def create_label_file(
molecule_file="molecule.sdf",
molecule_attributes_file="molecule_attributes.yaml",
reaction_file="reaction.yaml",
label_file="label.yaml",
):
"""
Convert input molecule, attributes, and reaction file to an atom mapped label file.
The molecule, attributes, and label file can then be used by the training code.
See the `examples/train` directory for example molecule, attributes, and reaction file.
Args:
molecule_file (str): path to the input molecule file
molecule_attributes_file (str): path to the input molecule attributes file
reaction_file (str): path to the reaction file
label_file (str or None): path to the output label file. If `None` no file will
be written, but the molecules and reactions will be directly returned.
"""
molecules = _read_molecules(molecule_file, molecule_attributes_file)
reactions = _read_reactions(molecules, reaction_file)
rxn_coll = ReactionCollection(reactions)
if label_file is not None:
out = rxn_coll.create_regression_dataset_reaction_network_simple(
struct_file=os.devnull, label_file=label_file, feature_file=None)
else:
out = rxn_coll.create_regression_dataset_reaction_network_simple(
write_to_file=False)
rdmols, rxns, attrs = out
return rdmols, attrs, rxns
def prepare_data(self):
reactions = self.read_input()
extractor = ReactionCollection(reactions)
out = extractor.create_regression_dataset_reaction_network_simple(
write_to_file=False)
return out
def plot_reaction_energy_difference_arcoss_reactant_charge(
filename="~/Applications/db_access/mol_builder/reactions.pkl",
# filename="~/Applications/db_access/mol_builder/reactions_n200.pkl",
# filename="~/Applications/db_access/mol_builder/reactions_C5H8Li1O3.pkl",
):
"""
Plot a histogram showing the energy difference of the same reaction between
different charges.
e.g.
A(+1) -> B(+1) + C(0) G1
A(0) -> B(0) + C(0) G2
Delta G = G2-G2
we plot delta G
"""
def plot_hist(data, filename, s1, s2, c1, c2):
fig = plt.figure()
ax = fig.gca()
ax.hist(data, 20)
ax.set_xlabel("E diff. species:{} {}; charge {} {}".format(
s1, s2, c1, c2))
ax.set_ylabel("counts")
fig.savefig(filename, bbox_inches="tight")
def extract_one(extractor, s1=None, s2=None):
results = extractor.group_by_reactant_charge_pair()
for charge in [(-1, 0), (-1, 1), (0, 1)]:
reactions = results[charge]
energies = []
for rxn1, rxn2 in reactions:
e_diff = rxn2.get_free_energy() - rxn1.get_free_energy()
energies.append(e_diff)
outname = "~/Applications/db_access/mol_builder/reactant_e_diff/"
outname += "reactant_e_diff_{}{}_{}_{}.pdf".format(s1, s2, *charge)
create_directory(outname)
outname = to_path(outname)
plot_hist(energies, outname, s1, s2, *charge)
# all species together
extractor = ReactionCollection.from_file(filename)
all_reactions = extractor.reactions
extract_one(extractor)
# species pairs
species = ["H", "Li", "C", "O", "F", "P"]
for s1, s2 in itertools.combinations_with_replacement(species, 2):
extractor = ReactionCollection(molecules=None, reactions=all_reactions)
extractor.filter_reactions_by_bond_type_and_order(bond_type=[s1, s2])
extract_one(extractor, s1, s2)
def prepare_data(self):
"""
Convert to standard format that the fitting code uses.
"""
self.read_molecules()
self.read_reactions()
extractor = ReactionCollection(self.reactions)
mols, labls, feats = extractor.create_regression_dataset_reaction_network_simple(
write_to_file=False)
return mols, labls, feats
def nrel_create_struct_label_dataset_bond_based_regression(
filename="~/Documents/Dataset/NREL_BDE/rdf_data_190531_n200.csv", ):
reactions = read_nrel_bde_dataset(filename)
extractor = ReactionCollection(reactions)
extractor.create_struct_label_dataset_bond_based_regression(
struct_file=
"~/Applications/db_access/nrel_bde/nrel_struct_bond_rgrn_n200.sdf",
label_file=
"~/Applications/db_access/nrel_bde/nrel_label_bond_rgrn_n200.yaml",
feature_file=
"~/Applications/db_access/nrel_bde/nrel_feature_bond_rgrn_n200.yaml",
)
def reactant_broken_bond_fraction():
"""
Get the fraction of bonds that broken with respect to all the bonds in a reactant.
