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2 Commits
cb9babace1 ... 23a676d654

Author SHA1 Message Date
Ricardo Montañana Gómez
23a676d654 Merge d90e21ec4c into 7b0673fd4b 2024-07-02 18:54:21 +02:00
Ricardo Montañana Gómez
d90e21ec4c Include upper_bound and lower_bound implementation 2024-07-02 18:54:07 +02:00
10 changed files with 782 additions and 412 deletions
Expand all files Collapse all files

2
BinDisc.cpp
View File

@@ -24,8 +24,10 @@ namespace mdlp {
return; return;
} }
if (strategy == strategy_t::QUANTILE) { if (strategy == strategy_t::QUANTILE) {
direction = bound_dir_t::RIGHT;
fit_quantile(X); fit_quantile(X);
} else if (strategy == strategy_t::UNIFORM) { } else if (strategy == strategy_t::UNIFORM) {
direction = bound_dir_t::RIGHT;
fit_uniform(X); fit_uniform(X);
} }
} }

1
CPPFImdlp.cpp
View File

@@ -12,6 +12,7 @@ namespace mdlp {
max_depth(max_depth_), max_depth(max_depth_),
proposed_cuts(proposed) proposed_cuts(proposed)
{ {
direction = bound_dir_t::LEFT;
} }
size_t CPPFImdlp::compute_max_num_cut_points() const size_t CPPFImdlp::compute_max_num_cut_points() const

41
Discretizer.cpp
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@@ -1,17 +1,52 @@
#include "Discretizer.h" #include "Discretizer.h"
namespace mdlp { 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) labels_t& Discretizer::transform(const samples_t& data)
{ {
discretizedData.clear(); discretizedData.clear();
discretizedData.reserve(data.size()); discretizedData.reserve(data.size());
// CutPoints always have more than two items // CutPoints always have at least two items
// Have to ignore first and last cut points provided // Have to ignore first and last cut points provided
auto first = cutPoints.begin() + 1; auto first = cutPoints.begin() + 1;
auto last = cutPoints.end() - 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>;
for (const precision_t& item : data) { for (const precision_t& item : data) {
auto upper = std::lower_bound(first, last, item); auto pos = bound(first, last, item);
int number = upper - first; int number = pos - first;
/* /*
OJO OJO
*/ */

5
Discretizer.h
View File

@@ -7,6 +7,10 @@
#include "typesFImdlp.h" #include "typesFImdlp.h"
namespace mdlp { namespace mdlp {
enum class bound_dir_t {
LEFT,
RIGHT
};
class Discretizer { class Discretizer {
public: public:
Discretizer() = default; Discretizer() = default;
@@ -22,6 +26,7 @@ namespace mdlp {
protected: protected:
labels_t discretizedData = labels_t(); labels_t discretizedData = labels_t();
cutPoints_t cutPoints; // At least two cutpoints must be provided, the first and the last will be ignored in transform cutPoints_t cutPoints; // At least two cutpoints must be provided, the first and the last will be ignored in transform
bound_dir_t direction; // used in transform
}; };
} }
#endif #endif

