summaryrefslogtreecommitdiffstats
diff options
context:
space:
mode:
-rw-r--r--Doc/library/math.rst42
-rw-r--r--Doc/whatsnew/2.6.rst2
-rw-r--r--Lib/test/test_math.py248
-rw-r--r--Lib/test/test_random.py2
-rw-r--r--Modules/mathmodule.c118
5 files changed, 201 insertions, 211 deletions
diff --git a/Doc/library/math.rst b/Doc/library/math.rst
index c8090b5..df4ec1b 100644
--- a/Doc/library/math.rst
+++ b/Doc/library/math.rst
@@ -76,6 +76,42 @@ Number-theoretic and representation functions:
apart" the internal representation of a float in a portable way.
+.. function:: fsum(iterable)
+
+ Return an accurate floating point sum of values in the iterable. Avoids
+ loss of precision by tracking multiple intermediate partial sums. The
+ algorithm's accuracy depends on IEEE-754 arithmetic guarantees and the
+ typical case where the rounding mode is half-even.
+
+ .. note::
+
+ On platforms where arithmetic results are not correctly rounded,
+ :func:`fsum` may occasionally produce incorrect results; these
+ results should be no less accurate than those from the builtin
+ :func:`sum` function, but nevertheless may have arbitrarily
+ large relative error.
+
+ In particular, this affects some older Intel hardware (for
+ example Pentium and earlier x86 processors) that makes use of
+ 'extended precision' floating-point registers with 64 bits of
+ precision instead of the 53 bits of precision provided by a C
+ double. Arithmetic operations using these registers may be
+ doubly rounded (rounded first to 64 bits, and then rerounded to
+ 53 bits), leading to incorrectly rounded results. To test
+ whether your machine is one of those affected, try the following
+ at a Python prompt::
+
+ >>> 1e16 + 2.9999
+ 10000000000000002.0
+
+ Machines subject to the double-rounding problem described above
+ are likely to print ``10000000000000004.0`` instead of
+ ``10000000000000002.0``.
+
+
+ .. versionadded:: 2.6
+
+
.. function:: isinf(x)
Checks if the float *x* is positive or negative infinite.
@@ -100,12 +136,6 @@ Number-theoretic and representation functions:
Return the fractional and integer parts of *x*. Both results carry the sign of
*x*, and both are floats.
-.. function:: sum(iterable)
-
- Return an accurate floating point sum of values in the iterable. Avoids
- loss of precision by tracking multiple intermediate partial sums. The
- algorithm's accuracy depends on IEEE-754 arithmetic guarantees and the
- typical case where the rounding mode is half-even.
.. function:: trunc(x)
diff --git a/Doc/whatsnew/2.6.rst b/Doc/whatsnew/2.6.rst
index a8d89cb..9959ecd 100644
--- a/Doc/whatsnew/2.6.rst
+++ b/Doc/whatsnew/2.6.rst
@@ -1537,7 +1537,7 @@ Here are all of the changes that Python 2.6 makes to the core Python language.
* :func:`~math.factorial` computes the factorial of a number.
(Contributed by Raymond Hettinger; :issue:`2138`.)
- * :func:`~math.sum` adds up the stream of numbers from an iterable,
+ * :func:`~math.fsum` adds up the stream of numbers from an iterable,
and is careful to avoid loss of precision by calculating partial sums.
(Contributed by Jean Brouwers, Raymond Hettinger, and Mark Dickinson;
:issue:`2819`.)
diff --git a/Lib/test/test_math.py b/Lib/test/test_math.py
index 1eafeba..9e646ac 100644
--- a/Lib/test/test_math.py
+++ b/Lib/test/test_math.py
@@ -359,6 +359,102 @@ class MathTests(unittest.TestCase):
self.assertEquals(math.frexp(NINF)[0], NINF)
self.assert_(math.isnan(math.frexp(NAN)[0]))
+ 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.
