class GuessIonTests(unittest.TestCase):
geneSet = genetic.generate_geneset()
df = genetic.load_data("saltInfo.csv")
df = df['anion_SMILES'].unique()
ohPickMe = random.sample(range(df.shape[0]), 1)
anion = Chem.MolFromSmiles(df[ohPickMe[0]])
def test_1_density(self):
target = random.sample(range(800, 1500), 1)[0]
self.guess_password(target)
def test_benchmark(self):
genetic.Benchmark.run(self.test_1_density)
def guess_password(self, target):
startTime = datetime.datetime.now()
def fnGetFitness(genes):
return get_fitness(self.anion, genes, target)
def fnDisplay(candidate, mutation):
display(candidate, mutation, startTime)
def fnShowIon(genes, target, mutation_attempts):
show_ion(genes, target, mutation_attempts)
optimalFitness = 0.99
best = genetic.get_best(fnGetFitness, optimalFitness, self.geneSet,
fnDisplay, fnShowIon, target)
return best
def _guess_password(target, anion_smiles, parent_candidates, models, deslists,
seed=None, hull=None):
"""
for interacting with the main engine. Contains helper functions
to pass to the engine what it expects
"""
startTime = datetime.datetime.now()
anion = Chem.MolFromSmiles(anion_smiles)
def fnGetFitness(genes):
return _get_fitness(anion, genes, target, models, deslists)
def fndisplay(candidate, mutation):
_display(candidate, mutation, startTime)
def fnShowIon(genes, target, mutation_attempts, sim_score,
molecular_relative):
_show_ion(genes, target, mutation_attempts, sim_score,
molecular_relative, models, deslists, anion_smiles)
optimalFitness = 0.95
geneSet = genetic.generate_geneset()
best = genetic.get_best(fnGetFitness, optimalFitness, geneSet,
fndisplay, fnShowIon, target,
parent_candidates, seed=seed, convex_strategy=hull)
return best
class GuessIonTests(unittest.TestCase):
geneSet = genetic.generate_geneset()
df = salty.load_data("cationInfo.csv")
parent_candidates = df['smiles'].unique()
df = salty.load_data("anionInfo.csv")
df = df['smiles'].unique()
random.seed(1234)
ohPickMe = random.sample(range(df.shape[0]), 1)
anion = Chem.MolFromSmiles(df[ohPickMe[0]])
def test_1_density(self):
target = 1250
self.guess_password(target)
def test_benchmark(self):
genetic.Benchmark.run(self.test_1_density)
def guess_password(self, target):
startTime = datetime.datetime.now()
def fnGetFitness(genes, target):
return get_fitness(self.anion, genes, target)
def fnDisplay(candidate, mutation, target):
display(candidate, mutation, startTime)
def fnShowIon(genes, target, mutation_attempts, sim_score,
molecular_relative):
show_ion(genes, target, mutation_attempts, sim_score,
molecular_relative, self.anion)
optimalFitness = 0.9
best = genetic.get_best(fnGetFitness,
optimalFitness,
self.geneSet,
fnDisplay,
fnShowIon,
target,
self.parent_candidates,
seed=123)
cation = best.Mol
anion = self.anion
# Uncomment PDB lines to wrote PDB file
# cation = Chem.AddHs(best.Mol)
# Chem.EmbedMolecule(cation, Chem.ETKDG())
# Chem.UFFOptimizeMolecule(cation)
# Chem.rdmolfiles.MolToPDBFile(cation, "cation_test.pdb")
# anion = Chem.AddHs(self.anion)
# Chem.EmbedMolecule(anion, Chem.ETKDG())
# Chem.UFFOptimizeMolecule(anion)
# Chem.rdmolfiles.MolToPDBFile(anion, "anion_test.pdb")
return cation, anion
def _guess_password(target,
anion_smiles,
parent_candidates,
models,
deslists,
seed=None,
hull=None,
simplex=None,
exp_data=None,
verbose=0,
hull_bounds=[0, 1],
inner_search=True,
parent_cap=25,
mutation_cap=1000):
"""
for interacting with the main engine. Contains helper functions
to pass to the engine what it expects
"""
startTime = datetime.datetime.now()
anion = Chem.MolFromSmiles(anion_smiles)
def fnGetFitness(genes):
return _get_fitness(anion, genes, target, models, deslists)
def fndisplay(candidate, mutation):
genes = candidate.Genes
scr, pre = _get_fitness(anion, genes, target, models, deslists)
_display(candidate, mutation, startTime, scr, pre, target)
def fnShowIon(genes, target, mutation_attempts, sim_score,
molecular_relative):
_show_ion(genes, target, mutation_attempts, sim_score,
molecular_relative, models, deslists, anion_smiles, exp_data)
optimalFitness = 0.95
geneSet = genetic.generate_geneset()
best = genetic.get_best(fnGetFitness,
optimalFitness,
geneSet,
fndisplay,
fnShowIon,
target,
parent_candidates,
seed=seed,
hull=hull,
simplex=simplex,
verbose=verbose,
hull_bounds=hull_bounds,
inner_search=inner_search,
parent_cap=parent_cap,
mutation_cap=mutation_cap)
return best
def _guess_password(target, anion, parent_candidates, model_ID):
"""
for interacting with the main engine. Contains helper functions
to pass to the engine what it expects
"""
startTime = datetime.datetime.now()
def fnGetFitness(genes):
return _get_fitness(anion, genes, target, model_ID)
def fndisplay(candidate, mutation):
_display(candidate, mutation, startTime)
def fnShowIon(genes, target, mutation_attempts, sim_score,
molecular_relative):
_show_ion(genes, target, mutation_attempts, sim_score,
molecular_relative, model_ID, anion)
optimalFitness = 0.99
geneSet = genetic.generate_geneset()
best = genetic.get_best(fnGetFitness, optimalFitness, geneSet, fndisplay,
fnShowIon, target, parent_candidates)
return best
class GuessIonTests(unittest.TestCase):
geneSet = genetic.generate_geneset()
df = salty.load_data("cationInfo.csv")
df = df.loc[df["name"].str.contains("imid", case=False)]
class GuessIonTests(unittest.TestCase):
geneSet = genetic.generate_geneset()
def test_1_similarity_map(self):
df = genetic.load_data("saltInfo.csv")
df = df.loc[df["cation_name"].str.contains("imid", case=False)]