Skip to content
Projects
Groups
Snippets
Help
Loading...
Help
Support
Keyboard shortcuts
?
Submit feedback
Contribute to GitLab
Sign in / Register
Toggle navigation
C
cpython
Project overview
Project overview
Details
Activity
Releases
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Issues
0
Issues
0
List
Boards
Labels
Milestones
Merge Requests
0
Merge Requests
0
Analytics
Analytics
Repository
Value Stream
Wiki
Wiki
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Create a new issue
Commits
Issue Boards
Open sidebar
Kirill Smelkov
cpython
Commits
c630e104
Commit
c630e104
authored
Aug 11, 2018
by
Raymond Hettinger
Committed by
GitHub
Aug 11, 2018
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
Factor-out common code. Also, optimize common cases by preallocating space on the stack. GH-8738
Improves speed by 9 to 10ns per call.
parent
13990745
Changes
1
Hide whitespace changes
Inline
Side-by-side
Showing
1 changed file
with
56 additions
and
41 deletions
+56
-41
Modules/mathmodule.c
Modules/mathmodule.c
+56
-41
No files found.
Modules/mathmodule.c
View file @
c630e104
...
@@ -2032,10 +2032,10 @@ math_fmod_impl(PyObject *module, double x, double y)
...
@@ -2032,10 +2032,10 @@ math_fmod_impl(PyObject *module, double x, double y)
}
}
/*
/*
Given an *n* length *vec* of non-negative
, non-nan, non-inf
values
Given an *n* length *vec* of non-negative values
where *max* is the largest value in the vector, compute:
where *max* is the largest value in the vector, compute:
sum((x / max) ** 2 for x in vec
)
max * sqrt(sum((x / max) ** 2 for x in vec)
)
When a maximum value is found, it is swapped to the end. This
When a maximum value is found, it is swapped to the end. This
lets us skip one loop iteration and just add 1.0 at the end.
lets us skip one loop iteration and just add 1.0 at the end.
...
@@ -2045,19 +2045,31 @@ Kahan summation is used to improve accuracy. The *csum*
...
@@ -2045,19 +2045,31 @@ Kahan summation is used to improve accuracy. The *csum*
variable tracks the cumulative sum and *frac* tracks
variable tracks the cumulative sum and *frac* tracks
fractional round-off error for the most recent addition.
fractional round-off error for the most recent addition.
The value of the *max* variable must be present in *vec*
or should equal to 0.0 when n==0. Likewise, *max* will
be INF if an infinity is present in the vec.
The *found_nan* variable indicates whether some member of
the *vec* is a NaN.
*/
*/
static
inline
double
static
inline
double
scaled_vector_squared
(
Py_ssize_t
n
,
double
*
vec
,
double
max
)
vector_norm
(
Py_ssize_t
n
,
double
*
vec
,
double
max
,
int
found_nan
)
{
{
double
x
,
csum
=
0
.
0
,
oldcsum
,
frac
=
0
.
0
;
double
x
,
csum
=
0
.
0
,
oldcsum
,
frac
=
0
.
0
;
Py_ssize_t
i
;
Py_ssize_t
i
;
if
(
Py_IS_INFINITY
(
max
))
{
return
max
;
}
if
(
found_nan
)
{
return
Py_NAN
;
}
if
(
max
==
0
.
0
)
{
if
(
max
==
0
.
0
)
{
return
0
.
0
;
return
0
.
0
;
}
}
assert
(
n
>
0
);
assert
(
n
>
0
);
for
(
i
=
0
;
i
<
n
-
1
;
i
++
)
{
for
(
i
=
0
;
i
<
n
-
1
;
i
++
)
{
x
=
vec
[
i
];
x
=
vec
[
i
];
if
(
x
==
max
)
{
if
(
x
==
max
)
{
x
=
vec
[
n
-
1
];
x
=
vec
[
n
-
1
];
...
@@ -2071,9 +2083,11 @@ scaled_vector_squared(Py_ssize_t n, double *vec, double max)
...
@@ -2071,9 +2083,11 @@ scaled_vector_squared(Py_ssize_t n, double *vec, double max)
}
}
assert
(
vec
[
n
-
1
]
==
max
);
assert
(
vec
[
n
-
1
]
==
max
);
csum
+=
1
.
