# {py:mod}`elasticai.preprocessor.normalization.normalization` ```{py:module} elasticai.preprocessor.normalization.normalization ``` ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization :allowtitles: ``` ## Module Contents ### Classes ````{list-table} :class: autosummary longtable :align: left * - {py:obj}`DataNormalization ` - ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization.DataNormalization :summary: ``` ```` ### API `````{py:class} DataNormalization(method: str, do_global_scaling: bool = False, peak_mode: int = 2) :canonical: elasticai.preprocessor.normalization.normalization.DataNormalization ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization.DataNormalization ``` ```{rubric} Initialization ``` ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization.DataNormalization.__init__ ``` ````{py:method} list_normalization_methods(print_output: bool = True) -> list :canonical: elasticai.preprocessor.normalization.normalization.DataNormalization.list_normalization_methods ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization.DataNormalization.list_normalization_methods ``` ```` ````{py:method} get_peak_amplitude_values() -> numpy.ndarray | torch.Tensor :canonical: elasticai.preprocessor.normalization.normalization.DataNormalization.get_peak_amplitude_values ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization.DataNormalization.get_peak_amplitude_values ``` ```` ````{py:method} normalize(dataset: numpy.ndarray | torch.Tensor) -> numpy.ndarray | torch.Tensor :canonical: elasticai.preprocessor.normalization.normalization.DataNormalization.normalize ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization.DataNormalization.normalize ``` ```` ````{py:method} create_design(target: str, bitwidth: int, id: str, path2save: pathlib.Path, signed: bool = True) -> None :canonical: elasticai.preprocessor.normalization.normalization.DataNormalization.create_design ```{autodoc2-docstring} elasticai.preprocessor.normalization.normalization.DataNormalization.create_design ``` ```` `````