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Fix tests, samples and remove uneeded support files

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This commit is contained in:
Ricardo Montañana Gómez
2024-07-03 18:13:22 +02:00
parent d90e21ec4c
commit fcbd05d842
18 changed files with 426 additions and 997 deletions
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39
Discretizer.cpp
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@@ -1,40 +1,7 @@
#include "Discretizer.h"
namespace mdlp {
// The next to templates have been taken to have the chance to customize them to match
// np.searchsorted that is used in scikit-learn KBinsDiscretizer
// Code Taken from https://cplusplus.com/reference/algorithm/upper_bound/?kw=upper_bound
template <class ForwardIterator, class T>
ForwardIterator upper_bound(ForwardIterator first, ForwardIterator last, const T& val)
{
ForwardIterator it;
typename iterator_traits<ForwardIterator>::difference_type count, step;
count = std::distance(first, last);
while (count > 0) {
it = first; step = count / 2; std::advance(it, step);
if (!(val < *it)) // or: if (!comp(val,*it)), for version (2)
{
first = ++it; count -= step + 1;
} else count = step;
}
return first;
}
// Code Taken from https://cplusplus.com/reference/algorithm/lower_bound/?kw=lower_bound
template <class ForwardIterator, class T>
ForwardIterator lower_bound(ForwardIterator first, ForwardIterator last, const T& val)
{
ForwardIterator it;
typename iterator_traits<ForwardIterator>::difference_type count, step;
count = distance(first, last);
while (count > 0) {
it = first; step = count / 2; advance(it, step);
if (*it < val) { // or: if (comp(*it,val)), for version (2)
first = ++it;
count -= step + 1;
} else count = step;
}
return first;
}
labels_t& Discretizer::transform(const samples_t& data)
{
discretizedData.clear();
@@ -43,7 +10,7 @@ namespace mdlp {
// Have to ignore first and last cut points provided
auto first = cutPoints.begin() + 1;
auto last = cutPoints.end() - 1;
auto bound = direction == bound_dir_t::LEFT ? my_lower_bound<std::vector<float>::iterator, float> : my_upper_bound<std::vector<float>::iterator, float>;
auto bound = direction == bound_dir_t::LEFT ? std::lower_bound<std::vector<precision_t>::iterator, precision_t> : std::upper_bound<std::vector<precision_t>::iterator, precision_t>;
for (const precision_t& item : data) {
auto pos = bound(first, last, item);
int number = pos - first;
@@ -71,7 +38,7 @@ namespace mdlp {
torch::Tensor Discretizer::transform_t(torch::Tensor& X_)
{
auto num_elements = X_.numel();
samples_t X(X_.data_ptr<float>(), X_.data_ptr<float>() + num_elements);
samples_t X(X_.data_ptr<precision_t>(), X_.data_ptr<precision_t>() + num_elements);
auto result = transform(X);
return torch::tensor(result, torch::kInt32);
}