aopp_deconv_tool.algorithm.deconv.clean_modified.CleanModified

A modified verison of the CLEAN algorithm, designed to account for extended emission.

# ARGUMENTS #

n_iter : int = 1000

Number of iterations to perform

loop_gain : float = 0.02

Fraction of emission that could be accounted for by a PSF added to components with each iteration. Higher values are faster but unstable

threshold : float = 0.3

Fraction of maximum brightness of residual above which pixels will be included in CLEAN step, if negative will use the "maximum fractional difference otsu threshold". 0.3 is a good default value, if stippling becomes an issue, reduce or set to a negative value. Lower positive numbers will require more iterations, but give a more "accurate" result.

n_positive_iter : int = 0

Number of iterations to do that only "adds" emission, before switching to "adding and subtracting" emission.

noise_std : float = 1E-1

Estimate of the deviation of the noise present in the observation

rms_frac_threshold : float = 1E-3

Fraction of original RMS of residual at which iteration is stopped, lower values continue iteration for longer.

fabs_frac_threshold : float = 1E-3

Fraction of original Absolute Brightest Pixel of residual at which iteration is stopped, lower values continue iteration for longer.

max_stat_increase : float = np.inf

Maximum fractional increase of a statistic before terminating

min_frac_stat_delta : float = 1E-3

Minimum fractional standard deviation of statistics before assuming no progress is being made and terminating iteration.

give_best_result : bool = True

If True, will return the best (measured by statistics) result instead of final result.

# RETURNS #

A "CleanModified" instance. Run the model using the __call__(...) method. e.g. ``` from aopp_deconv_tool.algorithm.deconv.clean_modified import CleanModified

deconvolver = CleanModified() ... deconv_components, deconv_residual, deconv_iters = deconvolver(processed_obs, normed_psf)

``` See aopp_deconv_tool.deconvolve for a full example.