This repository was created to automate the analysis of stellar flux and magnitude over multiple images using the astropy and photutils packages. The name is short for "altitude photometry" as the original use case for this repository was to help determine how stellar magnitude varies with the altitude of an observer.
The DAOFIND algorithm is used to detect stars with a peak amplitude above a certain threshold (sigma-clipping allows for this threshold to be relative to background noise) and a size and shape similar to a 2D Gaussian kernel with a certain full width at half maximum (FWHM). Then, multi-aperture photometry is performed for the detected objects, using a configurable analysis aperture and background annulus. The flux and magnitude of the sources is calculated from this process. The detected sources, apertures, and annuli can be visualized in visualization.py.
The remaining processing is slightly different depending on whether the images are classified or not. If the data is not classified, the file single_folder.py simply calculates the flux and magnitude of each image using the specified parameter, creating two graphs of the flux and magnitude of the brightest object versus file index, where filenames are sorted in alphabetical order. If the images are classified within subfolders, e.g., by altitude as in the case of the populated code, the file alt_folder_new.py should be used. This generates four graphs—two of which are identical to those in single_folder.py, organized by file index—and two that consist of the averaged values of flux and magnitude of the images within each subfolder. For the latter two graphs, the subfolder names are presumed to indicate the value of the independent variable. For example, if the subfolders indicate the altitude from which measurements were taken at, the bottom two plots graph the average flux and magnitude of the brightest star by altitude.