0
-
frac
;
csum
+=
1
.
0
-
frac
;
return
csum
;
return
max
*
sqrt
(
csum
)
;
}
}
#define NUM_STACK_ELEMS 16
/*[clinic input]
/*[clinic input]
math.dist
math.dist
...
@@ -2095,11 +2109,12 @@ math_dist_impl(PyObject *module, PyObject *p, PyObject *q)
...
@@ -2095,11 +2109,12 @@ math_dist_impl(PyObject *module, PyObject *p, PyObject *q)
/*[clinic end generated code: output=56bd9538d06bbcfe input=937122eaa5f19272]*/
/*[clinic end generated code: output=56bd9538d06bbcfe input=937122eaa5f19272]*/
{
{
PyObject
*
item
;
PyObject
*
item
;
double
*
diffs
;
double
max
=
0
.
0
;
double
max
=
0
.
0
;
double
x
,
px
,
qx
,
result
;
double
x
,
px
,
qx
,
result
;
Py_ssize_t
i
,
m
,
n
;
Py_ssize_t
i
,
m
,
n
;
int
found_nan
=
0
;
int
found_nan
=
0
;
double
diffs_on_stack
[
NUM_STACK_ELEMS
];
double
*
diffs
=
diffs_on_stack
;
m
=
PyTuple_GET_SIZE
(
p
);
m
=
PyTuple_GET_SIZE
(
p
);
n
=
PyTuple_GET_SIZE
(
q
);
n
=
PyTuple_GET_SIZE
(
q
);
...
@@ -2109,22 +2124,22 @@ math_dist_impl(PyObject *module, PyObject *p, PyObject *q)
...
@@ -2109,22 +2124,22 @@ math_dist_impl(PyObject *module, PyObject *p, PyObject *q)
return
NULL
;
return
NULL
;
}
}
diffs
=
(
double
*
)
PyObject_Malloc
(
n
*
sizeof
(
double
));
if
(
n
>
NUM_STACK_ELEMS
)
{
if
(
diffs
==
NULL
)
{
diffs
=
(
double
*
)
PyObject_Malloc
(
n
*
sizeof
(
double
));
return
NULL
;
if
(
diffs
==
NULL
)
{
return
NULL
;
}
}
}
for
(
i
=
0
;
i
<
n
;
i
++
)
{
for
(
i
=
0
;
i
<
n
;
i
++
)
{
item
=
PyTuple_GET_ITEM
(
p
,
i
);
item
=
PyTuple_GET_ITEM
(
p
,
i
);
px
=
PyFloat_AsDouble
(
item
);
px
=
PyFloat_AsDouble
(
item
);
if
(
px
==
-
1
.
0
&&
PyErr_Occurred
())
{
if
(
px
==
-
1
.
0
&&
PyErr_Occurred
())
{
PyObject_Free
(
diffs
);
goto
error_exit
;
return
NULL
;
}
}
item
=
PyTuple_GET_ITEM
(
q
,
i
);
item
=
PyTuple_GET_ITEM
(
q
,
i
);
qx
=
PyFloat_AsDouble
(
item
);
qx
=
PyFloat_AsDouble
(
item
);
if
(
qx
==
-
1
.
0
&&
PyErr_Occurred
())
{
if
(
qx
==
-
1
.
0
&&
PyErr_Occurred
())
{
PyObject_Free
(
diffs
);
goto
error_exit
;
return
NULL
;
}
}
x
=
fabs
(
px
-
qx
);
x
=
fabs
(
px
-
qx
);
diffs
[
i
]
=
x
;
diffs
[
i
]
=
x
;
...
@@ -2133,19 +2148,17 @@ math_dist_impl(PyObject *module, PyObject *p, PyObject *q)
...
