Merge pull request #92 from yuehhua/burger_visualization

Reformat code

Author: yuehhua

example/Burgers/notebook/mno.jl

@@ -8,18 +8,20 @@ dataset = Burgers.get_data(n = 1000);
 m = Burgers.get_model();
 input_data, ground_truth = dataset[1], dataset[2];
 
-
 i = 1
-plot(input_data[1,:,1],ground_truth[1, :, i], label = "ground_truth",title = "                                              Burgers equation u(x,T_end)");
-p1 = plot!(input_data[1,:,1],m(view(input_data, :, :, i:i))[1, :, 1],label = "predict");
-plot(input_data[1,:,1],ground_truth[1, :, i + 1],label = "ground_truth");
-p2 = plot!(input_data[1,:,1],m(view(input_data, :, :, (i + 1):(i + 1)))[1, :, 1],label = "predict");
-i = 3
+plot(input_data[1, :, 1], ground_truth[1, :, i], label = "ground_truth",
+     title = "                                              Burgers equation u(x,T_end)");
+p1 = plot!(input_data[1, :, 1], m(view(input_data, :, :, i:i))[1, :, 1], label = "predict");
 
-plot(input_data[1,:,1],ground_truth[1, :, i], label = "ground_truth");
-p3 = plot!(input_data[1,:,1],m(view(input_data, :, :, i:i))[1, :, 1],label = "predict");
-plot(input_data[1,:,1],ground_truth[1, :, i + 1], label = "ground_truth");
-p4 = plot!(input_data[1,:,1],m(view(input_data, :, :, (i + 1):(i + 1)))[1, :, 1], label = "predict");
-p = plot(p1, p2, p3, p4)
+plot(input_data[1, :, 1], ground_truth[1, :, i + 1], label = "ground_truth");
+p2 = plot!(input_data[1, :, 1], m(view(input_data, :, :, (i + 1):(i + 1)))[1, :, 1],
+           label = "predict");
+i = 3
 
+plot(input_data[1, :, 1], ground_truth[1, :, i], label = "ground_truth");
+p3 = plot!(input_data[1, :, 1], m(view(input_data, :, :, i:i))[1, :, 1], label = "predict");
 
+plot(input_data[1, :, 1], ground_truth[1, :, i + 1], label = "ground_truth");
+p4 = plot!(input_data[1, :, 1], m(view(input_data, :, :, (i + 1):(i + 1)))[1, :, 1],
+           label = "predict");
+p = plot(p1, p2, p3, p4)

example/Burgers/src/Burgers.jl

@@ -19,9 +19,7 @@ function register_burgers()
 
                      * `a`: initial conditions u(x,0)
                      * `u`: solutions u(x,t_end)
-                     """,
-
-                     "http://www.med.cgu.edu.tw/NeuralOperators/Burgers_R10.zip",
+                     """, "http://www.med.cgu.edu.tw/NeuralOperators/Burgers_R10.zip",
                      "9cbbe5070556c777b1ba3bacd49da5c36ea8ed138ba51b6ee76a24b971066ecd",
                      post_fetch_method = unpack))
 end
@@ -114,7 +112,6 @@ function train_nomad(; n = 300, cuda = true, learning_rate = 0.001, epochs = 400
     return mean_diff
 end
 
-
 function get_model()
     model_path = joinpath(@__DIR__, "../model/")
     model_file = readdir(model_path)[end]