Version: 3.x

rasa.utils.plotting

plot_confusion_matrix

@_needs_matplotlib_backend
def 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
def 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
def 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