JuliaAstro · sefffal · Jun 15, 2022 · Dec 28, 2021 · Dec 28, 2021 · Dec 28, 2021
diff --git a/.gitignore b/.gitignore
@@ -7,3 +7,7 @@ Manifest.toml
 
 # test files
 /test/data
+
+
+# built docs
+/docs/build
diff --git a/Project.toml b/Project.toml
@@ -1,29 +1,39 @@
 name = "AstroImages"
 uuid = "fe3fc30c-9b16-11e9-1c73-17dabf39f4ad"
-authors = ["Mosè Giordano", "Rohit Kumar"]
-version = "0.2.0"
+authors = ["Mosè Giordano", "Rohit Kumar", "William Thompson"]
+version = "0.3.0"
 
 [deps]
+AbstractFFTs = "621f4979-c628-5d54-868e-fcf4e3e8185c"
+AstroAngles = "5c4adb95-c1fc-4c53-b4ea-2a94080c53d2"
+ColorSchemes = "35d6a980-a343-548e-a6ea-1d62b119f2f4"
+DimensionalData = "0703355e-b756-11e9-17c0-8b28908087d0"
 FITSIO = "525bcba6-941b-5504-bd06-fd0dc1a4d2eb"
 FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
-ImageMagick = "6218d12a-5da1-5696-b52f-db25d2ecc6d1"
-Images = "916415d5-f1e6-5110-898d-aaa5f9f070e0"
-Interact = "c601a237-2ae4-5e1e-952c-7a85b0c7eef1"
+ImageAxes = "2803e5a7-5153-5ecf-9a86-9b4c37f5f5ac"
+ImageCore = "a09fc81d-aa75-5fe9-8630-4744c3626534"
+ImageMetadata = "bc367c6b-8a6b-528e-b4bd-a4b897500b49"
+ImageShow = "4e3cecfd-b093-5904-9786-8bbb286a6a31"
+ImageTransformations = "02fcd773-0e25-5acc-982a-7f6622650795"
+MappedArrays = "dbb5928d-eab1-5f90-85c2-b9b0edb7c900"
+PlotUtils = "995b91a9-d308-5afd-9ec6-746e21dbc043"
+Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 RecipesBase = "3cdcf5f2-1ef4-517c-9805-6587b60abb01"
-Reproject = "d1dcc2e6-806e-11e9-2897-3f99785db2ae"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+Tables = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
+UUIDs = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
 WCS = "15f3aee2-9e10-537f-b834-a6fb8bdb944d"
-MappedArrays = "dbb5928d-eab1-5f90-85c2-b9b0edb7c900"
 
 [compat]
-julia = "^1.0.0"
-Reproject = "^0.3.0"
+DimensionalData = "^0.20"
+julia = "^1.6.0"
 
 [extras]
+JLD = "4138dd39-2aa7-5051-a626-17a0bb65d9c8"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+SHA = "ea8e919c-243c-51af-8825-aaa63cd721ce"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 Widgets = "cc8bc4a8-27d6-5769-a93b-9d913e69aa62"
-JLD = "4138dd39-2aa7-5051-a626-17a0bb65d9c8"
-SHA = "ea8e919c-243c-51af-8825-aaa63cd721ce"
 
 [targets]
 test = ["Test", "Random", "Widgets", "JLD", "SHA"]
diff --git a/README.md b/README.md
@@ -8,17 +8,17 @@
 Introduction
 ------------
 
-`AstroImage.jl` allows you to plot images from an
+`AstroImages.jl` allows you to plot images from an
 astronomical [`FITS`](https://en.wikipedia.org/wiki/FITS) file using the
 popular [`Images.jl`](https://github.com/JuliaImages/Images.jl)
 and [`Plots.jl`](https://github.com/JuliaPlots/Plots.jl) Julia packages.
-`AstroImage.jl` uses [`FITSIO.jl`](https://github.com/JuliaAstro/FITSIO.jl) to
+`AstroImages.jl` uses [`FITSIO.jl`](https://github.com/JuliaAstro/FITSIO.jl) to
 read FITS files.
 
 Installation
 ------------
 
-`AstroImage.jl` is available for Julia 1.0 and later versions, and can be
+`AstroImages.jl` is available for Julia 1.6 and later versions, and can be
 installed with [Julia built-in package
 manager](https://docs.julialang.org/en/v1/stdlib/Pkg/).
 