+
+ if not float.__getformat__("double").startswith("IEEE"):
+ return
+
+ # on IEEE 754 compliant machines, both of the expressions
+ # below should round to 10000000000000002.0.
+ if 1e16+2.0 != 1e16+2.9999:
+ return
+
+ # 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 http://code.activestate.com/recipes/393090/
+
+ """
+ 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),
+ ([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')),
+ ([1.7**(i+1)-1.7**i for i in range(1000)] + [-1.7**1000], -1.0),
+ ([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')),
+ ]
+
+ 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))
+
def testHypot(self):
self.assertRaises(TypeError, math.hypot)
self.ftest('hypot(0,0)', math.hypot(0,0), 0)
@@ -641,158 +737,6 @@ class MathTests(unittest.TestCase):
self.assertRaises(ValueError, math.sqrt, NINF)
self.assert_(math.isnan(math.sqrt(NAN)))
- def testSum(self):
- # math.sum 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.sum 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.
-
- if not float.__getformat__("double").startswith("IEEE"):
- return
-
- # on IEEE 754 compliant machines, both of the expressions
- # below should round to 10000000000000002.0.
- if 1e16+2.999 != 1e16+2.9999:
- return
-
- # Python version of math.sum algorithm, for comparison
- def msum(iterable):
- """Full precision sum of values in iterable. Returns the value of
- the sum, rounded to the nearest representable floating-point number
- using the round-half-to-even rule.
-
- """
- # Stage 1: accumulate partials
- partials = []
- for x in iterable:
- i = 0
- for y in partials:
- if abs(x) < abs(y):
- x, y = y, x
- hi = x + y
- lo = y - (hi - x)
- if lo:
- partials[i] = lo
- i += 1
- x = hi
- partials[i:] = [x] if x else []
-
- # Stage 2: sum partials
- if not partials:
- return 0.0
-
- # sum from the top, stopping as soon as the sum is inexact.
- total = partials.pop()
- while partials:
- x = partials.pop()
- old_total, total = total, total + x
- error = x - (total - old_total)
- if error != 0.0:
- # adjust for correct rounding if necessary
- if partials and (partials[-1] > 0.0) == (error > 0.0) and \
- total + 2*error - total == 2*error:
- total += 2*error
- break
- return total
-
- from sys import float_info
- maxfloat = float_info.max
- twopow = 2.**(float_info.max_exp - 1)
-
- test_values = [
- ([], 0.0),
- ([0.0], 0.0),
- ([1e100, 1.0, -1e100, 1e-100, 1e50, -1.0, -1e50], 1e-100),
- ([1e308, 1e308, -1e308], OverflowError),
- ([-1e308, 1e308, 1e308], 1e308),
- ([1e308, -1e308, 1e308], 1e308),
- ([2.0**1023, 2.0**1023, -2.0**1000], OverflowError),
- ([twopow, twopow, twopow, twopow, -twopow, -twopow, -twopow],
- OverflowError),
- ([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),
- ([2.0**1023-2.0**970, -1.0, 2.0**1023], OverflowError),
- ([maxfloat, maxfloat*2.**-54], maxfloat),
- ([maxfloat, maxfloat*2.**-53], OverflowError),
- ([1./n for n in range(1, 1001)], 7.4854708605503451),
- ([(-1.)**n/n for n in range(1, 1001)], -0.69264743055982025),
