def create_confusion_matrix(
mat: np.ndarray,
class_labels: Optional[Sequence[str]] = None) -> plt.Figure:
mat = mat / mat.sum(axis=1, keepdims=True)
mat = pd.DataFrame(mat, index=class_labels, columns=class_labels)
if len(mat) != len(mat.columns):
raise ValueError("'mat' is not squared!")
if class_labels is not None and len(class_labels) != len(mat):
raise ValueError(
f"Incorrect number of class labels provided: {len(class_labels)}/{len(mat)}"
)
mat_str = mat.applymap(lambda x: str(int(x))
if x.is_integer() else f"{x:.2f}")
fig = plt.figure(figsize=(14, 10))
# noinspection PyUnresolvedReferences
sn.heatmap(mat, annot=mat_str, cmap=plt.cm.Blues, cbar=False, fmt="")
ax: plt.Axes = fig.get_axes()[0]
ax.tick_params(labelsize="large")
fig.tight_layout()
return fig
