name)
# ...and write the pickle file.
hf.write_pickle(
(
AA_morphology_dict,
CG_morphology_dict,
CG_to_AAID_master,
parameter_dict,
chromophore_list,
),
os.path.join(
parameter_dict["output_morph_dir"],
os.path.splitext(parameter_dict["morphology"])[0],
"code",
"".join([os.path.splitext(parameter_dict["morphology"])[0], ".pickle"]),
),
)
return (
AA_morphology_dict,
CG_morphology_dict,
CG_to_AAID_master,
parameter_dict,
chromophore_list,
)
