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added Gval option to MOF RACs #194

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Dec 8, 2023
Merged

added Gval option to MOF RACs #194

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432ee72
added Gval option to MOF RACs
gianmarco-terrones Dec 8, 2023
81de14c
[pre-commit.ci] auto fixes from pre-commit hooks
pre-commit-ci[bot] Dec 8, 2023
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50 changes: 34 additions & 16 deletions molSimplify/Informatics/MOF/MOF_descriptors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,7 +110,7 @@ def load_sbu_lc_descriptors(sbupath):

return sbu_descriptor_path, sbu_descriptors, lc_descriptors

def gen_and_append_desc(temp_mol, target_list, depth, descriptor_names, descriptors, feature_type):
def gen_and_append_desc(temp_mol, target_list, depth, descriptor_names, descriptors, Gval, feature_type):
"""
Generate and append descriptors, both standard and delta.

Expand All @@ -126,6 +126,8 @@ def gen_and_append_desc(temp_mol, target_list, depth, descriptor_names, descript
The RAC descriptor names. Will be appended to.
descriptors : list
The RAC descriptor values. Will be appended to.
Gval : bool
Whether to use G value as RAC.
feature_type : str
Either 'lc' or 'func'.

Expand All @@ -139,10 +141,10 @@ def gen_and_append_desc(temp_mol, target_list, depth, descriptor_names, descript
The updated RAC descriptor values.
"""

results_dictionary = generate_atomonly_autocorrelations(temp_mol, target_list, depth=depth, loud=False, oct=False, polarizability=True)
results_dictionary = generate_atomonly_autocorrelations(temp_mol, target_list, depth=depth, loud=False, oct=False, polarizability=True, Gval=Gval)
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors, results_dictionary['colnames'], results_dictionary['results'], feature_type, 'all')

results_dictionary = generate_atomonly_deltametrics(temp_mol, target_list, depth=depth, loud=False, oct=False, polarizability=True)
results_dictionary = generate_atomonly_deltametrics(temp_mol, target_list, depth=depth, loud=False, oct=False, polarizability=True, Gval=Gval)
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors, results_dictionary['colnames'], results_dictionary['results'], f'D_{feature_type}', 'all')

return results_dictionary, descriptor_names, descriptors
Expand All @@ -153,7 +155,8 @@ def gen_and_append_desc(temp_mol, target_list, depth, descriptor_names, descript
# the vector to be of constant dimension so we can correlate the output property. #
#########################################################################################

def make_MOF_SBU_RACs(SBUlist, SBU_subgraph, molcif, depth, name, cell_v, anchoring_atoms, sbupath, linkeranchors_superlist, connections_list=False, connections_subgraphlist=False):
def make_MOF_SBU_RACs(SBUlist, SBU_subgraph, molcif, depth, name, cell_v, anchoring_atoms, sbupath, linkeranchors_superlist,
Gval, connections_list=False, connections_subgraphlist=False):
"""
Generated RACs on the SBUs of the MOF, as well as on the lc atoms (SBU-connected atoms of linkers).

