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Merge remote-tracking branch 'remotes/origin/main' into feature/add-typhoon
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commit
e454b2eeb6
3 changed files with 69 additions and 18 deletions
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@ -1,6 +1,8 @@
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import random
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from internbootcamp.bootcamp.base import Basebootcamp
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from internbootcamp.libs.chemStructure2Property.ChemStructureGenerator import InChIGenerator
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from .utils import last_boxed_only_string, remove_boxed
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from internbootcamp.bootcamp.ChemStructure2Property.utils import last_boxed_only_string, remove_boxed
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from rdkit import Chem
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from rdkit.Chem import Crippen
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@ -18,7 +20,11 @@ class InChI2logPbootcamp(Basebootcamp):
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生成一组数字和目标值。
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"""
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self.InChIGenerator = InChIGenerator(max_atoms=self.max_atoms, min_atoms=self.min_atoms, elements=None, seed=None)
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return self.InChIGenerator.generate_n_valid_inchi(1)[0]
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inchis = self.InChIGenerator.generate_n_valid_inchi(10)
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# print(inchis)
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n = random.randint(0, 9)
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# print(n)
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return inchis[n]
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def prompt_func(self, InChI) -> str:
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@ -45,9 +51,10 @@ class InChI2logPbootcamp(Basebootcamp):
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return remove_boxed(output)
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@classmethod
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def _verify_correction(cls, solution, InChI)->bool:
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def _verify_correction(cls, solution, InChI) -> float:
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"""
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Verify the correction of the solution.
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Verify the correction of the solution and return a score between 0 and 1.
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The score is based on the relative error with respect to a maximum relative error of 0.1.
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"""
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mol = Chem.MolFromInchi(InChI)
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true_logp = Crippen.MolLogP(mol)
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@ -55,6 +62,27 @@ class InChI2logPbootcamp(Basebootcamp):
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# Handle case where true_logp is 0
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if true_logp == 0:
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return abs(solution_float) <= 0.01 # Just check if solution is close to 0
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# If true_logp is 0, we check how close the solution is to 0
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relative_error = abs(solution_float)
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else:
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return abs(true_logp - solution_float)/abs(true_logp) <= 0.01
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# Calculate the relative error
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relative_error = abs(true_logp - solution_float) / abs(true_logp)
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# Define the maximum allowed relative error
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max_relative_error = 0.1
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# Calculate the score based on the relative error
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if relative_error >= max_relative_error:
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return 0.0 # Error is too large, score is 0
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else:
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# Linear interpolation: score decreases linearly from 1 to 0 as error goes from 0 to max_relative_error
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return 1.0
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return 1 - (relative_error / max_relative_error) * 0.5 ## For RL
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if __name__ == "__main__":
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bootcamp = InChI2logPbootcamp()
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while True:
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case = bootcamp.case_generator()
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print('case')
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print(case)
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input()
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@ -1,3 +1,5 @@
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import random
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from internbootcamp.bootcamp.base import Basebootcamp
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from internbootcamp.libs.chemStructure2Property.ChemStructureGenerator import SMILESGenerator
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from .utils import last_boxed_only_string, remove_boxed
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@ -19,7 +21,7 @@ class SMILES2logPbootcamp(InChI2logPbootcamp):
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生成一组数字和目标值。
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"""
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self.SMILESGenerator = SMILESGenerator(min_len=self.min_len, max_len=self.max_len, seed=None)
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return self.SMILESGenerator.generate_n_valid_smiles(1)[0]
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return self.SMILESGenerator.generate_n_valid_smiles(10)[random.randint(0, 9)]
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def prompt_func(self, SMILES) -> str:
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@ -31,14 +33,35 @@ class SMILES2logPbootcamp(InChI2logPbootcamp):
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@classmethod
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def _verify_correction(cls, solution, SMILES)->bool:
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def _verify_correction(cls, solution, SMILES) -> float:
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"""
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Verify the correction of the solution.
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Verify the correction of the solution and return a score between 0 and 1.
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The score is based on the relative error with respect to a maximum relative error of 0.1.
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"""
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mol = Chem.MolFromSmiles(SMILES)
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if mol is None:
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raise ValueError("Invalid SMILES string provided.")
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true_logp = Crippen.MolLogP(mol)
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solution_float = float(solution)
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# print('true_logp: ', true_logp, ' solution_float: ', solution_float)
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# Handle case where true_logp is 0
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if true_logp == 0:
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return abs(solution_float) <= 0.01 # Just check if solution is close to 0
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# If true_logp is 0, we check how close the solution is to 0
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relative_error = abs(solution_float)
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else:
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return abs(true_logp - solution_float)/abs(true_logp) <= 0.01
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# Calculate the relative error
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relative_error = abs(true_logp - solution_float) / abs(true_logp)
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# Define the maximum allowed relative error
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max_relative_error = 0.1
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# Calculate the score based on the relative error
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if relative_error >= max_relative_error:
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return 0.0 # Error is too large, score is 0
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else:
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# Linear interpolation: score decreases linearly from 1 to 0 as error goes from 0 to max_relative_error
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return 1.0
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return 1 - (relative_error / max_relative_error) * 0.5 ## For RL
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@ -9,7 +9,7 @@ class InChIGenerator:
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def __init__(self, max_atoms=15, min_atoms=3, elements=None,
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seed=None):
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RDLogger.DisableLog('rdApp.*')
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random.seed(42) if seed is None else random.seed(seed)
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random.seed(seed)
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self.max_atoms = max_atoms
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self.min_atoms = min_atoms
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if elements is None:
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@ -123,7 +123,7 @@ class SMILESGenerator:
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def __init__(self, min_len=5, max_len=25,
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seed=None):
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RDLogger.DisableLog('rdApp.*')
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random.seed(42) if seed is None else random.seed(seed)
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random.seed(seed)
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self.min_len = min_len
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self.max_len = max_len
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