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commit b403a4723aad78eed6b0e9484576e1540689f0f9
Author: aherbert <aherb...@apache.org>
AuthorDate: Tue Feb 21 15:05:32 2023 +0000
Repeated timings with final implementation
This reflects an update from timings obtained using the simple pow
(previously named fastPow) and the compensated pow implementation (named
pow), to a compensated pow (fastPow) and triple-double pow
implementation, i.e. timings have changed as:
simplePow -> fastPow
fastPow -> pow
---
.../KolmogorovSmirnovDistributionTest.java | 92 +++++++++++-----------
1 file changed, 45 insertions(+), 47 deletions(-)
diff --git
a/commons-statistics-inference/src/test/java/org/apache/commons/statistics/inference/KolmogorovSmirnovDistributionTest.java
b/commons-statistics-inference/src/test/java/org/apache/commons/statistics/inference/KolmogorovSmirnovDistributionTest.java
index 3d517f2..7ccb31c 100644
---
a/commons-statistics-inference/src/test/java/org/apache/commons/statistics/inference/KolmogorovSmirnovDistributionTest.java
+++
b/commons-statistics-inference/src/test/java/org/apache/commons/statistics/inference/KolmogorovSmirnovDistributionTest.java
@@ -427,31 +427,30 @@ class KolmogorovSmirnovDistributionTest {
"4e-3, 1000001, 1.2630034559846114e-14, 2e-16", // Requires 6.0*n*x
not 6.0*(n*x)
"7e-3, 1000001, 2.7357189636541477e-43, 2e-16",
"1e-2, 1000001, 1.374426245809477e-87, 2e-16",
- // XXX repeat timings
// Computed using the double-double implementation (fastPowScaled,
with timings)
- "1.0E-4, 1000001, 0.9801333136251243, 6e-8", // 0.634074s
- "0.001, 1000001, 0.13524481927494492, 6e-8", // 0.504505s
- "0.0015, 1000001, 0.011097829274951359, 2e-6", // 0.527094s
- "0.00175, 1000001, 0.0021849210146805925, 3e-6", // 0.512000s
- "0.002, 1000001, 3.3501117508103243E-4, 6e-6", // 0.505427s
- "0.0025, 1000001, 3.720346483702557E-6, 2e-5", // 0.488436s
- "0.003, 1000001, 1.519879017846374E-8, 4e-5", // 0.464440s
- "0.0035, 1000001, 2.2842024589556203E-11, 7e-5", // 0.457859s
- "0.004, 1000001, 1.2628687945778359E-14, 2e-4", // 0.440603s
- "0.007, 1000001, 2.7328605923747603E-43, 2e-3", // 0.383890s
- "0.01, 1000001, 1.3683915090193192E-87, 5e-3", // 0.348474s
+ "1.0E-4, 1000001, 0.9801333136251243, 6e-8", // 0.724783s
+ "0.001, 1000001, 0.13524481927494492, 6e-8", // 0.709156s
+ "0.0015, 1000001, 0.011097829274951359, 2e-6", // 0.699217s
+ "0.00175, 1000001, 0.0021849210146805925, 3e-6", // 0.696271s
+ "0.002, 1000001, 3.3501117508103243E-4, 6e-6", // 0.679680s
+ "0.0025, 1000001, 3.720346483702557E-6, 2e-5", // 0.658114s
+ "0.003, 1000001, 1.519879017846374E-8, 4e-5", // 0.640645s
+ "0.0035, 1000001, 2.2842024589556203E-11, 7e-5", // 0.629275s
+ "0.004, 1000001, 1.2628687945778359E-14, 2e-4", // 0.613186s
+ "0.007, 1000001, 2.7328605923747603E-43, 2e-3", // 0.534130s
+ "0.01, 1000001, 1.3683915090193192E-87, 5e-3", // 0.487097s
// Computed using the double-double implementation (powScaled, with
timings)
- "1.0E-4, 1000001, 0.9801333136251243, 6e-8", // 0.736033s
