/orcanizator

generate ORCA input files from SMILES

Primary LanguagePythonMIT LicenseMIT

orcanizator

generate ORCA input files from SMILES

Global Variables

  • ORCA_EXECUTABLE - it is a global variable, because I wanted it to appear on top of the file; it is utilised only by one function but it is meant to be changed by the user.

function orca_generator

orca_generator(smiles: str, nb: int) → None

Generate ORCA input file from SMILES. ORCA arguments are hardcoded into the function.

Arguments:

smiles {str} -- SMILES structure of the molecule.
nb {int} -- number. This will be the name of the input file.

function orca_reader

orca_reader(smiles: str, nb: int) → dict

Read following properties of ORCA output file:

  1. HOMO energy
  2. LUMO energy
  3. Dipole moment
  4. Isotropic polarizability
  5. Total thermal energy, U
  6. Total enthalpy, H
  7. Entropy term, S
  8. Gibbs free energy, G
  9. Rotational constant, A
  10. Rotational constant, B
  11. Rotational constant, C

Arguments:

smiles {str} -- SMILES structure of the molecule.
nb {int} -- number. This is the name of the output file to be read.

Returns: {dict} -- a dictionary of read properties.

function orcanize

orcanize(smiles: str, nb: int) → dict

This function does the following steps:

  1. Generate ORCA input file based on molecule SMILES by calling orca_generator function.
  2. Call ORCA job with generated input file.
  3. Read calculated properties from generated output file and return them as dictionary. This is done by calling orca_reader function.

SMILES of successfully processed molecules are saved into done.log file. The done.log also contains the number which is input and output files name. If there was an error in calculations, then the molecule's SMILES is saved into undone.log file.

Arguments:

smiles {str} -- [SMILES molecule structure]
nb {int} -- [Number. This is ORCA input and output file name]

Returns: {dict} -- [Dictionary of properties]

function orcanize_many

orcanize_many(molecules: List[str], save: bool = True) → DataFrame

Run orcanize function with a collection of SMILES.

Arguments:

molecules {Union[str]} -- collection of SMILES strings.
save {bool} -- save the pandas dataframe to csv(True, default) or not(False); by convention it is saved everytime ORCA successfully finishes calculation

Returns: {pd.DataFrame} -- pandas dataframe with read properties

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