- ([1.7**(i+1)-1.7**i for i in range(1000)] + [-1.7**1000], -1.0),
- ([INF, -INF, NAN], ValueError),
- ([NAN, INF, -INF], ValueError),
- ([INF, NAN, INF], ValueError),
-
- ([INF, INF], OverflowError),
- ([INF, -INF], ValueError),
- ([-INF, 1e308, 1e308, -INF], OverflowError),
- ([2.0**1023-2.0**970, 0.0, 2.0**1023], OverflowError),
- ([2.0**1023-2.0**970, 1.0, 2.0**1023], OverflowError),
- ([2.0**1023, 2.0**1023], OverflowError),
- ([2.0**1023, 2.0**1023, -1.0], OverflowError),
- ([twopow, twopow, twopow, twopow, -twopow, -twopow],
- OverflowError),
- ([twopow, twopow, twopow, twopow, -twopow, twopow], OverflowError),
- ([-twopow, -twopow, -twopow, -twopow], OverflowError),
-
- ([2.**1023, 2.**1023, -2.**971], OverflowError),
- ([2.**1023, 2.**1023, -2.**970], OverflowError),
- ([-2.**970, 2.**1023, 2.**1023, -2.**-1074], OverflowError),
- ([ 2.**1023, 2.**1023, -2.**970, 2.**-1074], OverflowError),
- ([-2.**1023, 2.**971, -2.**1023], -maxfloat),
- ([-2.**1023, -2.**1023, 2.**970], OverflowError),
- ([-2.**1023, -2.**1023, 2.**970, 2.**-1074], OverflowError),
- ([-2.**-1074, -2.**1023, -2.**1023, 2.**970], OverflowError),
- ([2.**930, -2.**980, 2.**1023, 2.**1023, twopow, -twopow],
- OverflowError),
- ([2.**1023, 2.**1023, -1e307], OverflowError),
- ([1e16, 1., 1e-16], 10000000000000002.0),
- ([1e16-2., 1.-2.**-53, -(1e16-2.), -(1.-2.**-53)], 0.0),
- ]
-
- for i, (vals, s) in enumerate(test_values):
- if isinstance(s, type) and issubclass(s, Exception):
- try:
- m = math.sum(vals)
- except s:
- pass
- else:
- self.fail("test %d failed: got %r, expected %r "
- "for math.sum(%.100r)" %
- (i, m, s.__name__, vals))
- else:
- try:
- self.assertEqual(math.sum(vals), s)
- except OverflowError:
- self.fail("test %d failed: got OverflowError, expected %r "
- "for math.sum(%.100r)" % (i, s, vals))
- except ValueError:
- self.fail("test %d failed: got ValueError, expected %r "
- "for math.sum(%.100r)" % (i, s, vals))
-
- # compare with output of msum above, but only when
- # result isn't an IEEE special or an exception
- if not math.isinf(s) and not math.isnan(s):
- self.assertEqual(msum(vals), s)
-
- 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.sum(vals))
-
-
def testTan(self):
self.assertRaises(TypeError, math.tan)
self.ftest('tan(0)', math.tan(0), 0)
diff --git a/Lib/test/test_random.py b/Lib/test/test_random.py
index da62a4f..14e9fca 100644
--- a/Lib/test/test_random.py
+++ b/Lib/test/test_random.py
@@ -5,7 +5,7 @@ import random
import time
import pickle
import warnings
-from math import log, exp, sqrt, pi, sum as msum
+from math import log, exp, sqrt, pi, fsum as msum
from test import support
class TestBasicOps(unittest.TestCase):
diff --git a/Modules/mathmodule.c b/Modules/mathmodule.c
index a196834..d23d2ff 100644
--- a/Modules/mathmodule.c
+++ b/Modules/mathmodule.c
@@ -396,7 +396,7 @@ FUNC1(tanh, tanh, 0,
Note 4: A similar implementation is in Modules/cmathmodule.c.
Be sure to update both when making changes.
