Merge pull request #125 from QuantEcon/vectorized-plots

jbrightuniverse · web-flow · commit 63274c9b7055 · 2021-09-18T10:26:33.000-07:00
Remove gr(fmt=:png)
diff --git a/lectures/continuous_time/covid_sde.md b/lectures/continuous_time/covid_sde.md
@@ -70,7 +70,7 @@ others covered in previous lectures
 ```{code-cell} julia
 using OrdinaryDiffEq, StochasticDiffEq
 using Parameters, Plots
-gr(fmt=:png);
+
 ```
 
 ## The Basic SIR/SIRD Model
diff --git a/lectures/continuous_time/seir_model.md b/lectures/continuous_time/seir_model.md
@@ -68,7 +68,7 @@ In addition, we will be exploring the [Ordinary Differential Equations](https://
 ```{code-cell} julia
 using OrdinaryDiffEq
 using Parameters, Plots
-gr(fmt=:png);
+
 ```
 
 ## The SEIR Model
diff --git a/lectures/dynamic_programming/career.md b/lectures/dynamic_programming/career.md
@@ -155,7 +155,7 @@ using Test
 
 ```{code-cell} julia
 using Plots, QuantEcon, Distributions
-gr(fmt=:png);
+
 
 n = 50
 a_vals = [0.5, 1, 100]
diff --git a/lectures/dynamic_programming/coleman_policy_iter.md b/lectures/dynamic_programming/coleman_policy_iter.md
@@ -391,7 +391,7 @@ using Test
 ```{code-cell} julia
 using BenchmarkTools, Interpolations, Parameters, Plots, QuantEcon, Roots
 
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming/discrete_dp.md b/lectures/dynamic_programming/discrete_dp.md
@@ -428,7 +428,7 @@ using Test
 
 ```{code-cell} julia
 using BenchmarkTools, Plots, QuantEcon, Parameters
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming/egm_policy_iter.md b/lectures/dynamic_programming/egm_policy_iter.md
@@ -144,7 +144,7 @@ Here's an implementation of $K$ using EGM as described above.
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using BenchmarkTools, Interpolations, Parameters, Plots, QuantEcon, Random, Roots
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming/ifp.md b/lectures/dynamic_programming/ifp.md
@@ -378,7 +378,7 @@ using Test
 using LinearAlgebra, Statistics
 using BenchmarkTools, Optim, Parameters, Plots, QuantEcon, Random
 using Optim: converged, maximum, maximizer, minimizer, iterations
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming/jv.md b/lectures/dynamic_programming/jv.md
@@ -46,7 +46,7 @@ tags: [hide-output]
 using LinearAlgebra, Statistics
 using Distributions, QuantEcon, Interpolations, Expectations, Parameters
 using Plots, NLsolve, Random
-gr(fmt = :png);
+
 ```
 
 ## Model
diff --git a/lectures/dynamic_programming/lqcontrol.md b/lectures/dynamic_programming/lqcontrol.md
@@ -639,7 +639,7 @@ using Test, Random
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using Plots, Plots.PlotMeasures, QuantEcon
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming/mccall_model.md b/lectures/dynamic_programming/mccall_model.md
@@ -302,7 +302,7 @@ using Test
 ```
 
 ```{code-cell} julia
-gr(fmt = :png);
+
 ```
 
 Here's the distribution of wage offers we'll work with
diff --git a/lectures/dynamic_programming/mccall_model_with_separation.md b/lectures/dynamic_programming/mccall_model_with_separation.md
@@ -300,7 +300,7 @@ McCallModel = @with_kw (α = 0.2,
 
 ```{code-cell} julia
 # plots setting
-gr(fmt=:png);
+
 
 mcm = McCallModel()
 @unpack V, U = solve_mccall_model(mcm)
diff --git a/lectures/dynamic_programming/odu.md b/lectures/dynamic_programming/odu.md
@@ -163,7 +163,7 @@ using Test # At the head of every lecture.
 using LinearAlgebra, Statistics
 using Distributions, Plots, QuantEcon, Interpolations, Parameters
 
-gr(fmt=:png);
+
 
 w_max = 2
 x = range(0,  w_max, length = 200)
diff --git a/lectures/dynamic_programming/optgrowth.md b/lectures/dynamic_programming/optgrowth.md
@@ -465,7 +465,7 @@ tags: [hide-output]
 ---
 using LinearAlgebra, Statistics
 using Plots, QuantEcon, Interpolations, NLsolve, Optim, Random
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming/perm_income.md b/lectures/dynamic_programming/perm_income.md
@@ -477,7 +477,7 @@ using Test
 
 ```{code-cell} julia
 using Plots, Random
-gr(fmt=:png);
+
 
 Random.seed!(42)
 
diff --git a/lectures/dynamic_programming/perm_income_cons.md b/lectures/dynamic_programming/perm_income_cons.md
@@ -328,7 +328,7 @@ using Test
 ```{code-cell} julia
 using QuantEcon, LinearAlgebra
 using Plots
-gr(fmt=:png);
+
 
