The only function needed to convert a LaTeX string into a SymPy expression. Args: s (str): The input LaTeX string. It should be a val

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Lower text and remove punctuation, articles and extra whitespace.

Lower text and remove punctuation, extra whitespace.

Compute normalized Smith-Waterman score for protein sequences. Args: seq1, seq2 (str): Protein sequences (uppercase letters)

Get the frame-based position of the given global position Args: pos (): the global position of shape (*, 3) Ret

Input a string like below: xxx[[5]]xxx, and extract the score

Predict win rates between all models using their ELO ratings. Args: ratings_df (pd.DataFrame): DataFrame containing model ratings

In BT we only need the unique (matchup,outcome) sets along with the weights of how often they occur.

Read a JSONL file and return its contents as a list of dictionaries. Args: file_path: Path to the JSONL file Returns:

Remove invisible characters.

Remove the overall {xxx} brace.

Reset stdout and stderr, also change logger stream handler.

Normalizes content for rule 5. Args: content (str): The content to normalize. Returns: list: Sorted list of

Calculates retrosynthesis prediction accuracy. Args: predictions (list): A flat list of predicted SMILES strings.

Strips off the changes.

Convert a SymPy expression into a tree structure. This function takes a SymPy expression and recursively converts it into a tree represen

move to angstrom Args: in_place: if to use in_place operation Returns:

Dump the result to a json file.

Dump the result to a json file.

Dump the result to a json file.

Dump the result to a json file.

Dump the result to a json file.

Dump the result to a json file.

Computes the similarity score and distance metrics between two LaTeX expressions. This function evaluates the equivalence of two mathematical