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cpython/Lib/test/test_math.py

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# Python test set -- math module
# XXXX Should not do tests around zero only
from test.support import verbose, requires_IEEE_754
from test import support
import unittest
import fractions
import itertools
import decimal
import math
import os
import platform
import random
import struct
import sys
eps = 1E-05
NAN = float('nan')
INF = float('inf')
NINF = float('-inf')
FLOAT_MAX = sys.float_info.max
FLOAT_MIN = sys.float_info.min
# detect evidence of double-rounding: fsum is not always correctly
# rounded on machines that suffer from double rounding.
x, y = 1e16, 2.9999 # use temporary values to defeat peephole optimizer
HAVE_DOUBLE_ROUNDING = (x + y == 1e16 + 4)
# locate file with test values
if __name__ == '__main__':
file = sys.argv[0]
else:
file = __file__
test_dir = os.path.dirname(file) or os.curdir
math_testcases = os.path.join(test_dir, 'mathdata', 'math_testcases.txt')
test_file = os.path.join(test_dir, 'mathdata', 'cmath_testcases.txt')
def to_ulps(x):
"""Convert a non-NaN float x to an integer, in such a way that
adjacent floats are converted to adjacent integers. Then
abs(ulps(x) - ulps(y)) gives the difference in ulps between two
floats.
The results from this function will only make sense on platforms
where native doubles are represented in IEEE 754 binary64 format.
Note: 0.0 and -0.0 are converted to 0 and -1, respectively.
"""
n = struct.unpack('<q', struct.pack('<d', x))[0]
if n < 0:
n = ~(n+2**63)
return n
# Here's a pure Python version of the math.factorial algorithm, for
# documentation and comparison purposes.
#
# Formula:
#
# factorial(n) = factorial_odd_part(n) << (n - count_set_bits(n))
#
# where
#
# factorial_odd_part(n) = product_{i >= 0} product_{0 < j <= n >> i; j odd} j
#
# The outer product above is an infinite product, but once i >= n.bit_length,
# (n >> i) < 1 and the corresponding term of the product is empty. So only the
# finitely many terms for 0 <= i < n.bit_length() contribute anything.
#
# We iterate downwards from i == n.bit_length() - 1 to i == 0. The inner
# product in the formula above starts at 1 for i == n.bit_length(); for each i
# < n.bit_length() we get the inner product for i from that for i + 1 by
# multiplying by all j in {n >> i+1 < j <= n >> i; j odd}. In Python terms,
# this set is range((n >> i+1) + 1 | 1, (n >> i) + 1 | 1, 2).
def count_set_bits(n):
"""Number of '1' bits in binary expansion of a nonnnegative integer."""
return 1 + count_set_bits(n & n - 1) if n else 0
def partial_product(start, stop):
"""Product of integers in range(start, stop, 2), computed recursively.
start and stop should both be odd, with start <= stop.
"""
numfactors = (stop - start) >> 1
if not numfactors:
return 1
elif numfactors == 1:
return start
else:
mid = (start + numfactors) | 1
return partial_product(start, mid) * partial_product(mid, stop)
def py_factorial(n):
"""Factorial of nonnegative integer n, via "Binary Split Factorial Formula"
described at http://www.luschny.de/math/factorial/binarysplitfact.html
"""
inner = outer = 1
for i in reversed(range(n.bit_length())):
inner *= partial_product((n >> i + 1) + 1 | 1, (n >> i) + 1 | 1)
outer *= inner
return outer << (n - count_set_bits(n))
def ulp_abs_check(expected, got, ulp_tol, abs_tol):
"""Given finite floats `expected` and `got`, check that they're
approximately equal to within the given number of ulps or the
given absolute tolerance, whichever is bigger.
Returns None on success and an error message on failure.
"""
ulp_error = abs(to_ulps(expected) - to_ulps(got))
abs_error = abs(expected - got)
# Succeed if either abs_error <= abs_tol or ulp_error <= ulp_tol.
if abs_error <= abs_tol or ulp_error <= ulp_tol:
return None
else:
fmt = ("error = {:.3g} ({:d} ulps); "
"permitted error = {:.3g} or {:d} ulps")
return fmt.format(abs_error, ulp_error, abs_tol, ulp_tol)
def parse_mtestfile(fname):
"""Parse a file with test values
-- starts a comment
blank lines, or lines containing only a comment, are ignored
other lines are expected to have the form
id fn arg -> expected [flag]*
"""
with open(fname, encoding="utf-8") as fp:
for line in fp:
# strip comments, and skip blank lines
if '--' in line:
line = line[:line.index('--')]
if not line.strip():
continue
lhs, rhs = line.split('->')
id, fn, arg = lhs.split()
rhs_pieces = rhs.split()
exp = rhs_pieces[0]
flags = rhs_pieces[1:]
yield (id, fn, float(arg), float(exp), flags)
def parse_testfile(fname):
"""Parse a file with test values
Empty lines or lines starting with -- are ignored
yields id, fn, arg_real, arg_imag, exp_real, exp_imag
"""
with open(fname, encoding="utf-8") as fp:
for line in fp:
# skip comment lines and blank lines
if line.startswith('--') or not line.strip():
continue
lhs, rhs = line.split('->')
id, fn, arg_real, arg_imag = lhs.split()
rhs_pieces = rhs.split()
exp_real, exp_imag = rhs_pieces[0], rhs_pieces[1]
flags = rhs_pieces[2:]
yield (id, fn,
float(arg_real), float(arg_imag),
float(exp_real), float(exp_imag),
flags)
def result_check(expected, got, ulp_tol=5, abs_tol=0.0):
# Common logic of MathTests.(ftest, test_testcases, test_mtestcases)
"""Compare arguments expected and got, as floats, if either
is a float, using a tolerance expressed in multiples of
ulp(expected) or absolutely (if given and greater).
As a convenience, when neither argument is a float, and for
non-finite floats, exact equality is demanded. Also, nan==nan
as far as this function is concerned.
Returns None on success and an error message on failure.
"""
# Check exactly equal (applies also to strings representing exceptions)
if got == expected:
return None
failure = "not equal"
# Turn mixed float and int comparison (e.g. floor()) to all-float
if isinstance(expected, float) and isinstance(got, int):
got = float(got)
elif isinstance(got, float) and isinstance(expected, int):
expected = float(expected)
if isinstance(expected, float) and isinstance(got, float):
if math.isnan(expected) and math.isnan(got):
# Pass, since both nan
failure = None
elif math.isinf(expected) or math.isinf(got):
# We already know they're not equal, drop through to failure
pass
else:
# Both are finite floats (now). Are they close enough?
failure = ulp_abs_check(expected, got, ulp_tol, abs_tol)
# arguments are not equal, and if numeric, are too far apart
if failure is not None:
fail_fmt = "expected {!r}, got {!r}"
fail_msg = fail_fmt.format(expected, got)
fail_msg += ' ({})'.format(failure)
return fail_msg
else:
return None
class FloatLike:
def __init__(self, value):
self.value = value
def __float__(self):
return self.value
class IntSubclass(int):
pass
# Class providing an __index__ method.
class MyIndexable(object):
def __init__(self, value):
self.value = value
def __index__(self):
return self.value
class BadDescr:
def __get__(self, obj, objtype=None):
raise ValueError
class MathTests(unittest.TestCase):
def ftest(self, name, got, expected, ulp_tol=5, abs_tol=0.0):
"""Compare arguments expected and got, as floats, if either
is a float, using a tolerance expressed in multiples of
ulp(expected) or absolutely, whichever is greater.
As a convenience, when neither argument is a float, and for
non-finite floats, exact equality is demanded. Also, nan==nan
in this function.
"""
failure = result_check(expected, got, ulp_tol, abs_tol)
if failure is not None:
self.fail("{}: {}".format(name, failure))
def testConstants(self):
# Ref: Abramowitz & Stegun (Dover, 1965)
self.ftest('pi', math.pi, 3.141592653589793238462643)
self.ftest('e', math.e, 2.718281828459045235360287)
self.assertEqual(math.tau, 2*math.pi)
def testAcos(self):
self.assertRaises(TypeError, math.acos)
self.ftest('acos(-1)', math.acos(-1), math.pi)
self.ftest('acos(0)', math.acos(0), math.pi/2)
self.ftest('acos(1)', math.acos(1), 0)
self.assertRaises(ValueError, math.acos, INF)
self.assertRaises(ValueError, math.acos, NINF)
self.assertRaises(ValueError, math.acos, 1 + eps)
self.assertRaises(ValueError, math.acos, -1 - eps)
self.assertTrue(math.isnan(math.acos(NAN)))
def testAcosh(self):
self.assertRaises(TypeError, math.acosh)
self.ftest('acosh(1)', math.acosh(1), 0)
self.ftest('acosh(2)', math.acosh(2), 1.3169578969248168)
self.assertRaises(ValueError, math.acosh, 0)
self.assertRaises(ValueError, math.acosh, -1)
self.assertEqual(math.acosh(INF), INF)
self.assertRaises(ValueError, math.acosh, NINF)
self.assertTrue(math.isnan(math.acosh(NAN)))
def testAsin(self):
self.assertRaises(TypeError, math.asin)
self.ftest('asin(-1)', math.asin(-1), -math.pi/2)
self.ftest('asin(0)', math.asin(0), 0)
self.ftest('asin(1)', math.asin(1), math.pi/2)
self.assertRaises(ValueError, math.asin, INF)
self.assertRaises(ValueError, math.asin, NINF)
self.assertRaises(ValueError, math.asin, 1 + eps)
self.assertRaises(ValueError, math.asin, -1 - eps)
self.assertTrue(math.isnan(math.asin(NAN)))
def testAsinh(self):
self.assertRaises(TypeError, math.asinh)
self.ftest('asinh(0)', math.asinh(0), 0)
self.ftest('asinh(1)', math.asinh(1), 0.88137358701954305)
self.ftest('asinh(-1)', math.asinh(-1), -0.88137358701954305)
self.assertEqual(math.asinh(INF), INF)
self.assertEqual(math.asinh(NINF), NINF)
self.assertTrue(math.isnan(math.asinh(NAN)))
def testAtan(self):
self.assertRaises(TypeError, math.atan)
self.ftest('atan(-1)', math.atan(-1), -math.pi/4)
self.ftest('atan(0)', math.atan(0), 0)
self.ftest('atan(1)', math.atan(1), math.pi/4)
self.ftest('atan(inf)', math.atan(INF), math.pi/2)
self.ftest('atan(-inf)', math.atan(NINF), -math.pi/2)
self.assertTrue(math.isnan(math.atan(NAN)))
def testAtanh(self):
self.assertRaises(TypeError, math.atan)
self.ftest('atanh(0)', math.atanh(0), 0)
self.ftest('atanh(0.5)', math.atanh(0.5), 0.54930614433405489)
self.ftest('atanh(-0.5)', math.atanh(-0.5), -0.54930614433405489)
self.assertRaises(ValueError, math.atanh, 1)
self.assertRaises(ValueError, math.atanh, -1)
self.assertRaises(ValueError, math.atanh, INF)
self.assertRaises(ValueError, math.atanh, NINF)
self.assertTrue(math.isnan(math.atanh(NAN)))
def testAtan2(self):
self.assertRaises(TypeError, math.atan2)
self.ftest('atan2(-1, 0)', math.atan2(-1, 0), -math.pi/2)
self.ftest('atan2(-1, 1)', math.atan2(-1, 1), -math.pi/4)
self.ftest('atan2(0, 1)', math.atan2(0, 1), 0)
self.ftest('atan2(1, 1)', math.atan2(1, 1), math.pi/4)
self.ftest('atan2(1, 0)', math.atan2(1, 0), math.pi/2)
self.ftest('atan2(1, -1)', math.atan2(1, -1), 3*math.pi/4)
# math.atan2(0, x)
self.ftest('atan2(0., -inf)', math.atan2(0., NINF), math.pi)
self.ftest('atan2(0., -2.3)', math.atan2(0., -2.3), math.pi)
self.ftest('atan2(0., -0.)', math.atan2(0., -0.), math.pi)
self.assertEqual(math.atan2(0., 0.), 0.)
self.assertEqual(math.atan2(0., 2.3), 0.)
self.assertEqual(math.atan2(0., INF), 0.)
self.assertTrue(math.isnan(math.atan2(0., NAN)))
# math.atan2(-0, x)
self.ftest('atan2(-0., -inf)', math.atan2(-0., NINF), -math.pi)
self.ftest('atan2(-0., -2.3)', math.atan2(-0., -2.3), -math.pi)
self.ftest('atan2(-0., -0.)', math.atan2(-0., -0.), -math.pi)
self.assertEqual(math.atan2(-0., 0.), -0.)
self.assertEqual(math.atan2(-0., 2.3), -0.)
self.assertEqual(math.atan2(-0., INF), -0.)
self.assertTrue(math.isnan(math.atan2(-0., NAN)))
# math.atan2(INF, x)
self.ftest('atan2(inf, -inf)', math.atan2(INF, NINF), math.pi*3/4)
self.ftest('atan2(inf, -2.3)', math.atan2(INF, -2.3), math.pi/2)
self.ftest('atan2(inf, -0.)', math.atan2(INF, -0.0), math.pi/2)
self.ftest('atan2(inf, 0.)', math.atan2(INF, 0.0), math.pi/2)
self.ftest('atan2(inf, 2.3)', math.atan2(INF, 2.3), math.pi/2)
self.ftest('atan2(inf, inf)', math.atan2(INF, INF), math.pi/4)
self.assertTrue(math.isnan(math.atan2(INF, NAN)))
# math.atan2(NINF, x)
self.ftest('atan2(-inf, -inf)', math.atan2(NINF, NINF), -math.pi*3/4)
self.ftest('atan2(-inf, -2.3)', math.atan2(NINF, -2.3), -math.pi/2)
self.ftest('atan2(-inf, -0.)', math.atan2(NINF, -0.0), -math.pi/2)
self.ftest('atan2(-inf, 0.)', math.atan2(NINF, 0.0), -math.pi/2)
self.ftest('atan2(-inf, 2.3)', math.atan2(NINF, 2.3), -math.pi/2)
self.ftest('atan2(-inf, inf)', math.atan2(NINF, INF), -math.pi/4)
self.assertTrue(math.isnan(math.atan2(NINF, NAN)))
# math.atan2(+finite, x)
self.ftest('atan2(2.3, -inf)', math.atan2(2.3, NINF), math.pi)
self.ftest('atan2(2.3, -0.)', math.atan2(2.3, -0.), math.pi/2)
self.ftest('atan2(2.3, 0.)', math.atan2(2.3, 0.), math.pi/2)
self.assertEqual(math.atan2(2.3, INF), 0.)
self.assertTrue(math.isnan(math.atan2(2.3, NAN)))
# math.atan2(-finite, x)
self.ftest('atan2(-2.3, -inf)', math.atan2(-2.3, NINF), -math.pi)
self.ftest('atan2(-2.3, -0.)', math.atan2(-2.3, -0.), -math.pi/2)
self.ftest('atan2(-2.3, 0.)', math.atan2(-2.3, 0.), -math.pi/2)
self.assertEqual(math.atan2(-2.3, INF), -0.)
