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update links and codes in quickstart (#122)
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docs/src/quickstart.md

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defines a 4d image (3 space dimensions plus one time dimension) with
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the specified name and physical pixel spacing for each coordinate.
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The `AxisArrays` package supports rich and efficient operations on such
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The [`AxisArrays`](https://github.com/JuliaArrays/AxisArrays.jl) package supports rich and efficient operations on such
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arrays, and can be useful to keep track of not just pixel spacing but
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the
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[orientation convention used for multidimensional images](http://www.grahamwideman.com/gw/brain/orientation/orientterms.htm).
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JuliaImages interoperates smoothly with `AxisArrays` and many other
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packages. As further examples,
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- the `ImageMetadata` package (incorporated into `Images` itself)
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- the [`ImageMetadata`](https://github.com/JuliaImages/ImageMetadata.jl) package (incorporated into `Images` itself)
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allows you to "tag" images with custom metadata
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- the `IndirectArrays` package supports indexed (colormap) images
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- the [`IndirectArrays`](https://github.com/JuliaArrays/IndirectArrays.jl) package supports indexed (colormap) images
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- the `MappedArrays` package allows you to represent
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- the [`MappedArrays`](https://github.com/JuliaArrays/MappedArrays.jl) package allows you to represent
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[lazy](https://en.wikipedia.org/wiki/Lazy_evaluation)
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value-transformations, facilitating work with images that may be too
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large to store in memory at once
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- `ImageTransformations` allows you to encode rotations, shears,
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- [`ImageTransformations`](https://github.com/JuliaImages/ImageTransformations.jl) allows you to encode rotations, shears,
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deformations, etc., either eagerly or lazily
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It is very easy to define new array types in Julia--and consequently
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img_lab = rand(Lab, 2, 2)
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```
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```@example pixel
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mosaicview(cat(RGB.(img_gray), # hide
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RGB.(img_rgb), # hide
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RGB.(img_lab), dims=3), # hide
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RGB(1, 1, 1), # hide
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mosaicview(RGB.(img_gray), RGB.(img_rgb), RGB.(img_lab), # hide
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fillvalue=RGB(1, 1, 1), # hide
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nrow=1, npad=2) # hide
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```
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adjacent storage in memory). For more details, please refer to the performance tip:
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[Access arrays in memory order, along columns](https://docs.julialang.org/en/v1/manual/performance-tips/#Access-arrays-in-memory-order,-along-columns-1)
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You can use `permuteddimsview` to "reinterpret" the orientation of a
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You can use `PermutedDimsArray` to "reinterpret" the orientation of a
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chunk of memory without making a copy, or `permutedims` if you want a
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copy.
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float.(img_n0f8_raw)
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```
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Conversions between the storage type without changing the color type are supported
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by the following functions:
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Conversions between the storage type, i.e., the actual numeric type, without changing the color type
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are supported by the following functions:
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* `float32`, `float64`
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* `n0f8`, `n6f10`, `n4f12`, `n2f14`, `n0f16`
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* [`float32`](@ref), [`float64`](@ref)
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* [`n0f8`](@ref), [`n6f10`](@ref), [`n4f12`](@ref), [`n2f14`](@ref), [`n0f16`](@ref)
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```@repl fixedpoint
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img = rand(Gray{N0f8}, 2, 2)

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