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.

Mask2D(mask, pixel_scales[, sub_size, ...])

A 2D mask, used for masking values which are associated with a a uniform rectangular grid of pixels.

Array2D(values, mask[, header, ...])

A uniform 2D array of values, which are paired with a 2D mask of pixels which may be split into sub-pixels.

Charge Injection Imaging#

For charge injection datasets taken with a CCD (or similar imaging device).

ImagingCI(data, noise_map, pre_cti_data, layout)

A class containing an imaging dataset, including the image data, noise-map and a point spread function (PSF).

Layout2DCI(shape_2d, region_list[, ...])

A charge injection layout, which defines the regions charge injections appear on a charge injection image.

SettingsImagingCI([parallel_pixels, ...])

The lens dataset is the collection of data_type (image, noise-map, PSF), a mask, grid, convolver and other utilities that are used for modeling and fitting an image of a strong lens.

SimulatorImagingCI(pixel_scales, norm[, ...])

A class representing a Imaging observation, using the shape of the image, the pixel scale, psf, exposure time, etc.

1D Data Structures#

One-dimensional data structures store and mask 1D arrays containing data (e.g. 1D CTI datasets images) and grids of (y,x) Cartesian coordinates.

Mask1D(mask, pixel_scales[, sub_size, ...])

A 1D mask, representing 1D data on a uniform line of pixels with equal spacing.

Array1D(values, mask[, header, store_native])

ArrayIrregular(values)

A collection of values which are structured as follows:

Dataset 1D#

For 1D datasets.

Dataset1D(data, noise_map, pre_cti_data, ...)

A collection of abstract data structures for different types of data (an image, pixel-scale, noise-map, etc.)

SettingsDataset1D([grid_class, ...])

A dataset is a collection of data structures (e.g.

SimulatorDataset1D(pixel_scales, norm[, ...])

A class representing a Imaging observation, using the shape of the data, the pixel scale, psf, exposure time, etc.