self.assertTrue(math.isnan(math.atan2(-2.3, NAN)))
# math.atan2(NAN, x)
self.assertTrue(math.isnan(math.atan2(NAN, NINF)))
self.assertTrue(math.isnan(math.atan2(NAN, -2.3)))
self.assertTrue(math.isnan(math.atan2(NAN, -0.)))
self.assertTrue(math.isnan(math.atan2(NAN, 0.)))
self.assertTrue(math.isnan(math.atan2(NAN, 2.3)))
self.assertTrue(math.isnan(math.atan2(NAN, INF)))
self.assertTrue(math.isnan(math.atan2(NAN, NAN)))
def testCbrt(self):
self.assertRaises(TypeError, math.cbrt)
self.ftest('cbrt(0)', math.cbrt(0), 0)
self.ftest('cbrt(1)', math.cbrt(1), 1)
self.ftest('cbrt(8)', math.cbrt(8), 2)
self.ftest('cbrt(0.0)', math.cbrt(0.0), 0.0)
self.ftest('cbrt(-0.0)', math.cbrt(-0.0), -0.0)
self.ftest('cbrt(1.2)', math.cbrt(1.2), 1.062658569182611)
self.ftest('cbrt(-2.6)', math.cbrt(-2.6), -1.375068867074141)
self.ftest('cbrt(27)', math.cbrt(27), 3)
self.ftest('cbrt(-1)', math.cbrt(-1), -1)
self.ftest('cbrt(-27)', math.cbrt(-27), -3)
self.assertEqual(math.cbrt(INF), INF)
self.assertEqual(math.cbrt(NINF), NINF)
self.assertTrue(math.isnan(math.cbrt(NAN)))
def testCeil(self):
self.assertRaises(TypeError, math.ceil)
self.assertEqual(int, type(math.ceil(0.5)))
self.assertEqual(math.ceil(0.5), 1)
self.assertEqual(math.ceil(1.0), 1)
self.assertEqual(math.ceil(1.5), 2)
self.assertEqual(math.ceil(-0.5), 0)
self.assertEqual(math.ceil(-1.0), -1)
self.assertEqual(math.ceil(-1.5), -1)
self.assertEqual(math.ceil(0.0), 0)
self.assertEqual(math.ceil(-0.0), 0)
#self.assertEqual(math.ceil(INF), INF)
#self.assertEqual(math.ceil(NINF), NINF)
#self.assertTrue(math.isnan(math.ceil(NAN)))
class TestCeil:
def __ceil__(self):
return 42
class FloatCeil(float):
def __ceil__(self):
return 42
class TestNoCeil:
pass
class TestBadCeil:
__ceil__ = BadDescr()
self.assertEqual(math.ceil(TestCeil()), 42)
self.assertEqual(math.ceil(FloatCeil()), 42)
self.assertEqual(math.ceil(FloatLike(42.5)), 43)
self.assertRaises(TypeError, math.ceil, TestNoCeil())
self.assertRaises(ValueError, math.ceil, TestBadCeil())
t = TestNoCeil()
t.__ceil__ = lambda *args: args
self.assertRaises(TypeError, math.ceil, t)
self.assertRaises(TypeError, math.ceil, t, 0)
self.assertEqual(math.ceil(FloatLike(+1.0)), +1.0)
self.assertEqual(math.ceil(FloatLike(-1.0)), -1.0)
@requires_IEEE_754
def testCopysign(self):
self.assertEqual(math.copysign(1, 42), 1.0)
self.assertEqual(math.copysign(0., 42), 0.0)
self.assertEqual(math.copysign(1., -42), -1.0)
self.assertEqual(math.copysign(3, 0.), 3.0)
self.assertEqual(math.copysign(4., -0.), -4.0)
self.assertRaises(TypeError, math.copysign)
# copysign should let us distinguish signs of zeros
self.assertEqual(math.copysign(1., 0.), 1.)
self.assertEqual(math.copysign(1., -0.), -1.)
self.assertEqual(math.copysign(INF, 0.), INF)
self.assertEqual(math.copysign(INF, -0.), NINF)
self.assertEqual(math.copysign(NINF, 0.), INF)
self.assertEqual(math.copysign(NINF, -0.), NINF)
# and of infinities
self.assertEqual(math.copysign(1., INF), 1.)
self.assertEqual(math.copysign(1., NINF), -1.)
self.assertEqual(math.copysign(INF, INF), INF)
self.assertEqual(math.copysign(INF, NINF), NINF)
self.assertEqual(math.copysign(NINF, INF), INF)
self.assertEqual(math.copysign(NINF, NINF), NINF)
self.assertTrue(math.isnan(math.copysign(NAN, 1.)))
self.assertTrue(math.isnan(math.copysign(NAN, INF)))
self.assertTrue(math.isnan(math.copysign(NAN, NINF)))
self.assertTrue(math.isnan(math.copysign(NAN, NAN)))
# copysign(INF, NAN) may be INF or it may be NINF, since
# we don't know whether the sign bit of NAN is set on any
# given platform.
self.assertTrue(math.isinf(math.copysign(INF, NAN)))
# similarly, copysign(2., NAN) could be 2. or -2.
self.assertEqual(abs(math.copysign(2., NAN)), 2.)
def testCos(self):
self.assertRaises(TypeError, math.cos)
self.ftest('cos(-pi/2)', math.cos(-math.pi/2), 0, abs_tol=math.ulp(1))
self.ftest('cos(0)', math.cos(0), 1)
self.ftest('cos(pi/2)', math.cos(math.pi/2), 0, abs_tol=math.ulp(1))
self.ftest('cos(pi)', math.cos(math.pi), -1)
try:
self.assertTrue(math.isnan(math.cos(INF)))
self.assertTrue(math.isnan(math.cos(NINF)))
except ValueError:
self.assertRaises(ValueError, math.cos, INF)
self.assertRaises(ValueError, math.cos, NINF)
self.assertTrue(math.isnan(math.cos(NAN)))
@unittest.skipIf(sys.platform == 'win32' and platform.machine() in ('ARM', 'ARM64'),
"Windows UCRT is off by 2 ULP this test requires accuracy within 1 ULP")
def testCosh(self):
self.assertRaises(TypeError, math.cosh)
self.ftest('cosh(0)', math.cosh(0), 1)
self.ftest('cosh(2)-2*cosh(1)**2', math.cosh(2)-2*math.cosh(1)**2, -1) # Thanks to Lambert
self.assertEqual(math.cosh(INF), INF)
self.assertEqual(math.cosh(NINF), INF)
self.assertTrue(math.isnan(math.cosh(NAN)))
def testDegrees(self):
self.assertRaises(TypeError, math.degrees)
self.ftest('degrees(pi)', math.degrees(math.pi), 180.0)
self.ftest('degrees(pi/2)', math.degrees(math.pi/2), 90.0)
self.ftest('degrees(-pi/4)', math.degrees(-math.pi/4), -45.0)
self.ftest('degrees(0)', math.degrees(0), 0)
def testExp(self):
self.assertRaises(TypeError, math.exp)
self.ftest('exp(-1)', math.exp(-1), 1/math.e)
self.ftest('exp(0)', math.exp(0), 1)
self.ftest('exp(1)', math.exp(1), math.e)
self.assertEqual(math.exp(INF), INF)
self.assertEqual(math.exp(NINF), 0.)
self.assertTrue(math.isnan(math.exp(NAN)))
self.assertRaises(OverflowError, math.exp, 1000000)
def testExp2(self):
self.assertRaises(TypeError, math.exp2)
self.ftest('exp2(-1)', math.exp2(-1), 0.5)
self.ftest('exp2(0)', math.exp2(0), 1)
self.ftest('exp2(1)', math.exp2(1), 2)
self.ftest('exp2(2.3)', math.exp2(2.3), 4.924577653379665)
self.assertEqual(math.exp2(INF), INF)
self.assertEqual(math.exp2(NINF), 0.)
self.assertTrue(math.isnan(math.exp2(NAN)))
self.assertRaises(OverflowError, math.exp2, 1000000)
def testFabs(self):
self.assertRaises(TypeError, math.fabs)
self.ftest('fabs(-1)', math.fabs(-1), 1)
self.ftest('fabs(0)', math.fabs(0), 0)
self.ftest('fabs(1)', math.fabs(1), 1)
def testFactorial(self):
self.assertEqual(math.factorial(0), 1)
total = 1
for i in range(1, 1000):
total *= i
self.assertEqual(math.factorial(i), total)
self.assertEqual(math.factorial(i), py_factorial(i))
self.assertRaises(ValueError, math.factorial, -1)
self.assertRaises(ValueError, math.factorial, -10**100)
def testFactorialNonIntegers(self):
self.assertRaises(TypeError, math.factorial, 5.0)
self.assertRaises(TypeError, math.factorial, 5.2)
self.assertRaises(TypeError, math.factorial, -1.0)
self.assertRaises(TypeError, math.factorial, -1e100)
self.assertRaises(TypeError, math.factorial, decimal.Decimal('5'))
self.assertRaises(TypeError, math.factorial, decimal.Decimal('5.2'))
self.assertRaises(TypeError, math.factorial, "5")
# Other implementations may place different upper bounds.
@support.cpython_only
def testFactorialHugeInputs(self):
# Currently raises OverflowError for inputs that are too large
# to fit into a C long.
self.assertRaises(OverflowError, math.factorial, 10**100)
self.assertRaises(TypeError, math.factorial, 1e100)
def testFloor(self):
self.assertRaises(TypeError, math.floor)
self.assertEqual(int, type(math.floor(0.5)))
self.assertEqual(math.floor(0.5), 0)
self.assertEqual(math.floor(1.0), 1)
self.assertEqual(math.floor(1.5), 1)
self.assertEqual(math.floor(-0.5), -1)
self.assertEqual(math.floor(-1.0), -1)
self.assertEqual(math.floor(-1.5), -2)
#self.assertEqual(math.ceil(INF), INF)
#self.assertEqual(math.ceil(NINF), NINF)
#self.assertTrue(math.isnan(math.floor(NAN)))
class TestFloor:
def __floor__(self):
return 42
class FloatFloor(float):
def __floor__(self):
return 42
class TestNoFloor:
pass
class TestBadFloor:
__floor__ = BadDescr()
self.assertEqual(math.floor(TestFloor()), 42)
self.assertEqual(math.floor(FloatFloor()), 42)
self.assertEqual(math.floor(FloatLike(41.9)), 41)
self.assertRaises(TypeError, math.floor, TestNoFloor())
self.assertRaises(ValueError, math.floor, TestBadFloor())
t = TestNoFloor()
t.__floor__ = lambda *args: args
self.assertRaises(TypeError, math.floor, t)
self.assertRaises(TypeError, math.floor, t, 0)
self.assertEqual(math.floor(FloatLike(+1.0)), +1.0)
self.assertEqual(math.floor(FloatLike(-1.0)), -1.0)
def testFmod(self):
self.assertRaises(TypeError, math.fmod)
self.ftest('fmod(10, 1)', math.fmod(10, 1), 0.0)
self.ftest('fmod(10, 0.5)', math.fmod(10, 0.5), 0.0)
self.ftest('fmod(10, 1.5)', math.fmod(10, 1.5), 1.0)
self.ftest('fmod(-10, 1)', math.fmod(-10, 1), -0.0)
self.ftest('fmod(-10, 0.5)', math.fmod(-10, 0.5), -0.0)
self.ftest('fmod(-10, 1.5)', math.fmod(-10, 1.5), -1.0)
self.assertTrue(math.isnan(math.fmod(NAN, 1.)))
self.assertTrue(math.isnan(math.fmod(1., NAN)))
self.assertTrue(math.isnan(math.fmod(NAN, NAN)))
self.assertRaises(ValueError, math.fmod, 1., 0.)
self.assertRaises(ValueError, math.fmod, INF, 1.)
self.assertRaises(ValueError, math.fmod, NINF, 1.)
self.assertRaises(ValueError, math.fmod, INF, 0.)
self.assertEqual(math.fmod(3.0, INF), 3.0)
self.assertEqual(math.fmod(-3.0, INF), -3.0)
self.assertEqual(math.fmod(3.0, NINF), 3.0)
self.assertEqual(math.fmod(-3.0, NINF), -3.0)
self.assertEqual(math.fmod(0.0, 3.0), 0.0)
self.assertEqual(math.fmod(0.0, NINF), 0.0)
self.assertRaises(ValueError, math.fmod, INF, INF)
def testFrexp(self):
self.assertRaises(TypeError, math.frexp)
def testfrexp(name, result, expected):
(mant, exp), (emant, eexp) = result, expected
if abs(mant-emant) > eps or exp != eexp:
self.fail('%s returned %r, expected %r'%\
(name, result, expected))
testfrexp('frexp(-1)', math.frexp(-1), (-0.5, 1))
testfrexp('frexp(0)', math.frexp(0), (0, 0))
testfrexp('frexp(1)', math.frexp(1), (0.5, 1))
testfrexp('frexp(2)', math.frexp(2), (0.5, 2))
self.assertEqual(math.frexp(INF)[0], INF)
self.assertEqual(math.frexp(NINF)[0], NINF)
self.assertTrue(math.isnan(math.frexp(NAN)[0]))
@requires_IEEE_754
@unittest.skipIf(HAVE_DOUBLE_ROUNDING,
"fsum is not exact on machines with double rounding")
def testFsum(self):
