Plotter.evaluate_training

Plotter.evaluate_training(attributes: List[str] = None, range_bins: List[List[Tuple[float, float]]] = None, transformed: bool = False, per_column: bool = False, bottom_top: Tuple[float, float] = (None, None), downsamp: int = 2, n_bins: int = 10, datamodule: DataModule = None, output_name: str = None) → Figure | None[source]

Compact plot for evaluating the training of the (V)AE model, in which there is a subplot for each selected attribute with the following traces:

  • Density plot of the attribute for the training and validation set.

  • Mean evaluation loss with confidence interval of the attribute for the validation data (= y error) binned across the attributes domain

  • Mean evaluation loss with confidence interval of the input data (= x error) binned across the attributes domain

  • Percentile lines (bottom and top) of the attribute’s density for training data (optional)

Parameters:

  • attributes (List[str], optional, default=None) – List of attributes (= names of DataObject’s) to select. If None, all attributes (specified in DataModule.output_ml_dblock) are considered.

  • range_bins (List[List[Tuple[float, float]]], optional, default=None) – To specify a custom range where to obtain the bins to evaluate the training. If None, the range is obtained from the training data.

  • transformed (bool, optional, default=False) – If True, the data is plotted transformed, while False returns the plots it in its original domain

  • per_column (bool, optional, default=False) – If True, multi-dimensional attributes are plotted as separate traces and subplots, otherwise all data is flattened to a single trace.

  • bottom_top (Tuple[float, float], optional, default=(None, None)) – Tuple of two floats, defining the percentile lines (bottom and top) to be plotted in the histogram as vertical lines.)

  • downsamp (int, optional, default=2) – Down-sampling factor for the data.

  • n_bins (int, optional, default=10) – Number of bins used for the error traces.

  • datamodule (DataModule, optional, default=None) – A DataModule object used for evaluation. If None, the datamodule provided when creating the plotter is used.

  • output_name (str, optional, default=None) – Name of the output file.

Returns:

Optional[plotly.graph_objects.Figure] – Plotly figure object, if self.output is None, otherwise None.