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Description
Create plot routine for extractor StetsonL.
Path: feets.extractors.ext_stetson.py
Features
- StetsonL
Extractor Documentation
These three features are based on the Welch/Stetson variability index I (Stetson, 1996) defined by the equation:
$$I = \sqrt{\frac{1}{n(n-1)}} \sum_{i=1}^n { (\frac{b_i-\hat{b}}{\sigma_{b,i}}) (\frac{v_i - \hat{v}}{\sigma_{v,i}})}$$ where :math:b_i and vi are the apparent magnitudes obtained for the candidate star in two observations closely spaced in time on some occasion i, σb, i and σv, i are the standard errors of those magnitudes, b̂ and hat{v} are the weighted mean magnitudes in the two filters, and n is the number of observation pairs.
Since a given frame pair may include data from two filters which did not have equal numbers of observations overall, the "relative error" is calculated as follows:
$$\delta = \sqrt{\frac{n}{n-1}} \frac{v-\hat{v}}{\sigma_v}$$ allowing all residuals to be compared on an equal basis.
StetsonL
Stetson L variability index describes the synchronous variability of different bands and is defined as:
$$L = \frac{JK}{0.798}$$ Again, for a Gaussian magnitude distribution, L should take a value close to zero:
>>> fs = feets.FeatureSpace(only=['SlottedL']) >>> features, values = fs.extract(**lc_normal) >>> dict(zip(features, values)) {'StetsonL': 0.0085957106316273714}References