- Note 5: The signature of math.sum() differs from __builtin__.sum()
+ Note 5: The signature of math.fsum() differs from __builtin__.sum()
because the start argument doesn't make sense in the context of
accurate summation. Since the partials table is collapsed before
returning a result, sum(seq2, start=sum(seq1)) may not equal the
@@ -407,7 +407,7 @@ FUNC1(tanh, tanh, 0,
/* Extend the partials array p[] by doubling its size. */
static int /* non-zero on error */
-_sum_realloc(double **p_ptr, Py_ssize_t n,
+_fsum_realloc(double **p_ptr, Py_ssize_t n,
double *ps, Py_ssize_t *m_ptr)
{
void *v = NULL;
@@ -425,7 +425,7 @@ _sum_realloc(double **p_ptr, Py_ssize_t n,
v = PyMem_Realloc(p, sizeof(double) * m);
}
if (v == NULL) { /* size overflow or no memory */
- PyErr_SetString(PyExc_MemoryError, "math sum partials");
+ PyErr_SetString(PyExc_MemoryError, "math.fsum partials");
return 1;
}
*p_ptr = (double*) v;
@@ -464,18 +464,19 @@ _sum_realloc(double **p_ptr, Py_ssize_t n,
*/
static PyObject*
-math_sum(PyObject *self, PyObject *seq)
+math_fsum(PyObject *self, PyObject *seq)
{
PyObject *item, *iter, *sum = NULL;
Py_ssize_t i, j, n = 0, m = NUM_PARTIALS;
double x, y, t, ps[NUM_PARTIALS], *p = ps;
+ double xsave, special_sum = 0.0, inf_sum = 0.0;
volatile double hi, yr, lo;
iter = PyObject_GetIter(seq);
if (iter == NULL)
return NULL;
- PyFPE_START_PROTECT("sum", Py_DECREF(iter); return NULL)
+ PyFPE_START_PROTECT("fsum", Py_DECREF(iter); return NULL)
for(;;) { /* for x in iterable */
assert(0 <= n && n <= m);
@@ -485,18 +486,19 @@ math_sum(PyObject *self, PyObject *seq)
item = PyIter_Next(iter);
if (item == NULL) {
if (PyErr_Occurred())
- goto _sum_error;
+ goto _fsum_error;
break;
}
x = PyFloat_AsDouble(item);
Py_DECREF(item);
if (PyErr_Occurred())
- goto _sum_error;
+ goto _fsum_error;
+ xsave = x;
for (i = j = 0; j < n; j++) { /* for y in partials */
y = p[j];
if (fabs(x) < fabs(y)) {
- t = x; x = y; y = t;
+ t = x; x = y; y = t;
}
hi = x + y;
yr = hi - x;
@@ -505,59 +507,73 @@ math_sum(PyObject *self, PyObject *seq)
p[i++] = lo;
x = hi;
}
-
- n = i; /* ps[i:] = [x] */
+
+ n = i; /* ps[i:] = [x] */
if (x != 0.0) {
- /* If non-finite, reset partials, effectively
- adding subsequent items without roundoff
- and yielding correct non-finite results,
- provided IEEE 754 rules are observed */
- if (! Py_IS_FINITE(x))
+ if (! Py_IS_FINITE(x)) {
+ /* a nonfinite x could arise either as
+ a result of intermediate overflow, or
+ as a result of a nan or inf in the
+ summands */
+ if (Py_IS_FINITE(xsave)) {
+ PyErr_SetString(PyExc_OverflowError,
+ "intermediate overflow in fsum");
+ goto _fsum_error;
+ }
+ if (Py_IS_INFINITY(xsave))
+ inf_sum += xsave;
+ special_sum += xsave;
+ /* reset partials */
n = 0;
- else if (n >= m && _sum_realloc(&p, n, ps, &m))
- goto _sum_error;
- p[n++] = x;
+ }
+ else if (n >= m && _fsum_realloc(&p, n, ps, &m))
+ goto _fsum_error;
+ else
+ p[n++] = x;
}
}