Note, this requires that when extracting the reactions, all the reactions
related to a reactant (ignore symmetry) should be extracted.
"""
filename = "~/Applications/db_access/mol_builder/reactions_n200.pkl"
# filename = "~/Applications/db_access_newest/mol_builder/reactions.pkl"
# filename = "~/Applications/db_access_newest/mol_builder/reactions_qc.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_qc_ws.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_qc_ws_charge0.pkl"
extractor = ReactionCollection.from_file(filename)
groups = extractor.group_by_reactant()
num_bonds = []
frac = []
for reactant, rxns in groups.items():
rmb = ReactionsMultiplePerBond(reactant, rxns)
rsbs = rmb.group_by_bond()
tot = len(rsbs)
bond_has_rxn = [True if len(x.reactions) > 0 else False for x in rsbs]
num_bonds.append(tot)
frac.append(sum(bond_has_rxn) / tot)
print("### number of bonds in dataset (mean):", np.mean(num_bonds))
print("### number of bonds in dataset (median):", np.median(num_bonds))
print("### broken bond ratio in dataset (mean):", np.mean(frac))
print("### broken bond ratio in dataset (median):", np.median(frac))
def create_struct_label_dataset_bond_based_regression(
# filename="~/Applications/db_access/mol_builder/reactions_qc.pkl",
filename="~/Applications/db_access/mol_builder/reactions_n200.pkl", ):
extractor = ReactionCollection.from_file(filename)
##############
# filter by reactant attributes
##############
# extractor.filter_reactions_by_reactant_attribute(
# key="id", values=["5e2a05838eab11f1fa104e29", "5e2a05d28eab11f1fa107899"]
# )
# extractor.filter_reactions_by_reactant_attribute(
# key="formula", values=["C3H4O3", "C3H3O3"]
# )
# extractor.filter_reactions_by_reactant_attribute(key="charge", values=[1])
# ##############
# # filter C-C bond
# ##############
# extractor.filter_reactions_by_bond_type_and_order(bond_type=("C", "C"))
extractor.create_struct_label_dataset_bond_based_regression(
struct_file="~/Applications/db_access/mol_builder/struct_n200.sdf",
label_file="~/Applications/db_access/mol_builder/label_n200.yaml",
feature_file="~/Applications/db_access/mol_builder/feature_n200.yaml",
# struct_file="~/Applications/db_access/mol_builder/struct_qc.sdf",
# label_file="~/Applications/db_access/mol_builder/label_qc.txt",
# feature_file="~/Applications/db_access/mol_builder/feature_qc.yaml",
group_mode="charge_0",
one_per_iso_bond_group=True,
)
def zinc_create_struct_label_dataset_reaction_network_based_regression(
# dirname="~/Documents/Dataset/ZINC_BDE_100",
dirname="~/Documents/Dataset/ZINC_BDE", ):
reactions = read_zinc_bde_dataset(dirname)
extractor = ReactionCollection(reactions)
extractor.create_regression_dataset_reaction_network_simple(
struct_file=
"~/Applications/db_access/zinc_bde/zinc_struct_rxn_ntwk_rgrn.sdf",
label_file=
"~/Applications/db_access/zinc_bde/zinc_label_rxn_ntwk_rgrn.yaml",
feature_file=
"~/Applications/db_access/zinc_bde/zinc_feature_rxn_ntwk_rgrn.yaml",
# struct_file="~/Applications/db_access/zinc_bde/zinc_struct_rxn_ntwk_rgrn_n200.sdf",
# label_file="~/Applications/db_access/zinc_bde/zinc_label_rxn_ntwk_rgrn_n200.yaml",
# feature_file="~/Applications/db_access/zinc_bde/zinc_feature_rxn_ntwk_rgrn_n200.yaml",
)
def zinc_create_struct_label_dataset_bond_based_regression(
