tkp.sourcefinder.extract
– Source extraction routines¶
Source Extraction Helpers.
These are used in conjunction with image.ImageData.
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class
tkp.sourcefinder.extract.
Detection
(paramset, imagedata, chunk=None, eps_ra=0, eps_dec=0)[source]¶ The result of a measurement at a given position in a given image.
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class
tkp.sourcefinder.extract.
Island
(data, rms, chunk, analysis_threshold, detection_map, beam, deblend_nthresh, deblend_mincont, structuring_element, rms_orig=None, flux_orig=None, subthrrange=None)[source]¶ The source extraction process forms islands, which it then fits. Each island needs to know its position in the image (ie, x, y pixel value at one corner), the threshold above which it is detected (analysis_threshold by default, but will increase if the island is the result of deblending), and a data array.
The island should provide a means of deblending: splitting itself apart and returning multiple sub-islands, if necessary.
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class
tkp.sourcefinder.extract.
ParamSet
(clean_bias=0.0, clean_bias_error=0.0, frac_flux_cal_error=0.0, alpha_maj1=2.5, alpha_min1=0.5, alpha_maj2=0.5, alpha_min2=2.5, alpha_maj3=1.5, alpha_min3=1.5)[source]¶ All the source fitting methods should go to produce a ParamSet, which gives all the information necessary to make a Detection.
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tkp.sourcefinder.extract.
source_profile_and_errors
(data, threshold, noise, beam, fixed=None)[source]¶ Return a number of measurable properties with errorbars
Given an island of pixels it will return a number of measurable properties including errorbars. It will also compute residuals from Gauss fitting and export these to a residual map.
In addition to handling the initial parameter estimation, and any fits which fail to converge, this function runs the goodness-of-fit calculations - see
tkp.sourcefinder.fitting.goodness_of_fit()
for details.Parameters: - data (numpy.ndarray) – array of pixel values, can be a masked array, which is necessary for proper Gauss fitting, because the pixels below the threshold in the corners and along the edges should not be included in the fitting process
- threshold (float) – Threshold used for selecting pixels for the source (ie, building an island)
- noise (float) – Noise level in data
- beam (tuple) – beam parameters (semimaj,semimin,theta)
Kwargs:
- fixed (dict): Parameters (and their values) to hold fixed while fitting.
- Passed on to fitting.fitgaussian().
Returns: - a populated ParamSet, and a residuals map.
- Note the residuals map is a regular ndarray, where masked (unfitted) regions have been filled with 0-values.
Return type: tuple