autocti.SimulatorImagingCI

class autocti.SimulatorImagingCI(pixel_scales: Union[Tuple[float], Tuple[float, float], float], norm: float, max_norm: float = inf, column_sigma: Optional[float] = None, row_slope: Optional[float] = 0.0, non_uniform_norm_limit=None, read_noise: Optional[float] = None, charge_noise: Optional[float] = None, noise_if_add_noise_false: float = 0.1, noise_seed: int = -1, ci_seed: int = -1)

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

Parameters:

exposure_time_map – The exposure time of an observation using this data_type.

__init__(pixel_scales: Union[Tuple[float], Tuple[float, float], float], norm: float, max_norm: float = inf, column_sigma: Optional[float] = None, row_slope: Optional[float] = 0.0, non_uniform_norm_limit=None, read_noise: Optional[float] = None, charge_noise: Optional[float] = None, noise_if_add_noise_false: float = 0.1, noise_seed: int = -1, ci_seed: int = -1)

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

Parameters:

exposure_time_map – The exposure time of an observation using this data_type.

Methods

__init__(pixel_scales, norm[, max_norm, ...])	A class representing a Imaging observation, using the shape of the image, the pixel scale, psf, exposure time, etc.
injection_norm_list_with_limit_from(...)
median_list_from(total_columns)
pre_cti_data_non_uniform_from(layout)	Use this charge injection layout to generate a pre-cti charge injection image.
pre_cti_data_uniform_from(layout)	Use this charge injection layout_ci to generate a pre-cti charge injection image.
via_image_from(image)	Simulate an Imaging dataset from an input image.
via_layout_from(layout, clocker, cti[, ...])	Simulate a charge injection image, including effects like noises.
via_post_cti_data_from(post_cti_data, ...[, ...])
via_pre_cti_data_from(pre_cti_data, layout, ...)