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Speedup the reduce method of the maximum minimum family of ufuncs. #18

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Speedup the reduce method of the maximum minimum family of ufuncs. #18

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ded8267
ENH: Speed up reduce for maximum/minimum type ufuncs.
charris Nov 20, 2010
be7e38c
ENH: Add tests for reduce method of maximum, minimum, fmax and fmin.
charris Nov 21, 2010
6535b0c
BUG: Use isnan to test for nan, avoids problems with signed nans.
charris Nov 21, 2010
f4aec4b
ENH: Use fmax.reduce and fmin.reduce to implement nanmax and nanmin.
charris Nov 21, 2010
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62 changes: 49 additions & 13 deletions numpy/core/src/umath/loops.c.src
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Original file line number Diff line number Diff line change
Expand Up @@ -683,10 +683,19 @@ NPY_NO_EXPORT void
NPY_NO_EXPORT void
@S@@TYPE@_@kind@(char **args, intp *dimensions, intp *steps, void *NPY_UNUSED(func))
{
BINARY_LOOP {
const @s@@type@ in1 = *(@s@@type@ *)ip1;
const @s@@type@ in2 = *(@s@@type@ *)ip2;
*((@s@@type@ *)op1) = (in1 @OP@ in2) ? in1 : in2;
if (IS_BINARY_REDUCE) {
BINARY_REDUCE_LOOP(@s@@type@) {
const @s@@type@ in2 = *(@type@ *)ip2;
io1 = (io1 @OP@ in2) ? io1 : in2;
}
*((@s@@type@ *)iop1) = io1;
}
else {
BINARY_LOOP {
const @s@@type@ in1 = *(@s@@type@ *)ip1;
const @s@@type@ in2 = *(@s@@type@ *)ip2;
*((@s@@type@ *)op1) = (in1 @OP@ in2) ? in1 : in2;
}
}
}
/**end repeat2**/
Expand Down Expand Up @@ -921,11 +930,20 @@ NPY_NO_EXPORT void
NPY_NO_EXPORT void
@TYPE@_@kind@(char **args, intp *dimensions, intp *steps, void *NPY_UNUSED(func))
{
if (IS_BINARY_REDUCE) {
BINARY_REDUCE_LOOP(@type@) {
const @type@ in2 = *(@type@ *)ip2;
io1 = (io1 @OP@ in2) ? io1 : in2;
}
*((@type@ *)iop1) = io1;
}
else {
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
*((@type@ *)op1) = (in1 @OP@ in2) ? in1 : in2;
}
}
}
/**end repeat1**/

Expand All @@ -949,7 +967,7 @@ NPY_NO_EXPORT void

/**end repeat**/

/* FIXME: implement the following correctly using the metadata: data is the
/* FIXME: implement the following correctly using the metadata: data is the
sequence of ndarrays in the same order as args.
*/
NPY_NO_EXPORT void
Expand Down Expand Up @@ -1141,10 +1159,19 @@ NPY_NO_EXPORT void
@TYPE@_@kind@(char **args, intp *dimensions, intp *steps, void *NPY_UNUSED(func))
{
/* */
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
*((@type@ *)op1) = (in1 @OP@ in2 || npy_isnan(in1)) ? in1 : in2;
if (IS_BINARY_REDUCE) {
BINARY_REDUCE_LOOP(@type@) {
const @type@ in2 = *(@type@ *)ip2;
io1 = (io1 @OP@ in2 || npy_isnan(io1)) ? io1 : in2;
}
*((@type@ *)iop1) = io1;
}
else {
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
*((@type@ *)op1) = (in1 @OP@ in2 || npy_isnan(in1)) ? in1 : in2;
}
}
}
/**end repeat1**/
Expand All @@ -1157,10 +1184,19 @@ NPY_NO_EXPORT void
@TYPE@_@kind@(char **args, intp *dimensions, intp *steps, void *NPY_UNUSED(func))
{
/* */
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
*((@type@ *)op1) = (in1 @OP@ in2 || npy_isnan(in2)) ? in1 : in2;
if (IS_BINARY_REDUCE) {
BINARY_REDUCE_LOOP(@type@) {
const @type@ in2 = *(@type@ *)ip2;
io1 = (io1 @OP@ in2 || npy_isnan(in2)) ? io1 : in2;
}
*((@type@ *)iop1) = io1;
}
else {
BINARY_LOOP {
const @type@ in1 = *(@type@ *)ip1;
const @type@ in2 = *(@type@ *)ip2;
*((@type@ *)op1) = (in1 @OP@ in2 || npy_isnan(in2)) ? in1 : in2;
}
}
}
/**end repeat1**/
Expand Down
84 changes: 84 additions & 0 deletions numpy/core/tests/test_umath.py
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Original file line number Diff line number Diff line change
Expand Up @@ -413,6 +413,27 @@ def test_ldexp_overflow(self):