@@ -55,44 +55,44 @@ julia> load("file.fits", 3)
 [...]
 ```
 
-## AstroImage type
+## AstroImageMat type
 
-The package provides a new type, `AstroImage` to integrate FITS images with
-Julia packages for plotting and image processing.  The `AstroImage` function has
+The package provides a new type, `AstroImageMat` to integrate FITS images with
+Julia packages for plotting and image processing.  The `AstroImageMat` function has
 the same syntax as `load`.  This command:
 
 ```julia
-julia> img = AstroImage("file.fits")
-AstroImages.AstroImage{UInt16,ColorTypes.Gray,1,Float64}[...]
+julia> img = AstroImageMat("file.fits")
+AstroImages.AstroImageMat{UInt16,ColorTypes.Gray,1,Float64}[...]
 ```
 
 will read the first valid extension from the `file.fits` file and wrap its content in
 a `NTuple{N, Matrix{Gray}}`, that can be easily used with `Images.jl` and related packages.
 
-If you are working in a Jupyter notebook, an `AstroImage` object is
+If you are working in a Jupyter notebook, an `AstroImageMat` object is
 automatically rendered as a PNG image.
 
-`AstroImage` automatically extracts and store `wcs` information of images in a `NTuple{N, WCSTransform}`.
+`AstroImageMat` automatically extracts and store `wcs` information of images in a `NTuple{N, WCSTransform}`.
 
 ## Forming RGB image
-`AstroImage` can automatically construct a RGB image if 3 different colour band data is given.
+`AstroImageMat` can automatically construct a RGB image if 3 different colour band data is given.
 
 ```julia
-julia> img = AstroImage(RGB, ("file1.fits","file2.fits", "file3.fits"))
+julia> img = AstroImageMat(RGB, ("file1.fits","file2.fits", "file3.fits"))
 ```
 Where 1st index of `file1.fits`, `file2.fits`, `file3.fits` contains band data of red, blue and  green channels respectively.
 
-Optionally, `ccd2rgb` method can be used to form a coloured image from 3 bands without creating an `AstroImage`.
+Optionally, `ccd2rgb` method can be used to form a coloured image from 3 bands without creating an `AstroImageMat`.
 
 The formed image can be accessed using `img.property.rgb_image`. 
 `set_brightness!` and `set_contrast!` methods can be used to change brightness and contrast of formed `rgb_image`.
-`add_label!` method can be used to add/store Astronomical labels in an `AstroImage`.
+`add_label!` method can be used to add/store Astronomical labels in an `AstroImageMat`.
 `reset!` method resets `brightness`, `contrast` and `label` fields to defaults and construct a fresh `rgb_image` without any brightness, contrast operations.
 
 
-## Plotting an AstroImage
+## Plotting an AstroImageMat
 
-An `AstroImage` object can be plotted with `Plots.jl` package.  Just use
+An `AstroImageMat` object can be plotted with `Plots.jl` package.  Just use
 
 ```julia
 julia> using Plots

diff --git a/docs/Project.toml b/docs/Project.toml
@@ -0,0 +1,5 @@
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+
+[compat]
+Documenter = "0.27"
diff --git a/docs/make.jl b/docs/make.jl
@@ -0,0 +1,22 @@
+using Documenter, AstroImages
+makedocs(
+    sitename="AstroImages.jl",
+    pages = [
+        "Home" => "index.md",
+        "Tour" => "tour.md",
+        "Tutorials" => [
+            "Getting Started" => "getting-started.md"
+        ],
+        "API" => "api.md",
+    ],
+    format = Documenter.HTML(
+        prettyurls = get(ENV, "CI", nothing) == "true"
+    ),
+    workdir=".."
+)
+
+
+# deploydocs(
+#     repo = "github.com/sefffal/AstroImages.jl.git",
+#     devbranch = "main"
+# )
diff --git a/docs/src/api.md b/docs/src/api.md
@@ -0,0 +1,48 @@
+# API Documentation
+
+
+```@docs
+load
+save
+AstroImage
+AstroImageVec
+AstroImageMat
+arraydata
+header
+Comment
+History
+wcs
+pix_to_world
+pix_to_world!
+world_to_pix
+world!_to_pix
+X
+Y
+Z
+Dim
+At
+Near
+Between
+..
+dims
+refdims
+clampednormedview
+WCSGrid
+ccd2rgb
+composechannels
+reset!
+zscale
+percent
+logstretch
+powstretch
+sqrtstretch
+squarestretch
+asinhstretch
+sinhstretch
+powerdiststretch
+imview
+implot
+copyheader
+shareheader
+ImageCore.normedview
+```
diff --git a/docs/src/getting-started.md b/docs/src/getting-started.md
@@ -0,0 +1 @@
+# Getting Started
diff --git a/docs/src/index.md b/docs/src/index.md
@@ -0,0 +1,5 @@
+# Home
+
+AstroImages.jl is a Julia package for loading, manipulating, visualizing, and saving astronomical images.
+
+
diff --git a/docs/src/tour.md b/docs/src/tour.md
@@ -0,0 +1,21 @@
+# Package Tour
+
+To follow along, download the images from the [Fits Liberator](https://esahubble.org/projects/fits_liberator/eagledata/) page and unzip them.
+
+```@meta
+DocTestSetup = quote
+    using AstroImages
+end
+```
+
+```@repl
+using AstroImages
+```
+
+Let's start by loading a FITS file.
+```@repl
+using AstroImages
+eagle_656 = load("fits/656nmos.fits")
+save("eagle-1.png") # hide
+```
+![eagle](eagle-1.png)