# math.fsum relies on exact rounding for correct operation.
# There's a known problem with IA32 floating-point that causes
# inexact rounding in some situations, and will cause the
# math.fsum tests below to fail; see issue #2937. On non IEEE
# 754 platforms, and on IEEE 754 platforms that exhibit the
# problem described in issue #2937, we simply skip the whole
# test.
# Python version of math.fsum, for comparison. Uses a
# different algorithm based on frexp, ldexp and integer
# arithmetic.
from sys import float_info
mant_dig = float_info.mant_dig
etiny = float_info.min_exp - mant_dig
def msum(iterable):
"""Full precision summation. Compute sum(iterable) without any
intermediate accumulation of error. Based on the 'lsum' function
at https://code.activestate.com/recipes/393090-binary-floating-point-summation-accurate-to-full-p/
"""
tmant, texp = 0, 0
for x in iterable:
mant, exp = math.frexp(x)
mant, exp = int(math.ldexp(mant, mant_dig)), exp - mant_dig
if texp > exp:
tmant <<= texp-exp
texp = exp
else:
mant <<= exp-texp
tmant += mant
# Round tmant * 2**texp to a float. The original recipe
# used float(str(tmant)) * 2.0**texp for this, but that's
# a little unsafe because str -> float conversion can't be
# relied upon to do correct rounding on all platforms.
tail = max(len(bin(abs(tmant)))-2 - mant_dig, etiny - texp)
if tail > 0:
h = 1 << (tail-1)
tmant = tmant // (2*h) + bool(tmant & h and tmant & 3*h-1)
texp += tail
return math.ldexp(tmant, texp)
test_values = [
([], 0.0),
([0.0], 0.0),
([1e100, 1.0, -1e100, 1e-100, 1e50, -1.0, -1e50], 1e-100),
([1e100, 1.0, -1e100, 1e-100, 1e50, -1, -1e50], 1e-100),
([2.0**53, -0.5, -2.0**-54], 2.0**53-1.0),
([2.0**53, 1.0, 2.0**-100], 2.0**53+2.0),
([2.0**53+10.0, 1.0, 2.0**-100], 2.0**53+12.0),
([2.0**53-4.0, 0.5, 2.0**-54], 2.0**53-3.0),
([1./n for n in range(1, 1001)],
float.fromhex('0x1.df11f45f4e61ap+2')),
([(-1.)**n/n for n in range(1, 1001)],
float.fromhex('-0x1.62a2af1bd3624p-1')),
([1e16, 1., 1e-16], 10000000000000002.0),
([1e16-2., 1.-2.**-53, -(1e16-2.), -(1.-2.**-53)], 0.0),
# exercise code for resizing partials array
([2.**n - 2.**(n+50) + 2.**(n+52) for n in range(-1074, 972, 2)] +
[-2.**1022],
float.fromhex('0x1.5555555555555p+970')),
]
# Telescoping sum, with exact differences (due to Sterbenz)
terms = [1.7**i for i in range(1001)]
test_values.append((
[terms[i+1] - terms[i] for i in range(1000)] + [-terms[1000]],
-terms[0]
))
for i, (vals, expected) in enumerate(test_values):
try:
actual = math.fsum(vals)
except OverflowError:
self.fail("test %d failed: got OverflowError, expected %r "
"for math.fsum(%.100r)" % (i, expected, vals))
except ValueError:
self.fail("test %d failed: got ValueError, expected %r "
"for math.fsum(%.100r)" % (i, expected, vals))
self.assertEqual(actual, expected)
from random import random, gauss, shuffle
for j in range(1000):
vals = [7, 1e100, -7, -1e100, -9e-20, 8e-20] * 10
s = 0
for i in range(200):
v = gauss(0, random()) ** 7 - s
s += v
vals.append(v)
shuffle(vals)
s = msum(vals)
self.assertEqual(msum(vals), math.fsum(vals))
self.assertEqual(math.fsum([1.0, math.inf]), math.inf)
self.assertTrue(math.isnan(math.fsum([math.nan, 1.0])))
self.assertEqual(math.fsum([1e100, FloatLike(1.0), -1e100, 1e-100,
1e50, FloatLike(-1.0), -1e50]), 1e-100)
self.assertRaises(OverflowError, math.fsum, [1e+308, 1e+308])
self.assertRaises(ValueError, math.fsum, [math.inf, -math.inf])
self.assertRaises(TypeError, math.fsum, ['spam'])
self.assertRaises(TypeError, math.fsum, 1)
self.assertRaises(OverflowError, math.fsum, [10**1000])
def bad_iter():
yield 1.0
raise ZeroDivisionError
self.assertRaises(ZeroDivisionError, math.fsum, bad_iter())
def testGcd(self):
gcd = math.gcd
self.assertEqual(gcd(0, 0), 0)
self.assertEqual(gcd(1, 0), 1)
self.assertEqual(gcd(-1, 0), 1)
self.assertEqual(gcd(0, 1), 1)
self.assertEqual(gcd(0, -1), 1)
self.assertEqual(gcd(7, 1), 1)
self.assertEqual(gcd(7, -1), 1)
self.assertEqual(gcd(-23, 15), 1)
self.assertEqual(gcd(120, 84), 12)
self.assertEqual(gcd(84, -120), 12)
self.assertEqual(gcd(1216342683557601535506311712,
436522681849110124616458784), 32)
x = 434610456570399902378880679233098819019853229470286994367836600566
y = 1064502245825115327754847244914921553977
for c in (652560,
576559230871654959816130551884856912003141446781646602790216406874):
a = x * c
b = y * c
self.assertEqual(gcd(a, b), c)
self.assertEqual(gcd(b, a), c)
self.assertEqual(gcd(-a, b), c)
self.assertEqual(gcd(b, -a), c)
self.assertEqual(gcd(a, -b), c)
self.assertEqual(gcd(-b, a), c)
self.assertEqual(gcd(-a, -b), c)
self.assertEqual(gcd(-b, -a), c)
self.assertEqual(gcd(), 0)
self.assertEqual(gcd(120), 120)
self.assertEqual(gcd(-120), 120)
self.assertEqual(gcd(120, 84, 102), 6)
self.assertEqual(gcd(120, 1, 84), 1)
self.assertRaises(TypeError, gcd, 120.0)
self.assertRaises(TypeError, gcd, 120.0, 84)
self.assertRaises(TypeError, gcd, 120, 84.0)
self.assertRaises(TypeError, gcd, 120, 1, 84.0)
self.assertEqual(gcd(MyIndexable(120), MyIndexable(84)), 12)
def testHypot(self):
from decimal import Decimal
from fractions import Fraction
hypot = math.hypot
# Test different numbers of arguments (from zero to five)
# against a straightforward pure python implementation
args = math.e, math.pi, math.sqrt(2.0), math.gamma(3.5), math.sin(2.1)
for i in range(len(args)+1):
self.assertAlmostEqual(
hypot(*args[:i]),
math.sqrt(sum(s**2 for s in args[:i]))
)
# Test allowable types (those with __float__)
self.assertEqual(hypot(12.0, 5.0), 13.0)
self.assertEqual(hypot(12, 5), 13)
self.assertEqual(hypot(1, -1), math.sqrt(2))
self.assertEqual(hypot(1, FloatLike(-1.)), math.sqrt(2))
self.assertEqual(hypot(Decimal(12), Decimal(5)), 13)
self.assertEqual(hypot(Fraction(12, 32), Fraction(5, 32)), Fraction(13, 32))
self.assertEqual(hypot(bool(1), bool(0), bool(1), bool(1)), math.sqrt(3))
# Test corner cases
self.assertEqual(hypot(0.0, 0.0), 0.0) # Max input is zero
self.assertEqual(hypot(-10.5), 10.5) # Negative input
self.assertEqual(hypot(), 0.0) # Negative input
self.assertEqual(1.0,
math.copysign(1.0, hypot(-0.0)) # Convert negative zero to positive zero
)
self.assertEqual( # Handling of moving max to the end
hypot(1.5, 1.5, 0.5),
hypot(1.5, 0.5, 1.5),
)
# Test handling of bad arguments
with self.assertRaises(TypeError): # Reject keyword args
hypot(x=1)
with self.assertRaises(TypeError): # Reject values without __float__
hypot(1.1, 'string', 2.2)
int_too_big_for_float = 10 ** (sys.float_info.max_10_exp + 5)
with self.assertRaises((ValueError, OverflowError)):
hypot(1, int_too_big_for_float)
# Any infinity gives positive infinity.
self.assertEqual(hypot(INF), INF)
self.assertEqual(hypot(0, INF), INF)
self.assertEqual(hypot(10, INF), INF)
self.assertEqual(hypot(-10, INF), INF)
self.assertEqual(hypot(NAN, INF), INF)
self.assertEqual(hypot(INF, NAN), INF)
self.assertEqual(hypot(NINF, NAN), INF)
self.assertEqual(hypot(NAN, NINF), INF)
self.assertEqual(hypot(-INF, INF), INF)
self.assertEqual(hypot(-INF, -INF), INF)
self.assertEqual(hypot(10, -INF), INF)
# If no infinity, any NaN gives a NaN.
self.assertTrue(math.isnan(hypot(NAN)))
self.assertTrue(math.isnan(hypot(0, NAN)))
self.assertTrue(math.isnan(hypot(NAN, 10)))
self.assertTrue(math.isnan(hypot(10, NAN)))
self.assertTrue(math.isnan(hypot(NAN, NAN)))
self.assertTrue(math.isnan(hypot(NAN)))
# Verify scaling for extremely large values
fourthmax = FLOAT_MAX / 4.0
for n in range(32):
self.assertTrue(math.isclose(hypot(*([fourthmax]*n)),
fourthmax * math.sqrt(n)))
# Verify scaling for extremely small values
for exp in range(32):
scale = FLOAT_MIN / 2.0 ** exp
self.assertEqual(math.hypot(4*scale, 3*scale), 5*scale)
self.assertRaises(TypeError, math.hypot, *([1.0]*18), 'spam')
@requires_IEEE_754
@unittest.skipIf(HAVE_DOUBLE_ROUNDING,
"hypot() loses accuracy on machines with double rounding")
def testHypotAccuracy(self):
# Verify improved accuracy in cases that were known to be inaccurate.
#
# The new algorithm's accuracy depends on IEEE 754 arithmetic
# guarantees, on having the usual ROUND HALF EVEN rounding mode, on
# the system not having double rounding due to extended precision,
# and on the compiler maintaining the specified order of operations.
#
# This test is known to succeed on most of our builds. If it fails
# some build, we either need to add another skipIf if the cause is
# identifiable; otherwise, we can remove this test entirely.
hypot = math.hypot
Decimal = decimal.Decimal
high_precision = decimal.Context(prec=500)
for hx, hy in [
# Cases with a 1 ulp error in Python 3.7 compiled with Clang
('0x1.10e89518dca48p+29', '0x1.1970f7565b7efp+30'),
('0x1.10106eb4b44a2p+29', '0x1.ef0596cdc97f8p+29'),
('0x1.459c058e20bb7p+30', '0x1.993ca009b9178p+29'),
('0x1.378371ae67c0cp+30', '0x1.fbe6619854b4cp+29'),
('0x1.f4cd0574fb97ap+29', '0x1.50fe31669340ep+30'),
('0x1.494b2cdd3d446p+29', '0x1.212a5367b4c7cp+29'),
('0x1.f84e649f1e46dp+29', '0x1.1fa56bef8eec4p+30'),
('0x1.2e817edd3d6fap+30', '0x1.eb0814f1e9602p+29'),
('0x1.0d3a6e3d04245p+29', '0x1.32a62fea52352p+30'),
('0x1.888e19611bfc5p+29', '0x1.52b8e70b24353p+29'),
# Cases with 2 ulp error in Python 3.8
('0x1.538816d48a13fp+29', '0x1.7967c5ca43e16p+29'),
('0x1.57b47b7234530p+29', '0x1.74e2c7040e772p+29'),
('0x1.821b685e9b168p+30', '0x1.677dc1c1e3dc6p+29'),
('0x1.9e8247f67097bp+29', '0x1.24bd2dc4f4baep+29'),
('0x1.b73b59e0cb5f9p+29', '0x1.da899ab784a97p+28'),
('0x1.94a8d2842a7cfp+30', '0x1.326a51d4d8d8ap+30'),
('0x1.e930b9cd99035p+29', '0x1.5a1030e18dff9p+30'),
('0x1.1592bbb0e4690p+29', '0x1.a9c337b33fb9ap+29'),
('0x1.1243a50751fd4p+29', '0x1.a5a10175622d9p+29'),
('0x1.57a8596e74722p+30', '0x1.42d1af9d04da9p+30'),
# Cases with 1 ulp error in version fff3c28052e6b0
('0x1.ee7dbd9565899p+29', '0x1.7ab4d6fc6e4b4p+29'),
('0x1.5c6bfbec5c4dcp+30', '0x1.02511184b4970p+30'),
('0x1.59dcebba995cap+30', '0x1.50ca7e7c38854p+29'),
('0x1.768cdd94cf5aap+29', '0x1.9cfdc5571d38ep+29'),
('0x1.dcf137d60262ep+29', '0x1.1101621990b3ep+30'),
('0x1.3a2d006e288b0p+30', '0x1.e9a240914326cp+29'),
('0x1.62a32f7f53c61p+29', '0x1.47eb6cd72684fp+29'),
('0x1.d3bcb60748ef2p+29', '0x1.3f13c4056312cp+30'),
('0x1.282bdb82f17f3p+30', '0x1.640ba4c4eed3ap+30'),
('0x1.89d8c423ea0c6p+29', '0x1.d35dcfe902bc3p+29'),
]:
x = float.fromhex(hx)
y = float.fromhex(hy)
with self.subTest(hx=hx, hy=hy, x=x, y=y):
with decimal.localcontext(high_precision):
z = float((Decimal(x)**2 + Decimal(y)**2).sqrt())
self.assertEqual(hypot(x, y), z)
def testDist(self):
from decimal import Decimal as D
from fractions import Fraction as F
dist = math.dist
sqrt = math.sqrt
# Simple exact cases
self.assertEqual(dist((1.0, 2.0, 3.0), (4.0, 2.0, -1.0)), 5.0)
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 non-tuple inputs
self.assertEqual(dist([1.0, 2.0, 3.0], [4.0, 2.0, -1.0]), 5.0)
self.assertEqual(dist(iter([1.0, 2.0, 3.0]), iter([4.0, 2.0, -1.0])), 5.0)
# 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((FloatLike(14.), 1), (2, -4)), 13)
self.assertEqual(dist((11, 1), (FloatLike(-1.), -4)), 13)
self.assertEqual(dist((14, FloatLike(-1.)), (2, -6)), 13)
self.assertEqual(dist((14, -1), (2, -6)), 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,)))
)
self.assertEqual( # Handling of moving max to the end
dist((1.5, 1.5, 0.5), (0, 0, 0)),
dist((1.5, 0.5, 1.5), (0, 0, 0))
)
# Verify tuple subclasses are allowed
class T(tuple):
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): # 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))
with self.assertRaises(TypeError):
dist((1,)*17 + ("spam",), (1,)*18)
with self.assertRaises(TypeError): # Rejects invalid types
dist("abc", "xyz")
int_too_big_for_float = 10 ** (sys.float_info.max_10_exp + 5)
with self.assertRaises((ValueError, OverflowError)):
dist((1, int_too_big_for_float), (2, 3))
with self.assertRaises((ValueError, OverflowError)):
dist((2, 3), (1, int_too_big_for_float))
with self.assertRaises(TypeError):
dist((1,), 2)
with self.assertRaises(TypeError):
dist([1], 2)
class BadFloat:
__float__ = BadDescr()
with self.assertRaises(ValueError):
dist([1], [BadFloat()])
# Verify that the one dimensional case is 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.assertTrue(math.isclose(dist(p, q), fourthmax * math.sqrt(n)))
self.assertTrue(math.isclose(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 test_math_dist_leak(self):
# gh-98897: Check for error handling does not leak memory
with self.assertRaises(ValueError):
math.dist([1, 2], [3, 4, 5])
def testIsqrt(self):
