Merge pull request #4 from HumphreyYang/fix-string

[FIX] Fix string warnings
QuantEcon · Jan 21, 2025 · c7827e8 · c7827e8
2 parents 2c59dfe + 684547c
commit c7827e8
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diff --git a/lectures/calvo_machine_learn.md b/lectures/calvo_machine_learn.md
@@ -1230,7 +1230,7 @@ Let's plot the regression line $\mu_t = .0645 + 1.5995 \theta_t$  and the points
 
 ```{code-cell} ipython3
 plt.scatter(θs, μs, label=r'$\mu_t$')
-plt.plot(θs, results1.predict(X1_θ), 'grey', label='$\hat \mu_t$', linestyle='--')
+plt.plot(θs, results1.predict(X1_θ), 'grey', label=r'$\hat \mu_t$', linestyle='--')
 plt.xlabel(r'$\theta_t$')
 plt.ylabel(r'$\mu_t$')
 plt.legend()
@@ -1321,7 +1321,7 @@ X3_grid = np.column_stack((np.ones(len(θ_grid)), θ_grid, θ_grid**2))
 
 plt.scatter(θs, v_t)
 plt.plot(θ_grid, results3.predict(X3_grid), color='grey', 
-         label='$\hat v_t$', linestyle='--')
+         label=r'$\hat v_t$', linestyle='--')
 plt.axhline(V_CR, color='C1', alpha=0.5)
 
 plt.text(max(θ_grid) - max(θ_grid)*0.025, V_CR, '$V^{CR}$', color='C1', 

diff --git a/lectures/jv.md b/lectures/jv.md
@@ -532,8 +532,8 @@ def xbar(ϕ):
 
 ϕ_grid = np.linspace(0, 1, 100)
 fig, ax = plt.subplots(figsize=(9, 7))
-ax.set(xlabel='$\phi$')
-ax.plot(ϕ_grid, [xbar(ϕ) * (1 - ϕ) for ϕ in ϕ_grid], label='$w^*(\phi)$')
+ax.set(xlabel=r'$\phi$')
+ax.plot(ϕ_grid, [xbar(ϕ) * (1 - ϕ) for ϕ in ϕ_grid], label=r'$w^*(\phi)$')
 ax.legend()
 
 plt.show()

diff --git a/lectures/linear_models.md b/lectures/linear_models.md
@@ -794,15 +794,15 @@ for i in range(I):
     ensemble_mean = ensemble_mean + y
 
 ensemble_mean = ensemble_mean / I
-ax.plot(ensemble_mean, color='b', lw=2, alpha=0.8, label='$\\bar y_t$')
+ax.plot(ensemble_mean, color='b', lw=2, alpha=0.8, label=r'$\bar y_t$')
 m = ar.moment_sequence()
 
 population_means = []
 for t in range(T):
     μ_x, μ_y, Σ_x, Σ_y = next(m)
     population_means.append(float(μ_y))
 
-ax.plot(population_means, color='g', lw=2, alpha=0.8, label='$G\mu_t$')
+ax.plot(population_means, color='g', lw=2, alpha=0.8, label=r'$G\mu_t$')
 ax.set_ylim(ymin, ymax)
 ax.set_xlabel('time', fontsize=12)
 ax.set_ylabel('$y_t$', fontsize=12)

diff --git a/lectures/lqcontrol.md b/lectures/lqcontrol.md
@@ -1605,7 +1605,7 @@ ax.set(xlabel='Time', xlim=(0, max(time)))
 ax.plot(time, q_bar, 'k-', lw=2, alpha=0.6, label=r'$\bar q_t$')
 ax.plot(time, q, 'b-', lw=2, alpha=0.6, label='$q_t$')
 ax.legend(ncol=2, **legend_args)
-s = f'dynamics with $\gamma = {γ}$'
+s = fr'dynamics with $\gamma = {γ}$'
 ax.text(max(time) * 0.6, 1 * q_bar.max(), s, fontsize=14)
 plt.show()
 ```

diff --git a/lectures/opt_tax_recur.md b/lectures/opt_tax_recur.md
@@ -1242,7 +1242,7 @@ for ax, title, plot in zip(axes, titles, [tax_policy, interest_rate]):
     ax.set(title=title, xlim=(min(gov_debt), max(gov_debt)))
     ax.grid()
 
-axes[0].legend(('Time $t=0$', 'Time $t \geq 1$'))
+axes[0].legend(('Time $t=0$', r'Time $t \geq 1$'))
 axes[1].set_xlabel('Initial Government Debt')
 
 fig.tight_layout()

diff --git a/lectures/rob_markov_perf.md b/lectures/rob_markov_perf.md
@@ -469,7 +469,7 @@ The function's code is as follows
 def nnash_robust(A, C, B1, B2, R1, R2, Q1, Q2, S1, S2, W1, W2, M1, M2,
                  θ1, θ2, beta=1.0, tol=1e-8, max_iter=1000):
 
-    """
+    r"""
     Compute the limit of a Nash linear quadratic dynamic game with
     robustness concern.