class TestMaximum(TestCase):
def test_reduce(self):
dflt = np.typecodes['AllFloat']
dint = np.typecodes['AllInteger']
seq1 = np.arange(11)
seq2 = seq1[::-1]
func = np.maximum.reduce
for dt in dint:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 10)
assert_equal(func(tmp2), 10)
for dt in dflt:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 10)
assert_equal(func(tmp2), 10)
tmp1[::2] = np.nan
tmp2[::2] = np.nan
assert_equal(func(tmp1), np.nan)
assert_equal(func(tmp2), np.nan)

def test_reduce_complex(self):
assert_equal(np.maximum.reduce([1,2j]),1)
assert_equal(np.maximum.reduce([1+3j,2j]),1+3j)
Expand All @@ -434,6 +455,27 @@ def test_complex_nans(self):


class TestMinimum(TestCase):
def test_reduce(self):
dflt = np.typecodes['AllFloat']
dint = np.typecodes['AllInteger']
seq1 = np.arange(11)
seq2 = seq1[::-1]
func = np.minimum.reduce
for dt in dint:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 0)
assert_equal(func(tmp2), 0)
for dt in dflt:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 0)
assert_equal(func(tmp2), 0)
tmp1[::2] = np.nan
tmp2[::2] = np.nan
assert_equal(func(tmp1), np.nan)
assert_equal(func(tmp2), np.nan)

def test_reduce_complex(self):
assert_equal(np.minimum.reduce([1,2j]),2j)
assert_equal(np.minimum.reduce([1+3j,2j]),2j)
Expand All @@ -455,6 +497,27 @@ def test_complex_nans(self):


class TestFmax(TestCase):
def test_reduce(self):
dflt = np.typecodes['AllFloat']
dint = np.typecodes['AllInteger']
seq1 = np.arange(11)
seq2 = seq1[::-1]
func = np.fmax.reduce
for dt in dint:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 10)
assert_equal(func(tmp2), 10)
for dt in dflt:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 10)
assert_equal(func(tmp2), 10)
tmp1[::2] = np.nan
tmp2[::2] = np.nan
assert_equal(func(tmp1), 9)
assert_equal(func(tmp2), 9)

def test_reduce_complex(self):
assert_equal(np.fmax.reduce([1,2j]),1)
assert_equal(np.fmax.reduce([1+3j,2j]),1+3j)
Expand All @@ -476,6 +539,27 @@ def test_complex_nans(self):


class TestFmin(TestCase):
def test_reduce(self):
dflt = np.typecodes['AllFloat']
dint = np.typecodes['AllInteger']
seq1 = np.arange(11)
seq2 = seq1[::-1]
func = np.fmin.reduce
for dt in dint:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 0)
assert_equal(func(tmp2), 0)
for dt in dflt:
tmp1 = seq1.astype(dt)
tmp2 = seq2.astype(dt)
assert_equal(func(tmp1), 0)
assert_equal(func(tmp2), 0)
tmp1[::2] = np.nan
tmp2[::2] = np.nan
assert_equal(func(tmp1), 1)
assert_equal(func(tmp2), 1)

def test_reduce_complex(self):
assert_equal(np.fmin.reduce([1,2j]),2j)
assert_equal(np.fmin.reduce([1+3j,2j]),2j)
Expand Down
20 changes: 14 additions & 6 deletions numpy/lib/function_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1447,8 +1447,7 @@ def nanmin(a, axis=None):
Positive infinity is treated as a very large number and negative infinity
is treated as a very small (i.e. negative) number.

If the input has a integer type, an integer type is returned unless
the input contains NaNs and infinity.
If the input has a integer type the function is equivalent to np.min.


Examples
Expand All @@ -1469,7 +1468,12 @@ def nanmin(a, axis=None):
-inf

"""
return _nanop(np.min, np.inf, a, axis)
#return _nanop(np.min, np.inf, a, axis)
a = np.asanyarray(a)
if axis is not None:
return np.fmin.reduce(a, axis)
else:
return np.fmin.reduce(a.flat)

def nanargmin(a, axis=None):
"""
Expand Down Expand Up @@ -1541,8 +1545,7 @@ def nanmax(a, axis=None):
Positive infinity is treated as a very large number and negative infinity
is treated as a very small (i.e. negative) number.

If the input has a integer type, an integer type is returned unless
the input contains NaNs and infinity.
If the input has a integer type the function is equivalent to np.max.

Examples
--------
Expand All @@ -1562,7 +1565,12 @@ def nanmax(a, axis=None):
inf

"""
return _nanop(np.max, -np.inf, a, axis)
#return _nanop(np.max, -np.inf, a, axis)
a = np.asanyarray(a)
if axis is not None:
return np.fmax.reduce(a, axis)
else:
return np.fmax.reduce(a.flat)

def nanargmax(a, axis=None):
"""
Expand Down
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