Update app.py

app.py

@@ -1,6 +1,7 @@
 import numpy as np
 import streamlit as st
 import matplotlib.pyplot as plt
+plt.style.use('fivethirtyeight')
 
 st.subheader("Gaussian Process Regression with Squared Exponential Kernel")
 
@@ -29,7 +30,7 @@ def rbf_kernel(x1, x2, lengthscale, variance):
     dist_sqr = (x1_ - x2_) ** 2
     return variance * np.exp(-dist_sqr)
 
-fig, ax = plt.subplots(figsize=(10,4))
+fig, ax = plt.subplots(figsize=(10,4), facecolor='white')
 
 x_train = np.array([0.2, 0.5, 0.8]).reshape(-1,1)
 y_train = np.array([0.8, 0.3, 0.6]).reshape(-1,1)
@@ -57,6 +58,7 @@ ax.fill_between(x_test.ravel(), pred_mean.ravel()-pred_std2.ravel(),
                 pred_mean.ravel()+pred_std2.ravel(), alpha=0.5, label='$\\mu \\pm 2\\sigma$')
 ax.set_xlabel('x')
 ax.set_ylabel('y')
+ax.set_facecolor('white')
 ax.legend()
 
 with st_col: