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).

`Mask2D`	A 2D mask, used for masking values which are associated with a a uniform rectangular grid of pixels.
`Array2D`	A uniform 2D array of values, which are paired with a 2D mask of pixels.
`Grid2D`	A grid of 2D (y,x) coordinates, which are paired to a uniform 2D mask of pixels.
`Grid2DIrregular`	An irregular grid of (y,x) coordinates.

Imaging#

For datasets taken with a CCD (or similar imaging device), including objects which perform 2D convolution.

`Imaging`	An imaging dataset, containing the image data, noise-map, PSF and associated quantities for calculations like the grid.
`SimulatorImaging`	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.
`Kernel2D`	An array of values, which are paired to a uniform 2D mask of pixels.
`Convolver`	Class to setup the 1D convolution of an / mapping matrix.

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.

`Interferometer`	An interferometer dataset, containing the visibilities data, noise-map, real-space msk, Fourier transformer and associated quantities for calculations like the grid.
`SimulatorInterferometer`	A class representing a Imaging observation, using the shape of the image, the pixel scale, psf, exposure time, etc.
`Visibilities`	A collection of (real, imag) visibilities which are used to represent the data in an Interferometer dataset.
`TransformerDFT`
`TransformerNUFFT`

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).

`Mask1D`	A 1D mask, representing 1D data on a uniform line of pixels with equal spacing.
`Array1D`
`ArrayIrregular`	A collection of values which are structured as follows:
`Grid1D`	A grid of 1D (x) coordinates, which are paired to a uniform 1D mask of pixels.