read_tensorboard_pr_curves

read_tensorboard_pr_curves(logdir, *, tags=None, runs=None, step=None)

Read the PR curve charts of a TensorBoard log directory.

One chart per tag, as TensorBoard’s PR Curves dashboard draws it: recall along the x axis, precision along the y axis, one line per run.

Parameters

Name	Type	Description	Default
logdir	str or os.PathLike	The directory TensorBoard would be started with, such as the one PyTorch’s add_pr_curve or TensorBoard’s pr_curve summary wrote.	required
tags	iterable of str	Only these tags, in this order, and only these runs.	None
runs	iterable of str	Only these tags, in this order, and only these runs.	None
step	int	The step each run’s curve is read at: the last one logged at or before it. By default each run’s last.	None

Returns

Name	Type	Description
	list of TensorBoardChart	One per tag.

Notes

Each line is named with its run, its average precision and the share of positives – the precision a random guess reaches, which a useful classifier stays above – such as good (AP 0.91, chance 0.30). A threshold at which nothing was predicted positive has no precision, and is left out of the line rather than read as a precision of 0.

Examples

>>> import maidr
>>> for chart in maidr.read_tensorboard_pr_curves("runs"):
...     maidr.show(chart)