Data Structures#
2D Data Structures#
Two-dimensional data structures store and mask 2D arrays containing data (e.g. images) and grids of (y,x) Cartesian coordinates (which are used for evaluating light profiles).
A 2D mask, used for masking values which are associated with a a uniform rectangular grid of pixels. |
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A uniform 2D array of values, which are paired with a 2D mask of pixels. |
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A grid of 2D (y,x) coordinates, which are paired to a uniform 2D mask of pixels. |
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An irregular grid of (y,x) coordinates. |
Imaging#
For datasets taken with a CCD (or similar imaging device), including objects which perform 2D convolution.
An imaging dataset, containing the image data, noise-map, PSF and associated quantities for calculations like the grid. |
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Simulates observations of Imaging data, including simulating the image, noise, blurring due to the telescope optics via the Point Spread Function (PSF) and the background sky. |
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A 2D convolution kernel paired with a mask, providing real-space and FFT-based convolution of images or mapping matrices. |
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A 2D convolution kernel paired with a mask, providing real-space and FFT-based convolution of images or mapping matrices. |
Interferometer#
For datasets taken with an interferometer (E.g. ALMA), including objects which perform a fast Fourier transform to map data to the uv-plane.
An interferometer dataset, containing the visibilities data, noise-map, real-space msk, Fourier transformer and associated quantities for calculations like the grid. |
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Simulates observations of Interferometer data, including transforming a real-space image to complex-valued visibilities in Fourier space and optionally adding complex Gaussian noise. |
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A collection of (real, imag) visibilities which are used to represent the data in an Interferometer dataset. |
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A direct Fourier transform (DFT) operator for radio interferometric imaging. |
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JAX-native Non-Uniform FFT for image -> visibilities, backed by nufftax. |
Over Sampling#
Calculations using grids approximate a 2D line integral of the light in the galaxy which falls in each image-pixel. Different over sampling schemes can be used to efficiently approximate this integral and these objects can be applied to datasets to apply over sampling to their fit.
1D Data Structures#
One-dimensional data structures store and mask 1D arrays and grids of (x) Cartesian coordinates.
Their most common use is manipulating 1D representations of a light or mass profile (e.g. computing the intensity versus radius in 1D, or convergene vs radius).
A 1D mask, representing 1D data on a uniform line of pixels with equal spacing. |
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A uniform 1D array of values, paired with a 1D mask of pixels. |
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A collection of values which are structured as follows: |
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A grid of 1D (x) coordinates, which are paired to a uniform 1D mask of pixels. |