Expand All @@ -177,6 +180,8 @@ def make_MOF_SBU_RACs(SBUlist, SBU_subgraph, molcif, depth, name, cell_v, anchor
Path of the folder to make a csv file in and TXT files containing connection index information.
linkeranchors_superlist : list of set
Coordinating atoms of linkers. Number of sets is the number of linkers.
Gval : bool
Whether to use G value as RAC.
connections_list : list of lists of int
Each inner list is its own separate linker. The ints are the atom indices of that linker. Length is # of linkers.
connections_subgraphlist : list of scipy.sparse.csr.csr_matrix
Expand Down Expand Up @@ -239,7 +244,7 @@ def make_MOF_SBU_RACs(SBUlist, SBU_subgraph, molcif, depth, name, cell_v, anchor
"""""""""
Generate all of the lc autocorrelations (from the connecting atoms)
"""""""""
results_dictionary, descriptor_names, descriptors = gen_and_append_desc(temp_mol, link_list, depth, descriptor_names, descriptors, 'lc')
results_dictionary, descriptor_names, descriptors = gen_and_append_desc(temp_mol, link_list, depth, descriptor_names, descriptors, Gval, 'lc')
"""""""""
If heteroatom functional groups exist (anything that is not C or H, so methyl is missed, also excludes anything lc, so carboxylic metal-coordinating oxygens skipped),
compile the list of atoms
Expand All @@ -253,10 +258,15 @@ def make_MOF_SBU_RACs(SBUlist, SBU_subgraph, molcif, depth, name, cell_v, anchor
Generate all of the functional group autocorrelations
"""""""""
if len(functional_atoms) > 0:
results_dictionary, descriptor_names, descriptors = gen_and_append_desc(temp_mol, functional_atoms, depth, descriptor_names, descriptors, 'func')
results_dictionary, descriptor_names, descriptors = gen_and_append_desc(temp_mol, functional_atoms, depth, descriptor_names, descriptors, Gval, 'func')
else: # There are no functional atoms.
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors,results_dictionary['colnames'],list([np.zeros(int(6*(depth + 1)))]),'func','all')
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors,results_dictionary['colnames'],list([np.zeros(int(6*(depth + 1)))]),'D_func','all')
if Gval:
num_atomic_properties = 7
else:
num_atomic_properties = 6

descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors,results_dictionary['colnames'],list([np.zeros(int(num_atomic_properties*(depth + 1)))]),'func','all')
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors,results_dictionary['colnames'],list([np.zeros(int(num_atomic_properties*(depth + 1)))]),'D_func','all')

for val in descriptors:
if not (type(val) == float or isinstance(val, np.float64)):
Expand Down Expand Up @@ -302,12 +312,12 @@ def make_MOF_SBU_RACs(SBUlist, SBU_subgraph, molcif, depth, name, cell_v, anchor
"""""""""
Generate all of the SBU based RACs (full scope, mc)
"""""""""
results_dictionary = generate_full_complex_autocorrelations(SBU_mol,depth=depth,loud=False,flag_name=False)
results_dictionary = generate_full_complex_autocorrelations(SBU_mol,depth=depth,loud=False,flag_name=False,Gval=Gval)
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors,results_dictionary['colnames'],results_dictionary['results'],'f','all')
#### Now starts at every metal on the graph and autocorrelates
results_dictionary = generate_multimetal_autocorrelations(molcif,depth=depth,loud=False)
results_dictionary = generate_multimetal_autocorrelations(molcif,depth=depth,loud=False,Gval=Gval)
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors, results_dictionary['colnames'],results_dictionary['results'],'mc','all')
results_dictionary = generate_multimetal_deltametrics(molcif,depth=depth,loud=False)
results_dictionary = generate_multimetal_deltametrics(molcif,depth=depth,loud=False,Gval=Gval)
descriptor_names, descriptors = append_descriptors(descriptor_names, descriptors,results_dictionary['colnames'],results_dictionary['results'],'D_mc','all')

# Some formatting
Expand All @@ -326,7 +336,7 @@ def make_MOF_SBU_RACs(SBUlist, SBU_subgraph, molcif, depth, name, cell_v, anchor
averaged_SBU_descriptors = np.mean(np.array(descriptor_list), axis=0) # Average the SBU RACs over all of the SBUs in the MOF.
return names, averaged_SBU_descriptors, lc_names, averaged_lc_descriptors

def make_MOF_linker_RACs(linkerlist, linker_subgraphlist, molcif, depth, name, cell_v, linkerpath, linkeranchors_superlist):
def make_MOF_linker_RACs(linkerlist, linker_subgraphlist, molcif, depth, name, cell_v, linkerpath, linkeranchors_superlist, Gval):
"""
Generate RACs on the linkers of the MOF.

Expand All @@ -348,6 +358,8 @@ def make_MOF_linker_RACs(linkerlist, linker_subgraphlist, molcif, depth, name, c
Path of the folder to make a csv file in and TXT files containing connection index information.
linkeranchors_superlist : list of set
Coordinating atoms of linkers. Number of sets is the number of linkers.
Gval : bool
Whether to use G value as RAC.

