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AK: Use AK:quickselect_inline to compute AK::Statistics::median

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Quick select is an algorithm that is able to find the median
of a Vector without fully sorting it.
This replaces the old very naive implementation
for `AK::Statistics::median()` with `AK::quickselect_inline`
This commit is contained in:
Staubfinger 2023-01-08 14:44:59 +01:00 committed by Jelle Raaijmakers
parent becd6d106f
commit 6b9344e86c
Notes: sideshowbarker 2024-07-17 00:50:01 +09:00 
Author: https://github.com/Popaulol
Commit: https://github.com/SerenityOS/serenity/commit/6b9344e86c
Pull-request: https://github.com/SerenityOS/serenity/pull/16906
Reviewed-by: https://github.com/BenWiederhake
1 changed files with 27 additions and 6 deletions
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33
AK/Statistics.h
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@ -8,7 +8,7 @@
#include <AK/Concepts.h>
#include <AK/Math.h>
#include <AK/QuickSort.h>
#include <AK/QuickSelect.h>
#include <AK/Vector.h>
namespace AK {
@ -27,10 +27,24 @@ public:
}
T const sum() const { return m_sum; }
float average() const { return (float)sum() / size(); }
// FIXME: Unclear Wording, average can mean a lot of different things
// Median, Arithmetic Mean (which this is), Geometric Mean, Harmonic Mean etc
float average() const
{
// Let's assume the average of an empty dataset is 0
if (size() == 0)
return 0;
// TODO: sum might overflow so maybe do multiple partial sums and intermediate divisions here
return (float)sum() / size();
}
T const min() const
{
// Lets Rather fail than read over the end of a collection
VERIFY(size() != 0);
T minimum = m_values[0];
for (T number : values()) {
if (number < minimum) {
@ -42,6 +56,9 @@ public:
T const max() const
{
// Lets Rather fail than read over the end of a collection
VERIFY(size() != 0);
T maximum = m_values[0];
for (T number : values()) {
if (number > maximum) {
@ -51,16 +68,20 @@ public:
return maximum;
}
// FIXME: Implement a better algorithm
T const median()
{
quick_sort(m_values);
// Let's assume the Median of an empty dataset is 0
if (size() == 0)
return 0;
// If the number of values is even, the median is the arithmetic mean of the two middle values
if (size() % 2 == 0) {
auto index = size() / 2;
return (m_values.at(index) + m_values.at(index + 1)) / 2;
auto median1 = m_values.at(AK::quickselect_inplace(m_values, index));
auto median2 = m_values.at(AK::quickselect_inplace(m_values, index - 1));
return (median1 + median2) / 2;
}
return m_values.at(size() / 2);
return m_values.at(AK::quickselect_inplace(m_values, size() / 2));
}
float standard_deviation() const { return sqrt(variance()); }