# Python: round float values to interval limits / grid

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I've got an array of (random) floating point numbers. I want to round each value up to a limit of an arbitrary grid. See the following example:

``import numpy as np np.random.seed(1)  # Setup sample = np.random.normal(loc=20, scale=6, size=10) intervals = [-np.inf, 10, 12, 15, 18, 21, 25, 30, np.inf]  # Round each interval up for i in range(len(intervals) - 1):     sample[np.logical_and(sample > intervals[i], sample <= intervals[i+1])] = intervals[i+1] ``

This results in:

``[ 30.  18.  18.  15.  30.  10.  inf  18.  25.  21.] ``

How can I avoid the `for` loop? I'm sure there's some way using NumPy's array magic that I don't see right now.

If `intervals` is sorted, you can use `np.searchsorted`:

``np.array(intervals)[np.searchsorted(intervals, sample)] # array([ 30.,  18.,  18.,  15.,  30.,  10.,  inf,  18.,  25.,  21.]) ``

`searchsorted` returns the index of the interval where the element belongs to:

``np.searchsorted(intervals, sample) # array([7, 4, 4, 3, 7, 1, 8, 4, 6, 5]) ``

The default `side='left'` returns the smallest index of such interval and the result falls into the left open, right close scenario.