# Test a variety of inputs, large and small.
test_values = (
list(range(1000))
+ list(range(10**6 - 1000, 10**6 + 1000))
+ [2**e + i for e in range(60, 200) for i in range(-40, 40)]
+ [3**9999, 10**5001]
)
for value in test_values:
with self.subTest(value=value):
s = math.isqrt(value)
self.assertIs(type(s), int)
self.assertLessEqual(s*s, value)
self.assertLess(value, (s+1)*(s+1))
# Negative values
with self.assertRaises(ValueError):
math.isqrt(-1)
# Integer-like things
s = math.isqrt(True)
self.assertIs(type(s), int)
self.assertEqual(s, 1)
s = math.isqrt(False)
self.assertIs(type(s), int)
self.assertEqual(s, 0)
class IntegerLike(object):
def __init__(self, value):
self.value = value
def __index__(self):
return self.value
s = math.isqrt(IntegerLike(1729))
self.assertIs(type(s), int)
self.assertEqual(s, 41)
with self.assertRaises(ValueError):
math.isqrt(IntegerLike(-3))
# Non-integer-like things
bad_values = [
3.5, "a string", decimal.Decimal("3.5"), 3.5j,
100.0, -4.0,
]
for value in bad_values:
with self.subTest(value=value):
with self.assertRaises(TypeError):
math.isqrt(value)
def test_lcm(self):
lcm = math.lcm
self.assertEqual(lcm(0, 0), 0)
self.assertEqual(lcm(1, 0), 0)
self.assertEqual(lcm(-1, 0), 0)
self.assertEqual(lcm(0, 1), 0)
self.assertEqual(lcm(0, -1), 0)
self.assertEqual(lcm(7, 1), 7)
self.assertEqual(lcm(7, -1), 7)
self.assertEqual(lcm(-23, 15), 345)
self.assertEqual(lcm(120, 84), 840)
self.assertEqual(lcm(84, -120), 840)
self.assertEqual(lcm(1216342683557601535506311712,
436522681849110124616458784),
16592536571065866494401400422922201534178938447014944)
x = 43461045657039990237
y = 10645022458251153277
for c in (652560,
57655923087165495981):
a = x * c
b = y * c
d = x * y * c
self.assertEqual(lcm(a, b), d)
self.assertEqual(lcm(b, a), d)
self.assertEqual(lcm(-a, b), d)
self.assertEqual(lcm(b, -a), d)
self.assertEqual(lcm(a, -b), d)
self.assertEqual(lcm(-b, a), d)
self.assertEqual(lcm(-a, -b), d)
self.assertEqual(lcm(-b, -a), d)
self.assertEqual(lcm(), 1)
self.assertEqual(lcm(120), 120)
self.assertEqual(lcm(-120), 120)
self.assertEqual(lcm(120, 84, 102), 14280)
self.assertEqual(lcm(120, 0, 84), 0)
self.assertRaises(TypeError, lcm, 120.0)
self.assertRaises(TypeError, lcm, 120.0, 84)
self.assertRaises(TypeError, lcm, 120, 84.0)
self.assertRaises(TypeError, lcm, 120, 0, 84.0)
self.assertEqual(lcm(MyIndexable(120), MyIndexable(84)), 840)
def testLdexp(self):
self.assertRaises(TypeError, math.ldexp)
self.assertRaises(TypeError, math.ldexp, 2.0, 1.1)
self.ftest('ldexp(0,1)', math.ldexp(0,1), 0)
self.ftest('ldexp(1,1)', math.ldexp(1,1), 2)
self.ftest('ldexp(1,-1)', math.ldexp(1,-1), 0.5)
self.ftest('ldexp(-1,1)', math.ldexp(-1,1), -2)
self.assertRaises(OverflowError, math.ldexp, 1., 1000000)
self.assertRaises(OverflowError, math.ldexp, -1., 1000000)
self.assertEqual(math.ldexp(1., -1000000), 0.)
self.assertEqual(math.ldexp(-1., -1000000), -0.)
self.assertEqual(math.ldexp(INF, 30), INF)
self.assertEqual(math.ldexp(NINF, -213), NINF)
self.assertTrue(math.isnan(math.ldexp(NAN, 0)))
# large second argument
for n in [10**5, 10**10, 10**20, 10**40]:
self.assertEqual(math.ldexp(INF, -n), INF)
self.assertEqual(math.ldexp(NINF, -n), NINF)
self.assertEqual(math.ldexp(1., -n), 0.)
self.assertEqual(math.ldexp(-1., -n), -0.)
self.assertEqual(math.ldexp(0., -n), 0.)
self.assertEqual(math.ldexp(-0., -n), -0.)
self.assertTrue(math.isnan(math.ldexp(NAN, -n)))
self.assertRaises(OverflowError, math.ldexp, 1., n)
self.assertRaises(OverflowError, math.ldexp, -1., n)
self.assertEqual(math.ldexp(0., n), 0.)
self.assertEqual(math.ldexp(-0., n), -0.)
self.assertEqual(math.ldexp(INF, n), INF)
self.assertEqual(math.ldexp(NINF, n), NINF)
self.assertTrue(math.isnan(math.ldexp(NAN, n)))
def testLog(self):
self.assertRaises(TypeError, math.log)
self.assertRaises(TypeError, math.log, 1, 2, 3)
self.ftest('log(1/e)', math.log(1/math.e), -1)
self.ftest('log(1)', math.log(1), 0)
self.ftest('log(e)', math.log(math.e), 1)
self.ftest('log(32,2)', math.log(32,2), 5)
self.ftest('log(10**40, 10)', math.log(10**40, 10), 40)
self.ftest('log(10**40, 10**20)', math.log(10**40, 10**20), 2)
self.ftest('log(10**1000)', math.log(10**1000),
2302.5850929940457)
self.assertRaises(ValueError, math.log, -1.5)
self.assertRaises(ValueError, math.log, -10**1000)
self.assertRaises(ValueError, math.log, 10, -10)
self.assertRaises(ValueError, math.log, NINF)
self.assertEqual(math.log(INF), INF)
self.assertTrue(math.isnan(math.log(NAN)))
def testLog1p(self):
self.assertRaises(TypeError, math.log1p)
for n in [2, 2**90, 2**300]:
self.assertAlmostEqual(math.log1p(n), math.log1p(float(n)))
self.assertRaises(ValueError, math.log1p, -1)
self.assertEqual(math.log1p(INF), INF)
@requires_IEEE_754
def testLog2(self):
self.assertRaises(TypeError, math.log2)
# Check some integer values
self.assertEqual(math.log2(1), 0.0)
self.assertEqual(math.log2(2), 1.0)
self.assertEqual(math.log2(4), 2.0)
# Large integer values
self.assertEqual(math.log2(2**1023), 1023.0)
self.assertEqual(math.log2(2**1024), 1024.0)
self.assertEqual(math.log2(2**2000), 2000.0)
self.assertRaises(ValueError, math.log2, -1.5)
self.assertRaises(ValueError, math.log2, NINF)
self.assertTrue(math.isnan(math.log2(NAN)))
@requires_IEEE_754
# log2() is not accurate enough on Mac OS X Tiger (10.4)
@support.requires_mac_ver(10, 5)
def testLog2Exact(self):
# Check that we get exact equality for log2 of powers of 2.
actual = [math.log2(math.ldexp(1.0, n)) for n in range(-1074, 1024)]
expected = [float(n) for n in range(-1074, 1024)]
self.assertEqual(actual, expected)
def testLog10(self):
self.assertRaises(TypeError, math.log10)
self.ftest('log10(0.1)', math.log10(0.1), -1)
self.ftest('log10(1)', math.log10(1), 0)
self.ftest('log10(10)', math.log10(10), 1)
self.ftest('log10(10**1000)', math.log10(10**1000), 1000.0)
self.assertRaises(ValueError, math.log10, -1.5)
self.assertRaises(ValueError, math.log10, -10**1000)
self.assertRaises(ValueError, math.log10, NINF)
self.assertEqual(math.log(INF), INF)
self.assertTrue(math.isnan(math.log10(NAN)))
def testSumProd(self):
sumprod = math.sumprod
Decimal = decimal.Decimal
Fraction = fractions.Fraction
# Core functionality
self.assertEqual(sumprod(iter([10, 20, 30]), (1, 2, 3)), 140)
self.assertEqual(sumprod([1.5, 2.5], [3.5, 4.5]), 16.5)
self.assertEqual(sumprod([], []), 0)
self.assertEqual(sumprod([-1], [1.]), -1)
self.assertEqual(sumprod([1.], [-1]), -1)
# Type preservation and coercion
for v in [
(10, 20, 30),
(1.5, -2.5),
(Fraction(3, 5), Fraction(4, 5)),
(Decimal(3.5), Decimal(4.5)),
(2.5, 10), # float/int
(2.5, Fraction(3, 5)), # float/fraction
(25, Fraction(3, 5)), # int/fraction
(25, Decimal(4.5)), # int/decimal
]:
for p, q in [(v, v), (v, v[::-1])]:
with self.subTest(p=p, q=q):
expected = sum(p_i * q_i for p_i, q_i in zip(p, q, strict=True))
actual = sumprod(p, q)
self.assertEqual(expected, actual)
self.assertEqual(type(expected), type(actual))
# Bad arguments
self.assertRaises(TypeError, sumprod) # No args
self.assertRaises(TypeError, sumprod, []) # One arg
self.assertRaises(TypeError, sumprod, [], [], []) # Three args
self.assertRaises(TypeError, sumprod, None, [10]) # Non-iterable
self.assertRaises(TypeError, sumprod, [10], None) # Non-iterable
self.assertRaises(TypeError, sumprod, ['x'], [1.0])
# Uneven lengths
self.assertRaises(ValueError, sumprod, [10, 20], [30])
self.assertRaises(ValueError, sumprod, [10], [20, 30])
# Overflows
self.assertEqual(sumprod([10**20], [1]), 10**20)
self.assertEqual(sumprod([1], [10**20]), 10**20)
self.assertEqual(sumprod([10**10], [10**10]), 10**20)
self.assertEqual(sumprod([10**7]*10**5, [10**7]*10**5), 10**19)
self.assertRaises(OverflowError, sumprod, [10**1000], [1.0])
self.assertRaises(OverflowError, sumprod, [1.0], [10**1000])
# Error in iterator
def raise_after(n):
for i in range(n):
yield i
raise RuntimeError
with self.assertRaises(RuntimeError):
sumprod(range(10), raise_after(5))
with self.assertRaises(RuntimeError):
sumprod(raise_after(5), range(10))
from test.test_iter import BasicIterClass
self.assertEqual(sumprod(BasicIterClass(1), [1]), 0)
self.assertEqual(sumprod([1], BasicIterClass(1)), 0)
# Error in multiplication
class BadMultiply:
def __mul__(self, other):
raise RuntimeError
def __rmul__(self, other):
raise RuntimeError
with self.assertRaises(RuntimeError):
sumprod([10, BadMultiply(), 30], [1, 2, 3])
with self.assertRaises(RuntimeError):
sumprod([1, 2, 3], [10, BadMultiply(), 30])
# Error in addition
with self.assertRaises(TypeError):
sumprod(['abc', 3], [5, 10])
with self.assertRaises(TypeError):
sumprod([5, 10], ['abc', 3])
# Special values should give the same as the pure python recipe
self.assertEqual(sumprod([10.1, math.inf], [20.2, 30.3]), math.inf)
self.assertEqual(sumprod([10.1, math.inf], [math.inf, 30.3]), math.inf)
self.assertEqual(sumprod([10.1, math.inf], [math.inf, math.inf]), math.inf)
self.assertEqual(sumprod([10.1, -math.inf], [20.2, 30.3]), -math.inf)
self.assertTrue(math.isnan(sumprod([10.1, math.inf], [-math.inf, math.inf])))
self.assertTrue(math.isnan(sumprod([10.1, math.nan], [20.2, 30.3])))
self.assertTrue(math.isnan(sumprod([10.1, math.inf], [math.nan, 30.3])))
self.assertTrue(math.isnan(sumprod([10.1, math.inf], [20.3, math.nan])))
# Error cases that arose during development
args = ((-5, -5, 10), (1.5, 4611686018427387904, 2305843009213693952))
self.assertEqual(sumprod(*args), 0.0)
@requires_IEEE_754
@unittest.skipIf(HAVE_DOUBLE_ROUNDING,
"sumprod() accuracy not guaranteed on machines with double rounding")
@support.cpython_only # Other implementations may choose a different algorithm
def test_sumprod_accuracy(self):
sumprod = math.sumprod
self.assertEqual(sumprod([0.1] * 10, [1]*10), 1.0)
self.assertEqual(sumprod([0.1] * 20, [True, False] * 10), 1.0)
self.assertEqual(sumprod([True, False] * 10, [0.1] * 20), 1.0)
self.assertEqual(sumprod([1.0, 10E100, 1.0, -10E100], [1.0]*4), 2.0)
@support.requires_resource('cpu')
def test_sumprod_stress(self):
sumprod = math.sumprod
product = itertools.product
Decimal = decimal.Decimal
Fraction = fractions.Fraction
class Int(int):
def __add__(self, other):
return Int(int(self) + int(other))
def __mul__(self, other):
return Int(int(self) * int(other))
__radd__ = __add__
__rmul__ = __mul__
def __repr__(self):
return f'Int({int(self)})'
class Flt(float):
def __add__(self, other):
return Int(int(self) + int(other))
def __mul__(self, other):
return Int(int(self) * int(other))
__radd__ = __add__
__rmul__ = __mul__
def __repr__(self):
return f'Flt({int(self)})'
def baseline_sumprod(p, q):
"""This defines the target behavior including expections and special values.
However, it is subject to rounding errors, so float inputs should be exactly
representable with only a few bits.
"""
total = 0
for p_i, q_i in zip(p, q, strict=True):
total += p_i * q_i
return total
def run(func, *args):
"Make comparing functions easier. Returns error status, type, and result."
try:
result = func(*args)
except (AssertionError, NameError):
raise
except Exception as e:
return type(e), None, 'None'
return None, type(result), repr(result)
pools = [
(-5, 10, -2**20, 2**31, 2**40, 2**61, 2**62, 2**80, 1.5, Int(7)),
(5.25, -3.5, 4.75, 11.25, 400.5, 0.046875, 0.25, -1.0, -0.078125),
(-19.0*2**500, 11*2**1000, -3*2**1500, 17*2*333,
5.25, -3.25, -3.0*2**(-333), 3, 2**513),
(3.75, 2.5, -1.5, float('inf'), -float('inf'), float('NaN'), 14,
9, 3+4j, Flt(13), 0.0),
(13.25, -4.25, Decimal('10.5'), Decimal('-2.25'), Fraction(13, 8),
Fraction(-11, 16), 4.75 + 0.125j, 97, -41, Int(3)),
(Decimal('6.125'), Decimal('12.375'), Decimal('-2.75'), Decimal(0),
Decimal('Inf'), -Decimal('Inf'), Decimal('NaN'), 12, 13.5),
(-2.0 ** -1000, 11*2**1000, 3, 7, -37*2**32, -2*2**-537, -2*2**-538,
2*2**-513),
(-7 * 2.0 ** -510, 5 * 2.0 ** -520, 17, -19.0, -6.25),
(11.25, -3.75, -0.625, 23.375, True, False, 7, Int(5)),
]
for pool in pools:
for size in range(4):
for args1 in product(pool, repeat=size):
for args2 in product(pool, repeat=size):
args = (args1, args2)
self.assertEqual(
run(baseline_sumprod, *args),
run(sumprod, *args),
args,
)
@requires_IEEE_754
@unittest.skipIf(HAVE_DOUBLE_ROUNDING,
"sumprod() accuracy not guaranteed on machines with double rounding")
@support.cpython_only # Other implementations may choose a different algorithm
@support.requires_resource('cpu')
def test_sumprod_extended_precision_accuracy(self):
import operator
from fractions import Fraction
from itertools import starmap
from collections import namedtuple
from math import log2, exp2, fabs
from random import choices, uniform, shuffle
from statistics import median
DotExample = namedtuple('DotExample', ('x', 'y', 'target_sumprod', 'condition'))
def DotExact(x, y):
vec1 = map(Fraction, x)
vec2 = map(Fraction, y)
return sum(starmap(operator.mul, zip(vec1, vec2, strict=True)))
def Condition(x, y):
return 2.0 * DotExact(map(abs, x), map(abs, y)) / abs(DotExact(x, y))
def linspace(lo, hi, n):
width = (hi - lo) / (n - 1)
return [lo + width * i for i in range(n)]
def GenDot(n, c):
""" Algorithm 6.1 (GenDot) works as follows. The condition number (5.7) of
the dot product xT y is proportional to the degree of cancellation. In
order to achieve a prescribed cancellation, we generate the first half of
the vectors x and y randomly within a large exponent range. This range is
chosen according to the anticipated condition number. The second half of x
and y is then constructed choosing xi randomly with decreasing exponent,
and calculating yi such that some cancellation occurs. Finally, we permute
the vectors x, y randomly and calculate the achieved condition number.
