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September 3, 2023 15:09
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Simple Theil-Sen estimator example
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| #pragma once | |
| template<int Limit, std::floating_point ValueType, std::ranges::sized_range Range, ValueType Epsilon = std::numeric_limits<ValueType>::epsilon() * Limit> | |
| requires std::convertible_to<std::ranges::range_value_t<Range>, std::pair<ValueType, ValueType>> | |
| auto theil_sen_slope(Range value_pairs) { | |
| if (value_pairs.size() <= 1) { | |
| return ValueType{0}; | |
| } | |
| std::vector<std::pair<ValueType, ValueType>> sample_holder; | |
| Range sample_range = value_pairs; | |
| if (sample_range.size() > Limit) { | |
| sample_holder.reserve(Limit); | |
| std::ranges::sample(value_pairs, std::back_inserter(sample_holder), Limit, g_gen); | |
| sample_range = sample_holder; | |
| } | |
| std::vector<ValueType> slopes; | |
| slopes.reserve(sample_range.size() * value_pairs.size()); | |
| for (auto const& sample : sample_range) { | |
| for (auto const& pair : value_pairs) { | |
| auto [x1, y1] = sample; | |
| auto [x2, y2] = pair; | |
| ValueType den = x1 - x2; | |
| if (std::abs(den) > Epsilon) { | |
| slopes.emplace_back((y1 - y2) / den); | |
| } | |
| } | |
| } | |
| if (slopes.empty()) { | |
| return ValueType{0}; | |
| } | |
| // Median | |
| std::nth_element(slopes.begin(), slopes.begin() + slopes.size() / 2, slopes.end()); | |
| return slopes[slopes.size() / 2]; | |
| } |
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