688
tests/BinDisc_unittest.cpp
View File

@@ -35,382 +35,360 @@ namespace mdlp {
public: public:
TestBinDisc4Q(int n_bins = 4) : BinDisc(n_bins, strategy_t::QUANTILE) {}; TestBinDisc4Q(int n_bins = 4) : BinDisc(n_bins, strategy_t::QUANTILE) {};
}; };
TEST_F(TestBinDisc3U, Easy3BinsUniform) // TEST_F(TestBinDisc3U, Easy3BinsUniform)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
auto y = labels_t(); // auto y = labels_t();
fit(X, y); // fit(X, y);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(4, cuts.size()); // ASSERT_EQ(4, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(3.66667, cuts.at(1), margin); // EXPECT_NEAR(3.66667, cuts.at(1), margin);
EXPECT_NEAR(6.33333, cuts.at(2), margin); // EXPECT_NEAR(6.33333, cuts.at(2), margin);
EXPECT_NEAR(9.0, cuts.at(3), margin); // EXPECT_NEAR(9.0, cuts.at(3), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 }; // labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3Q, Easy3BinsQuantile) // TEST_F(TestBinDisc3Q, Easy3BinsQuantile)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(4, cuts.size()); // ASSERT_EQ(4, cuts.size());
EXPECT_NEAR(1, cuts[0], margin); // EXPECT_NEAR(1, cuts[0], margin);
EXPECT_NEAR(3.666667, cuts[1], margin); // EXPECT_NEAR(3.666667, cuts[1], margin);
EXPECT_NEAR(6.333333, cuts[2], margin); // EXPECT_NEAR(6.333333, cuts[2], margin);
EXPECT_NEAR(9, cuts[3], margin); // EXPECT_NEAR(9, cuts[3], margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 }; // labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3U, X10BinsUniform) // TEST_F(TestBinDisc3U, X10BinsUniform)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(4, cuts.size()); // ASSERT_EQ(4, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(4.0, cuts.at(1), margin); // EXPECT_NEAR(4.0, cuts.at(1), margin);
EXPECT_NEAR(7.0, cuts.at(2), margin); // EXPECT_NEAR(7.0, cuts.at(2), margin);
EXPECT_NEAR(10.0, cuts.at(3), margin); // EXPECT_NEAR(10.0, cuts.at(3), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3Q, X10BinsQuantile) // TEST_F(TestBinDisc3Q, X10BinsQuantile)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(4, cuts.size()); // ASSERT_EQ(4, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(4.0, cuts.at(1), margin); // EXPECT_NEAR(4.0, cuts.at(1), margin);
EXPECT_NEAR(7.0, cuts.at(2), margin); // EXPECT_NEAR(7.0, cuts.at(2), margin);
EXPECT_NEAR(10.0, cuts.at(3), margin); // EXPECT_NEAR(10.0, cuts.at(3), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3U, X11BinsUniform) // TEST_F(TestBinDisc3U, X11BinsUniform)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(4, cuts.size()); // ASSERT_EQ(4, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(4.33333, cuts.at(1), margin); // EXPECT_NEAR(4.33333, cuts.at(1), margin);
EXPECT_NEAR(7.66667, cuts.at(2), margin); // EXPECT_NEAR(7.66667, cuts.at(2), margin);
EXPECT_NEAR(11.0, cuts.at(3), margin); // EXPECT_NEAR(11.0, cuts.at(3), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3U, X11BinsQuantile) // TEST_F(TestBinDisc3U, X11BinsQuantile)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(4, cuts.size()); // ASSERT_EQ(4, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(4.33333, cuts.at(1), margin); // EXPECT_NEAR(4.33333, cuts.at(1), margin);
EXPECT_NEAR(7.66667, cuts.at(2), margin); // EXPECT_NEAR(7.66667, cuts.at(2), margin);
EXPECT_NEAR(11.0, cuts.at(3), margin); // EXPECT_NEAR(11.0, cuts.at(3), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 2 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3U, ConstantUniform) // TEST_F(TestBinDisc3U, ConstantUniform)
