atommap_eval

Evaluate the equivalence of atom-mapped reaction SMILES using graph-based isomorphism.

Overview

atommap_eval is a Python package for comparing two atom-mapped reactions and determining whether they are chemically equivalent, using their graph (networkx) representation and RDKit.

How it works:

• Optional preprocessing: "Canonicalization" and standardization of reaction SMILES to ensure all reactions are in the right format.
• Reactions graphs construction with atom-level / bond-level attributes and mapping
• Graph isomorphism checks using networkx.is_isomorphic()

It allows consistent evaluation of atom-mapping validity (e.g. against a ground truth atom-mapped reaction) by taking into account equivalence of some atoms (i.e. all CH3 in t-Bu are equivalent, any shuffling of atom-map indices should not impact correctness of the mapping)

Warning: tautomeric mappings are not considered equivalent even though from a chemist's perspective they are. Because template extraction of the underlying reactivity would yield different results. Flags for tautomers will however be implemented in further implementations to better deal with this specific case.

By default, if the isomorphism takes more than 10 seconds, it is interrupted and returns None with status "timeout".

Next steps:

• clean preprocessing implementation
• test CLI for >1.0.0
• update all tests >1.0.0
• define clearly how evaluation needs to be considered and what are edge cases examples

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Installation

Quick install for users (pip)

pip install atommap-eval

For developers

# Clone the repo and install in editable mode
git clone https://github.com/yvsgrndjn/atommap_eval.git
cd atommap_eval
pip install -e ".[dev]"

or in case you want to create a new environment with Conda:

conda create -n atommap_eval python=3.9 -c conda-forge rdkit
conda activate atommap_eval
pip install -e ".[dev]"

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Usage

Preprocessing

Preprocessing helps format atom-mapped reactions for a fair evaluation. It is split in 2 parts:

• canonicalization + sanitization : sorts reaction SMILES and atom-mapping indices deterministically. Sanitizes reactions. Returns None if one of the steps fails (associated with flags A, B, C, S )
• Format analyis : raises specific flags (D) if preprocessing worked but the reaction format will lead to a negative evaluation.

To preprocess data, either use the simple wrapper if it matches your needs:

import atommap_eval.preprocess as preprocess

preprocess_df = preprocess.preprocess_dataset(df, path_to_save)

Python

If you have few examples, use the following:

# simple case
from atommap_eval.evaluator import are_atom_maps_equivalent

gt = "[C:1](=[O:2])[O-:3].[H+:4]>>[C:1](=[O:2])[OH:3]"
pred = "[H+:4].[C:1](=[O:2])[O-:3]>>[C:1](=[O:2])[OH:3]"
result = are_atom_maps_equivalent(gt, pred)
print(result) # True

However, if you have more reactions to evaluate, use:

from atommap_eval.pair_evaluation import evaluate_pairs_batched

# `pairs` is either a list of tuples (rxn1, rxn2) or ReactionPair objects from atommap_eval.data_models
# for example if you store reactions in `your_df` under columns "ground_truth_rxn" and "predicted_rxn":
pairs = [
    ReactionPair(row.ground_truth_rxn, row.predicted_rxn)
    for _, row in your_df.iterrows()
]

results = evaluate_pairs_batched(pairs)
# results is a list of tuples (result: bool, status: str) where status can be "ok", "timeout", "error:{e}"

CLI

atommap_eval reactions.csv -f csv -p 4 -o results.csv

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Project structure

src/atommap_eval/
├── preprocess.py
├── cli.py
├── data_models.py
├── evaluator.py
├── input_io.py
├── pair_evaluation.py
├── rxn_graph.py
├── rxnmapper_utils.py
tests/

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Development

Run tests:

make test

Format code:

make format

Lint:

make lint

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Test examples

Unit tests are located under test/ and cover evaluator logic, CLI execution, and multiprocessing correctness.

License

MIT License © 2025 Yves Grandjean