Developed and added documentatios

.github/workflows/ci.yml

@@ -0,0 +1,64 @@
+name: CI
+on:
+  pull_request:
+    branches:
+      - main
+      - develop
+  push:
+    branches:
+      - main
+      - develop
+    tags: '*'
+concurrency:
+  # Skip intermediate builds: always.
+  # Cancel intermediate builds: only if it is a pull request build.
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: ${{ startsWith(github.ref, 'refs/pull/') }}
+jobs:
+  test:
+    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }} - ${{ github.event_name }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        version:
+          - '1.9'
+        os:
+          - [ubuntu-latest] 
+        arch:
+          - x64
+    steps:
+      - uses: actions/checkout@v3
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: ${{ matrix.version }}
+          arch: ${{ matrix.arch }}
+      - uses: julia-actions/cache@v1
+      - name: Add unregistered dependencies
+        run: julia -e 'using Pkg; Pkg.develop(PackageSpec(url="https://github.com/rainerheintzmann/EvalMultiPoly.jl"))'
+
+      - uses: julia-actions/julia-buildpkg@v1
+      - uses: julia-actions/julia-runtest@v1
+      - uses: julia-actions/julia-processcoverage@v1
+      - uses: codecov/codecov-action@v4
+        env:
+          CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
+        with:
+          file: lcov.info
+
+
+  docs:
+    name: Documentation
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+      - uses: julia-actions/setup-julia@v1
+        with:
+          version: "1.9"
+      - name: Add unregistered dependencies
+        run: julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(url="https://github.com/rainerheintzmann/EvalMultiPoly.jl")); Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
+
+      - uses: julia-actions/julia-docdeploy@releases/v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }}

.gitignore

@@ -22,3 +22,19 @@ docs/site/
 # committed for packages, but should be committed for applications that require a static
 # environment.
 Manifest.toml
+examples/Manifest.toml
+examples/*.tiff
+examples/image_registration_2dpolim.jl
+
+*.mp4
+*.png
+examples/figures/*
+examples/*.tif
+examples/*.ipynb
+*.jpeg
+*.gif
+*.jpg
+*.txt
+*.txt
+.*tiff
+examples/6-4-Rigis.jl

Project.toml

@@ -4,5 +4,25 @@ authors = ["RainerHeintzmann <heintzmann@gmail.com>"]
 version = "0.1.0"
 
 [deps]
+EvalMultiPoly = "c78649ec-f9ed-405e-be6d-0472f43586aa"
 FourierTools = "b18b359b-aebc-45ac-a139-9c0ccbb2871e"
 Interpolations = "a98d9a8b-a2ab-59e6-89dd-64a1c18fca59"
+Requires = "ae029012-a4dd-5104-9daa-d747884805df"
+StaticArrays = "90137ffa-7385-5640-81b9-e52037218182"
+
+[compat]
+FourierTools = "0.4"
+Interpolations = "0.15.1, 0.16"
+StaticArrays = "1.9.6, 1.10"
+Aqua = "0.8"
+Test = "1.9.3"
+Zygote = "0.6.70"
+julia = "1"
+
+[extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
+
+[targets]
+test = ["Aqua", "Test", "Zygote"]

README.md

@@ -1,2 +1,6 @@
 # DataToFunctions.jl
-Represents (measured) data as a function, which supports scaling and shifting. It is intended to be used as a tool for fitting data, where the fitting function is given by measured data.
+Represents (measured) data as a function, which supports affine and generally, matrix transformations for arrays. It is intended to be used as a tool for fitting data, where the fitting function is given by measured data.
+
+It assumes the data as an Interpolation object (function), then it can transform the data to any arbitrary affine or matrix transformations.
+
+What is important about this package is that it does not assume any pre-defined function as the data for the inverse modeling procedures.

