notice

This is documentation for Rasa Documentation v2.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (3.x).

Version: 2.x

rasa.utils.plotting

plot_confusion_matrix

@_needs_matplotlib_backend
plot_confusion_matrix(confusion_matrix: np.ndarray, classes: Union[np.ndarray, List[Text]], normalize: bool = False, title: Text = "Confusion matrix", color_map: Any = None, zmin: int = 1, output_file: Optional[Text] = None) -> None

Print and plot the provided confusion matrix. Normalization can be applied by setting normalize=True.

Arguments:

  • confusion_matrix - confusion matrix to plot
  • classes - class labels
  • normalize - If set to true, normalization will be applied.
  • title - title of the plot
  • color_map - color mapping zmin:
  • output_file - output file to save plot to

plot_paired_histogram

@_needs_matplotlib_backend
plot_paired_histogram(histogram_data: List[List[float]], title: Text, output_file: Optional[Text] = None, num_bins: int = 25, colors: Tuple[Text, Text] = ("#009292", "#920000",), axes_label: Tuple[Text, Text] = ("Correct", "Wrong"), frame_label: Tuple[Text, Text] = ("Number of Samples", "Confidence"), density: bool = False, x_pad_fraction: float = 0.05, y_pad_fraction: float = 0.10) -> None

Plots a side-by-side comparative histogram of the confidence distribution.

Arguments:

  • histogram_data - Two data vectors
  • title - Title to be displayed above the plot
  • output_file - File to save the plot to
  • num_bins - Number of bins to be used for the histogram
  • colors - Left and right bar colors as hex color strings
  • axes_label - Labels shown above the left and right histogram, respectively
  • frame_label - Labels shown below and on the left of the histogram, respectively
  • density - If true, generate a probability density histogram
  • x_pad_fraction - Percentage of extra space in the horizontal direction
  • y_pad_fraction - Percentage of extra space in the vertical direction

plot_curve

@_needs_matplotlib_backend
plot_curve(output_directory: Text, number_of_examples: List[int], x_label_text: Text, y_label_text: Text, graph_path: Text) -> None

Plot the results from a model comparison.

Arguments:

  • output_directory - Output directory to save resulting plots to
  • number_of_examples - Number of examples per run
  • x_label_text - text for the x axis
  • y_label_text - text for the y axis
  • graph_path - output path of the plot