 # Set parameters
 α, β, ρ1, ρ2, σ = 10.0, 0.95, 0.9, 0.0, 1.0
diff --git a/lectures/dynamic_programming/robustness.md b/lectures/dynamic_programming/robustness.md
@@ -934,7 +934,7 @@ using Test
 
 ```{code-cell} julia
 using QuantEcon, Plots, LinearAlgebra, Interpolations
-gr(fmt = :png);
+
 
 # model parameters
 a_0 = 100
diff --git a/lectures/dynamic_programming/smoothing.md b/lectures/dynamic_programming/smoothing.md
@@ -357,7 +357,7 @@ using Test
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using Parameters, Plots, QuantEcon, Random
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming/wald_friedman.md b/lectures/dynamic_programming/wald_friedman.md
@@ -166,7 +166,7 @@ tags: [hide-output]
 ---
 using LinearAlgebra, Statistics
 using Distributions, Parameters, Printf, Random, Roots, Plots
-gr(fmt = :png)
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming_squared/amss.md b/lectures/dynamic_programming_squared/amss.md
@@ -1495,7 +1495,7 @@ sim_seq_l = simulate(time_sequential, 1., 1, 7, sHist_l)
 sim_bel_l = simulate(time_bellman, 1., 1, 7, sHist_l)
 
 using Plots
-gr(fmt=:png);
+
 titles = hcat("Consumption", "Labor Supply", "Government Debt",
               "Tax Rate", "Government Spending", "Output")
 sim_seq_l_plot = hcat(sim_seq_l[1:3]..., sim_seq_l[4],
diff --git a/lectures/dynamic_programming_squared/dyn_stack.md b/lectures/dynamic_programming_squared/dyn_stack.md
@@ -915,7 +915,7 @@ dynamic program as outlined above
 
 ```{code-cell} julia
 using QuantEcon, Plots, LinearAlgebra, Statistics, Parameters, Random
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/dynamic_programming_squared/lqramsey.md b/lectures/dynamic_programming_squared/lqramsey.md
@@ -583,7 +583,7 @@ using Test
 
 ```{code-cell} julia
 using QuantEcon, Plots, LinearAlgebra, Parameters
-gr(fmt = :png);
+
 
 abstract type AbstractStochProcess end
 
diff --git a/lectures/dynamic_programming_squared/opt_tax_recur.md b/lectures/dynamic_programming_squared/opt_tax_recur.md
@@ -1548,7 +1548,7 @@ sim_seq_h = simulate(PP_seq_time, 1.0, 1, 7, sHist_h)
 sim_seq_l = simulate(PP_seq_time, 1.0, 1, 7, sHist_l)
 
 using Plots
-gr(fmt=:png);
+
 titles = hcat("Consumption",
               "Labor Supply",
               "Government Debt",
diff --git a/lectures/getting_started_julia/introduction_to_types.md b/lectures/getting_started_julia/introduction_to_types.md
@@ -852,7 +852,7 @@ We can use auto-differentiation to compare the results.
 
 ```{code-cell} julia
 using Plots, ForwardDiff
-gr(fmt = :png);
+
 
 # operator to get the derivative of this function using AD
 D(f) = x -> ForwardDiff.derivative(f, x)
diff --git a/lectures/getting_started_julia/julia_by_example.md b/lectures/getting_started_julia/julia_by_example.md
@@ -1054,7 +1054,6 @@ Here's one solution
 
 ```{code-cell} julia
 using Plots
-gr(fmt=:png); # setting for easier display in jupyter notebooks
 α = 0.9
 n = 200
 x = zeros(n + 1)
diff --git a/lectures/getting_started_julia/julia_essentials.md b/lectures/getting_started_julia/julia_essentials.md
@@ -998,7 +998,7 @@ f(x) = x^2
 h = snapabove(f, 2.0)
 
 using Plots
-gr(fmt=:png);
+
 plot(h, 0.0:0.1:3.0)
 ```
 
diff --git a/lectures/more_julia/general_packages.md b/lectures/more_julia/general_packages.md
@@ -119,7 +119,7 @@ We begin by creating some data points, using a sine function
 ```{code-cell} julia
 using Interpolations
 using Plots
-gr(fmt=:png);
+
 
 x = -7:7 # x points, coase grid
 y = sin.(x) # corresponding y points
diff --git a/lectures/more_julia/generic_programming.md b/lectures/more_julia/generic_programming.md
@@ -66,7 +66,7 @@ tags: [hide-output]
 ---
 using LinearAlgebra, Statistics
 using Distributions, Plots, QuadGK, Polynomials, Interpolations
-gr(fmt = :png);
+
 ```
 
 ## Exploring Type Trees
diff --git a/lectures/multi_agent_models/aiyagari.md b/lectures/multi_agent_models/aiyagari.md
@@ -206,7 +206,7 @@ using Test, Random
 
 ```{code-cell} julia
 using Parameters, Plots, QuantEcon
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/multi_agent_models/arellano.md b/lectures/multi_agent_models/arellano.md
@@ -585,7 +585,7 @@ To the extent that you can, replicate the figures shown above
 