{ // {
samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 }; // samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(2, cuts.size()); // ASSERT_EQ(2, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(1, cuts.at(1), margin); // EXPECT_NEAR(1, cuts.at(1), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 0, 0 }; // labels_t expected = { 0, 0, 0, 0, 0, 0 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3Q, ConstantQuantile) // TEST_F(TestBinDisc3Q, ConstantQuantile)
{ // {
samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 }; // samples_t X = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(2, cuts.size()); // ASSERT_EQ(2, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(1, cuts.at(1), margin); // EXPECT_NEAR(1, cuts.at(1), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 0, 0 }; // labels_t expected = { 0, 0, 0, 0, 0, 0 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc3U, EmptyUniform) // TEST_F(TestBinDisc3U, EmptyUniform)
{ // {
samples_t X = {}; // samples_t X = {};
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(2, cuts.size()); // ASSERT_EQ(2, cuts.size());
EXPECT_NEAR(0, cuts.at(0), margin); // EXPECT_NEAR(0, cuts.at(0), margin);
EXPECT_NEAR(0, cuts.at(1), margin); // EXPECT_NEAR(0, cuts.at(1), margin);
} // }
TEST_F(TestBinDisc3Q, EmptyQuantile) // TEST_F(TestBinDisc3Q, EmptyQuantile)
{ // {
samples_t X = {}; // samples_t X = {};
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(2, cuts.size()); // ASSERT_EQ(2, cuts.size());
EXPECT_NEAR(0, cuts.at(0), margin); // EXPECT_NEAR(0, cuts.at(0), margin);
EXPECT_NEAR(0, cuts.at(1), margin); // EXPECT_NEAR(0, cuts.at(1), margin);
} // }
TEST(TestBinDisc3, ExceptionNumberBins) // TEST(TestBinDisc3, ExceptionNumberBins)
{ // {
EXPECT_THROW(BinDisc(2), std::invalid_argument); // EXPECT_THROW(BinDisc(2), std::invalid_argument);
} // }
TEST_F(TestBinDisc3U, EasyRepeated) // TEST_F(TestBinDisc3U, EasyRepeated)
{ // {
samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 }; // samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(4, cuts.size()); // ASSERT_EQ(4, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(1.66667, cuts.at(1), margin); // EXPECT_NEAR(1.66667, cuts.at(1), margin);
EXPECT_NEAR(2.33333, cuts.at(2), margin); // EXPECT_NEAR(2.33333, cuts.at(2), margin);
EXPECT_NEAR(3.0, cuts.at(3), margin); // EXPECT_NEAR(3.0, cuts.at(3), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 2, 0, 0, 2, 0, 0, 2, 0, 0 }; // labels_t expected = { 2, 0, 0, 2, 0, 0, 2, 0, 0 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
ASSERT_EQ(3.0, X[0]); // X is not modified // ASSERT_EQ(3.0, X[0]); // X is not modified
} // }
TEST_F(TestBinDisc3Q, EasyRepeated) // TEST_F(TestBinDisc3Q, EasyRepeated)
{ // {
samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 }; // samples_t X = { 3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(3, cuts.size()); // ASSERT_EQ(3, cuts.size());
EXPECT_NEAR(1, cuts.at(0), margin); // EXPECT_NEAR(1, cuts.at(0), margin);
EXPECT_NEAR(1.66667, cuts.at(1), margin); // EXPECT_NEAR(1.66667, cuts.at(1), margin);
EXPECT_NEAR(3.0, cuts.at(2), margin); // EXPECT_NEAR(3.0, cuts.at(2), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 1, 0, 0, 1, 0, 0, 1, 0, 0 }; // labels_t expected = { 1, 0, 0, 1, 0, 0, 1, 0, 0 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
ASSERT_EQ(3.0, X[0]); // X is not modified // ASSERT_EQ(3.0, X[0]); // X is not modified
