bpo-33089: Add math.dist() for computing the Euclidean distance between two points (GH-8561)

This commit is contained in:
Raymond Hettinger 2018-07-31 00:45:49 -07:00 committed by GitHub
parent 9d5727326a
commit 9c18b1ae52
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
5 changed files with 236 additions and 1 deletions

View file

@ -4,9 +4,11 @@
from test.support import run_unittest, verbose, requires_IEEE_754
from test import support
import unittest
import itertools
import math
import os
import platform
import random
import struct
import sys
import sysconfig
@ -787,6 +789,107 @@ class MathTests(unittest.TestCase):
scale = FLOAT_MIN / 2.0 ** exp
self.assertEqual(math.hypot(4*scale, 3*scale), 5*scale)
def testDist(self):
from decimal import Decimal as D
from fractions import Fraction as F
dist = math.dist
sqrt = math.sqrt
# Simple exact case
self.assertEqual(dist((1, 2, 3), (4, 2, -1)), 5.0)
# Test different numbers of arguments (from zero to nine)
# against a straightforward pure python implementation
for i in range(9):
for j in range(5):
p = tuple(random.uniform(-5, 5) for k in range(i))
q = tuple(random.uniform(-5, 5) for k in range(i))
self.assertAlmostEqual(
dist(p, q),
sqrt(sum((px - qx) ** 2.0 for px, qx in zip(p, q)))
)
# Test allowable types (those with __float__)
self.assertEqual(dist((14.0, 1.0), (2.0, -4.0)), 13.0)
self.assertEqual(dist((14, 1), (2, -4)), 13)
self.assertEqual(dist((D(14), D(1)), (D(2), D(-4))), D(13))
self.assertEqual(dist((F(14, 32), F(1, 32)), (F(2, 32), F(-4, 32))),
F(13, 32))
self.assertEqual(dist((True, True, False, True, False),
(True, False, True, True, False)),
sqrt(2.0))
# Test corner cases
self.assertEqual(dist((13.25, 12.5, -3.25),
(13.25, 12.5, -3.25)),
0.0) # Distance with self is zero
self.assertEqual(dist((), ()), 0.0) # Zero-dimensional case
self.assertEqual(1.0, # Convert negative zero to positive zero
math.copysign(1.0, dist((-0.0,), (0.0,)))
)
self.assertEqual(1.0, # Convert negative zero to positive zero
math.copysign(1.0, dist((0.0,), (-0.0,)))
)
# Verify tuple subclasses are allowed
class T(tuple): # tuple subclas
pass
self.assertEqual(dist(T((1, 2, 3)), ((4, 2, -1))), 5.0)
# Test handling of bad arguments
with self.assertRaises(TypeError): # Reject keyword args
dist(p=(1, 2, 3), q=(4, 5, 6))
with self.assertRaises(TypeError): # Too few args
dist((1, 2, 3))
with self.assertRaises(TypeError): # Too many args
dist((1, 2, 3), (4, 5, 6), (7, 8, 9))
with self.assertRaises(TypeError): # Scalars not allowed
dist(1, 2)
with self.assertRaises(TypeError): # Lists not allowed
dist([1, 2, 3], [4, 5, 6])
with self.assertRaises(TypeError): # Reject values without __float__
dist((1.1, 'string', 2.2), (1, 2, 3))
with self.assertRaises(ValueError): # Check dimension agree
dist((1, 2, 3, 4), (5, 6, 7))
with self.assertRaises(ValueError): # Check dimension agree
dist((1, 2, 3), (4, 5, 6, 7))
# Verify that the one dimensional case equivalent to abs()
for i in range(20):
p, q = random.random(), random.random()
self.assertEqual(dist((p,), (q,)), abs(p - q))
# Test special values
values = [NINF, -10.5, -0.0, 0.0, 10.5, INF, NAN]
for p in itertools.product(values, repeat=3):
for q in itertools.product(values, repeat=3):
diffs = [px - qx for px, qx in zip(p, q)]
if any(map(math.isinf, diffs)):
# Any infinite difference gives positive infinity.
self.assertEqual(dist(p, q), INF)
elif any(map(math.isnan, diffs)):
# If no infinity, any NaN gives a Nan.
self.assertTrue(math.isnan(dist(p, q)))
# Verify scaling for extremely large values
fourthmax = FLOAT_MAX / 4.0
for n in range(32):
p = (fourthmax,) * n
q = (0.0,) * n
self.assertEqual(dist(p, q), fourthmax * math.sqrt(n))
self.assertEqual(dist(q, p), fourthmax * math.sqrt(n))
# Verify scaling for extremely small values
for exp in range(32):
scale = FLOAT_MIN / 2.0 ** exp
p = (4*scale, 3*scale)
q = (0.0, 0.0)
self.assertEqual(math.dist(p, q), 5*scale)
self.assertEqual(math.dist(q, p), 5*scale)
def testLdexp(self):
self.assertRaises(TypeError, math.ldexp)
self.ftest('ldexp(0,1)', math.ldexp(0,1), 0)