 ```{code-cell} julia
 using DataFrames, Plots
-gr(fmt=:png);
+
 ```
 
 Compute the value function, policy and equilibrium prices
diff --git a/lectures/multi_agent_models/lake_model.md b/lectures/multi_agent_models/lake_model.md
@@ -209,7 +209,7 @@ using Test
 ```
 
 ```{code-cell} julia
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/multi_agent_models/lucas_model.md b/lectures/multi_agent_models/lucas_model.md
@@ -388,7 +388,7 @@ using Test
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using Distributions, Interpolations, Parameters, Plots, QuantEcon, Random
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/multi_agent_models/markov_asset.md b/lectures/multi_agent_models/markov_asset.md
@@ -296,7 +296,7 @@ using Test, Random
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using Parameters, Plots, QuantEcon
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/multi_agent_models/markov_perf.md b/lectures/multi_agent_models/markov_perf.md
@@ -521,7 +521,7 @@ The following program
 
 ```{code-cell} julia
 using Plots
-gr(fmt=:png);
+
 
 AF = A - B1 * F1 - B2 * F2
 n = 20
diff --git a/lectures/multi_agent_models/matsuyama.md b/lectures/multi_agent_models/matsuyama.md
@@ -338,7 +338,7 @@ using Test
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using Plots, Parameters
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/multi_agent_models/schelling.md b/lectures/multi_agent_models/schelling.md
@@ -149,7 +149,7 @@ using Test, Random
 
 ```{code-cell} julia
 using Parameters, Plots, LinearAlgebra, Statistics
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/multi_agent_models/uncertainty_traps.md b/lectures/multi_agent_models/uncertainty_traps.md
@@ -232,7 +232,7 @@ using Test, Random
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using DataFrames, Parameters, Plots
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/time_series_models/additive_functionals.md b/lectures/time_series_models/additive_functionals.md
@@ -220,7 +220,7 @@ using Test, Random
 
 ```{code-cell} julia
 using Distributions, Parameters, Plots, QuantEcon
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/time_series_models/arma.md b/lectures/time_series_models/arma.md
@@ -231,7 +231,7 @@ using Test
 
 ```{code-cell} julia
 using Plots
-gr(fmt=:png);
+
 
 plt_1=plot()
 plt_2=plot()
diff --git a/lectures/time_series_models/estspec.md b/lectures/time_series_models/estspec.md
@@ -223,7 +223,7 @@ using Test
 
 ```{code-cell} julia
 using QuantEcon, Plots, Random
-gr(fmt = :png);
+
 Random.seed!(42) # For reproducible results.
 
 n = 40              # Data size
diff --git a/lectures/time_series_models/lu_tricks.md b/lectures/time_series_models/lu_tricks.md
@@ -1143,7 +1143,7 @@ using Test
 ```
 
 ```{code-cell} julia
-gr(fmt=:png);
+
 
 # set seed and generate a_t sequence
 Random.seed!(123)
diff --git a/lectures/time_series_models/multiplicative_functionals.md b/lectures/time_series_models/multiplicative_functionals.md
@@ -115,7 +115,7 @@ using Test, Random
 using LinearAlgebra, Statistics
 using Distributions, Parameters, Plots, QuantEcon
 import Distributions: loglikelihood
-gr(fmt = :png);
+
 ```
 
 ```{code-cell} julia
diff --git a/lectures/tools_and_techniques/finite_markov.md b/lectures/tools_and_techniques/finite_markov.md
@@ -45,7 +45,7 @@ Prerequisite knowledge is basic probability and linear algebra.
 ```{code-cell} julia
 using LinearAlgebra, Statistics
 using Distributions, Plots, Printf, QuantEcon, Random
-gr(fmt = :png);
+
 ```
 
 ## Definitions
diff --git a/lectures/tools_and_techniques/iterative_methods_sparsity.md b/lectures/tools_and_techniques/iterative_methods_sparsity.md
@@ -334,7 +334,7 @@ First, interpolate with $N = 5$ and avoid taking the inverse.  In that case, as
 
 ```{code-cell} julia
 using Plots
-gr(fmt=:png);
+
 
 N_display = 100
 g(x) = 1/(1 + 25x^2)
diff --git a/lectures/tools_and_techniques/kalman.md b/lectures/tools_and_techniques/kalman.md
@@ -112,7 +112,6 @@ using Test
 
 ```{code-cell} julia
 using Plots, Distributions
-gr(fmt = :png); # plots setup
 ```
 
 ```{code-cell} julia
diff --git a/lectures/tools_and_techniques/linear_algebra.md b/lectures/tools_and_techniques/linear_algebra.md
diff --git a/lectures/tools_and_techniques/linear_models.md b/lectures/tools_and_techniques/linear_models.md
diff --git a/lectures/tools_and_techniques/lln_clt.md b/lectures/tools_and_techniques/lln_clt.md
diff --git a/lectures/tools_and_techniques/numerical_linear_algebra.md b/lectures/tools_and_techniques/numerical_linear_algebra.md
diff --git a/lectures/tools_and_techniques/stationary_densities.md b/lectures/tools_and_techniques/stationary_densities.md