"""
assert n >= 6
n2 = n // 2
x = [0.0] * n
y = [0.0] * n
b = log2(c)
# First half with exponents from 0 to |_b/2_| and random ints in between
e = choices(range(int(b/2)), k=n2)
e[0] = int(b / 2) + 1
e[-1] = 0.0
x[:n2] = [uniform(-1.0, 1.0) * exp2(p) for p in e]
y[:n2] = [uniform(-1.0, 1.0) * exp2(p) for p in e]
# Second half
e = list(map(round, linspace(b/2, 0.0 , n-n2)))
for i in range(n2, n):
x[i] = uniform(-1.0, 1.0) * exp2(e[i - n2])
y[i] = (uniform(-1.0, 1.0) * exp2(e[i - n2]) - DotExact(x, y)) / x[i]
# Shuffle
pairs = list(zip(x, y))
shuffle(pairs)
x, y = zip(*pairs)
return DotExample(x, y, DotExact(x, y), Condition(x, y))
def RelativeError(res, ex):
x, y, target_sumprod, condition = ex
n = DotExact(list(x) + [-res], list(y) + [1])
return fabs(n / target_sumprod)
def Trial(dotfunc, c, n):
ex = GenDot(10, c)
res = dotfunc(ex.x, ex.y)
return RelativeError(res, ex)
times = 1000 # Number of trials
n = 20 # Length of vectors
c = 1e30 # Target condition number
# If the following test fails, it means that the C math library
# implementation of fma() is not compliant with the C99 standard
# and is inaccurate. To solve this problem, make a new build
# with the symbol UNRELIABLE_FMA defined. That will enable a
# slower but accurate code path that avoids the fma() call.
relative_err = median(Trial(math.sumprod, c, n) for i in range(times))
self.assertLess(relative_err, 1e-16)
def testModf(self):
self.assertRaises(TypeError, math.modf)
def testmodf(name, result, expected):
(v1, v2), (e1, e2) = result, expected
if abs(v1-e1) > eps or abs(v2-e2):
self.fail('%s returned %r, expected %r'%\
(name, result, expected))
testmodf('modf(1.5)', math.modf(1.5), (0.5, 1.0))
testmodf('modf(-1.5)', math.modf(-1.5), (-0.5, -1.0))
self.assertEqual(math.modf(INF), (0.0, INF))
self.assertEqual(math.modf(NINF), (-0.0, NINF))
modf_nan = math.modf(NAN)
self.assertTrue(math.isnan(modf_nan[0]))
self.assertTrue(math.isnan(modf_nan[1]))
def testPow(self):
self.assertRaises(TypeError, math.pow)
self.ftest('pow(0,1)', math.pow(0,1), 0)
self.ftest('pow(1,0)', math.pow(1,0), 1)
self.ftest('pow(2,1)', math.pow(2,1), 2)
self.ftest('pow(2,-1)', math.pow(2,-1), 0.5)
self.assertEqual(math.pow(INF, 1), INF)
self.assertEqual(math.pow(NINF, 1), NINF)
self.assertEqual((math.pow(1, INF)), 1.)
self.assertEqual((math.pow(1, NINF)), 1.)
self.assertTrue(math.isnan(math.pow(NAN, 1)))
self.assertTrue(math.isnan(math.pow(2, NAN)))
self.assertTrue(math.isnan(math.pow(0, NAN)))
self.assertEqual(math.pow(1, NAN), 1)
self.assertRaises(OverflowError, math.pow, 1e+100, 1e+100)
# pow(0., x)
self.assertEqual(math.pow(0., INF), 0.)
self.assertEqual(math.pow(0., 3.), 0.)
self.assertEqual(math.pow(0., 2.3), 0.)
self.assertEqual(math.pow(0., 2.), 0.)
self.assertEqual(math.pow(0., 0.), 1.)
self.assertEqual(math.pow(0., -0.), 1.)
self.assertRaises(ValueError, math.pow, 0., -2.)
self.assertRaises(ValueError, math.pow, 0., -2.3)
self.assertRaises(ValueError, math.pow, 0., -3.)
self.assertEqual(math.pow(0., NINF), INF)
self.assertTrue(math.isnan(math.pow(0., NAN)))
# pow(INF, x)
self.assertEqual(math.pow(INF, INF), INF)
self.assertEqual(math.pow(INF, 3.), INF)
self.assertEqual(math.pow(INF, 2.3), INF)
self.assertEqual(math.pow(INF, 2.), INF)
self.assertEqual(math.pow(INF, 0.), 1.)
self.assertEqual(math.pow(INF, -0.), 1.)
self.assertEqual(math.pow(INF, -2.), 0.)
self.assertEqual(math.pow(INF, -2.3), 0.)
self.assertEqual(math.pow(INF, -3.), 0.)
self.assertEqual(math.pow(INF, NINF), 0.)
self.assertTrue(math.isnan(math.pow(INF, NAN)))
# pow(-0., x)
self.assertEqual(math.pow(-0., INF), 0.)
self.assertEqual(math.pow(-0., 3.), -0.)
self.assertEqual(math.pow(-0., 2.3), 0.)
self.assertEqual(math.pow(-0., 2.), 0.)
self.assertEqual(math.pow(-0., 0.), 1.)
self.assertEqual(math.pow(-0., -0.), 1.)
self.assertRaises(ValueError, math.pow, -0., -2.)
self.assertRaises(ValueError, math.pow, -0., -2.3)
self.assertRaises(ValueError, math.pow, -0., -3.)
self.assertEqual(math.pow(-0., NINF), INF)
self.assertTrue(math.isnan(math.pow(-0., NAN)))
# pow(NINF, x)
self.assertEqual(math.pow(NINF, INF), INF)
self.assertEqual(math.pow(NINF, 3.), NINF)
self.assertEqual(math.pow(NINF, 2.3), INF)
self.assertEqual(math.pow(NINF, 2.), INF)
self.assertEqual(math.pow(NINF, 0.), 1.)
self.assertEqual(math.pow(NINF, -0.), 1.)
self.assertEqual(math.pow(NINF, -2.), 0.)
self.assertEqual(math.pow(NINF, -2.3), 0.)
self.assertEqual(math.pow(NINF, -3.), -0.)
self.assertEqual(math.pow(NINF, NINF), 0.)
self.assertTrue(math.isnan(math.pow(NINF, NAN)))
# pow(-1, x)
self.assertEqual(math.pow(-1., INF), 1.)
self.assertEqual(math.pow(-1., 3.), -1.)
self.assertRaises(ValueError, math.pow, -1., 2.3)
self.assertEqual(math.pow(-1., 2.), 1.)
self.assertEqual(math.pow(-1., 0.), 1.)
self.assertEqual(math.pow(-1., -0.), 1.)
self.assertEqual(math.pow(-1., -2.), 1.)
self.assertRaises(ValueError, math.pow, -1., -2.3)
self.assertEqual(math.pow(-1., -3.), -1.)
self.assertEqual(math.pow(-1., NINF), 1.)
self.assertTrue(math.isnan(math.pow(-1., NAN)))
# pow(1, x)
self.assertEqual(math.pow(1., INF), 1.)
self.assertEqual(math.pow(1., 3.), 1.)
self.assertEqual(math.pow(1., 2.3), 1.)
self.assertEqual(math.pow(1., 2.), 1.)
self.assertEqual(math.pow(1., 0.), 1.)
self.assertEqual(math.pow(1., -0.), 1.)
self.assertEqual(math.pow(1., -2.), 1.)
self.assertEqual(math.pow(1., -2.3), 1.)
self.assertEqual(math.pow(1., -3.), 1.)
self.assertEqual(math.pow(1., NINF), 1.)
self.assertEqual(math.pow(1., NAN), 1.)
# pow(x, 0) should be 1 for any x
self.assertEqual(math.pow(2.3, 0.), 1.)
self.assertEqual(math.pow(-2.3, 0.), 1.)
self.assertEqual(math.pow(NAN, 0.), 1.)
self.assertEqual(math.pow(2.3, -0.), 1.)
self.assertEqual(math.pow(-2.3, -0.), 1.)
self.assertEqual(math.pow(NAN, -0.), 1.)
# pow(x, y) is invalid if x is negative and y is not integral
self.assertRaises(ValueError, math.pow, -1., 2.3)
self.assertRaises(ValueError, math.pow, -15., -3.1)
# pow(x, NINF)
self.assertEqual(math.pow(1.9, NINF), 0.)
self.assertEqual(math.pow(1.1, NINF), 0.)
self.assertEqual(math.pow(0.9, NINF), INF)
self.assertEqual(math.pow(0.1, NINF), INF)
self.assertEqual(math.pow(-0.1, NINF), INF)
self.assertEqual(math.pow(-0.9, NINF), INF)
self.assertEqual(math.pow(-1.1, NINF), 0.)
self.assertEqual(math.pow(-1.9, NINF), 0.)
# pow(x, INF)
self.assertEqual(math.pow(1.9, INF), INF)
self.assertEqual(math.pow(1.1, INF), INF)
self.assertEqual(math.pow(0.9, INF), 0.)
self.assertEqual(math.pow(0.1, INF), 0.)
self.assertEqual(math.pow(-0.1, INF), 0.)
self.assertEqual(math.pow(-0.9, INF), 0.)
self.assertEqual(math.pow(-1.1, INF), INF)
self.assertEqual(math.pow(-1.9, INF), INF)
# pow(x, y) should work for x negative, y an integer
self.ftest('(-2.)**3.', math.pow(-2.0, 3.0), -8.0)
self.ftest('(-2.)**2.', math.pow(-2.0, 2.0), 4.0)
self.ftest('(-2.)**1.', math.pow(-2.0, 1.0), -2.0)
self.ftest('(-2.)**0.', math.pow(-2.0, 0.0), 1.0)
self.ftest('(-2.)**-0.', math.pow(-2.0, -0.0), 1.0)
self.ftest('(-2.)**-1.', math.pow(-2.0, -1.0), -0.5)
self.ftest('(-2.)**-2.', math.pow(-2.0, -2.0), 0.25)
self.ftest('(-2.)**-3.', math.pow(-2.0, -3.0), -0.125)
self.assertRaises(ValueError, math.pow, -2.0, -0.5)
self.assertRaises(ValueError, math.pow, -2.0, 0.5)
# the following tests have been commented out since they don't
# really belong here: the implementation of ** for floats is
# independent of the implementation of math.pow
#self.assertEqual(1**NAN, 1)
#self.assertEqual(1**INF, 1)
#self.assertEqual(1**NINF, 1)
#self.assertEqual(1**0, 1)
#self.assertEqual(1.**NAN, 1)
#self.assertEqual(1.**INF, 1)
#self.assertEqual(1.**NINF, 1)
#self.assertEqual(1.**0, 1)
def testRadians(self):
self.assertRaises(TypeError, math.radians)
self.ftest('radians(180)', math.radians(180), math.pi)
self.ftest('radians(90)', math.radians(90), math.pi/2)
self.ftest('radians(-45)', math.radians(-45), -math.pi/4)
self.ftest('radians(0)', math.radians(0), 0)
@requires_IEEE_754
def testRemainder(self):
from fractions import Fraction
def validate_spec(x, y, r):
"""
Check that r matches remainder(x, y) according to the IEEE 754
specification. Assumes that x, y and r are finite and y is nonzero.
"""
fx, fy, fr = Fraction(x), Fraction(y), Fraction(r)
# r should not exceed y/2 in absolute value
self.assertLessEqual(abs(fr), abs(fy/2))
# x - r should be an exact integer multiple of y
n = (fx - fr) / fy
self.assertEqual(n, int(n))
if abs(fr) == abs(fy/2):
# If |r| == |y/2|, n should be even.
self.assertEqual(n/2, int(n/2))