docs/Project.toml

@@ -0,0 +1,11 @@
+[deps]
+DataToFunctions = "64cfdffa-4d02-49ee-ae8b-a805370874f5"
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+DocumenterTools = "35a29f4d-8980-5a13-9543-d66fff28ecb8"
+EvalMultiPoly = "c78649ec-f9ed-405e-be6d-0472f43586aa"
+GR = "28b8d3ca-fb5f-59d9-8090-bfdbd6d07a71"
+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"

docs/make.jl

@@ -0,0 +1,23 @@
+import Pkg
+Pkg.activate(@__DIR__)
+
+cd(@__DIR__) # go into `docs` folder
+
+using Documenter, Literate, DataToFunctions
+
+# convert tutorial/examples to markdown
+Literate.markdown("./src/tutorial.jl", "./src")
+# Which markdown files to compile to HTML
+# (which is also the sidebar and the table
+# of contents for your documentation)
+
+pages = Any[
+        "Introduction" => "index.md",
+        "Tutorial" => "tutorial.md",
+        "API" => "api.md",
+        ]
+
+# compile to HTML:
+makedocs(; sitename="DataToFunctions.jl", pages, modules = [DataToFunctions], warnonly = true)
+
+deploydocs(repo = "github.com/RainerHeintzmann/DataToFunctions.jl.git", devbranch = "develop")

docs/src/api.md

@@ -0,0 +1,20 @@
+# API
+
+```@docs
+get_function
+add_dim
+red_dim
+red_dim_apply
+idx_appy
+mat_mul
+func_transform
+func_transform_tup
+apply_transform
+apply_transform_homogen
+apply_transform_affine
+get_function_tuple
+get_function_svec
+get_function_affine
+get_function_poly
+split_tuple
+```

docs/src/index.md

@@ -0,0 +1,5 @@
+# DataTofunctions.jl
+
+```@docs
+DataToFunctions
+```

docs/src/tutorial.jl

@@ -0,0 +1,50 @@
+# 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
+using StaticArrays
+using Random
+using Plots
+
+# We set the Random.seed for reproducibility
+Random.seed!(14)
+
+# Define the data
+sz = 128
+data = filaments3D((sz, sz, 1), num_filaments=3)[:, :, 1]
+
+# define the interpolation function using this package
+f_affine = get_function_affine(data)
+
+# define the transformation parameters
+params = [1.0, 2.0, 1.2, 0.8, 0.0, 0.0, 0.0]
+
+# apply the transformation
+data_transformed = f_affine(params)
+heatmap(data_transformed, aspect_ratio=1
+        , title="Transformed data using a transformation parameters vector"
+        , titlefontsize=10, size=(500, 500)
+        , xlabel="X", ylabel="Y")
+
+
+## The next example is to use a transformation matrix
+matrix_c = [1.0 0.0 2.0;
+            0.0 1.0 3.0;
+            0.0 0.0 1.0]
+
+data_transformed_m = f_affine(SMatrix{3, 3}(matrix_c))
+heatmap(data_transformed_m, aspect_ratio=1
+        , title="Transformed data using a transformation matrix"
+        , titlefontsize=10, size=(500, 500)
+        , xlabel="X", ylabel="Y")
+
+
+# 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 

docs/src/tutorial.md

@@ -0,0 +1,78 @@
+```@meta
+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
+using DataToFunctions
+using SyntheticObjects
+using StaticArrays
+using Random
+using Plots
+````
+
+We set the Random.seed for reproducibility
+
+````@example tutorial
+Random.seed!(14)
+````
+
+Define the data
+
+````@example tutorial
+sz = 128
+data = filaments3D((sz, sz, 1), num_filaments=3)[:, :, 1]
+````
+
+define the interpolation function using this package
+
+````@example tutorial
+f_affine = get_function_affine(data)
+````
+
+define the transformation parameters
+
+````@example tutorial
+params = [1.0, 2.0, 1.2, 0.8, 0.0, 0.0, 0.0]
+````
+
+apply the transformation
+
+````@example tutorial
+data_transformed = f_affine(params)
+heatmap(data_transformed, aspect_ratio=1
+        , title="Transformed data using a transformation parameters vector"
+        , titlefontsize=10, size=(500, 500)
+        , xlabel="X", ylabel="Y")
+
+
+# The next example is to use a transformation matrix
+matrix_c = [1.0 0.0 2.0;
+            0.0 1.0 3.0;
+            0.0 0.0 1.0]
+
+data_transformed_m = f_affine(SMatrix{3, 3}(matrix_c))
+heatmap(data_transformed_m, aspect_ratio=1
+        , title="Transformed data using a transformation matrix"
+        , titlefontsize=10, size=(500, 500)
+        , xlabel="X", ylabel="Y")
+````
+
+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
+
+---
+
+*This page was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*
+