#0152

Clamp Values to a Range

EasyNumPy15 min10 XP

Problem

Given an array and low/high bounds, return a new array where every value is between low and high.

Why This Matters

Clipping is common for image pixels, robust preprocessing, and bounded model outputs.

Function Signature

def clamp_values(arr, low, high):

Examples

Example 1

Inputnp.array([-2, 0, 5, 12]), low = 0, high = 10

Outputnp.array([0, 0, 5, 10])

Values below 0 become 0; values above 10 become 10.

Constraints

Return the exact requested value.
Handle empty or small inputs when the prompt allows them.
Keep the code readable and deterministic.

CodePython

import numpy as np

def clamp_values(arr, low, high):
    """
    Input example: np.array([-2, 0, 5, 12]), low = 0, high = 10
    Return: np.array([0, 0, 5, 10])
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return arr

import numpy as np

def clamp_values(arr, low, high):
    """
    Input example: np.array([-2, 0, 5, 12]), low = 0, high = 10
    Return: np.array([0, 0, 5, 10])
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return arr

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

Inputnp.array([-2, 0, 5, 12]), low = 0, high = 10

Expectednp.array([0, 0, 5, 10])

Values below 0 become 0; values above 10 become 10.

Hidden Test Categories

empty or smallest inputduplicates or repeated valueslarger realistic input