# triples (x, y, remainder(x, y)) in hexadecimal form.
testcases = [
# Remainders modulo 1, showing the ties-to-even behaviour.
'-4.0 1 -0.0',
'-3.8 1 0.8',
'-3.0 1 -0.0',
'-2.8 1 -0.8',
'-2.0 1 -0.0',
'-1.8 1 0.8',
'-1.0 1 -0.0',
'-0.8 1 -0.8',
'-0.0 1 -0.0',
' 0.0 1 0.0',
' 0.8 1 0.8',
' 1.0 1 0.0',
' 1.8 1 -0.8',
' 2.0 1 0.0',
' 2.8 1 0.8',
' 3.0 1 0.0',
' 3.8 1 -0.8',
' 4.0 1 0.0',
# Reductions modulo 2*pi
'0x0.0p+0 0x1.921fb54442d18p+2 0x0.0p+0',
'0x1.921fb54442d18p+0 0x1.921fb54442d18p+2 0x1.921fb54442d18p+0',
'0x1.921fb54442d17p+1 0x1.921fb54442d18p+2 0x1.921fb54442d17p+1',
'0x1.921fb54442d18p+1 0x1.921fb54442d18p+2 0x1.921fb54442d18p+1',
'0x1.921fb54442d19p+1 0x1.921fb54442d18p+2 -0x1.921fb54442d17p+1',
'0x1.921fb54442d17p+2 0x1.921fb54442d18p+2 -0x0.0000000000001p+2',
'0x1.921fb54442d18p+2 0x1.921fb54442d18p+2 0x0p0',
'0x1.921fb54442d19p+2 0x1.921fb54442d18p+2 0x0.0000000000001p+2',
'0x1.2d97c7f3321d1p+3 0x1.921fb54442d18p+2 0x1.921fb54442d14p+1',
'0x1.2d97c7f3321d2p+3 0x1.921fb54442d18p+2 -0x1.921fb54442d18p+1',
'0x1.2d97c7f3321d3p+3 0x1.921fb54442d18p+2 -0x1.921fb54442d14p+1',
'0x1.921fb54442d17p+3 0x1.921fb54442d18p+2 -0x0.0000000000001p+3',
'0x1.921fb54442d18p+3 0x1.921fb54442d18p+2 0x0p0',
'0x1.921fb54442d19p+3 0x1.921fb54442d18p+2 0x0.0000000000001p+3',
'0x1.f6a7a2955385dp+3 0x1.921fb54442d18p+2 0x1.921fb54442d14p+1',
'0x1.f6a7a2955385ep+3 0x1.921fb54442d18p+2 0x1.921fb54442d18p+1',
'0x1.f6a7a2955385fp+3 0x1.921fb54442d18p+2 -0x1.921fb54442d14p+1',
'0x1.1475cc9eedf00p+5 0x1.921fb54442d18p+2 0x1.921fb54442d10p+1',
'0x1.1475cc9eedf01p+5 0x1.921fb54442d18p+2 -0x1.921fb54442d10p+1',
# Symmetry with respect to signs.
' 1 0.c 0.4',
'-1 0.c -0.4',
' 1 -0.c 0.4',
'-1 -0.c -0.4',
' 1.4 0.c -0.4',
'-1.4 0.c 0.4',
' 1.4 -0.c -0.4',
'-1.4 -0.c 0.4',
# Huge modulus, to check that the underlying algorithm doesn't
# rely on 2.0 * modulus being representable.
'0x1.dp+1023 0x1.4p+1023 0x0.9p+1023',
'0x1.ep+1023 0x1.4p+1023 -0x0.ap+1023',
'0x1.fp+1023 0x1.4p+1023 -0x0.9p+1023',
]
for case in testcases:
with self.subTest(case=case):
x_hex, y_hex, expected_hex = case.split()
x = float.fromhex(x_hex)
y = float.fromhex(y_hex)
expected = float.fromhex(expected_hex)
validate_spec(x, y, expected)
actual = math.remainder(x, y)
# Cheap way of checking that the floats are
# as identical as we need them to be.
self.assertEqual(actual.hex(), expected.hex())
# Test tiny subnormal modulus: there's potential for
# getting the implementation wrong here (for example,
# by assuming that modulus/2 is exactly representable).
tiny = float.fromhex('1p-1074') # min +ve subnormal
for n in range(-25, 25):
if n == 0:
continue
y = n * tiny
for m in range(100):
x = m * tiny
actual = math.remainder(x, y)
validate_spec(x, y, actual)
actual = math.remainder(-x, y)
validate_spec(-x, y, actual)
# Special values.
# NaNs should propagate as usual.
for value in [NAN, 0.0, -0.0, 2.0, -2.3, NINF, INF]:
self.assertIsNaN(math.remainder(NAN, value))
self.assertIsNaN(math.remainder(value, NAN))
# remainder(x, inf) is x, for non-nan non-infinite x.
for value in [-2.3, -0.0, 0.0, 2.3]:
self.assertEqual(math.remainder(value, INF), value)
self.assertEqual(math.remainder(value, NINF), value)
# remainder(x, 0) and remainder(infinity, x) for non-NaN x are invalid
# operations according to IEEE 754-2008 7.2(f), and should raise.
for value in [NINF, -2.3, -0.0, 0.0, 2.3, INF]:
with self.assertRaises(ValueError):
math.remainder(INF, value)
with self.assertRaises(ValueError):
math.remainder(NINF, value)
with self.assertRaises(ValueError):
math.remainder(value, 0.0)
with self.assertRaises(ValueError):
math.remainder(value, -0.0)
def testSin(self):
self.assertRaises(TypeError, math.sin)
self.ftest('sin(0)', math.sin(0), 0)
self.ftest('sin(pi/2)', math.sin(math.pi/2), 1)
self.ftest('sin(-pi/2)', math.sin(-math.pi/2), -1)
try:
self.assertTrue(math.isnan(math.sin(INF)))
self.assertTrue(math.isnan(math.sin(NINF)))
except ValueError:
self.assertRaises(ValueError, math.sin, INF)
self.assertRaises(ValueError, math.sin, NINF)
self.assertTrue(math.isnan(math.sin(NAN)))
def testSinh(self):
self.assertRaises(TypeError, math.sinh)
self.ftest('sinh(0)', math.sinh(0), 0)
self.ftest('sinh(1)**2-cosh(1)**2', math.sinh(1)**2-math.cosh(1)**2, -1)
self.ftest('sinh(1)+sinh(-1)', math.sinh(1)+math.sinh(-1), 0)
self.assertEqual(math.sinh(INF), INF)
self.assertEqual(math.sinh(NINF), NINF)
self.assertTrue(math.isnan(math.sinh(NAN)))
def testSqrt(self):
self.assertRaises(TypeError, math.sqrt)
self.ftest('sqrt(0)', math.sqrt(0), 0)
self.ftest('sqrt(0)', math.sqrt(0.0), 0.0)
self.ftest('sqrt(2.5)', math.sqrt(2.5), 1.5811388300841898)
self.ftest('sqrt(0.25)', math.sqrt(0.25), 0.5)
self.ftest('sqrt(25.25)', math.sqrt(25.25), 5.024937810560445)
self.ftest('sqrt(1)', math.sqrt(1), 1)
self.ftest('sqrt(4)', math.sqrt(4), 2)
self.assertEqual(math.sqrt(INF), INF)
self.assertRaises(ValueError, math.sqrt, -1)
self.assertRaises(ValueError, math.sqrt, NINF)
self.assertTrue(math.isnan(math.sqrt(NAN)))
def testTan(self):
self.assertRaises(TypeError, math.tan)
self.ftest('tan(0)', math.tan(0), 0)
self.ftest('tan(pi/4)', math.tan(math.pi/4), 1)
self.ftest('tan(-pi/4)', math.tan(-math.pi/4), -1)
try:
self.assertTrue(math.isnan(math.tan(INF)))
self.assertTrue(math.isnan(math.tan(NINF)))
except:
self.assertRaises(ValueError, math.tan, INF)
self.assertRaises(ValueError, math.tan, NINF)
self.assertTrue(math.isnan(math.tan(NAN)))
def testTanh(self):
self.assertRaises(TypeError, math.tanh)
self.ftest('tanh(0)', math.tanh(0), 0)
self.ftest('tanh(1)+tanh(-1)', math.tanh(1)+math.tanh(-1), 0,
abs_tol=math.ulp(1))
self.ftest('tanh(inf)', math.tanh(INF), 1)
self.ftest('tanh(-inf)', math.tanh(NINF), -1)
self.assertTrue(math.isnan(math.tanh(NAN)))
@requires_IEEE_754
def testTanhSign(self):
# check that tanh(-0.) == -0. on IEEE 754 systems
self.assertEqual(math.tanh(-0.), -0.)
self.assertEqual(math.copysign(1., math.tanh(-0.)),
math.copysign(1., -0.))
def test_trunc(self):
self.assertEqual(math.trunc(1), 1)
self.assertEqual(math.trunc(-1), -1)
self.assertEqual(type(math.trunc(1)), int)
self.assertEqual(type(math.trunc(1.5)), int)
self.assertEqual(math.trunc(1.5), 1)
self.assertEqual(math.trunc(-1.5), -1)
self.assertEqual(math.trunc(1.999999), 1)
self.assertEqual(math.trunc(-1.999999), -1)
self.assertEqual(math.trunc(-0.999999), -0)
self.assertEqual(math.trunc(-100.999), -100)
class TestTrunc:
def __trunc__(self):
return 23
class FloatTrunc(float):
def __trunc__(self):
return 23
class TestNoTrunc:
pass
class TestBadTrunc:
__trunc__ = BadDescr()
self.assertEqual(math.trunc(TestTrunc()), 23)
self.assertEqual(math.trunc(FloatTrunc()), 23)
self.assertRaises(TypeError, math.trunc)
self.assertRaises(TypeError, math.trunc, 1, 2)
self.assertRaises(TypeError, math.trunc, FloatLike(23.5))
self.assertRaises(TypeError, math.trunc, TestNoTrunc())
self.assertRaises(ValueError, math.trunc, TestBadTrunc())
def testIsfinite(self):
self.assertTrue(math.isfinite(0.0))
self.assertTrue(math.isfinite(-0.0))
self.assertTrue(math.isfinite(1.0))
self.assertTrue(math.isfinite(-1.0))
self.assertFalse(math.isfinite(float("nan")))
self.assertFalse(math.isfinite(float("inf")))
self.assertFalse(math.isfinite(float("-inf")))
def testIsnan(self):
self.assertTrue(math.isnan(float("nan")))
self.assertTrue(math.isnan(float("-nan")))
self.assertTrue(math.isnan(float("inf") * 0.))
self.assertFalse(math.isnan(float("inf")))
self.assertFalse(math.isnan(0.))
self.assertFalse(math.isnan(1.))
def testIsinf(self):
self.assertTrue(math.isinf(float("inf")))
self.assertTrue(math.isinf(float("-inf")))
self.assertTrue(math.isinf(1E400))
self.assertTrue(math.isinf(-1E400))
self.assertFalse(math.isinf(float("nan")))
self.assertFalse(math.isinf(0.))
self.assertFalse(math.isinf(1.))
def test_nan_constant(self):
# `math.nan` must be a quiet NaN with positive sign bit
self.assertTrue(math.isnan(math.nan))
self.assertEqual(math.copysign(1., math.nan), 1.)
def test_inf_constant(self):
self.assertTrue(math.isinf(math.inf))
self.assertGreater(math.inf, 0.0)
self.assertEqual(math.inf, float("inf"))
self.assertEqual(-math.inf, float("-inf"))
# RED_FLAG 16-Oct-2000 Tim
# While 2.0 is more consistent about exceptions than previous releases, it
# still fails this part of the test on some platforms. For now, we only
# *run* test_exceptions() in verbose mode, so that this isn't normally
# tested.
@unittest.skipUnless(verbose, 'requires verbose mode')
def test_exceptions(self):
try:
x = math.exp(-1000000000)
except:
# mathmodule.c is failing to weed out underflows from libm, or
# we've got an fp format with huge dynamic range
self.fail("underflowing exp() should not have raised "
"an exception")
if x != 0:
self.fail("underflowing exp() should have returned 0")
# If this fails, probably using a strict IEEE-754 conforming libm, and x
# is +Inf afterwards. But Python wants overflows detected by default.
try:
x = math.exp(1000000000)
except OverflowError:
pass
else:
self.fail("overflowing exp() didn't trigger OverflowError")
# If this fails, it could be a puzzle. One odd possibility is that
# mathmodule.c's macros are getting confused while comparing
# Inf (HUGE_VAL) to a NaN, and artificially setting errno to ERANGE
# as a result (and so raising OverflowError instead).
try:
x = math.sqrt(-1.0)
except ValueError:
pass
else:
self.fail("sqrt(-1) didn't raise ValueError")
@requires_IEEE_754
def test_testfile(self):
# Some tests need to be skipped on ancient OS X versions.
# See issue #27953.
SKIP_ON_TIGER = {'tan0064'}
osx_version = None
if sys.platform == 'darwin':
version_txt = platform.mac_ver()[0]
try:
osx_version = tuple(map(int, version_txt.split('.')))
except ValueError:
pass
fail_fmt = "{}: {}({!r}): {}"
failures = []
for id, fn, ar, ai, er, ei, flags in parse_testfile(test_file):
# Skip if either the input or result is complex
if ai != 0.0 or ei != 0.0:
continue
if fn in ['rect', 'polar']:
# no real versions of rect, polar
continue
# Skip certain tests on OS X 10.4.
if osx_version is not None and osx_version < (10, 5):
if id in SKIP_ON_TIGER:
continue
func = getattr(math, fn)
if 'invalid' in flags or 'divide-by-zero' in flags:
er = 'ValueError'
elif 'overflow' in flags:
er = 'OverflowError'
try:
result = func(ar)
except ValueError:
result = 'ValueError'
except OverflowError:
result = 'OverflowError'
# Default tolerances
ulp_tol, abs_tol = 5, 0.0
failure = result_check(er, result, ulp_tol, abs_tol)
if failure is None:
continue
msg = fail_fmt.format(id, fn, ar, failure)
failures.append(msg)
if failures:
self.fail('Failures in test_testfile:\n ' +
'\n '.join(failures))
@requires_IEEE_754
def test_mtestfile(self):
fail_fmt = "{}: {}({!r}): {}"
failures = []
for id, fn, arg, expected, flags in parse_mtestfile(math_testcases):
func = getattr(math, fn)
if 'invalid' in flags or 'divide-by-zero' in flags:
expected = 'ValueError'
elif 'overflow' in flags:
expected = 'OverflowError'
try:
got = func(arg)
except ValueError:
got = 'ValueError'
except OverflowError:
got = 'OverflowError'
# Default tolerances
ulp_tol, abs_tol = 5, 0.0
# Exceptions to the defaults
if fn == 'gamma':
# Experimental results on one platform gave
# an accuracy of <= 10 ulps across the entire float
# domain. We weaken that to require 20 ulp accuracy.
ulp_tol = 20
elif fn == 'lgamma':
# we use a weaker accuracy test for lgamma;
# lgamma only achieves an absolute error of
# a few multiples of the machine accuracy, in
# general.
abs_tol = 1e-15
elif fn == 'erfc' and arg >= 0.0:
