From f2c7b437094c1e24e26a5eba2581ea45ecbf89a8 Mon Sep 17 00:00:00 2001
From: alexanmv <56640707+alexanmv@users.noreply.github.com>
Date: Fri, 18 Feb 2022 16:39:34 +0200
Subject: [PATCH 1/2] Update plot_logistic_path.py

making the '# ####' comment line to '# %%' type and making a header for demo path functions. Also made a header with '# %%' type for author and license. Thought also about making author and license into note style but header seemed better.
---
 examples/linear_model/plot_logistic_path.py | 14 +++++++++++---
 1 file changed, 11 insertions(+), 3 deletions(-)

diff --git a/examples/linear_model/plot_logistic_path.py b/examples/linear_model/plot_logistic_path.py
index b74d6a67021d0..014bf8ad5c164 100644
--- a/examples/linear_model/plot_logistic_path.py
+++ b/examples/linear_model/plot_logistic_path.py
@@ -25,8 +25,15 @@
 
 """
 
-# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
-# License: BSD 3 clause
+# %%
+# Author
+# ---------------------------------------------------
+# Alexandre Gramfort <alexandre.gramfort@inria.fr>
+
+# %%
+# License
+# ---------------------------------------------------
+# BSD 3 clause
 
 from time import time
 import numpy as np
@@ -45,8 +52,9 @@
 
 X /= X.max()  # Normalize X to speed-up convergence
 
-# #############################################################################
+# %%
 # Demo path functions
+# ---------------------------------------------------
 
 cs = l1_min_c(X, y, loss="log") * np.logspace(0, 7, 16)
 

From 1bcc7ab4ca2e1fc430fa8c665fc436cfdf3c2d7e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Lo=C3=AFc=20Est=C3=A8ve?= <loic.esteve@ymail.com>
Date: Tue, 22 Feb 2022 11:22:13 +0100
Subject: [PATCH 2/2] Tweak example

---
 examples/linear_model/plot_logistic_path.py | 37 ++++++++++-----------
 1 file changed, 18 insertions(+), 19 deletions(-)

diff --git a/examples/linear_model/plot_logistic_path.py b/examples/linear_model/plot_logistic_path.py
index 014bf8ad5c164..a52b082eaed32 100644
--- a/examples/linear_model/plot_logistic_path.py
+++ b/examples/linear_model/plot_logistic_path.py
@@ -25,23 +25,14 @@
 
 """
 
-# %%
-# Author
-# ---------------------------------------------------
-# Alexandre Gramfort <alexandre.gramfort@inria.fr>
+# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
+# License: BSD 3 clause
 
 # %%
-# License
-# ---------------------------------------------------
-# BSD 3 clause
+# Load data
+# ---------
 
-from time import time
-import numpy as np
-import matplotlib.pyplot as plt
-
-from sklearn import linear_model
 from sklearn import datasets
-from sklearn.svm import l1_min_c
 
 iris = datasets.load_iris()
 X = iris.data
@@ -53,14 +44,16 @@
 X /= X.max()  # Normalize X to speed-up convergence
 
 # %%
-# Demo path functions
-# ---------------------------------------------------
+# Compute regularization path
+# ---------------------------
 
-cs = l1_min_c(X, y, loss="log") * np.logspace(0, 7, 16)
+import numpy as np
 
+from sklearn import linear_model
+from sklearn.svm import l1_min_c
+
+cs = l1_min_c(X, y, loss="log") * np.logspace(0, 7, 16)
 
-print("Computing regularization path ...")
-start = time()
 clf = linear_model.LogisticRegression(
     penalty="l1",
     solver="liblinear",
@@ -74,9 +67,15 @@
     clf.set_params(C=c)
     clf.fit(X, y)
     coefs_.append(clf.coef_.ravel().copy())
-print("This took %0.3fs" % (time() - start))
 
 coefs_ = np.array(coefs_)
+
+# %%
+# Plot regularization path
+# ------------------------
+
+import matplotlib.pyplot as plt
+
 plt.plot(np.log10(cs), coefs_, marker="o")
 ymin, ymax = plt.ylim()
 plt.xlabel("log(C)")