#0200

Pairwise L1 Distance

MediumNumPy25 min20 XP

Problem

Return a matrix where result[i, j] is the Manhattan distance between A[i] and B[j].

Why This Matters

Pairwise distances power nearest neighbors, clustering, retrieval, and recommendation prototypes.

Function Signature

def pairwise_l1(A, B):

Examples

Example 1

InputA = [[1,2],[3,4]], B = [[1,1],[5,4]]

Output[[1, 6], [5, 2]]

Distance from [1,2] to [1,1] is 1; from [1,2] to [5,4] is 6.

Constraints

Return the exact requested result.
Handle common edge cases.
Keep the solution readable before optimizing.

CodePython

import numpy as np

def pairwise_l1(A, B):
    """
    Input example: A = [[1,2],[3,4]], B = [[1,1],[5,4]]
    Return: [[1, 6], [5, 2]]
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return None

import numpy as np

def pairwise_l1(A, B):
    """
    Input example: A = [[1,2],[3,4]], B = [[1,1],[5,4]]
    Return: [[1, 6], [5, 2]]
    Return the value from the function so the tests can compare it. Do not print unless the prompt asks.
    """
    # write your code here
    return None

Visible browser tests run here when available.

Testcases1 visible / 3 hidden categories

Core example

InputA = [[1,2],[3,4]], B = [[1,1],[5,4]]

Expected[[1, 6], [5, 2]]

Distance from [1,2] to [1,1] is 1; from [1,2] to [5,4] is 6.

Hidden Test Categories

empty or minimal inputrepeated valueslarger realistic input