# erfc has less-than-ideal accuracy for large
# arguments (x ~ 25 or so), mainly due to the
# error involved in computing exp(-x*x).
#
# Observed between CPython and mpmath at 25 dp:
# x < 0 : err <= 2 ulp
# 0 <= x < 1 : err <= 10 ulp
# 1 <= x < 10 : err <= 100 ulp
# 10 <= x < 20 : err <= 300 ulp
# 20 <= x : < 600 ulp
#
if arg < 1.0:
ulp_tol = 10
elif arg < 10.0:
ulp_tol = 100
else:
ulp_tol = 1000
failure = result_check(expected, got, ulp_tol, abs_tol)
if failure is None:
continue
msg = fail_fmt.format(id, fn, arg, failure)
failures.append(msg)
if failures:
self.fail('Failures in test_mtestfile:\n ' +
'\n '.join(failures))
def test_prod(self):
from fractions import Fraction as F
prod = math.prod
self.assertEqual(prod([]), 1)
self.assertEqual(prod([], start=5), 5)
self.assertEqual(prod(list(range(2,8))), 5040)
self.assertEqual(prod(iter(list(range(2,8)))), 5040)
self.assertEqual(prod(range(1, 10), start=10), 3628800)
self.assertEqual(prod([1, 2, 3, 4, 5]), 120)
self.assertEqual(prod([1.0, 2.0, 3.0, 4.0, 5.0]), 120.0)
self.assertEqual(prod([1, 2, 3, 4.0, 5.0]), 120.0)
self.assertEqual(prod([1.0, 2.0, 3.0, 4, 5]), 120.0)
self.assertEqual(prod([1., F(3, 2)]), 1.5)
# Error in multiplication
class BadMultiply:
def __rmul__(self, other):
raise RuntimeError
with self.assertRaises(RuntimeError):
prod([10., BadMultiply()])
# Test overflow in fast-path for integers
self.assertEqual(prod([1, 1, 2**32, 1, 1]), 2**32)
# Test overflow in fast-path for floats
self.assertEqual(prod([1.0, 1.0, 2**32, 1, 1]), float(2**32))
self.assertRaises(TypeError, prod)
self.assertRaises(TypeError, prod, 42)
self.assertRaises(TypeError, prod, ['a', 'b', 'c'])
self.assertRaises(TypeError, prod, ['a', 'b', 'c'], start='')
self.assertRaises(TypeError, prod, [b'a', b'c'], start=b'')
values = [bytearray(b'a'), bytearray(b'b')]
self.assertRaises(TypeError, prod, values, start=bytearray(b''))
self.assertRaises(TypeError, prod, [[1], [2], [3]])
self.assertRaises(TypeError, prod, [{2:3}])
self.assertRaises(TypeError, prod, [{2:3}]*2, start={2:3})
self.assertRaises(TypeError, prod, [[1], [2], [3]], start=[])
# Some odd cases
self.assertEqual(prod([2, 3], start='ab'), 'abababababab')
self.assertEqual(prod([2, 3], start=[1, 2]), [1, 2, 1, 2, 1, 2, 1, 2, 1, 2, 1, 2])
self.assertEqual(prod([], start={2: 3}), {2:3})
with self.assertRaises(TypeError):
prod([10, 20], 1) # start is a keyword-only argument
self.assertEqual(prod([0, 1, 2, 3]), 0)
self.assertEqual(prod([1, 0, 2, 3]), 0)
self.assertEqual(prod([1, 2, 3, 0]), 0)
def _naive_prod(iterable, start=1):
for elem in iterable:
start *= elem
return start
# Big integers
iterable = range(1, 10000)
self.assertEqual(prod(iterable), _naive_prod(iterable))
iterable = range(-10000, -1)
self.assertEqual(prod(iterable), _naive_prod(iterable))
iterable = range(-1000, 1000)
self.assertEqual(prod(iterable), 0)
# Big floats
iterable = [float(x) for x in range(1, 1000)]
self.assertEqual(prod(iterable), _naive_prod(iterable))
iterable = [float(x) for x in range(-1000, -1)]
self.assertEqual(prod(iterable), _naive_prod(iterable))
iterable = [float(x) for x in range(-1000, 1000)]
self.assertIsNaN(prod(iterable))
# Float tests
self.assertIsNaN(prod([1, 2, 3, float("nan"), 2, 3]))
self.assertIsNaN(prod([1, 0, float("nan"), 2, 3]))
self.assertIsNaN(prod([1, float("nan"), 0, 3]))
self.assertIsNaN(prod([1, float("inf"), float("nan"),3]))
self.assertIsNaN(prod([1, float("-inf"), float("nan"),3]))
self.assertIsNaN(prod([1, float("nan"), float("inf"),3]))
self.assertIsNaN(prod([1, float("nan"), float("-inf"),3]))
self.assertEqual(prod([1, 2, 3, float('inf'),-3,4]), float('-inf'))
self.assertEqual(prod([1, 2, 3, float('-inf'),-3,4]), float('inf'))
self.assertIsNaN(prod([1,2,0,float('inf'), -3, 4]))
self.assertIsNaN(prod([1,2,0,float('-inf'), -3, 4]))
self.assertIsNaN(prod([1, 2, 3, float('inf'), -3, 0, 3]))
self.assertIsNaN(prod([1, 2, 3, float('-inf'), -3, 0, 2]))
# Type preservation
self.assertEqual(type(prod([1, 2, 3, 4, 5, 6])), int)
self.assertEqual(type(prod([1, 2.0, 3, 4, 5, 6])), float)
self.assertEqual(type(prod(range(1, 10000))), int)
self.assertEqual(type(prod(range(1, 10000), start=1.0)), float)
self.assertEqual(type(prod([1, decimal.Decimal(2.0), 3, 4, 5, 6])),
decimal.Decimal)
def testPerm(self):
perm = math.perm
factorial = math.factorial
# Test if factorial definition is satisfied
for n in range(500):
for k in (range(n + 1) if n < 100 else range(30) if n < 200 else range(10)):
self.assertEqual(perm(n, k),
factorial(n) // factorial(n - k))
# Test for Pascal's identity
for n in range(1, 100):
for k in range(1, n):
self.assertEqual(perm(n, k), perm(n - 1, k - 1) * k + perm(n - 1, k))
# Test corner cases
for n in range(1, 100):
self.assertEqual(perm(n, 0), 1)
self.assertEqual(perm(n, 1), n)
self.assertEqual(perm(n, n), factorial(n))
# Test one argument form
for n in range(20):
self.assertEqual(perm(n), factorial(n))
self.assertEqual(perm(n, None), factorial(n))
# Raises TypeError if any argument is non-integer or argument count is
# not 1 or 2
self.assertRaises(TypeError, perm, 10, 1.0)
self.assertRaises(TypeError, perm, 10, decimal.Decimal(1.0))
self.assertRaises(TypeError, perm, 10, "1")
self.assertRaises(TypeError, perm, 10.0, 1)
self.assertRaises(TypeError, perm, decimal.Decimal(10.0), 1)
self.assertRaises(TypeError, perm, "10", 1)
self.assertRaises(TypeError, perm)
self.assertRaises(TypeError, perm, 10, 1, 3)
self.assertRaises(TypeError, perm)
# Raises Value error if not k or n are negative numbers
self.assertRaises(ValueError, perm, -1, 1)
self.assertRaises(ValueError, perm, -2**1000, 1)
self.assertRaises(ValueError, perm, 1, -1)
self.assertRaises(ValueError, perm, 1, -2**1000)
# Returns zero if k is greater than n
self.assertEqual(perm(1, 2), 0)
self.assertEqual(perm(1, 2**1000), 0)
n = 2**1000
self.assertEqual(perm(n, 0), 1)
self.assertEqual(perm(n, 1), n)
self.assertEqual(perm(n, 2), n * (n-1))
if support.check_impl_detail(cpython=True):
self.assertRaises(OverflowError, perm, n, n)
for n, k in (True, True), (True, False), (False, False):
self.assertEqual(perm(n, k), 1)
self.assertIs(type(perm(n, k)), int)
self.assertEqual(perm(IntSubclass(5), IntSubclass(2)), 20)
self.assertEqual(perm(MyIndexable(5), MyIndexable(2)), 20)
for k in range(3):
self.assertIs(type(perm(IntSubclass(5), IntSubclass(k))), int)
self.assertIs(type(perm(MyIndexable(5), MyIndexable(k))), int)
def testComb(self):
comb = math.comb
factorial = math.factorial
# Test if factorial definition is satisfied
for n in range(500):
for k in (range(n + 1) if n < 100 else range(30) if n < 200 else range(10)):
self.assertEqual(comb(n, k), factorial(n)
// (factorial(k) * factorial(n - k)))
# Test for Pascal's identity
for n in range(1, 100):
for k in range(1, n):
self.assertEqual(comb(n, k), comb(n - 1, k - 1) + comb(n - 1, k))
# Test corner cases
for n in range(100):
self.assertEqual(comb(n, 0), 1)
self.assertEqual(comb(n, n), 1)
for n in range(1, 100):
self.assertEqual(comb(n, 1), n)
self.assertEqual(comb(n, n - 1), n)
# Test Symmetry
for n in range(100):
for k in range(n // 2):
self.assertEqual(comb(n, k), comb(n, n - k))
# Raises TypeError if any argument is non-integer or argument count is
# not 2
self.assertRaises(TypeError, comb, 10, 1.0)
self.assertRaises(TypeError, comb, 10, decimal.Decimal(1.0))
self.assertRaises(TypeError, comb, 10, "1")
self.assertRaises(TypeError, comb, 10.0, 1)
self.assertRaises(TypeError, comb, decimal.Decimal(10.0), 1)
self.assertRaises(TypeError, comb, "10", 1)
self.assertRaises(TypeError, comb, 10)
self.assertRaises(TypeError, comb, 10, 1, 3)
self.assertRaises(TypeError, comb)
# Raises Value error if not k or n are negative numbers
self.assertRaises(ValueError, comb, -1, 1)
self.assertRaises(ValueError, comb, -2**1000, 1)
self.assertRaises(ValueError, comb, 1, -1)
self.assertRaises(ValueError, comb, 1, -2**1000)
# Returns zero if k is greater than n
self.assertEqual(comb(1, 2), 0)
self.assertEqual(comb(1, 2**1000), 0)
n = 2**1000
self.assertEqual(comb(n, 0), 1)
self.assertEqual(comb(n, 1), n)
self.assertEqual(comb(n, 2), n * (n-1) // 2)
self.assertEqual(comb(n, n), 1)
self.assertEqual(comb(n, n-1), n)
self.assertEqual(comb(n, n-2), n * (n-1) // 2)
if support.check_impl_detail(cpython=True):
self.assertRaises(OverflowError, comb, n, n//2)
for n, k in (True, True), (True, False), (False, False):
self.assertEqual(comb(n, k), 1)
self.assertIs(type(comb(n, k)), int)
self.assertEqual(comb(IntSubclass(5), IntSubclass(2)), 10)
self.assertEqual(comb(MyIndexable(5), MyIndexable(2)), 10)
for k in range(3):
self.assertIs(type(comb(IntSubclass(5), IntSubclass(k))), int)
self.assertIs(type(comb(MyIndexable(5), MyIndexable(k))), int)
@requires_IEEE_754
def test_nextafter(self):
# around 2^52 and 2^63
self.assertEqual(math.nextafter(4503599627370496.0, -INF),
4503599627370495.5)
self.assertEqual(math.nextafter(4503599627370496.0, INF),
4503599627370497.0)
self.assertEqual(math.nextafter(9223372036854775808.0, 0.0),
9223372036854774784.0)
self.assertEqual(math.nextafter(-9223372036854775808.0, 0.0),
-9223372036854774784.0)
# around 1.0
self.assertEqual(math.nextafter(1.0, -INF),
float.fromhex('0x1.fffffffffffffp-1'))
self.assertEqual(math.nextafter(1.0, INF),
float.fromhex('0x1.0000000000001p+0'))
self.assertEqual(math.nextafter(1.0, -INF, steps=1),
float.fromhex('0x1.fffffffffffffp-1'))
self.assertEqual(math.nextafter(1.0, INF, steps=1),
float.fromhex('0x1.0000000000001p+0'))
self.assertEqual(math.nextafter(1.0, -INF, steps=3),
float.fromhex('0x1.ffffffffffffdp-1'))
self.assertEqual(math.nextafter(1.0, INF, steps=3),
float.fromhex('0x1.0000000000003p+0'))
# x == y: y is returned
for steps in range(1, 5):
self.assertEqual(math.nextafter(2.0, 2.0, steps=steps), 2.0)
self.assertEqualSign(math.nextafter(-0.0, +0.0, steps=steps), +0.0)
self.assertEqualSign(math.nextafter(+0.0, -0.0, steps=steps), -0.0)
# around 0.0
smallest_subnormal = sys.float_info.min * sys.float_info.epsilon
self.assertEqual(math.nextafter(+0.0, INF), smallest_subnormal)
self.assertEqual(math.nextafter(-0.0, INF), smallest_subnormal)
self.assertEqual(math.nextafter(+0.0, -INF), -smallest_subnormal)
self.assertEqual(math.nextafter(-0.0, -INF), -smallest_subnormal)
self.assertEqualSign(math.nextafter(smallest_subnormal, +0.0), +0.0)
self.assertEqualSign(math.nextafter(-smallest_subnormal, +0.0), -0.0)
self.assertEqualSign(math.nextafter(smallest_subnormal, -0.0), +0.0)
self.assertEqualSign(math.nextafter(-smallest_subnormal, -0.0), -0.0)
# around infinity
largest_normal = sys.float_info.max
self.assertEqual(math.nextafter(INF, 0.0), largest_normal)
self.assertEqual(math.nextafter(-INF, 0.0), -largest_normal)
self.assertEqual(math.nextafter(largest_normal, INF), INF)
self.assertEqual(math.nextafter(-largest_normal, -INF), -INF)
# NaN
self.assertIsNaN(math.nextafter(NAN, 1.0))
self.assertIsNaN(math.nextafter(1.0, NAN))
self.assertIsNaN(math.nextafter(NAN, NAN))
self.assertEqual(1.0, math.nextafter(1.0, INF, steps=0))
with self.assertRaises(ValueError):
math.nextafter(1.0, INF, steps=-1)
@requires_IEEE_754
def test_ulp(self):
self.assertEqual(math.ulp(1.0), sys.float_info.epsilon)
# use int ** int rather than float ** int to not rely on pow() accuracy
self.assertEqual(math.ulp(2 ** 52), 1.0)
self.assertEqual(math.ulp(2 ** 53), 2.0)
self.assertEqual(math.ulp(2 ** 64), 4096.0)
# min and max
self.assertEqual(math.ulp(0.0),
sys.float_info.min * sys.float_info.epsilon)
self.assertEqual(math.ulp(FLOAT_MAX),
FLOAT_MAX - math.nextafter(FLOAT_MAX, -INF))
# special cases
self.assertEqual(math.ulp(INF), INF)
self.assertIsNaN(math.ulp(math.nan))
# negative number: ulp(-x) == ulp(x)
for x in (0.0, 1.0, 2 ** 52, 2 ** 64, INF):
with self.subTest(x=x):
self.assertEqual(math.ulp(-x), math.ulp(x))
def test_issue39871(self):
# A SystemError should not be raised if the first arg to atan2(),
# copysign(), or remainder() cannot be converted to a float.
class F:
def __float__(self):
self.converted = True
1/0
for func in math.atan2, math.copysign, math.remainder:
y = F()
with self.assertRaises(TypeError):
func("not a number", y)
# There should not have been any attempt to convert the second
# argument to a float.
self.assertFalse(getattr(y, "converted", False))
def test_input_exceptions(self):
self.assertRaises(TypeError, math.exp, "spam")
self.assertRaises(TypeError, math.erf, "spam")
self.assertRaises(TypeError, math.atan2, "spam", 1.0)
self.assertRaises(TypeError, math.atan2, 1.0, "spam")
self.assertRaises(TypeError, math.atan2, 1.0)
self.assertRaises(TypeError, math.atan2, 1.0, 2.0, 3.0)
# Custom assertions.
def assertIsNaN(self, value):
if not math.isnan(value):
self.fail("Expected a NaN, got {!r}.".format(value))
def assertEqualSign(self, x, y):
"""Similar to assertEqual(), but compare also the sign with copysign().
Function useful to compare signed zeros.
