MAINT: remove %matplotlib inline

lectures/cattle_cycles.md

@@ -53,7 +53,6 @@ import matplotlib.pyplot as plt
 from collections import namedtuple
 from quantecon import DLE
 from math import sqrt
-%matplotlib inline
 ```
 
 ## The Model

lectures/cons_news.md

@@ -607,7 +607,6 @@ As usual, we start by importing packages.
 import numpy as np
 import quantecon as qe
 import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 ```{code-cell} python3

lectures/growth_in_dles.md

@@ -52,7 +52,6 @@ We require the following imports
 ```{code-cell} ipython
 import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
 from quantecon import DLE
 ```
 

lectures/hs_invertibility_example.md

@@ -49,7 +49,6 @@ import quantecon as qe
 import matplotlib.pyplot as plt
 from quantecon import DLE
 from math import sqrt
-%matplotlib inline
 ```
 
 This lecture describes  an early contribution to what is now often called

lectures/irfs_in_hall_model.md

@@ -44,7 +44,6 @@ We'll make these imports:
 ```{code-cell} ipython
 import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
 from quantecon import DLE
 ```
 

lectures/kalman_2.md

@@ -51,7 +51,6 @@ In addition to what's in Anaconda, this lecture will need the following librarie
 To conduct simulations, we bring in these imports, as in {doc}`A First Look at the Kalman filter <kalman>`.
 
 ```{code-cell} ipython3
-%matplotlib inline
 import matplotlib.pyplot as plt
 plt.rcParams["figure.figsize"] = (11, 5)  #set default figure size
 import numpy as np

lectures/lqramsey.md

@@ -81,7 +81,6 @@ We'll need the following imports:
 import sys
 import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
 from numpy import sqrt, eye, zeros, cumsum
 from numpy.random import randn
 import scipy.linalg

lectures/lucas_asset_pricing_dles.md

@@ -56,7 +56,6 @@ We'll also need the following imports
 import numpy as np
 import matplotlib.pyplot as plt
 from quantecon import DLE
-%matplotlib inline
 ```
 
 We use a linear-quadratic version of an economy that Lucas (1978) {cite}`Lucas1978` used

lectures/markov_jump_lq.md

@@ -254,7 +254,6 @@ import quantecon as qe
 import matplotlib.pyplot as plt
 from mpl_toolkits.mplot3d import Axes3D
 
-%matplotlib inline
 ```
 
 ```{code-cell} python3

lectures/muth_kalman.md

@@ -40,7 +40,6 @@ We'll also need the following imports:
 
 ```{code-cell} ipython
 import matplotlib.pyplot as plt
-%matplotlib inline
 import numpy as np
 
 from quantecon import Kalman

lectures/permanent_income_dles.md

@@ -56,7 +56,6 @@ We'll also require the following imports
 ```{code-cell} ipython
 import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
 from quantecon import DLE
 
 np.set_printoptions(suppress=True, precision=4)

lectures/rosen_schooling_model.md

@@ -46,7 +46,6 @@ import numpy as np
 import matplotlib.pyplot as plt
 from collections import namedtuple
 from quantecon import DLE
-%matplotlib inline
 ```
 
 ## A One-Occupation Model

lectures/smoothing.md

@@ -83,7 +83,6 @@ Let's start with some imports:
 import numpy as np
 import quantecon as qe
 import matplotlib.pyplot as plt
-%matplotlib inline
 import scipy.linalg as la
 ```
 

lectures/smoothing_tax.md

@@ -97,7 +97,6 @@ Let's start with some standard imports:
 import numpy as np
 import quantecon as qe
 import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 To exploit the isomorphism between consumption-smoothing and tax-smoothing models, we  simply use code from {doc}`Consumption Smoothing with Complete and Incomplete Markets <smoothing>`

lectures/tax_smoothing_1.md

@@ -44,7 +44,6 @@ Let's start with some standard imports:
 import quantecon as qe
 import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 This lecture uses the method of   **Markov jump linear quadratic dynamic programming** that is described in lecture

lectures/tax_smoothing_2.md

@@ -79,7 +79,6 @@ Let's start with some standard imports:
 import quantecon as qe
 import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 ## Two example specifications

lectures/tax_smoothing_3.md

@@ -62,7 +62,6 @@ Let's start with some standard imports:
 import quantecon as qe
 import numpy as np
 import matplotlib.pyplot as plt
-%matplotlib inline
 ```
 
 ## Roll-Over Risk