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AK: Use AK:quickselect_inline
to compute AK::Statistics::median
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`
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parent
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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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@ -8,7 +8,7 @@
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#include <AK/Concepts.h>
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#include <AK/Math.h>
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#include <AK/QuickSort.h>
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#include <AK/QuickSelect.h>
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#include <AK/Vector.h>
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namespace AK {
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@ -27,10 +27,24 @@ public:
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}
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T const sum() const { return m_sum; }
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float average() const { return (float)sum() / size(); }
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// FIXME: Unclear Wording, average can mean a lot of different things
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// Median, Arithmetic Mean (which this is), Geometric Mean, Harmonic Mean etc
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float average() const
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{
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// Let's assume the average of an empty dataset is 0
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if (size() == 0)
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return 0;
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// TODO: sum might overflow so maybe do multiple partial sums and intermediate divisions here
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return (float)sum() / size();
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}
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T const min() const
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{
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// Lets Rather fail than read over the end of a collection
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VERIFY(size() != 0);
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T minimum = m_values[0];
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for (T number : values()) {
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if (number < minimum) {
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@ -42,6 +56,9 @@ public:
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T const max() const
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{
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// Lets Rather fail than read over the end of a collection
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VERIFY(size() != 0);
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T maximum = m_values[0];
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for (T number : values()) {
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if (number > maximum) {
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@ -51,16 +68,20 @@ public:
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return maximum;
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}
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// FIXME: Implement a better algorithm
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T const median()
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{
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quick_sort(m_values);
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// Let's assume the Median of an empty dataset is 0
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if (size() == 0)
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return 0;
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// If the number of values is even, the median is the arithmetic mean of the two middle values
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if (size() % 2 == 0) {
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auto index = size() / 2;
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return (m_values.at(index) + m_values.at(index + 1)) / 2;
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auto median1 = m_values.at(AK::quickselect_inplace(m_values, index));
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auto median2 = m_values.at(AK::quickselect_inplace(m_values, index - 1));
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return (median1 + median2) / 2;
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}
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return m_values.at(size() / 2);
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return m_values.at(AK::quickselect_inplace(m_values, size() / 2));
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}
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float standard_deviation() const { return sqrt(variance()); }
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