From 93017021bb463fc7d090e71cfa1a69e8f210a847 Mon Sep 17 00:00:00 2001
From: ycq091044 <ycqsjtu@gmail.com>
Date: Fri, 1 Sep 2023 11:35:47 -0500
Subject: [PATCH] add docs for fairness

---
 docs/api/metrics.rst                           |  1 +
 docs/api/metrics/pyhealth.metrics.fairness.rst | 14 ++++++++++++++
 docs/log.rst                                   |  6 ++++++
 pyhealth/metrics/fairness_utils/group.py       |  2 ++
 4 files changed, 23 insertions(+)
 create mode 100644 docs/api/metrics/pyhealth.metrics.fairness.rst

diff --git a/docs/api/metrics.rst b/docs/api/metrics.rst
index 9ab65e49..c66a6c06 100644
--- a/docs/api/metrics.rst
+++ b/docs/api/metrics.rst
@@ -17,3 +17,4 @@ tasks, such as drug drug interaction (DDI) rate.
     metrics/pyhealth.metrics.binary
     metrics/pyhealth.metrics.calibration
     metrics/pyhealth.metrics.prediction_set
+    metrics/pyhealth.metrics.fairness
diff --git a/docs/api/metrics/pyhealth.metrics.fairness.rst b/docs/api/metrics/pyhealth.metrics.fairness.rst
new file mode 100644
index 00000000..a92ee91b
--- /dev/null
+++ b/docs/api/metrics/pyhealth.metrics.fairness.rst
@@ -0,0 +1,14 @@
+pyhealth.metrics.fairness
+===================================
+
+.. currentmodule:: pyhealth.metrics.fairness
+
+.. autofunction:: fairness_metrics_fn
+
+.. currentmodule:: pyhealth.metrics.fairness_utils
+
+.. autofunction:: disparate_impact
+
+.. autofunction:: statistical_parity_difference
+
+.. autofunction:: sensitive_attributes_from_patient_ids
\ No newline at end of file
diff --git a/docs/log.rst b/docs/log.rst
index 3f9dfc75..b5739f55 100644
--- a/docs/log.rst
+++ b/docs/log.rst
@@ -2,6 +2,12 @@ Development logs
 ======================
 We track the new development here:
 
+**Sep 01, 2023**
+
+.. code-block:: rst
+
+    1. add Base fairness metrics and example `#216`.
+
 **July 22, 2023**
 
 .. code-block:: rst
diff --git a/pyhealth/metrics/fairness_utils/group.py b/pyhealth/metrics/fairness_utils/group.py
index c5543969..1a67f4f6 100644
--- a/pyhealth/metrics/fairness_utils/group.py
+++ b/pyhealth/metrics/fairness_utils/group.py
@@ -11,11 +11,13 @@ def disparate_impact(sensitive_attributes: np.ndarray, y_pred: np.ndarray, favor
     Computes the disparate impact between the the protected and unprotected group.
 
     disparate_impact = P(y_pred = favorable_outcome | P) / P(y_pred = favorable_outcome | U)
+    
     Args:
         sensitive_attributes: Sensitive attributes of shape (n_samples,) where 1 is the protected group and 0 is the unprotected group.
         y_pred: Predicted target values of shape (n_samples,).
         favorable_outcome: Label value which is considered favorable (i.e. "positive").
         allow_zero_division: If True, use epsilon instead of 0 in the denominator if the denominator is 0. Otherwise, raise a ValueError.
+    
     Returns:
         The disparate impact between the protected and unprotected group.
     """