Initial commit

2024-01-07 16:48:27 +01:00
parent 0b735a14c4
commit 6245df407a
26 changed files with 2942 additions and 0 deletions
--- a/folding.hpp
+++ b/folding.hpp
@@ -0,0 +1,138 @@
+#pragma once
+#include <torch/torch.h>
+#include <algorithm>
+#include <map>
+#include <random> 
+#include <vector>
+namespace folding {
+    class Fold {
+    protected:
+        int k;
+        int n;
+        int seed;
+        std::default_random_engine random_seed;
+    public:
+        Fold(int k, int n, int seed = -1);
+        virtual std::pair<std::vector<int>, std::vector<int>> getFold(int nFold) = 0;
+        virtual ~Fold() = default;
+        int getNumberOfFolds() { return k; }
+    };
+    class KFold : public Fold {
+    private:
+        std::vector<int> indices;
+    public:
+        KFold(int k, int n, int seed = -1);
+        std::pair<std::vector<int>, std::vector<int>> getFold(int nFold) override;
+    };
+    class StratifiedKFold : public Fold {
+    private:
+        std::vector<int> y;
+        std::vector<std::vector<int>> stratified_indices;
+        void build();
+        bool faulty = false; // Only true if the number of samples of any class is less than the number of folds.
+    public:
+        StratifiedKFold(int k, const std::vector<int>& y, int seed = -1);
+        StratifiedKFold(int k, torch::Tensor& y, int seed = -1);
+        std::pair<std::vector<int>, std::vector<int>> getFold(int nFold) override;
+        bool isFaulty() { return faulty; }
+    };
+    Fold::Fold(int k, int n, int seed) : k(k), n(n), seed(seed)
+    {
+        std::random_device rd;
+        random_seed = std::default_random_engine(seed == -1 ? rd() : seed);
+        std::srand(seed == -1 ? time(0) : seed);
+    }
+    KFold::KFold(int k, int n, int seed) : Fold(k, n, seed), indices(std::vector<int>(n))
+    {
+        std::iota(begin(indices), end(indices), 0); // fill with 0, 1, ..., n - 1
+        shuffle(indices.begin(), indices.end(), random_seed);
+    }
+    std::pair<std::vector<int>, std::vector<int>> KFold::getFold(int nFold)
+    {
+        if (nFold >= k || nFold < 0) {
+            throw std::out_of_range("nFold (" + std::to_string(nFold) + ") must be less than k (" + std::to_string(k) + ")");
+        }
+        int nTest = n / k;
+        auto train = std::vector<int>();
+        auto test = std::vector<int>();
+        for (int i = 0; i < n; i++) {
+            if (i >= nTest * nFold && i < nTest * (nFold + 1)) {
+                test.push_back(indices[i]);
+            } else {
+                train.push_back(indices[i]);
+            }
+        }
+        return { train, test };
+    }
+    StratifiedKFold::StratifiedKFold(int k, torch::Tensor& y, int seed) : Fold(k, y.numel(), seed)
+    {
+        n = y.numel();
+        this->y = std::vector<int>(y.data_ptr<int>(), y.data_ptr<int>() + n);
+        build();
+    }
+    StratifiedKFold::StratifiedKFold(int k, const std::vector<int>& y, int seed)
+        : Fold(k, y.size(), seed)
+    {
+        this->y = y;
+        n = y.size();
+        build();
+    }
+    void StratifiedKFold::build()
+    {
+        stratified_indices = std::vector<std::vector<int>>(k);
+        int fold_size = n / k;
+
+        // Compute class counts and indices
+        auto class_indices = std::map<int, std::vector<int>>();
+        std::vector<int> class_counts(*max_element(y.begin(), y.end()) + 1, 0);
+        for (auto i = 0; i < n; ++i) {
+            class_counts[y[i]]++;
+            class_indices[y[i]].push_back(i);
+        }
+        // Shuffle class indices
+        for (auto& [cls, indices] : class_indices) {
+            shuffle(indices.begin(), indices.end(), random_seed);
+        }
+        // Assign indices to folds
+        for (auto label = 0; label < class_counts.size(); ++label) {
+            auto num_samples_to_take = class_counts.at(label) / k;
+            if (num_samples_to_take == 0) {
+                std::cerr << "Warning! The number of samples in class " << label << " (" << class_counts.at(label)
+                    << ") is less than the number of folds (" << k << ")." << std::endl;
+                faulty = true;
+                continue;
+            }
+            auto remainder_samples_to_take = class_counts[label] % k;
+            for (auto fold = 0; fold < k; ++fold) {
+                auto it = next(class_indices[label].begin(), num_samples_to_take);
+                move(class_indices[label].begin(), it, back_inserter(stratified_indices[fold]));  // ##
+                class_indices[label].erase(class_indices[label].begin(), it);
+            }
+            auto chosen = std::vector<bool>(k, false);
+            while (remainder_samples_to_take > 0) {
+                int fold = (rand() % static_cast<int>(k));
+                if (chosen.at(fold)) {
+                    continue;
+                }
+                chosen[fold] = true;
+                auto it = next(class_indices[label].begin(), 1);
+                stratified_indices[fold].push_back(*class_indices[label].begin());
+                class_indices[label].erase(class_indices[label].begin(), it);
+                remainder_samples_to_take--;
+            }
+        }
+    }
+    std::pair<std::vector<int>, std::vector<int>> StratifiedKFold::getFold(int nFold)
+    {
+        if (nFold >= k || nFold < 0) {
+            throw std::out_of_range("nFold (" + std::to_string(nFold) + ") must be less than k (" + std::to_string(k) + ")");
+        }
+        std::vector<int> test_indices = stratified_indices[nFold];
+        std::vector<int> train_indices;
+        for (int i = 0; i < k; ++i) {
+            if (i == nFold) continue;
+            train_indices.insert(train_indices.end(), stratified_indices[i].begin(), stratified_indices[i].end());
+        }
+        return { train_indices, test_indices };
+    }
+}