Class SummaryOperations

monai/auto3dseg/operations.py:106–152

Apply statistical operation to summarize a dict. The key-value looks like: {"max", "min" ,"mean", ....}. The value may contain multiple values in a list format. Then this operation will apply the operation to the list. Typically, the dict is generated by multiple `SampleOperation` a

class SummaryOperations(Operations):
    """
    Apply statistical operation to summarize a dict. The key-value looks like: {"max", "min"
    ,"mean", ....}. The value may contain multiple values in a list format. Then this operation
    will apply the operation to the list. Typically, the dict is generated by multiple
    `SampleOperation` and `concat_multikeys_to_dict` functions.

    Examples:

        .. code-block:: python

            import numpy as np
            data = {
                "min": np.random.rand(4),
                "max": np.random.rand(4),
                "mean": np.random.rand(4),
                "sum": np.random.rand(4),
            }
            op = SummaryOperations()
            print(op.evaluate(data)) # "sum" is not registered yet, so it won't contain "sum"

            op.update({"sum", np.sum})
            print(op.evaluate(data)) # output has "sum"
    """

    def __init__(self) -> None:
        self.data = {
            "max": max,
            "mean": mean,
            "median": mean,
            "min": min,
            "stdev": mean,
            "percentile_00_5": mean,
            "percentile_10_0": mean,
            "percentile_90_0": mean,
            "percentile_99_5": mean,
        }

    def evaluate(self, data: Any, **kwargs: Any) -> dict:
        """
        Applies the callables to the data, and convert the numerics to list or Python
        numeric types (int/float).

        Args:
            data: input data
        """
        return {k: v(data[k], **kwargs).tolist() for k, v in self.data.items() if (callable(v) and k in data)}