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https://github.com/sefffal/directimages.jl
A library for reading, writing, and manipulating astronomical images from FITS files, with tools useful for high contrast (direct) imaging.
https://github.com/sefffal/directimages.jl
Last synced: about 2 months ago
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A library for reading, writing, and manipulating astronomical images from FITS files, with tools useful for high contrast (direct) imaging.
- Host: GitHub
- URL: https://github.com/sefffal/directimages.jl
- Owner: sefffal
- License: mit
- Created: 2020-10-22T20:31:13.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2021-11-08T19:46:01.000Z (about 3 years ago)
- Last Synced: 2024-10-13T18:10:46.908Z (3 months ago)
- Language: Julia
- Homepage:
- Size: 138 KB
- Stars: 3
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DirectImages.jl
A toolbox for working with FITS images in the context of high contrast / direct imaging.
Built on top of FITSIO and the Images ecosystem, this package also bundles
convenient tools for loading and manipulating astronomical images and datacubes.
The main data type is a fork of Tim Holy's ImageMetadata adapted to work with the FITS format
common in astronomy.
## Installation
This package is not in the General registery, but a personal registry for this and related packages.
You can add it as follows:
(`]` to enter Pkg mode)
```julia
pkg> registry add https://github.com/sefffal/DirectRegistry
pkg> add DirectImages
```
## Features
- easily reading and writing FITS images/cubes/etc
- easily access and set FITS headers and comments
- keep track of physical coordinates using OffsetArrays behind the scenes
- contrast measurements
- send data to SAO DS9 for viewing and manipulation
- display data using Plots with reasonable scale limits based +/- standard deviations
- Plots.jl recipe
- contrast measurements for High Contrast Imaging
## Roadmap
- image registration
- photometry
- other image quality metrics, including estimating Strehl
## Example
```julia
# Load an image
img = readfits("M32.fits.gz")
# Get or set headers as properties of the image.
img.DATE_OBS = "2020-01-01"
# Or use indexing
img[:DATE_OBS] = "2020-01-01"
img[:DATE_OBS,/] = "The date the observations were taken"
# Get list of headers
for key in propertnames(img)
println(img[key])
end
# Use offset indices to keep track of image positions
img[-10,10] == 1.2
writefits("out.fits", img)
```
## Measuring contrast
Measure the one-sigma contrast:
```julia
cont = contrast(centered(img))
```
As a linear interpolation function
```julia
cont_itp = contrast_interp(centered(img))
```
## Showing Images
```julia
using Plots
plot(image) # Works if you have a DirectImage
imshow(image) # Works with any abstract array
title!("my image")
```
Or without using Plots:
```julia
imshow2(image)
imshow2(image, cmap=:magma)
imshow2(image, cmap=:magma, clims=(0,10))
```
This will display as a PNG which is less flexible than a Plots heatmap, but much quicker.
By default, `imshow` applies τ=7 (you can override with `nothing`) and `plot` uses
the full colorscale.
Pass `skyconvention=true` to preserve the image, but flip the horizontal axis
so that the coordinates match RA offset. Useful when combining with DirectOrbits.jl.
## Sending to SAO DS9
DS9 must be installed in the usual location on your system.
```julia
# Open a frame or cube
ds9show(image)
# Open multiple frames or cube
ds9show(image1, image2, lock=true) # Lock locks most frame properties (true by default)
# Same as above
ds9show(images_vector, lock=true)
```
Calling `ds9show` with multiple images opens them in the same window. Calling `ds9show` separate times will launch new windows for each. Currently, on MacOS frames are always sent to the open window, whereas on Windows and Linux, a new window is created for each call to `ds9show`.