mirror of
https://github.com/rmontanana/mdlp.git
synced 2025-08-20 18:06:00 +00:00
102 lines
3.5 KiB
C++
102 lines
3.5 KiB
C++
#include <iostream>
|
|
#include <algorithm>
|
|
#include <cmath>
|
|
#include <vector>
|
|
#include <string>
|
|
|
|
typedef float precision_t;
|
|
|
|
std::vector<int> transform(const std::vector<float> cutPoints, const std::vector<float>& data)
|
|
{
|
|
std::vector<int> discretizedData;
|
|
discretizedData.reserve(data.size());
|
|
for (const float& item : data) {
|
|
auto upper = std::lower_bound(cutPoints.begin(), cutPoints.end(), item);
|
|
discretizedData.push_back(upper - cutPoints.begin());
|
|
}
|
|
return discretizedData;
|
|
}
|
|
template <typename T>
|
|
void show_vector(const std::vector<T>& data, std::string title)
|
|
{
|
|
std::cout << title << ": ";
|
|
std::string sep = "";
|
|
for (const auto& d : data) {
|
|
std::cout << sep << d;
|
|
sep = ", ";
|
|
}
|
|
std::cout << std::endl;
|
|
}
|
|
std::vector<precision_t> linspace(precision_t start, precision_t end, int num)
|
|
{
|
|
if (start == end) {
|
|
return { start, end };
|
|
}
|
|
precision_t delta = (end - start) / static_cast<precision_t>(num - 1);
|
|
std::vector<precision_t> linspc;
|
|
for (size_t i = 0; i < num - 1; ++i) {
|
|
precision_t val = start + delta * static_cast<precision_t>(i);
|
|
linspc.push_back(val);
|
|
}
|
|
return linspc;
|
|
}
|
|
size_t clip(const size_t n, size_t lower, size_t upper)
|
|
{
|
|
return std::max(lower, std::min(n, upper));
|
|
}
|
|
std::vector<precision_t> percentile(std::vector<precision_t>& data, std::vector<precision_t>& percentiles)
|
|
{
|
|
// Implementation taken from https://dpilger26.github.io/NumCpp/doxygen/html/percentile_8hpp_source.html
|
|
std::vector<precision_t> results;
|
|
results.reserve(percentiles.size());
|
|
for (auto percentile : percentiles) {
|
|
const size_t i = static_cast<size_t>(std::floor(static_cast<double>(data.size() - 1) * percentile / 100.));
|
|
const auto indexLower = clip(i, 0, data.size() - 2);
|
|
const double percentI = static_cast<double>(indexLower) / static_cast<double>(data.size() - 1);
|
|
const double fraction =
|
|
(percentile / 100.0 - percentI) /
|
|
(static_cast<double>(indexLower + 1) / static_cast<double>(data.size() - 1) - percentI);
|
|
const auto value = data[indexLower] + (data[indexLower + 1] - data[indexLower]) * fraction;
|
|
if (value != results.back())
|
|
results.push_back(value);
|
|
}
|
|
return results;
|
|
}
|
|
int main()
|
|
{
|
|
// std::vector<float> test;
|
|
// std::vector<float> cuts = { 0, 24.75, 49.5, 74.25, 10000 };
|
|
// for (int i = 0; i < 100; ++i) {
|
|
// test.push_back(i);
|
|
// }
|
|
// auto Xt = transform(cuts, test);
|
|
// show_vector(Xt, "Discretized data:");
|
|
// std::vector<float> test2 = { 0,1,2,3,4,5,6,7,8,9,10,11 };
|
|
// std::vector<float> cuts2 = { 0,1,2,3,4,5,6,7,8,9 };
|
|
// auto Xt2 = transform(cuts2, test2);
|
|
// show_vector(Xt2, "discretized data2: ");
|
|
auto quantiles = linspace(0.0, 100.0, 3 + 1);
|
|
std::vector<float> data = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
|
|
std::vector<float> cutPoints;
|
|
std::sort(data.begin(), data.end());
|
|
cutPoints = percentile(data, quantiles);
|
|
cutPoints.push_back(std::numeric_limits<precision_t>::max());
|
|
data.push_back(15);
|
|
data.push_back(0);
|
|
cutPoints.pop_back();
|
|
cutPoints.erase(cutPoints.begin());
|
|
cutPoints.clear();
|
|
cutPoints.push_back(9.0);
|
|
auto Xt = transform(cutPoints, data);
|
|
show_vector(data, "Original data");
|
|
show_vector(Xt, "Discretized data");
|
|
show_vector(cutPoints, "Cutpoints");
|
|
return 0;
|
|
}
|
|
/*
|
|
n_bins = 3
|
|
data = [1,2,3,4,5,6,7,8,9,10]
|
|
quantiles = np.linspace(0, 100, n_bins + 1)
|
|
bin_edges = np.percentile(data, quantiles)
|
|
|
|
*/ |