update figure size to avoid overlaps

Author: HumphreyYang

lectures/markov_chains_II.md

@@ -4,7 +4,7 @@ jupytext:
     extension: .md
     format_name: myst
     format_version: 0.13
-    jupytext_version: 1.14.4
+    jupytext_version: 1.16.1
 kernelspec:
   display_name: Python 3 (ipykernel)
   language: python
@@ -248,8 +248,6 @@ Hence we expect that $\hat p_n(x) \approx \psi^*(x)$ when $n$ is large.
 The next figure shows convergence of $\hat p_n(x)$ to $\psi^*(x)$ when $x=1$ and
 $X_0$ is either $0, 1$ or $2$.
 
-
-
 ```{code-cell} ipython3
 P = np.array([[0.971, 0.029, 0.000],
               [0.145, 0.778, 0.077],
@@ -312,7 +310,7 @@ P = np.array([[0, 1],
 ts_length = 10_000
 mc = qe.MarkovChain(P)
 n = len(P)
-fig, axes = plt.subplots(nrows=1, ncols=n)
+fig, axes = plt.subplots(figsize=(11, 5), nrows=1, ncols=n)
 ψ_star = mc.stationary_distributions[0]
 
 for i in range(n):
@@ -395,8 +393,6 @@ ax.legend()
 plt.show()
 ```
 
-
-
 ### Expectations of geometric sums
 
 Sometimes we want to compute the mathematical expectation of a geometric sum, such as