Round in numpy to Nearest Step

Question

I would like to know how I can round a number in numpy to an upper or lower threshold which is function of predefined step size. Hopefully stated in a clearer way, if I have the number 123 and a step size equal to 50, I need to round 123 to the closest of either 150 or 100, in this case 100. I came out with function below which does the work but I wonder if there is a better, more succint, way to do this.

Thanks in advance,

Paolo

def getRoundedThresholdv1(a, MinClip):
    import numpy as np
    import math
    digits = int(math.log10(MinClip))+1
    b = np.round(a, -digits)
    if b > a:  # rounded-up
        c = b - MinClip
        UpLow = np.array((b,c))
    else:  # rounded-down
        c = b + MinClip
        UpLow = np.array((c,b))
    AbsDelta = np.abs(a - UpLow)
    return UpLow[AbsDelta.argmin()]




getRoundedThresholdv1(143, 50)

Answer 1

The solution by pb360 is much better, using the second argument of builtin round in python3.

I think you don't need numpy:

def getRoundedThresholdv1(a, MinClip):
    return round(float(a) / MinClip) * MinClip

here a is a single number, if you want to vectorize this function you only need to replace round with np.round and float(a) with np.array(a, dtype=float)