dirname="~/Documents/Dataset/ZINC_BDE_100",
# dirname="~/Documents/Dataset/ZINC_BDE",
):
reactions = read_zinc_bde_dataset(dirname)
extractor = ReactionCollection(reactions)
extractor.create_struct_label_dataset_bond_based_regression(
struct_file=
"~/Applications/db_access/zinc_bde/zinc_struct_bond_rgrn.sdf",
label_file="~/Applications/db_access/zinc_bde/zinc_label_bond_rgrn.txt",
feature_file=
"~/Applications/db_access/zinc_bde/zinc_feature_bond_rgrn.yaml",
# struct_file="~/Applications/db_access/zinc_bde/zinc_struct_bond_rgrn_n200.sdf",
# label_file="~/Applications/db_access/zinc_bde/zinc_label_bond_rgrn_n200.txt",
# feature_file="~/Applications/db_access/zinc_bde/zinc_feature_bond_rgrn_n200.yaml",
group_mode="charge_0",
one_per_iso_bond_group=True,
)
def create_input_file_without_bond_mapping(
reaction_file,
mol_file="molecules.sdf",
mol_attr_file="molecule_attributes.yaml",
rxn_file="reactions.yaml",
):
rxn_coll = ReactionCollection.from_file(reaction_file)
rxn_coll.create_input_files(
mol_file,
mol_attr_file,
rxn_file,
)
def bond_energy_difference_in_molecule_nth_lowest():
"""
Get the nth lowest bond energy difference in molecules.
"""
def hist_analysis(data, xmin=0, xmax=1, num_bins=10, frac_all_data=True):
hist, bin_edge = np.histogram(data, bins=num_bins, range=(xmin, xmax))
outside = 0
for i in data:
if i > xmax:
outside += 1
if frac_all_data:
total = len(data)
else:
total = sum(hist)
print("Bond energy difference histogram")
print("energy counts %")
for i, n in enumerate(hist):
print("{:.2f}--{:.2f}: {} {:.1f}%".format(
bin_edge[i], bin_edge[i + 1], n, n / total * 100))
print("> {}: {} {:.1f}%".format(xmax, outside,
outside / total * 100))
filename = "~/Applications/db_access/mol_builder/reactions.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_n200.pkl"
########################
# nth lowest
########################
all_nth = [1, 2, 3, 4]
extractor = ReactionCollection.from_file(filename)
groups = extractor.group_by_reactant_lowest_energy()
for nth in all_nth:
bond_energy_diff = dict()
for rsr in groups:
energies = [rxn.get_free_energy() for rxn in rsr.reactions]
e_diff = [
abs(i - j) for i, j in itertools.combinations(energies, 2)
]
# get nth lowest
bond_energy_diff[rsr.reactant] = sorted(e_diff)[(nth - 1):nth]
diff = [v for k, v in bond_energy_diff.items()]
diff = np.concatenate(diff)
hist_analysis(diff, xmin=0, xmax=1, num_bins=10, frac_all_data=True)
hist_analysis(diff, xmin=0, xmax=0.1, num_bins=10, frac_all_data=False)
def create_struct_label_dataset_reaction_network_based_regression(
reaction_file,
struct_file="struct_rxn_ntwk_rgrn.sdf",
label_file="label_rxn_ntwk_rgrn.yaml",
feature_file="feature_rxn_ntwk_rgrn.yaml",
):
extractor = ReactionCollection.from_file(reaction_file)
extractor.create_struct_label_dataset_reaction_network_based_regression(
struct_file,
label_file,
feature_file,
group_mode="all",
one_per_iso_bond_group=True,
)
def bond_label_fraction(top_n=2):
"""
Get the fraction of each type of label 0 (low energy), 1 (high energy),
and 2 (unknown) in the dataset.
Note, this requires that when extracting the reactions, all the reactions
related to a reactant (ignore symmetry) should be extracted.
Note, here we analyze on the 0,0,0 type reactions.