- "0.001, 1000001, 0.13524481927494492, 6e-8", // 0.629389s
- "0.0015, 1000001, 0.011097829274951359, 2e-6", // 0.596412s
- "0.00175, 1000001, 0.0021849210146805925, 3e-6", // 0.591704s
- "0.002, 1000001, 3.350111750810325E-4, 6e-6", // 0.583618s
- "0.0025, 1000001, 3.720346483702557E-6, 2e-5", // 0.573333s
- "0.003, 1000001, 1.519879017846374E-8, 4e-5", // 0.554925s
- "0.0035, 1000001, 2.2842024589556203E-11, 7e-5", // 0.532223s
- "0.004, 1000001, 1.2628687945778359E-14, 2e-4", // 0.529170s
- "0.007, 1000001, 2.7328605923747603E-43, 2e-3", // 0.458782s
- "0.01, 1000001, 1.3683915090193192E-87, 5e-3", // 0.416742s
+ "1.0E-4, 1000001, 0.9801333136251243, 6e-8", // 2.119189s
+ "0.001, 1000001, 0.13524481927494492, 6e-8", // 1.933861s
+ "0.0015, 1000001, 0.011097829274951359, 2e-6", // 1.914388s
+ "0.00175, 1000001, 0.0021849210146805925, 3e-6", // 1.876002s
+ "0.002, 1000001, 3.350111750810325E-4, 6e-6", // 1.811108s
+ "0.0025, 1000001, 3.720346483702557E-6, 2e-5", // 1.781407s
+ "0.003, 1000001, 1.519879017846374E-8, 4e-5", // 1.739311s
+ "0.0035, 1000001, 2.2842024589556203E-11, 7e-5", // 1.697893s
+ "0.004, 1000001, 1.2628687945778359E-14, 2e-4", // 1.659005s
+ "0.007, 1000001, 2.7328605923747603E-43, 2e-3", // 1.452124s
+ "0.01, 1000001, 1.3683915090193192E-87, 5e-3", // 1.338291s
// n = 10^7
// Computed using: numpy.exp(-pow(6.0*n*x+1.0, 2)/(18.0*n)):
"1e-6, 10000000, 0.9999793279914467, 2e-16",
@@ -460,17 +459,17 @@ class KolmogorovSmirnovDistributionTest {
"8e-4, 10000000, 2.7593005372427517e-06, 2e-16",
"1e-3, 10000000, 2.059779966512744e-09, 2e-16",
// Computed using the double-double implementation (fastPowScaled,
with timings)
- "1.0E-6, 10000000, 0.9999793335473409, 1e-8", // 5.499433s
- "2.0E-6, 10000000, 0.9999186699759279, 1e-8", // 5.536423s
- "2.0E-4, 10000000, 0.4492690623747514, 2e-8", // 5.431289s
- "8.0E-4, 10000000, 2.7592963140010787E-6, 2e-6", // 4.979058s
- "0.001, 10000000, 2.059771738419037E-9, 5e-6", // 4.947680s
+ "1.0E-6, 10000000, 0.9999793335473409, 1e-8", // 8.119499s
+ "2.0E-6, 10000000, 0.9999186699759279, 1e-8", // 8.073493s
+ "2.0E-4, 10000000, 0.4492690623747514, 2e-8", // 8.014497s
+ "8.0E-4, 10000000, 2.7592963140010787E-6, 2e-6", // 7.610442s
+ "0.001, 10000000, 2.059771738419037E-9, 5e-6", // 7.383041s
// Computed using the double-double implementation (powScaled, with
timings)
- "1.0E-6, 10000000, 0.9999793335473409, 1e-8", // 6.965408s
- "2.0E-6, 10000000, 0.9999186699759279, 1e-8", // 6.737508s
- "2.0E-4, 10000000, 0.4492690623747514, 2e-8", // 6.905447s
- "8.0E-4, 10000000, 2.7592963140010787E-6, 2e-6", // 6.539566s
- "0.001, 10000000, 2.059771738419037E-9, 5e-6", // 6.196324s
+ "1.0E-6, 10000000, 0.9999793335473409, 1e-8", // 22.379404s
+ "2.0E-6, 10000000, 0.9999186699759279, 1e-8", // 22.142838s
+ "2.0E-4, 10000000, 0.4492690623747514, 2e-8", // 22.130956s
+ "8.0E-4, 10000000, 2.7592963140010787E-6, 2e-6", // 20.772157s
+ "0.001, 10000000, 2.059771738419037E-9, 5e-6", // 20.374969s
// n = 2^30