@@ -2133,19 +2148,17 @@ math_dist_impl(PyObject *module, PyObject *p, PyObject *q)
max
=
x
;
max
=
x
;
}
}
}
}
if
(
Py_IS_INFINITY
(
max
))
{
result
=
vector_norm
(
n
,
diffs
,
max
,
found_nan
);
result
=
max
;
if
(
diffs
!=
diffs_on_stack
)
{
goto
done
;
PyObject_Free
(
diffs
);
}
if
(
found_nan
)
{
result
=
Py_NAN
;
goto
done
;
}
}
result
=
max
*
sqrt
(
scaled_vector_squared
(
n
,
diffs
,
max
));
done:
PyObject_Free
(
diffs
);
return
PyFloat_FromDouble
(
result
);
return
PyFloat_FromDouble
(
result
);
error_exit:
if
(
diffs
!=
diffs_on_stack
)
{
PyObject_Free
(
diffs
);
}
return
NULL
;
}
}
/* AC: cannot convert yet, waiting for *args support */
/* AC: cannot convert yet, waiting for *args support */
...
@@ -2154,21 +2167,23 @@ math_hypot(PyObject *self, PyObject *args)
...
@@ -2154,21 +2167,23 @@ math_hypot(PyObject *self, PyObject *args)
{
{
Py_ssize_t
i
,
n
;
Py_ssize_t
i
,
n
;
PyObject
*
item
;
PyObject
*
item
;
double
*
coordinates
;
double
max
=
0
.
0
;
double
max
=
0
.
0
;
double
x
,
result
;
double
x
,
result
;
int
found_nan
=
0
;
int
found_nan
=
0
;
double
coord_on_stack
[
NUM_STACK_ELEMS
];
double
*
coordinates
=
coord_on_stack
;
n
=
PyTuple_GET_SIZE
(
args
);
n
=
PyTuple_GET_SIZE
(
args
);
coordinates
=
(
double
*
)
PyObject_Malloc
(
n
*
sizeof
(
double
));
if
(
n
>
NUM_STACK_ELEMS
)
{
if
(
coordinates
==
NULL
)
coordinates
=
(
double
*
)
PyObject_Malloc
(
n
*
sizeof
(
double
));
return
NULL
;
if
(
coordinates
==
NULL
)
return
NULL
;
}
for
(
i
=
0
;
i
<
n
;
i
++
)
{
for
(
i
=
0
;
i
<
n
;
i
++
)
{
item
=
PyTuple_GET_ITEM
(
args
,
i
);
item
=
PyTuple_GET_ITEM
(
args
,
i
);
x
=
PyFloat_AsDouble
(
item
);
x
=
PyFloat_AsDouble
(
item
);
if
(
x
==
-
1
.
0
&&
PyErr_Occurred
())
{
if
(
x
==
-
1
.
0
&&
PyErr_Occurred
())
{
PyObject_Free
(
coordinates
);
goto
error_exit
;
return
NULL
;
}
}
x
=
fabs
(
x
);
x
=
fabs
(
x
);
coordinates
[
i
]
=
x
;
coordinates
[
i
]
=
x
;
...
@@ -2177,21 +2192,21 @@ math_hypot(PyObject *self, PyObject *args)
...
@@ -2177,21 +2192,21 @@ math_hypot(PyObject *self, PyObject *args)
max
=
x
;
max
=
x
;
}
}
}
}
if
(
Py_IS_INFINITY
(
max
))
{
result
=
vector_norm
(
n
,
coordinates
,
max
,
found_nan
);
result
=
max
;
if
(
coordinates
!=
coord_on_stack
)
{
goto
done
;
PyObject_Free
(
coordinates
)
;
}
}
if
(
found_nan
)
{
result
=
Py_NAN
;
goto
done
;
}
result
=
max
*
sqrt
(
scaled_vector_squared
(
n
,
coordinates
,
max
));
done:
PyObject_Free
(
coordinates
);
return
PyFloat_FromDouble
(
result
);
return
PyFloat_FromDouble
(
result
);
error_exit:
if
(
coordinates
!=
coord_on_stack
)
{
PyObject_Free
(
coordinates
);
}
return
NULL
;
}
}
#undef NUM_STACK_ELEMS
PyDoc_STRVAR
(
math_hypot_doc
,
PyDoc_STRVAR
(
math_hypot_doc
,
"hypot(*coordinates) -> value
\n\n
\
"hypot(*coordinates) -> value
\n\n
\
Multidimensional Euclidean distance from the origin to a point.
\n
\
Multidimensional Euclidean distance from the origin to a point.
\n
\
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment