autolens.FitPositionsImagePair#
- class FitPositionsImagePair[source]#
Bases:
AbstractFitPositionsImagePair
A lens position fitter, which takes a set of positions (e.g. from a plane in the tracer) and computes their maximum separation, such that points which tracer closer to one another have a higher log_likelihood.
- Parameters:
data (Grid2DIrregular) – The (y,x) arc-second coordinates of positions which the maximum distance and log_likelihood is computed using.
noise_value – The noise-value assumed when computing the log likelihood.
Methods
square_distance
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
Overwrite this method to returns the data of the dataset.
log_likelihood
Returns the log likelihood of each model data point's fit to the dataset, where:
model_data
Returns the model positions, which are computed via the point solver.
noise_map
Overwrite this method to returns the noise-map of the dataset.
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:
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.
source_plane_coordinate
Returns the centre of the point-source in the source-plane, which is used when computing the model image-plane positions from the tracer.
source_plane_index
Returns the integer plane index containing the point source galaxy, which is used when computing the model image-plane positions from the tracer.
source_plane_redshift
Returns the redshift of the plane containing the point source galaxy, which is used when computing the model image-plane positions from the tracer.
- property residual_map: ArrayIrregular#
Returns the residual-map between the masked dataset and model data, where:
Residuals = (Data - Model_Data).