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. |
|
A uniform 2D array of values, which are paired with a 2D mask of pixels. |
|
A grid of 2D (y,x) coordinates, which are paired to a uniform 2D mask of pixels. |
|
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. |
|
Simulations observations of imaging data, including simulation of the image, noise-map, PSF, etc. |
|
An array of values, which are paired to a uniform 2D mask of pixels. |
|
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.
An interferometer dataset, containing the visibilities data, noise-map, real-space msk, Fourier transformer and associated quantities for calculations like the grid. |
|
A class representing a Imaging observation, using the shape of the image, the pixel scale, psf, exposure time, etc. |
|
A collection of (real, imag) visibilities which are used to represent the data in an Interferometer dataset. |
|
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.
Over samples grid calculations using a uniform sub-grid. |
|
Over samples grid calculations using an iterative sub-grid that increases the sampling until a threshold accuracy is met. |
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. |
|
A collection of values which are structured as follows: |
|
A grid of 1D (x) coordinates, which are paired to a uniform 1D mask of pixels. |