autocti.ImagingCI#

class autocti.ImagingCI(data: Array2D, noise_map: Array2D, pre_cti_data: Array2D, layout: Layout2DCI, cosmic_ray_map: Optional[Array2D] = None, mask_persistence=None, noise_scaling_map_dict: Optional[Dict] = None, fpr_value: Optional[float] = None, settings_dict: Optional[Dict] = None)[source]#

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

Parameters:

  • data – The array of the image data, for example in units of electrons per second.

  • noise_map – An array describing the RMS standard deviation error in each pixel, for example in units of electrons per second.

  • psf – An array describing the Point Spread Function kernel of the image which accounts for diffraction due to the telescope optics via 2D convolution.

  • settings – Controls settings of how the dataset is set up (e.g. the types of grids used to perform calculations).

  • check_noise_map – If True, the noise-map is checked to ensure all values are above zero.

__init__(data: Array2D, noise_map: Array2D, pre_cti_data: Array2D, layout: Layout2DCI, cosmic_ray_map: Optional[Array2D] = None, mask_persistence=None, noise_scaling_map_dict: Optional[Dict] = None, fpr_value: Optional[float] = None, settings_dict: Optional[Dict] = None)[source]#

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

Parameters:

  • data – The array of the image data, for example in units of electrons per second.

  • noise_map – An array describing the RMS standard deviation error in each pixel, for example in units of electrons per second.

  • psf – An array describing the Point Spread Function kernel of the image which accounts for diffraction due to the telescope optics via 2D convolution.

  • settings – Controls settings of how the dataset is set up (e.g. the types of grids used to perform calculations).

  • check_noise_map – If True, the noise-map is checked to ensure all values are above zero.

Methods

__init__(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).

apply_mask(mask)

Apply a mask to the imaging dataset, whereby the mask is applied to the image data, noise-map and other quantities one-by-one.

apply_settings(settings)

Returns a new instance of the imaging with the input SettingsImaging applied to them.

from_fits(pixel_scales, layout[, data_path, ...])

Load charge injection imaging from multiple .fits file.

output_to_fits(data_path[, noise_map_path, ...])

Output the charge injection imaging dataset to multiple .fits file.

set_noise_scaling_map_dict(...)

trimmed_after_convolution_from(kernel_shape)

Attributes

blurring_grid

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

convolver

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

grid

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

grid_pixelization

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

mask

noise_covariance_matrix_inv

A property that is only computed once per instance and then replaces itself with an ordinary attribute.

norm_columns_list

The layout describes the 2D regions on the data containing charge whose input signal properties are know beforehand (e.g.

pixel_scales

pre_cti_data_residual_map

The residuals of the data and the pre CTI data.

region_list

shape_native

shape_slim

signal_to_noise_map

The estimated signal-to-noise_maps mappers of the image.

signal_to_noise_max

The maximum value of signal-to-noise_maps in an image pixel in the image's signal-to-noise_maps mappers.

w_tilde

A property that is only computed once per instance and then replaces itself with an ordinary attribute.