adopt standard figsize for quantecon-book-theme (#108)

Author: mmcky

lectures/aiyagari.md

@@ -55,10 +55,11 @@ The Aiyagari model has been used to investigate many topics, including
 Let's start with some imports:
 
 ```{code-cell} ipython
+%matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 import numpy as np
 import quantecon as qe
-import matplotlib.pyplot as plt
-%matplotlib inline
 from quantecon.markov import DiscreteDP
 from numba import jit
 ```

lectures/ar1_processes.md

@@ -47,8 +47,9 @@ Let's start with some imports:
 
 ```{code-cell} ipython
 import numpy as np
-import matplotlib.pyplot as plt
 %matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 ```
 
 ## The AR(1) Model

lectures/cake_eating_numerical.md

@@ -46,10 +46,10 @@ accuracy of alternative numerical methods.
 We will use the following imports:
 
 ```{code-cell} ipython
-import numpy as np
-import matplotlib.pyplot as plt
 %matplotlib inline
-
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
+import numpy as np
 from interpolation import interp
 from scipy.optimize import minimize_scalar, bisect
 ```

lectures/cake_eating_problem.md

@@ -40,9 +40,10 @@ Readers might find it helpful to review the following lectures before reading th
 In what follows, we require the following imports:
 
 ```{code-cell} ipython
-import numpy as np
-import matplotlib.pyplot as plt
 %matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
+import numpy as np
 ```
 
 ## The Model

lectures/career.md

@@ -47,10 +47,11 @@ This exposition draws on the presentation in {cite}`Ljungqvist2012`, section 6.5
 We begin with some imports:
 
 ```{code-cell} ipython
+%matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 import numpy as np
 import quantecon as qe
-import matplotlib.pyplot as plt
-%matplotlib inline
 from numba import njit, prange
 from quantecon.distributions import BetaBinomial
 from scipy.special import binom, beta

lectures/cass_koopmans_1.md

@@ -54,11 +54,12 @@ The lecture uses important ideas including
 Let's start with some standard imports:
 
 ```{code-cell} ipython
+%matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 from numba import njit, float64
 from numba.experimental import jitclass
 import numpy as np
-import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 ## The Model

lectures/cass_koopmans_2.md

@@ -66,11 +66,12 @@ The present lecture uses  additional  ideas including
 Let's start with some standard imports:
 
 ```{code-cell} ipython
+%matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 from numba import njit, float64
 from numba.experimental import jitclass
 import numpy as np
-import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 ## Review of Cass-Koopmans Model

lectures/coleman_policy_iter.md

@@ -61,11 +61,11 @@ iteration can be further adjusted to obtain even more efficiency.
 Let's start with some imports:
 
 ```{code-cell} ipython
+%matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 import numpy as np
 import quantecon as qe
-import matplotlib.pyplot as plt
-%matplotlib inline
-
 from interpolation import interp
 from quantecon.optimize import brentq
 from numba import njit, float64

lectures/complex_and_trig.md

@@ -98,9 +98,10 @@ $$
 We'll need the following imports:
 
 ```{code-cell} ipython
-import numpy as np
-import matplotlib.pyplot as plt
 %matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
+import numpy as np
 from sympy import *
 ```
 

lectures/egm_policy_iter.md

@@ -51,14 +51,15 @@ The original reference is {cite}`Carroll2006`.
 Let's start with some standard imports:
 
 ```{code-cell} ipython
+%matplotlib inline
+import matplotlib.pyplot as plt
+plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 import numpy as np
 import quantecon as qe
 from interpolation import interp
 from numba import njit, float64
 from numba.experimental import jitclass
 from quantecon.optimize import brentq
-import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 ## Key Idea