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Batuhan Osman TASKAYA
cpython
Commits
0f6414a0
Kaydet (Commit)
0f6414a0
authored
Tem 31, 2008
tarafından
Mark Dickinson
Dosyalara gözat
Seçenekler
Dosyalara Gözat
İndir
Eposta Yamaları
Sade Fark
Rename testSum to testFsum and move it to proper place in test_math.py
üst
cda5ce24
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with
96 additions
and
97 deletions
+96
-97
test_math.py
Lib/test/test_math.py
+96
-97
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Lib/test/test_math.py
Dosyayı görüntüle @
0f6414a0
...
...
@@ -364,6 +364,102 @@ 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(
%.100
r)"
%
(
i
,
expected
,
vals
))
except
ValueError
:
self
.
fail
(
"test
%
d failed: got ValueError, expected
%
r "
"for math.fsum(
%.100
r)"
%
(
i
,
expected
,
vals
))
self
.
assertEqual
(
actual
,
expected
)
from
random
import
random
,
gauss
,
shuffle
for
j
in
xrange
(
1000
):
vals
=
[
7
,
1e100
,
-
7
,
-
1e100
,
-
9e-20
,
8e-20
]
*
10
s
=
0
for
i
in
xrange
(
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
)
...
...
@@ -645,103 +741,6 @@ class MathTests(unittest.TestCase):
self
.
assertRaises
(
ValueError
,
math
.
sqrt
,
NINF
)
self
.
assert_
(
math
.
isnan
(
math
.
sqrt
(
NAN
)))
def
testSum
(
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(
%.100
r)"
%
(
i
,
expected
,
vals
))
except
ValueError
:
self
.
fail
(
"test
%
d failed: got ValueError, expected
%
r "
"for math.fsum(
%.100
r)"
%
(
i
,
expected
,
vals
))
self
.
assertEqual
(
actual
,
expected
)
from
random
import
random
,
gauss
,
shuffle
for
j
in
xrange
(
1000
):
vals
=
[
7
,
1e100
,
-
7
,
-
1e100
,
-
9e-20
,
8e-20
]
*
10
s
=
0
for
i
in
xrange
(
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
testTan
(
self
):
self
.
assertRaises
(
TypeError
,
math
.
tan
)
self
.
ftest
(
'tan(0)'
,
math
.
tan
(
0
),
0
)
...
...
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