"""
self.assertEqual(x, y)
self.assertEqual(math.copysign(1.0, x), math.copysign(1.0, y))
class IsCloseTests(unittest.TestCase):
isclose = math.isclose # subclasses should override this
def assertIsClose(self, a, b, *args, **kwargs):
self.assertTrue(self.isclose(a, b, *args, **kwargs),
msg="%s and %s should be close!" % (a, b))
def assertIsNotClose(self, a, b, *args, **kwargs):
self.assertFalse(self.isclose(a, b, *args, **kwargs),
msg="%s and %s should not be close!" % (a, b))
def assertAllClose(self, examples, *args, **kwargs):
for a, b in examples:
self.assertIsClose(a, b, *args, **kwargs)
def assertAllNotClose(self, examples, *args, **kwargs):
for a, b in examples:
self.assertIsNotClose(a, b, *args, **kwargs)
def test_negative_tolerances(self):
# ValueError should be raised if either tolerance is less than zero
with self.assertRaises(ValueError):
self.assertIsClose(1, 1, rel_tol=-1e-100)
with self.assertRaises(ValueError):
self.assertIsClose(1, 1, rel_tol=1e-100, abs_tol=-1e10)
def test_identical(self):
# identical values must test as close
identical_examples = [(2.0, 2.0),
(0.1e200, 0.1e200),
(1.123e-300, 1.123e-300),
(12345, 12345.0),
(0.0, -0.0),
(345678, 345678)]
self.assertAllClose(identical_examples, rel_tol=0.0, abs_tol=0.0)
def test_eight_decimal_places(self):
# examples that are close to 1e-8, but not 1e-9
eight_decimal_places_examples = [(1e8, 1e8 + 1),
(-1e-8, -1.000000009e-8),
(1.12345678, 1.12345679)]
self.assertAllClose(eight_decimal_places_examples, rel_tol=1e-8)
self.assertAllNotClose(eight_decimal_places_examples, rel_tol=1e-9)
def test_near_zero(self):
# values close to zero
near_zero_examples = [(1e-9, 0.0),
(-1e-9, 0.0),
(-1e-150, 0.0)]
# these should not be close to any rel_tol
self.assertAllNotClose(near_zero_examples, rel_tol=0.9)
# these should be close to abs_tol=1e-8
self.assertAllClose(near_zero_examples, abs_tol=1e-8)
def test_identical_infinite(self):
# these are close regardless of tolerance -- i.e. they are equal
self.assertIsClose(INF, INF)
self.assertIsClose(INF, INF, abs_tol=0.0)
self.assertIsClose(NINF, NINF)
self.assertIsClose(NINF, NINF, abs_tol=0.0)
def test_inf_ninf_nan(self):
# these should never be close (following IEEE 754 rules for equality)
not_close_examples = [(NAN, NAN),
(NAN, 1e-100),
(1e-100, NAN),
(INF, NAN),
(NAN, INF),
(INF, NINF),
(INF, 1.0),
(1.0, INF),
(INF, 1e308),
(1e308, INF)]
# use largest reasonable tolerance
self.assertAllNotClose(not_close_examples, abs_tol=0.999999999999999)
def test_zero_tolerance(self):
# test with zero tolerance
zero_tolerance_close_examples = [(1.0, 1.0),
(-3.4, -3.4),
(-1e-300, -1e-300)]
self.assertAllClose(zero_tolerance_close_examples, rel_tol=0.0)
zero_tolerance_not_close_examples = [(1.0, 1.000000000000001),
(0.99999999999999, 1.0),
(1.0e200, .999999999999999e200)]
self.assertAllNotClose(zero_tolerance_not_close_examples, rel_tol=0.0)
def test_asymmetry(self):
# test the asymmetry example from PEP 485
self.assertAllClose([(9, 10), (10, 9)], rel_tol=0.1)
def test_integers(self):
# test with integer values
integer_examples = [(100000001, 100000000),
(123456789, 123456788)]
self.assertAllClose(integer_examples, rel_tol=1e-8)
self.assertAllNotClose(integer_examples, rel_tol=1e-9)
def test_decimals(self):
# test with Decimal values
from decimal import Decimal
decimal_examples = [(Decimal('1.00000001'), Decimal('1.0')),
(Decimal('1.00000001e-20'), Decimal('1.0e-20')),
(Decimal('1.00000001e-100'), Decimal('1.0e-100')),
(Decimal('1.00000001e20'), Decimal('1.0e20'))]
self.assertAllClose(decimal_examples, rel_tol=1e-8)
self.assertAllNotClose(decimal_examples, rel_tol=1e-9)
def test_fractions(self):
# test with Fraction values
from fractions import Fraction
fraction_examples = [
(Fraction(1, 100000000) + 1, Fraction(1)),
(Fraction(100000001), Fraction(100000000)),
(Fraction(10**8 + 1, 10**28), Fraction(1, 10**20))]
self.assertAllClose(fraction_examples, rel_tol=1e-8)
self.assertAllNotClose(fraction_examples, rel_tol=1e-9)
class FMATests(unittest.TestCase):
""" Tests for math.fma. """
def test_fma_nan_results(self):
# Selected representative values.
values = [
-math.inf, -1e300, -2.3, -1e-300, -0.0,
0.0, 1e-300, 2.3, 1e300, math.inf, math.nan
]
# If any input is a NaN, the result should be a NaN, too.
for a, b in itertools.product(values, repeat=2):
self.assertIsNaN(math.fma(math.nan, a, b))
self.assertIsNaN(math.fma(a, math.nan, b))
self.assertIsNaN(math.fma(a, b, math.nan))
def test_fma_infinities(self):
# Cases involving infinite inputs or results.
positives = [1e-300, 2.3, 1e300, math.inf]
finites = [-1e300, -2.3, -1e-300, -0.0, 0.0, 1e-300, 2.3, 1e300]
non_nans = [-math.inf, -2.3, -0.0, 0.0, 2.3, math.inf]
# ValueError due to inf * 0 computation.
for c in non_nans:
for infinity in [math.inf, -math.inf]:
for zero in [0.0, -0.0]:
with self.assertRaises(ValueError):
math.fma(infinity, zero, c)
with self.assertRaises(ValueError):
math.fma(zero, infinity, c)
# ValueError when a*b and c both infinite of opposite signs.
for b in positives:
with self.assertRaises(ValueError):
math.fma(math.inf, b, -math.inf)
with self.assertRaises(ValueError):
math.fma(math.inf, -b, math.inf)
with self.assertRaises(ValueError):
math.fma(-math.inf, -b, -math.inf)
with self.assertRaises(ValueError):
math.fma(-math.inf, b, math.inf)
with self.assertRaises(ValueError):
math.fma(b, math.inf, -math.inf)
with self.assertRaises(ValueError):
math.fma(-b, math.inf, math.inf)
with self.assertRaises(ValueError):
math.fma(-b, -math.inf, -math.inf)
with self.assertRaises(ValueError):
math.fma(b, -math.inf, math.inf)
# Infinite result when a*b and c both infinite of the same sign.
for b in positives:
self.assertEqual(math.fma(math.inf, b, math.inf), math.inf)
self.assertEqual(math.fma(math.inf, -b, -math.inf), -math.inf)
self.assertEqual(math.fma(-math.inf, -b, math.inf), math.inf)
self.assertEqual(math.fma(-math.inf, b, -math.inf), -math.inf)
self.assertEqual(math.fma(b, math.inf, math.inf), math.inf)
self.assertEqual(math.fma(-b, math.inf, -math.inf), -math.inf)
self.assertEqual(math.fma(-b, -math.inf, math.inf), math.inf)
self.assertEqual(math.fma(b, -math.inf, -math.inf), -math.inf)
# Infinite result when a*b finite, c infinite.
for a, b in itertools.product(finites, finites):
self.assertEqual(math.fma(a, b, math.inf), math.inf)
self.assertEqual(math.fma(a, b, -math.inf), -math.inf)
# Infinite result when a*b infinite, c finite.
for b, c in itertools.product(positives, finites):
self.assertEqual(math.fma(math.inf, b, c), math.inf)
self.assertEqual(math.fma(-math.inf, b, c), -math.inf)
self.assertEqual(math.fma(-math.inf, -b, c), math.inf)
self.assertEqual(math.fma(math.inf, -b, c), -math.inf)
self.assertEqual(math.fma(b, math.inf, c), math.inf)
self.assertEqual(math.fma(b, -math.inf, c), -math.inf)
self.assertEqual(math.fma(-b, -math.inf, c), math.inf)
self.assertEqual(math.fma(-b, math.inf, c), -math.inf)
# gh-73468: On some platforms, libc fma() doesn't implement IEE 754-2008
# properly: it doesn't use the right sign when the result is zero.
@unittest.skipIf(
sys.platform.startswith(("freebsd", "wasi"))
or (sys.platform == "android" and platform.machine() == "x86_64"),
f"this platform doesn't implement IEE 754-2008 properly")
def test_fma_zero_result(self):
nonnegative_finites = [0.0, 1e-300, 2.3, 1e300]
# Zero results from exact zero inputs.
for b in nonnegative_finites:
self.assertIsPositiveZero(math.fma(0.0, b, 0.0))
self.assertIsPositiveZero(math.fma(0.0, b, -0.0))
self.assertIsNegativeZero(math.fma(0.0, -b, -0.0))
self.assertIsPositiveZero(math.fma(0.0, -b, 0.0))
self.assertIsPositiveZero(math.fma(-0.0, -b, 0.0))
self.assertIsPositiveZero(math.fma(-0.0, -b, -0.0))
self.assertIsNegativeZero(math.fma(-0.0, b, -0.0))
self.assertIsPositiveZero(math.fma(-0.0, b, 0.0))
self.assertIsPositiveZero(math.fma(b, 0.0, 0.0))
self.assertIsPositiveZero(math.fma(b, 0.0, -0.0))
self.assertIsNegativeZero(math.fma(-b, 0.0, -0.0))
self.assertIsPositiveZero(math.fma(-b, 0.0, 0.0))
self.assertIsPositiveZero(math.fma(-b, -0.0, 0.0))
self.assertIsPositiveZero(math.fma(-b, -0.0, -0.0))
self.assertIsNegativeZero(math.fma(b, -0.0, -0.0))
self.assertIsPositiveZero(math.fma(b, -0.0, 0.0))
# Exact zero result from nonzero inputs.
self.assertIsPositiveZero(math.fma(2.0, 2.0, -4.0))
self.assertIsPositiveZero(math.fma(2.0, -2.0, 4.0))
self.assertIsPositiveZero(math.fma(-2.0, -2.0, -4.0))
self.assertIsPositiveZero(math.fma(-2.0, 2.0, 4.0))
# Underflow to zero.
tiny = 1e-300
self.assertIsPositiveZero(math.fma(tiny, tiny, 0.0))
self.assertIsNegativeZero(math.fma(tiny, -tiny, 0.0))
self.assertIsPositiveZero(math.fma(-tiny, -tiny, 0.0))
self.assertIsNegativeZero(math.fma(-tiny, tiny, 0.0))
self.assertIsPositiveZero(math.fma(tiny, tiny, -0.0))
self.assertIsNegativeZero(math.fma(tiny, -tiny, -0.0))
self.assertIsPositiveZero(math.fma(-tiny, -tiny, -0.0))
self.assertIsNegativeZero(math.fma(-tiny, tiny, -0.0))
# Corner case where rounding the multiplication would
# give the wrong result.
x = float.fromhex('0x1p-500')
y = float.fromhex('0x1p-550')
z = float.fromhex('0x1p-1000')
self.assertIsNegativeZero(math.fma(x-y, x+y, -z))
self.assertIsPositiveZero(math.fma(y-x, x+y, z))
self.assertIsNegativeZero(math.fma(y-x, -(x+y), -z))
self.assertIsPositiveZero(math.fma(x-y, -(x+y), z))
def test_fma_overflow(self):
a = b = float.fromhex('0x1p512')
c = float.fromhex('0x1p1023')
# Overflow from multiplication.
with self.assertRaises(OverflowError):
math.fma(a, b, 0.0)
self.assertEqual(math.fma(a, b/2.0, 0.0), c)
# Overflow from the addition.
with self.assertRaises(OverflowError):
math.fma(a, b/2.0, c)
# No overflow, even though a*b overflows a float.
self.assertEqual(math.fma(a, b, -c), c)
# Extreme case: a * b is exactly at the overflow boundary, so the
# tiniest offset makes a difference between overflow and a finite
# result.
a = float.fromhex('0x1.ffffffc000000p+511')
b = float.fromhex('0x1.0000002000000p+512')
c = float.fromhex('0x0.0000000000001p-1022')
with self.assertRaises(OverflowError):
math.fma(a, b, 0.0)
with self.assertRaises(OverflowError):
math.fma(a, b, c)
self.assertEqual(math.fma(a, b, -c),
float.fromhex('0x1.fffffffffffffp+1023'))
# Another extreme case: here a*b is about as large as possible subject
# to math.fma(a, b, c) being finite.
a = float.fromhex('0x1.ae565943785f9p+512')
b = float.fromhex('0x1.3094665de9db8p+512')
c = float.fromhex('0x1.fffffffffffffp+1023')
self.assertEqual(math.fma(a, b, -c), c)
def test_fma_single_round(self):
a = float.fromhex('0x1p-50')
self.assertEqual(math.fma(a - 1.0, a + 1.0, 1.0), a*a)
def test_random(self):
# A collection of randomly generated inputs for which the naive FMA
# (with two rounds) gives a different result from a singly-rounded FMA.
# tuples (a, b, c, expected)
test_values = [
('0x1.694adde428b44p-1', '0x1.371b0d64caed7p-1',
'0x1.f347e7b8deab8p-4', '0x1.19f10da56c8adp-1'),
('0x1.605401ccc6ad6p-2', '0x1.ce3a40bf56640p-2',
'0x1.96e3bf7bf2e20p-2', '0x1.1af6d8aa83101p-1'),
('0x1.e5abd653a67d4p-2', '0x1.a2e400209b3e6p-1',
'0x1.a90051422ce13p-1', '0x1.37d68cc8c0fbbp+0'),
('0x1.f94e8efd54700p-2', '0x1.123065c812cebp-1',
'0x1.458f86fb6ccd0p-1', '0x1.ccdcee26a3ff3p-1'),
('0x1.bd926f1eedc96p-1', '0x1.eee9ca68c5740p-1',
'0x1.960c703eb3298p-2', '0x1.3cdcfb4fdb007p+0'),
('0x1.27348350fbccdp-1', '0x1.3b073914a53f1p-1',
'0x1.e300da5c2b4cbp-1', '0x1.4c51e9a3c4e29p+0'),
('0x1.2774f00b3497bp-1', '0x1.7038ec336bff0p-2',
'0x1.2f6f2ccc3576bp-1', '0x1.99ad9f9c2688bp-1'),
('0x1.51d5a99300e5cp-1', '0x1.5cd74abd445a1p-1',
'0x1.8880ab0bbe530p-1', '0x1.3756f96b91129p+0'),
('0x1.73cb965b821b8p-2', '0x1.218fd3d8d5371p-1',
'0x1.d1ea966a1f758p-2', '0x1.5217b8fd90119p-1'),
('0x1.4aa98e890b046p-1', '0x1.954d85dff1041p-1',
'0x1.122b59317ebdfp-1', '0x1.0bf644b340cc5p+0'),
('0x1.e28f29e44750fp-1', '0x1.4bcc4fdcd18fep-1',
'0x1.fd47f81298259p-1', '0x1.9b000afbc9995p+0'),
('0x1.d2e850717fe78p-3', '0x1.1dd7531c303afp-1',
'0x1.e0869746a2fc2p-2', '0x1.316df6eb26439p-1'),
('0x1.cf89c75ee6fbap-2', '0x1.b23decdc66825p-1',
'0x1.3d1fe76ac6168p-1', '0x1.00d8ea4c12abbp+0'),
('0x1.3265ae6f05572p-2', '0x1.16d7ec285f7a2p-1',
'0x1.0b8405b3827fbp-1', '0x1.5ef33c118a001p-1'),
('0x1.c4d1bf55ec1a5p-1', '0x1.bc59618459e12p-2',
'0x1.ce5b73dc1773dp-1', '0x1.496cf6164f99bp+0'),
('0x1.d350026ac3946p-1', '0x1.9a234e149a68cp-2',
'0x1.f5467b1911fd6p-2', '0x1.b5cee3225caa5p-1'),
]
for a_hex, b_hex, c_hex, expected_hex in test_values:
a = float.fromhex(a_hex)
b = float.fromhex(b_hex)
c = float.fromhex(c_hex)
expected = float.fromhex(expected_hex)
self.assertEqual(math.fma(a, b, c), expected)
self.assertEqual(math.fma(b, a, c), expected)
# Custom assertions.
def assertIsNaN(self, value):
self.assertTrue(
math.isnan(value),
msg="Expected a NaN, got {!r}".format(value)
)
def assertIsPositiveZero(self, value):
self.assertTrue(
value == 0 and math.copysign(1, value) > 0,
msg="Expected a positive zero, got {!r}".format(value)
)
def assertIsNegativeZero(self, value):
self.assertTrue(
value == 0 and math.copysign(1, value) < 0,
msg="Expected a negative zero, got {!r}".format(value)
)
def load_tests(loader, tests, pattern):
from doctest import DocFileSuite
tests.addTest(DocFileSuite(os.path.join("mathdata", "ieee754.txt")))
return tests
if __name__ == '__main__':
unittest.main()
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