min_best_rescale

astroplan.min_best_rescale(vals, min_val, max_val, less_than_min=1)

rescales an input array vals to be a score (between zero and one), where the min_val goes to one, and the max_val goes to zero.

Parameters:

vals : array-like

the values that need to be rescaled to be between 0 and 1

min_val : float

worst acceptable value (rescales to 0)

max_val : float

best value cared about (rescales to 1)

less_than_min : 0 or 1

what is returned for vals below min_val. (in some cases anything less than min_val should also return one, in some cases it should return zero)

Returns:

array of floats between 0 and 1 inclusive rescaled so that

vals equal to max_val equal 0 and those equal to

min_val equal 1

Examples

rescale airmasses to between 0 and 1, with the best (1) and worst (2.25). All values outside the range should return 0. >>> from astroplan.constraints import min_best_rescale >>> import numpy as np >>> airmasses = np.array([1, 1.5, 2, 3, 0]) >>> min_best_rescale(airmasses, 1, 2.25, less_than_min = 0) array([ 1. , 0.6, 0.2, 0. , 0. ])