// Using scipy ksone.sf found an intermediate overflow bug in v1.9.3:
// https://github.com/scipy/scipy/issues/17775
@@ -482,12 +481,12 @@ class KolmogorovSmirnovDistributionTest {
"3e-4, 1073741824, 1.1542138829781214e-84, 2e-16",
"5e-4, 1073741824, 6.914816492890092e-234, 2e-16",
// Computed using the double-double implementation (fastPowScaled,
with timings)
- "1.0E-6, 1073741824, 0.9978541553094259, 6e-11", // 798.105071s
- "1.0E-5, 1073741824, 0.8067390416850888, 1e-10", // 799.473844s
- "1.0E-4, 1073741824, 4.715937547939537E-10, 5e-8", // 711.366173s
- "2.0E-4, 1073741824, 4.946862487288552E-38, 8e-7", // 608.890882s
- "3.0E-4, 1073741824, 1.154209467628123E-84, 4e-6", // 552.846079s
- "5.0E-4, 1073741824, 6.914611021963401E-234, 3e-5", // 481.010631s
+ "1.0E-6, 1073741824, 0.9978541553094261, 6e-11", // 1067.231777s
+ "1.0E-5, 1073741824, 0.806739041685089, 1e-10", // 1066.338235s
+ "1.0E-4, 1073741824, 4.715937547939542E-10, 5e-8", // 974.019864s
+ "2.0E-4, 1073741824, 4.946862487288558E-38, 8e-7", // 841.211851s
+ "3.0E-4, 1073741824, 1.1542094676281237E-84, 4e-6", // 761.320554s
+ "5.0E-4, 1073741824, 6.914611021963405E-234, 3e-5", // 681.080892s
})
void testOneSFAsymptotic(double x, int n, double p, double eps) {
final double p1 = KolmogorovSmirnovDistribution.One.sf(x, n);
@@ -576,13 +575,12 @@ class KolmogorovSmirnovDistributionTest {
"8e-3, 123456, 1.3636949699766825e-07, 2e-16",
"3e-2, 123456, 2.9034013257947777e-97, 2e-16",
// Close to the asymptotic limit (1e6).
- // XXX repeat timings
// Timings for the fastPowScaled.
- "1e-6, 999000, 0.9999972844391667, 2e-16", // 0.000033s
- "1e-5, 999000, 0.9997935546914299, 2e-15", // 0.586500s
- "1e-3, 999000, 0.13551585067528177, 2e-15", // 0.526206s
- "1.5e-3, 999000, 0.011147932231639623, 2e-15", // 0.510105s
- "1e-2, 999000, 1.671698905805492e-87, 2e-15", // 0.358407s
+ "1e-6, 999000, 0.9999972844391667, 2e-16", // 0.000114s
+ "1e-5, 999000, 0.9997935546914299, 2e-15", // 0.701445s
+ "1e-3, 999000, 0.13551585067528177, 2e-15", // 0.684693s
+ "1.5e-3, 999000, 0.011147932231639623, 2e-15", // 0.680678s
+ "1e-2, 999000, 1.671698905805492e-87, 2e-15", // 0.485230s
// Test cases requiring careful computation of
// k = floor(n*x), alpha = nx - k; x = (k+alpha)/n with 0 <= alpha < 1
// 0.8e-5 * 5e5 = 4.0, actually 3.99999999999999897195950...
@@ -1010,7 +1008,7 @@ class KolmogorovSmirnovDistributionTest {
// Debugging
final long start = System.nanoTime();
final double p = KolmogorovSmirnovDistribution.One.sf(x, n, power);
- //printf("\"%s, %d, %s\", // %.6fs%n", x, n, p, (System.nanoTime() -
start) * 1e-9);
+ //TestUtils.printf("\"%s, %d, %s\", // %.6fs%n", x, n, p,
(System.nanoTime() - start) * 1e-9);
return p;
}
@@ -1045,7 +1043,7 @@ class KolmogorovSmirnovDistributionTest {
// Debugging
final long start = System.nanoTime();
final double p = sf(x, n, mc);
- //printf("\"%s, %d, %s\", // %.6fs%n", x, n, p, (System.nanoTime() -
start) * 1e-9);
+ //TestUtils.printf("\"%s, %d, %s\", // %.6fs%n", x, n, p,
(System.nanoTime() - start) * 1e-9);
return p;
}
