Histogram

class ginga.AutoCuts.Histogram(logger, usecrop=None, sample='crop', full_px_limit=None, num_points=None, pct=0.999, numbins=2048)[source]

Bases: AutoCutsBase

Calculate the cut levels based on a histogram analysis of the data.

Parameters:

loggerLogger: Logger for tracing and debugging.
samplestr (optional, ‘crop’, ‘grid’, or ‘full’, default: ‘crop’): Specifies how to access the image for calculation: - crop: crop an area from the middle of the image - grid: sample data in a grid pattern across the image - full: use the full image data
full_px_limitint (optional, defaults to 1M): Specifies the limit for using the full data if sample == ‘full’. If the number of pixels in the image is larger than this, then the image will fall back to using a crop.
num_pointsint (optional, defaults to None): Specifies the number of points in the grid if sample == ‘grid’, or the diameter of the crop, if sample == ‘crop’ (or ‘full’ and number of pixels exceeds full_px_limit). If None, the number pixels will be calculated to a “reasonable representative sample”.
pctfloat (optional, range: 0.0 - 1.0, defaults to 0.999): Specifies the percentage of the histogram bins to retain
numbinsint (optional, defaults to 2048): Specifies the number of bins used in calculating the histogram

Methods Summary

`calc_cut_levels`(image)	See subclass documentation.
`calc_cut_levels_data`(data_np)	See subclass documentation.
`calc_histogram`(data[, pct, numbins])	Internal function used by this class.
`get_params_metadata`()

Methods Documentation

calc_cut_levels(image)[source]: See subclass documentation.

calc_cut_levels_data(data_np)[source]: See subclass documentation.

calc_histogram(data, pct=1.0, numbins=2048)[source]: Internal function used by this class.

classmethod get_params_metadata()[source]