"""
# filename = "~/Applications/db_access/mol_builder/reactions.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_n200.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_qc.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_qc_ws.pkl"
filename = "~/Applications/db_access/mol_builder/reactions_qc_ws_charge0.pkl"
extractor = ReactionCollection.from_file(filename)
groups = extractor.group_by_reactant_charge_0()
num_bonds = []
frac = defaultdict(list)
for ropb in groups:
counts = np.asarry([0, 0, 0])
all_none = True
for i, rxn in enumerate(ropb.order_reactions()):
energy = rxn.get_free_energy()
if energy is None:
counts[2] += 1
else:
all_none = False
if i < top_n:
counts[1] += 1
else:
counts[0] += 1
if all_none:
print(
"reactant {} {} has not broken bond reaction; should never happen"
.format(ropb.reactant.id, ropb.reactant.formula))
continue
n = len(ropb.order_reactions())
num_bonds.append(n)
frac = counts / n
print("### number of bonds in dataset (mean):", np.mean(num_bonds))
print("### number of bonds in dataset (median):", np.median(num_bonds))
for i, fr in enumerate(frac):
print(f"### label{i} bond ratio in dataset (mean): {np.mean(fr)}")
print(f"### label{i} bond ratio in dataset (mean): {np.median(fr)}")
def create_struct_label_dataset_reaction_based_regression(
filename="~/Applications/db_access/mol_builder/reactions_n200.pkl", ):
extractor = ReactionCollection.from_file(filename)
extractor.create_struct_label_dataset_reaction_based_regression(
struct_file=
"~/Applications/db_access/mol_builder/struct_rxn_rgrn_n200.sdf",
label_file=
"~/Applications/db_access/mol_builder/label_rxn_rgrn_n200.yaml",
feature_file=
"~/Applications/db_access/mol_builder/feature_rxn_rgrn_n200.yaml",
group_mode="all",
one_per_iso_bond_group=True,
)
def create_struct_label_dataset_reaction_network_based_classification(
reaction_file,
struct_file="struct_rxn_ntwk_clfn.sdf",
label_file="label_rxn_ntwk_clfn.yaml",
feature_file="feature_rxn_ntwk_clfn.yaml",
):
extractor = ReactionCollection.from_file(reaction_file)
extractor.create_struct_label_dataset_reaction_network_based_classification(
struct_file,
label_file,
feature_file,
group_mode="all",
top_n=2,
complement_reactions=True,
one_per_iso_bond_group=True,
)
def create_struct_label_dataset_mol_based():
filename = "~/Applications/db_access/mol_builder/reactions.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_n200.pkl"
# filename = "~/Applications/db_access/mol_builder/reactions_charge0.pkl"
extractor = ReactionCollection.from_file(filename)
extractor.create_struct_label_dataset_mol_based(
struct_file="~/Applications/db_access/mol_builder/struct_mol_based.sdf",
label_file="~/Applications/db_access/mol_builder/label_mol_based.txt",
feature_file=
"~/Applications/db_access/mol_builder/feature_mol_based.yaml",
# struct_file="~/Applications/db_access/mol_builder/struct_n200.sdf",
# label_file="~/Applications/db_access/mol_builder/label_n200.txt",
# feature_file="~/Applications/db_access/mol_builder/feature_n200.yaml",
# struct_file="~/Applications/db_access/mol_builder/struct_charge0.sdf",
# label_file="~/Applications/db_access/mol_builder/label_charge0.txt",
)
def create_struct_label_dataset_bond_based_classification(
# filename = "~/Applications/db_access/mol_builder/reactions.pkl",
filename="~/Applications/db_access/mol_builder/reactions_n200.pkl",
# filename="~/Applications/db_access/mol_builder/reactions_qc.pkl",
# filename="~/Applications/db_access/mol_builder/reactions_qc_wib.pkl",
):
extractor = ReactionCollection.from_file(filename)
extractor.create_struct_label_dataset_bond_based_classification(
struct_file=
"~/Applications/db_access/mol_builder/struct_bond_clfn_n200.sdf",
label_file=
"~/Applications/db_access/mol_builder/label_bond_clfn_n200.txt",
feature_file=
"~/Applications/db_access/mol_builder/feature_bond_clfn_n200.yaml",
# struct_file="~/Applications/db_access/mol_builder/struct_bond_clfn_qc.sdf",
# label_file="~/Applications/db_access/mol_builder/label_bond_clfn_qc.txt",
# feature_file="~/Applications/db_access/mol_builder/feature_bond_clfn_qc.yaml",
group_mode="charge_0",
top_n=2,
complement_reactions=False,
one_per_iso_bond_group=True,
)