eunoia.VennFit

class eunoia.VennFit(shapes: tuple[~eunoia._models.S, ...], original_values: dict[str, float], fitted_values: dict[str, float], residuals: dict[str, float], region_error: dict[str, float], diag_error: float, stress: float, loss: float, container: ~eunoia._models.Container | None = None, plot_data: dict[str, ~typing.Any] = <factory>)

Result of laying out a (non-proportional) Venn diagram.

Shares EulerFit’s structure and plot() method, but the diagram is topological: every set intersection is drawn regardless of its area, so the area-proportional error metrics are not meaningful and are left at zero. fitted_values holds the geometric area of each region; original_values is empty (a Venn layout has no requested areas).

__init__(shapes: tuple[~eunoia._models.S, ...], original_values: dict[str, float], fitted_values: dict[str, float], residuals: dict[str, float], region_error: dict[str, float], diag_error: float, stress: float, loss: float, container: ~eunoia._models.Container | None = None, plot_data: dict[str, ~typing.Any] = <factory>) → None

Methods

__init__(shapes, ...], original_values, ...)
plot(*[, ax, colors, fills, edges, labels, ...])	Render the fitted diagram with matplotlib.

Attributes

container
shapes
original_values
fitted_values
residuals
region_error
diag_error
stress
loss
plot_data