} // }
TEST_F(TestBinDisc4U, Easy4BinsUniform) // TEST_F(TestBinDisc4U, Easy4BinsUniform)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(3.75, cuts.at(1), margin); // EXPECT_NEAR(3.75, cuts.at(1), margin);
EXPECT_NEAR(6.5, cuts.at(2), margin); // EXPECT_NEAR(6.5, cuts.at(2), margin);
EXPECT_NEAR(9.25, cuts.at(3), margin); // EXPECT_NEAR(9.25, cuts.at(3), margin);
EXPECT_NEAR(12.0, cuts.at(4), margin); // EXPECT_NEAR(12.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 }; // labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4Q, Easy4BinsQuantile) // TEST_F(TestBinDisc4Q, Easy4BinsQuantile)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(3.75, cuts.at(1), margin); // EXPECT_NEAR(3.75, cuts.at(1), margin);
EXPECT_NEAR(6.5, cuts.at(2), margin); // EXPECT_NEAR(6.5, cuts.at(2), margin);
EXPECT_NEAR(9.25, cuts.at(3), margin); // EXPECT_NEAR(9.25, cuts.at(3), margin);
EXPECT_NEAR(12.0, cuts.at(4), margin); // EXPECT_NEAR(12.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 }; // labels_t expected = { 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4U, X13BinsUniform) // TEST_F(TestBinDisc4U, X13BinsUniform)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(4.0, cuts.at(1), margin); // EXPECT_NEAR(4.0, cuts.at(1), margin);
EXPECT_NEAR(7.0, cuts.at(2), margin); // EXPECT_NEAR(7.0, cuts.at(2), margin);
EXPECT_NEAR(10.0, cuts.at(3), margin); // EXPECT_NEAR(10.0, cuts.at(3), margin);
EXPECT_NEAR(13.0, cuts.at(4), margin); // EXPECT_NEAR(13.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4Q, X13BinsQuantile) // TEST_F(TestBinDisc4Q, X13BinsQuantile)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(4.0, cuts.at(1), margin); // EXPECT_NEAR(4.0, cuts.at(1), margin);
EXPECT_NEAR(7.0, cuts.at(2), margin); // EXPECT_NEAR(7.0, cuts.at(2), margin);
EXPECT_NEAR(10.0, cuts.at(3), margin); // EXPECT_NEAR(10.0, cuts.at(3), margin);
EXPECT_NEAR(13.0, cuts.at(4), margin); // EXPECT_NEAR(13.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4U, X14BinsUniform) // TEST_F(TestBinDisc4U, X14BinsUniform)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(4.25, cuts.at(1), margin); // EXPECT_NEAR(4.25, cuts.at(1), margin);
EXPECT_NEAR(7.5, cuts.at(2), margin); // EXPECT_NEAR(7.5, cuts.at(2), margin);
EXPECT_NEAR(10.75, cuts.at(3), margin); // EXPECT_NEAR(10.75, cuts.at(3), margin);
EXPECT_NEAR(14.0, cuts.at(4), margin); // EXPECT_NEAR(14.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4Q, X14BinsQuantile) // TEST_F(TestBinDisc4Q, X14BinsQuantile)
{ // {
samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 }; // samples_t X = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, 14.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(4.25, cuts.at(1), margin); // EXPECT_NEAR(4.25, cuts.at(1), margin);
EXPECT_NEAR(7.5, cuts.at(2), margin); // EXPECT_NEAR(7.5, cuts.at(2), margin);
EXPECT_NEAR(10.75, cuts.at(3), margin); // EXPECT_NEAR(10.75, cuts.at(3), margin);
EXPECT_NEAR(14.0, cuts.at(4), margin); // EXPECT_NEAR(14.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 1, 2, 2, 2, 3, 3, 3, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4U, X15BinsUniform) // TEST_F(TestBinDisc4U, X15BinsUniform)
{ // {
samples_t X = { 15.0, 8.0, 12.0, 14.0, 6.0, 1.0, 13.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 }; // samples_t X = { 15.0, 8.0, 12.0, 14.0, 6.0, 1.0, 13.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(4.5, cuts.at(1), margin); // EXPECT_NEAR(4.5, cuts.at(1), margin);
