modified tutorial to the new commits

RainerHeintzmann · Jul 15, 2024 · 76b7d14 · 76b7d14
1 parent 133ca00
commit 76b7d14
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Showing 4 changed files with 26 additions and 8 deletions.
diff --git a/docs/Project.toml b/docs/Project.toml
@@ -2,3 +2,7 @@
 DataToFunctions = "64cfdffa-4d02-49ee-ae8b-a805370874f5"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 Literate = "98b081ad-f1c9-55d3-8b20-4c87d4299306"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
+SyntheticObjects = "e7028c27-0967-45e9-8fdb-dbc10ccb2b0a"
diff --git a/docs/src/tutorial.jl b/docs/src/tutorial.jl
@@ -1,5 +1,11 @@
 # Tutorial for the DataToFunctions.jl package
 
+import Pkg
+Pkg.add("SyntheticObjects")
+Pkg.add("StaticArrays")
+Pkg.add("Plots")
+Pkg.add("Random")
+
 # Load the packages
 using DataToFunctions
 using SyntheticObjects
@@ -42,13 +48,13 @@ heatmap(data_transformed_m, aspect_ratio=1
 
 # Now we try to do the transformation using a polynomial function
 # we first define the interpolation object using the DataToFunctions package with a polynomial of order 1 
-f_polynomial = get_function_polynomial(data, 1)
+f_polynomial = get_function_poly(data, 1)
 
 # define the polynomial coefficients
-params = [1.0, 0.0, 1.0, 0.0, 1.0, 0.0]
+params = (1.0, 0.0, 1.0, 0.0, 1.0, 0.0)
 
 # apply the transformation
-data_transformed_polynomial = f_polynomial(params)
+data_transformed_polynomial = f_polynomial((params))
 
 heatmap(data_transformed_polynomial, aspect_ratio=1
         , title="Transformed data using a polynomial function of order 1"

diff --git a/docs/src/tutorial.md b/docs/src/tutorial.md
@@ -4,6 +4,14 @@ EditURL = "tutorial.jl"
 
 Tutorial for the DataToFunctions.jl package
 
+````@example tutorial
+import Pkg
+Pkg.add("SyntheticObjects")
+Pkg.add("StaticArrays")
+Pkg.add("Plots")
+Pkg.add("Random")
+````
+
 Load the packages
 
 ````@example tutorial
@@ -65,19 +73,19 @@ Now we try to do the transformation using a polynomial function
 we first define the interpolation object using the DataToFunctions package with a polynomial of order 1
 
 ````@example tutorial
-f_polynomial = get_function_polynomial(data, 1)
+f_polynomial = get_function_poly(data, 1)
 ````
 
 define the polynomial coefficients
 
 ````@example tutorial
-params = [1.0, 0.0, 1.0, 0.0, 1.0, 0.0]
+params = (1.0, 0.0, 1.0, 0.0, 1.0, 0.0)
 ````
 
 apply the transformation
 
 ````@example tutorial
-data_transformed_polynomial = f_polynomial(params)
+data_transformed_polynomial = f_polynomial((params))
 
 heatmap(data_transformed_polynomial, aspect_ratio=1
         , title="Transformed data using a polynomial function of order 1"

diff --git a/examples/deform_testimage.jl b/examples/deform_testimage.jl
@@ -1,5 +1,5 @@
 ### A Pluto.jl notebook ###
-# v0.19.43
+# v0.19.42
 
 using Markdown
 using InteractiveUtils
@@ -87,7 +87,7 @@ h = get_function_poly(data, 1)
 @bind c6 Slider(-2f0:0.05f0:2f0, default=1)
 
 # ╔═╡ 74228a9d-6cc2-4aaf-97da-67f32670341e
-Gray.(h((c1,c2,c3,c4,c5,c6,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0)))
+Gray.(h((0f0, 0f0, 1.0f0, 0f0, 1.00f0, 0f0)))#,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0)))
 
 # ╔═╡ 687a198b-9020-4959-8e27-fd0896d4b1fc
 maximum(h((c1,c2,c3,c4,c5,c6,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0,0f0)))