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| import numpy as np | |
| from aif360.datasets import StructuredDataset | |
| from aif360.metrics import Metric, utils | |
| class DatasetMetric(Metric): | |
| """Class for computing metrics based on one StructuredDataset.""" | |
| def __init__(self, dataset, unprivileged_groups=None, privileged_groups=None): | |
| """ | |
| Args: | |
| dataset (StructuredDataset): A StructuredDataset. | |
| privileged_groups (list(dict)): Privileged groups. Format is a list | |
| of `dicts` where the keys are `protected_attribute_names` and | |
| the values are values in `protected_attributes`. Each `dict` | |
| element describes a single group. See examples for more details. | |
| unprivileged_groups (list(dict)): Unprivileged groups in the same | |
| format as `privileged_groups`. | |
| Raises: | |
| TypeError: `dataset` must be a | |
| :obj:`~aif360.datasets.StructuredDataset` type. | |
| ValueError: `privileged_groups` and `unprivileged_groups` must be | |
| disjoint. | |
| Examples: | |
| >>> from aif360.datasets import GermanDataset | |
| >>> german = GermanDataset() | |
| >>> u = [{'sex': 1, 'age': 1}, {'sex': 0}] | |
| >>> p = [{'sex': 1, 'age': 0}] | |
| >>> dm = DatasetMetric(german, unprivileged_groups=u, privileged_groups=p) | |
| """ | |
| if not isinstance(dataset, StructuredDataset): | |
| raise TypeError("'dataset' should be a StructuredDataset") | |
| # sets self.dataset | |
| super(DatasetMetric, self).__init__(dataset) | |
| # TODO: should this deepcopy? | |
| self.privileged_groups = privileged_groups | |
| self.unprivileged_groups = unprivileged_groups | |
| # don't check if nothing was provided | |
| if not self.privileged_groups or not self.unprivileged_groups: | |
| return | |
| priv_mask = utils.compute_boolean_conditioning_vector( | |
| self.dataset.protected_attributes, | |
| self.dataset.protected_attribute_names, self.privileged_groups) | |
| unpriv_mask = utils.compute_boolean_conditioning_vector( | |
| self.dataset.protected_attributes, | |
| self.dataset.protected_attribute_names, self.unprivileged_groups) | |
| if np.any(np.logical_and(priv_mask, unpriv_mask)): | |
| raise ValueError("'privileged_groups' and 'unprivileged_groups'" | |
| " must be disjoint.") | |
| def _to_condition(self, privileged): | |
| """Converts a boolean condition to a group-specifying format that can be | |
| used to create a conditioning vector. | |
| """ | |
| if privileged is True and self.privileged_groups is None: | |
| raise AttributeError("'privileged_groups' was not provided when " | |
| "this object was initialized.") | |
| if privileged is False and self.unprivileged_groups is None: | |
| raise AttributeError("'unprivileged_groups' was not provided when " | |
| "this object was initialized.") | |
| if privileged is None: | |
| return None | |
| return self.privileged_groups if privileged else self.unprivileged_groups | |
| def difference(self, metric_fun): | |
| """Compute difference of the metric for unprivileged and privileged | |
| groups. | |
| """ | |
| return metric_fun(privileged=False) - metric_fun(privileged=True) | |
| def ratio(self, metric_fun): | |
| """Compute ratio of the metric for unprivileged and privileged groups. | |
| """ | |
| return metric_fun(privileged=False) / metric_fun(privileged=True) | |
| def num_instances(self, privileged=None): | |
| """Compute the number of instances, :math:`n`, in the dataset conditioned | |
| on protected attributes if necessary. | |
| Args: | |
| privileged (bool, optional): Boolean prescribing whether to | |
| condition this metric on the `privileged_groups`, if `True`, or | |
| the `unprivileged_groups`, if `False`. Defaults to `None` | |
| meaning this metric is computed over the entire dataset. | |
| Raises: | |
| AttributeError: `privileged_groups` or `unprivileged_groups` must be | |
| must be provided at initialization to condition on them. | |
| """ | |
| condition = self._to_condition(privileged) | |
| return utils.compute_num_instances(self.dataset.protected_attributes, | |
| self.dataset.instance_weights, | |
| self.dataset.protected_attribute_names, condition=condition) | |