+ if (special_sum != 0.0) {
+ if (Py_IS_NAN(inf_sum))
+ PyErr_SetString(PyExc_ValueError,
+ "-inf + inf in fsum");
+ else
+ sum = PyFloat_FromDouble(special_sum);
+ goto _fsum_error;
+ }
+
hi = 0.0;
if (n > 0) {
hi = p[--n];
- if (Py_IS_FINITE(hi)) {
- /* sum_exact(ps, hi) from the top, stop when the sum becomes inexact. */
- while (n > 0) {
- x = hi;
- y = p[--n];
- assert(fabs(y) < fabs(x));
- hi = x + y;
- yr = hi - x;
- lo = y - yr;
- if (lo != 0.0)
- break;
- }
- /* Make half-even rounding work across multiple partials. Needed
- so that sum([1e-16, 1, 1e16]) will round-up the last digit to
- two instead of down to zero (the 1e-16 makes the 1 slightly
- closer to two). With a potential 1 ULP rounding error fixed-up,
- math.sum() can guarantee commutativity. */
- if (n > 0 && ((lo < 0.0 && p[n-1] < 0.0) ||
- (lo > 0.0 && p[n-1] > 0.0))) {
- y = lo * 2.0;
- x = hi + y;
- yr = x - hi;
- if (y == yr)
- hi = x;
- }
+ /* sum_exact(ps, hi) from the top, stop when the sum becomes
+ inexact. */
+ while (n > 0) {
+ x = hi;
+ y = p[--n];
+ assert(fabs(y) < fabs(x));
+ hi = x + y;
+ yr = hi - x;
+ lo = y - yr;
+ if (lo != 0.0)
+ break;
}
- else { /* raise exception corresponding to a special value */
- errno = Py_IS_NAN(hi) ? EDOM : ERANGE;
- if (is_error(hi))
- goto _sum_error;
+ /* Make half-even rounding work across multiple partials.
+ Needed so that sum([1e-16, 1, 1e16]) will round-up the last
+ digit to two instead of down to zero (the 1e-16 makes the 1
+ slightly closer to two). With a potential 1 ULP rounding
+ error fixed-up, math.fsum() can guarantee commutativity. */
+ if (n > 0 && ((lo < 0.0 && p[n-1] < 0.0) ||
+ (lo > 0.0 && p[n-1] > 0.0))) {
+ y = lo * 2.0;
+ x = hi + y;
+ yr = x - hi;
+ if (y == yr)
+ hi = x;
}
}
sum = PyFloat_FromDouble(hi);
-_sum_error:
+_fsum_error:
PyFPE_END_PROTECT(hi)
Py_DECREF(iter);
if (p != ps)
@@ -567,7 +583,7 @@ _sum_error:
#undef NUM_PARTIALS
-PyDoc_STRVAR(math_sum_doc,
+PyDoc_STRVAR(math_fsum_doc,
"sum(iterable)\n\n\
Return an accurate floating point sum of values in the iterable.\n\
Assumes IEEE-754 floating point arithmetic.");
@@ -1078,6 +1094,7 @@ static PyMethodDef math_methods[] = {
{"floor", math_floor, METH_O, math_floor_doc},
{"fmod", math_fmod, METH_VARARGS, math_fmod_doc},
{"frexp", math_frexp, METH_O, math_frexp_doc},
+ {"fsum", math_fsum, METH_O, math_fsum_doc},
{"hypot", math_hypot, METH_VARARGS, math_hypot_doc},
{"isinf", math_isinf, METH_O, math_isinf_doc},
{"isnan", math_isnan, METH_O, math_isnan_doc},
@@ -1091,10 +1108,9 @@ static PyMethodDef math_methods[] = {
{"sin", math_sin, METH_O, math_sin_doc},
{"sinh", math_sinh, METH_O, math_sinh_doc},
{"sqrt", math_sqrt, METH_O, math_sqrt_doc},
- {"sum", math_sum, METH_O, math_sum_doc},
{"tan", math_tan, METH_O, math_tan_doc},
{"tanh", math_tanh, METH_O, math_tanh_doc},
- {"trunc", math_trunc, METH_O, math_trunc_doc},
+ {"trunc", math_trunc, METH_O, math_trunc_doc},
{NULL, NULL} /* sentinel */
};