MaCh3PythonUtils.file_handling package

Submodules

MaCh3PythonUtils.file_handling.chain_handler module

Python tool to load in some generic TTree objects and export to numpy array/pandas dataframe

class ChainHandler(file_name: str, ttree_name: str = 'posteriors', verbose=False)

Bases: object

Class to load in ROOT files containing a single TTree

Parameters:

• file_name (str) – Name of ROOT file containing useful TTree

• ttree_name (str, optional) – Name of TTree contained in ROOT file

add_additional_plots(additional_branches: List[str] | str, exact=False) → None

To add more branches to the plotting branch list :param additional_branches: List of branches to add to the plotting list :type additional_branches: list

add_new_cuts(new_cuts: str | List[str]) → None

Specifies list of cuts to apply to the TTree (something like [‘step>80000’, ‘dm23>0’]) :param new_cuts: List of/single cut to apply :type new_cuts: list, str

close_file() → None

Closes ROOT file, should be called to avoid memory issues!

convert_ttree_to_array(close_file=True) → None

Converts the TTree table to array :param close_file: Do you want to close the ROOT file after calling this method? :type close_file: bool, optional

ignore_plots(ignored_branches: List[str] | str) → None

List of plots to ignore

Parameters:

ignored_branches (List[str] | str) – _description_

property lower_bounds: ndarray[Any, dtype[_ScalarType_co]]

property ndim: int

property plot_branches: List[str]

Getter for list of useful branches :return: List of branches used in file :rtype: list

property ttree_array: DataFrame

Getter for the converted TTree array :return: Table containing TTree in non-ROOT format :rtype: Union[np.array, pd.DataFrame, ak.Array]

property upper_bounds: ndarray[Any, dtype[_ScalarType_co]]

Module contents