ms2pip.result

Definition and handling of MS²PIP results.

class ms2pip.result.ProcessingResult(*, psm_index, psm=None, theoretical_mz=None, predicted_intensity=None, observed_intensity=None, correlation=None, feature_vectors=None)[source]

Bases: BaseModel

Result of processing a single PSM.

Parameters:

psm_index (int) –
psm (PSM | None) –
theoretical_mz (Dict[str, ndarray] | None) –
predicted_intensity (Dict[str, ndarray] | None) –
observed_intensity (Dict[str, ndarray] | None) –
correlation (float | None) –
feature_vectors (ndarray | None) –

as_spectra()[source]

Convert result to predicted and observed spectra.

Return type:: Tuple[PredictedSpectrum | None, ObservedSpectrum | None]

plot_spectra()[source]

Plot predicted and observed spectra.

Return type:: matplotlib.axes.Axes

Notes

Requires optional dependency spectrum_utils to be installed.

ms2pip.result.calculate_correlations(results)[source]

Calculate and add Pearson correlations to list of results.

Parameters:: results (List[ProcessingResult]) –
Return type:: None

ms2pip.result.results_to_csv(results, output_file)[source]

Write processing results to CSV file.

Parameters:

results (List[ProcessingResult]) –
output_file (str) –

Return type:

None

ms2pip.result.correlations_to_csv(results, output_file)[source]

Write correlations to CSV file.

Parameters:

results (List[ProcessingResult]) –
output_file (str) –

Return type:

None