# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.

import sklearn.metrics as skm
from math import sqrt
from ._metrics_engine import make_group_metric, metric_by_group


group_accuracy_score = make_group_metric(skm.accuracy_score)
"""A grouped wrapper around the :py:func:`sklearn.metrics.accuracy_score` routine."""

group_confusion_matrix = make_group_metric(skm.confusion_matrix)
"""A grouped wrapper around the :py:func:`sklearn.metrics.confusion_matrix` routine."""

group_precision_score = make_group_metric(skm.precision_score)
"""A grouped wrapper around the :py:func:`sklearn.metrics.precision_score` routine
"""

group_recall_score = make_group_metric(skm.recall_score)
"""A grouped wrapper around the :py:func:`sklearn.metrics.recall_score` routine
"""

group_roc_auc_score = make_group_metric(skm.roc_auc_score)
"""A grouped wrapper around the :py:func:`sklearn.metrics.roc_auc_score` routine
"""

group_zero_one_loss = make_group_metric(skm.zero_one_loss)
"""A grouped wrapper around the :py:func:`sklearn.metrics.zero_one_loss` routine
"""

group_mean_squared_error = make_group_metric(skm.mean_squared_error)
"""A grouped wrapper around the :py:func:`sklearn.metrics.mean_squared_error` routine
"""


def group_root_mean_squared_error(y_true, y_pred, group_membership, *,
                                  multioutput='uniform_average',
                                  sample_weight=None):
    """Wrap the :py:func:`sklearn.metrics.mean_squared_error` routine.

    The arguments remain the same, with `group_membership` added.
    The result is then square rooted.
    However, the only positional arguments supported are `y_true`,
    `y_pred` and `group_membership`.
    All others must be specified by name.
    """
    def internal_rmse_wrapper(y_true, y_pred, sample_weight=None):
        return sqrt(skm.mean_squared_error(y_true, y_pred,
                                           multioutput=multioutput,
                                           sample_weight=sample_weight))

    return metric_by_group(internal_rmse_wrapper,
                           y_true, y_pred, group_membership, sample_weight=sample_weight)


group_r2_score = make_group_metric(skm.r2_score)
"""A grouped wrapper around the :py:func:`sklearn.metrics.r2_score` routine
"""

group_max_error = make_group_metric(skm.max_error)
"""A grouped wrapper around the :py:func:`sklearn.metrics.max_error` routine
"""

group_mean_absolute_error = make_group_metric(skm.mean_absolute_error)
"""A grouped wrapper around the :py:func:`sklearn.metrics.mean_absolute_error` routine
"""

group_mean_squared_log_error = make_group_metric(skm.mean_squared_log_error)
"""A grouped wrapper around the :py:func:`sklearn.metrics.mean_squared_log_error` routine
"""

group_median_absolute_error = make_group_metric(skm.median_absolute_error)
"""A grouped wrapper around the :py:func:`sklearn.metrics.median_absolute_error` routine
"""