Returns
-------
Expand Down Expand Up @@ -401,6 +413,9 @@ def make_MOF_linker_RACs(linkerlist, linker_subgraphlist, molcif, depth, name, c

allowed_strings = ['electronegativity', 'nuclear_charge', 'ident', 'topology', 'size']
labels_strings = ['chi', 'Z', 'I', 'T', 'S']
if Gval:
allowed_strings.append('group_number')
labels_strings.append('Gval')
colnames = []
lig_full = list()

Expand Down Expand Up @@ -850,7 +865,8 @@ def detect_1D_rod(SBU_list, molcif, allatomtypes, cell_v, logpath, name):
write2file(logpath,"/%s.log"%name,tmpstr)

def get_MOF_descriptors(data, depth, path=False, xyzpath=False, graph_provided=False, wiggle_room=1,
max_num_atoms=2000, get_sbu_linker_bond_info=False, surrounded_sbu_file_generation=False, detect_1D_rod_sbu=False):
max_num_atoms=2000, get_sbu_linker_bond_info=False, surrounded_sbu_file_generation=False, detect_1D_rod_sbu=False,
Gval=False):
"""
Generates RAC descriptors on a MOF, assuming it has P1 symmetry.
Writes three files: sbu_descriptors.csv, linker_descriptors.csv, and lc_descriptors.csv
Expand Down Expand Up @@ -884,6 +900,8 @@ def get_MOF_descriptors(data, depth, path=False, xyzpath=False, graph_provided=F
Whether or not an XYZ file for each SBU, surrounded by its connected linkers, will be generated.
detect_1D_rod_sbu : bool
Whether or not to check if SBU is a 1D rod.
Gval : bool
Whether to use G value as RAC, by default False.

Returns
-------
Expand Down Expand Up @@ -1001,7 +1019,7 @@ def get_MOF_descriptors(data, depth, path=False, xyzpath=False, graph_provided=F
# print('##### METAL LIST2', metal_list, [molcif.getAtom(val).symbol() for val in list(metal_list)])
# print('##### all LIST2', metal_list, [val.symbol() for val in molcif.atoms])
[SBUlist.update(set([metal])) for metal in molcif.findMetal(transition_metals_only=False)] # Consider all metals as part of the SBUs.
[SBUlist.update(set(molcif.getBondedAtomsSmart(metal))) for metal in molcif.findMetal(transition_metals_only=False)] # atoms connected to metals. # TODO why use this over adj_matrix?
[SBUlist.update(set(molcif.getBondedAtomsSmart(metal))) for metal in molcif.findMetal(transition_metals_only=False)] # atoms connected to metals.
removelist = set()
[removelist.update(set([metal])) for metal in molcif.findMetal(transition_metals_only=False)] # Remove all metals as part of the SBUs.
for metal in removelist:
Expand Down Expand Up @@ -1176,8 +1194,8 @@ def get_MOF_descriptors(data, depth, path=False, xyzpath=False, graph_provided=F
"""""""""
if len(linker_subgraphlist)>=1: # Featurize cases that did not fail.
# try:
descriptor_names, descriptors, lc_descriptor_names, lc_descriptors = make_MOF_SBU_RACs(SBU_list, SBU_subgraphlist, molcif, depth, name, cell_v, anc_atoms, sbupath, linkeranchors_superlist, connections_list, connections_subgraphlist)
lig_descriptor_names, lig_descriptors = make_MOF_linker_RACs(linker_list, linker_subgraphlist, molcif, depth, name, cell_v, linkerpath, linkeranchors_superlist)
descriptor_names, descriptors, lc_descriptor_names, lc_descriptors = make_MOF_SBU_RACs(SBU_list, SBU_subgraphlist, molcif, depth, name, cell_v, anc_atoms, sbupath, linkeranchors_superlist, Gval, connections_list, connections_subgraphlist)
lig_descriptor_names, lig_descriptors = make_MOF_linker_RACs(linker_list, linker_subgraphlist, molcif, depth, name, cell_v, linkerpath, linkeranchors_superlist, Gval)
full_names = descriptor_names+lig_descriptor_names+lc_descriptor_names #+ ECFP_names
full_descriptors = list(descriptors)+list(lig_descriptors)+list(lc_descriptors)
print(len(full_names),len(full_descriptors))
Expand Down