From 71122941599b9e3863f13cfade302463e940c25b Mon Sep 17 00:00:00 2001
From: ArturoAmorQ <arturo.amor-quiroz@polytechnique.edu>
Date: Wed, 7 Dec 2022 17:22:26 +0100
Subject: [PATCH] DOC Use notebook style in plot_gpr_on_structured_data.py

---
 .../plot_gpr_on_structured_data.py            | 30 +++++++++----------
 1 file changed, 15 insertions(+), 15 deletions(-)

diff --git a/examples/gaussian_process/plot_gpr_on_structured_data.py b/examples/gaussian_process/plot_gpr_on_structured_data.py
index bc8c169c91f67..ada50a0edf06b 100644
--- a/examples/gaussian_process/plot_gpr_on_structured_data.py
+++ b/examples/gaussian_process/plot_gpr_on_structured_data.py
@@ -38,8 +38,8 @@
 
 """
 
+# %%
 import numpy as np
-import matplotlib.pyplot as plt
 from sklearn.gaussian_process.kernels import Kernel, Hyperparameter
 from sklearn.gaussian_process.kernels import GenericKernelMixin
 from sklearn.gaussian_process import GaussianProcessRegressor
@@ -102,10 +102,11 @@ def clone_with_theta(self, theta):
 
 kernel = SequenceKernel()
 
-"""
-Sequence similarity matrix under the kernel
-===========================================
-"""
+# %%
+# Sequence similarity matrix under the kernel
+# ===========================================
+
+import matplotlib.pyplot as plt
 
 X = np.array(["AGCT", "AGC", "AACT", "TAA", "AAA", "GAACA"])
 
@@ -117,11 +118,11 @@ def clone_with_theta(self, theta):
 plt.xticks(np.arange(len(X)), X)
 plt.yticks(np.arange(len(X)), X)
 plt.title("Sequence similarity under the kernel")
+plt.show()
 
-"""
-Regression
-==========
-"""
+# %%
+# Regression
+# ==========
 
 X = np.array(["AGCT", "AGC", "AACT", "TAA", "AAA", "GAACA"])
 Y = np.array([1.0, 1.0, 2.0, 2.0, 3.0, 3.0])
@@ -136,11 +137,11 @@ def clone_with_theta(self, theta):
 plt.xticks(np.arange(len(X)), X)
 plt.title("Regression on sequences")
 plt.legend()
+plt.show()
 
-"""
-Classification
-==============
-"""
+# %%
+# Classification
+# ==============
 
 X_train = np.array(["AGCT", "CGA", "TAAC", "TCG", "CTTT", "TGCT"])
 # whether there are 'A's in the sequence
@@ -176,7 +177,7 @@ def clone_with_theta(self, theta):
     [1.0 if c else -1.0 for c in gp.predict(X_test)],
     s=100,
     marker="x",
-    edgecolor=(0, 1.0, 0.3),
+    facecolor="b",
     linewidth=2,
     label="prediction",
 )
@@ -184,5 +185,4 @@ def clone_with_theta(self, theta):
 plt.yticks([-1, 1], [False, True])
 plt.title("Classification on sequences")
 plt.legend()
-
 plt.show()