From 945aea9ee3f955b56d8ce93c06faf7f71b653e7b Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Joa=CC=83o=20Pedro=20Morais?=
 <15629444+ojoaomorais@users.noreply.github.com>
Date: Tue, 21 May 2024 15:37:48 -0300
Subject: [PATCH 1/2] removing warnings from plot_cv_indices examples

---
 examples/model_selection/plot_cv_indices.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/examples/model_selection/plot_cv_indices.py b/examples/model_selection/plot_cv_indices.py
index e6c3580c787f0..58e09644a59d7 100644
--- a/examples/model_selection/plot_cv_indices.py
+++ b/examples/model_selection/plot_cv_indices.py
@@ -12,10 +12,15 @@
 
 """
 
+import warnings
+
 import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.patches import Patch
 
+# Removing warnings from examples
+warnings.filterwarnings("ignore")
+
 from sklearn.model_selection import (
     GroupKFold,
     GroupShuffleSplit,

From bf10111d8e4ea2fcaa91994b2a82e3c854514b4c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Joa=CC=83o=20Pedro=20Morais?=
 <15629444+ojoaomorais@users.noreply.github.com>
Date: Wed, 22 May 2024 08:46:18 -0300
Subject: [PATCH 2/2] Applying #29072 PR suggestions

---
 examples/model_selection/plot_cv_indices.py | 10 +++-------
 1 file changed, 3 insertions(+), 7 deletions(-)

diff --git a/examples/model_selection/plot_cv_indices.py b/examples/model_selection/plot_cv_indices.py
index 58e09644a59d7..d456546891069 100644
--- a/examples/model_selection/plot_cv_indices.py
+++ b/examples/model_selection/plot_cv_indices.py
@@ -12,15 +12,10 @@
 
 """
 
-import warnings
-
 import matplotlib.pyplot as plt
 import numpy as np
 from matplotlib.patches import Patch
 
-# Removing warnings from examples
-warnings.filterwarnings("ignore")
-
 from sklearn.model_selection import (
     GroupKFold,
     GroupShuffleSplit,
@@ -104,9 +99,10 @@ def visualize_groups(classes, groups, name):
 
 def plot_cv_indices(cv, X, y, group, ax, n_splits, lw=10):
     """Create a sample plot for indices of a cross-validation object."""
-
+    use_groups = "Group" in type(cv).__name__
+    groups = group if use_groups else None
     # Generate the training/testing visualizations for each CV split
-    for ii, (tr, tt) in enumerate(cv.split(X=X, y=y, groups=group)):
+    for ii, (tr, tt) in enumerate(cv.split(X=X, y=y, groups=groups)):
         # Fill in indices with the training/test groups
         indices = np.array([np.nan] * len(X))
         indices[tt] = 1