autocti.FitDataset1D#

class autocti.FitDataset1D(dataset: Dataset1D, post_cti_data)[source]#

Bases: FitDataset

Fit a 1D CTI dataset with model cti data.

Parameters:

dataset – The charge injection image that is fitted.
post_cti_data – The pre_cti_data with cti added to it via the clocker and a CTI model.

Methods

Attributes

`chi_squared`	Returns the chi-squared terms of the model data's fit to an dataset, by summing the chi-squared-map.
`chi_squared_map`	Returns the chi-squared-map between the residual-map and noise-map, where:
`data`
`dataset_1d`
`figure_of_merit`
`inversion`	Overwrite this method so it returns the inversion used to fit the dataset.
`log_evidence`	Returns the log evidence of the inversion's fit to a dataset, where the log evidence includes a number of terms which quantify the complexity of an inversion's reconstruction (see the Inversion module):
`log_likelihood`	Returns the log likelihood of each model data point's fit to the dataset, where:
`log_likelihood_with_regularization`	Returns the log likelihood of an inversion's fit to the dataset, including a regularization term which comes from an inversion:
`mask`	Overwrite this method so it returns the mask of the dataset which is fitted to the input data.
`model_data`	Overwrite this method so it returns the model-data which is fitted to the input data.
`noise_map`
`noise_normalization`	Returns the noise-map normalization term of the noise-map, summing the noise_map value in every pixel as:
`normalized_residual_map`	Returns the normalized residual-map between the masked dataset and model data, where:
`pre_cti_data`
`reduced_chi_squared`
`residual_flux_fraction_map`	Returns the residual flux fraction map, which shows the fraction of signal in each pixel that is not fitted by the model, therefore where:
`residual_map`	Returns the residual-map between the masked dataset and model data, where:
`signal_to_noise_map`	The signal-to-noise_map of the dataset and noise-map which are fitted.

property mask: Mask1D#: Overwrite this method so it returns the mask of the dataset which is fitted to the input data.

property model_data: Array1D#: Overwrite this method so it returns the model-data which is fitted to the input data.