occult2#
- sunkit_image.trace.occult2(image, nsm1, rmin, lmin, nstruc, ngap, qthresh1, qthresh2)[source]#
Implements the Oriented Coronal CUrved Loop Tracing (OCCULT-2) algorithm for loop tracing in images.
- Parameters:
image (
numpy.ndarray
,sunpy.map.GenericMap
) – Image in which loops are to be detected.nsm1 (
int
) – Low pass filter boxcar smoothing constant.rmin (
int
) – The minimum radius of curvature of the loop to be detected in pixels.lmin (
int
) – The length of the smallest loop to be detected in pixels.nstruc (
int
) – Maximum limit of traced structures.ngap (
int
) – Number of pixels in the loop below the flux threshold.qthresh1 (
float
) – The ratio of image base flux and median flux. All the pixels in the image belowqthresh1 * median
intensity value are made to zero before tracing the loops.qthresh2 (
float
) – The factor which determines noise in the image. All the intensity values betweenqthresh2 * median
are considered to be noise. The median for noise is chosen after the base level is fixed.
- Returns:
list
– A list of all loop where each element is itself a list of points containingx
andy
pixel coordinates for each point.
References
Markus J. Aschwanden, Bart De Pontieu, Eugene A. Katrukha. Optimization of Curvi-Linear Tracing Applied to Solar Physics and Biophysics. Entropy, vol. 15, issue 8, pp. 3007-3030 https://doi.org/10.3390/e15083007