EXPECT_NEAR(8, cuts.at(2), margin); // EXPECT_NEAR(8, cuts.at(2), margin);
EXPECT_NEAR(11.5, cuts.at(3), margin); // EXPECT_NEAR(11.5, cuts.at(3), margin);
EXPECT_NEAR(15.0, cuts.at(4), margin); // EXPECT_NEAR(15.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 3, 1, 3, 3, 1, 0, 3, 2, 2, 2, 1, 0, 0, 1, 0 }; // labels_t expected = { 3, 1, 3, 3, 1, 0, 3, 2, 2, 2, 1, 0, 0, 1, 0 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4Q, X15BinsQuantile) // TEST_F(TestBinDisc4Q, X15BinsQuantile)
{ // {
samples_t X = { 15.0, 13.0, 12.0, 14.0, 6.0, 1.0, 8.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 }; // samples_t X = { 15.0, 13.0, 12.0, 14.0, 6.0, 1.0, 8.0, 11.0, 10.0, 9.0, 7.0, 4.0, 3.0, 5.0, 2.0 };
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(1.0, cuts.at(0), margin); // EXPECT_NEAR(1.0, cuts.at(0), margin);
EXPECT_NEAR(4.5, cuts.at(1), margin); // EXPECT_NEAR(4.5, cuts.at(1), margin);
EXPECT_NEAR(8, cuts.at(2), margin); // EXPECT_NEAR(8, cuts.at(2), margin);
EXPECT_NEAR(11.5, cuts.at(3), margin); // EXPECT_NEAR(11.5, cuts.at(3), margin);
EXPECT_NEAR(15.0, cuts.at(4), margin); // EXPECT_NEAR(15.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 3, 3, 3, 3, 1, 0, 1, 2, 2, 2, 1, 0, 0, 1, 0 }; // labels_t expected = { 3, 3, 3, 3, 1, 0, 1, 2, 2, 2, 1, 0, 0, 1, 0 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4U, RepeatedValuesUniform) // TEST_F(TestBinDisc4U, RepeatedValuesUniform)
{ // {
samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 }; // samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 };
// 0 1 2 3 4 5 6 7 8 9 // // 0 1 2 3 4 5 6 7 8 9
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(0.0, cuts.at(0), margin); // EXPECT_NEAR(0.0, cuts.at(0), margin);
EXPECT_NEAR(1.0, cuts.at(1), margin); // EXPECT_NEAR(1.0, cuts.at(1), margin);
EXPECT_NEAR(2.0, cuts.at(2), margin); // EXPECT_NEAR(2.0, cuts.at(2), margin);
EXPECT_NEAR(3.0, cuts.at(3), margin); // EXPECT_NEAR(3.0, cuts.at(3), margin);
EXPECT_NEAR(4.0, cuts.at(4), margin); // EXPECT_NEAR(4.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4Q, RepeatedValuesQuantile) // TEST_F(TestBinDisc4Q, RepeatedValuesQuantile)
{ // {
samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 }; // samples_t X = { 0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0 };
// 0 1 2 3 4 5 6 7 8 9 // // 0 1 2 3 4 5 6 7 8 9
fit(X); // fit(X);
auto cuts = getCutPoints(); // auto cuts = getCutPoints();
ASSERT_EQ(5, cuts.size()); // ASSERT_EQ(5, cuts.size());
EXPECT_NEAR(0.0, cuts.at(0), margin); // EXPECT_NEAR(0.0, cuts.at(0), margin);
EXPECT_NEAR(1.0, cuts.at(1), margin); // EXPECT_NEAR(1.0, cuts.at(1), margin);
EXPECT_NEAR(2.0, cuts.at(2), margin); // EXPECT_NEAR(2.0, cuts.at(2), margin);
EXPECT_NEAR(3.0, cuts.at(3), margin); // EXPECT_NEAR(3.0, cuts.at(3), margin);
EXPECT_NEAR(4.0, cuts.at(4), margin); // EXPECT_NEAR(4.0, cuts.at(4), margin);
auto labels = transform(X); // auto labels = transform(X);
labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 }; // labels_t expected = { 0, 0, 0, 0, 1, 1, 2, 2, 2, 3 };
EXPECT_EQ(expected, labels); // EXPECT_EQ(expected, labels);
} // }
TEST_F(TestBinDisc4U, irisUniform)
{
ArffFiles file;
file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX();
fit(X[0]);
auto Xt = transform(X[0]);
labels_t expected = { 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 2, 2, 1, 2, 1, 2, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 0, 1, 1, 1, 2, 0, 1, 2, 1, 3, 2, 2, 3, 0, 3, 2, 3, 2, 2, 2, 1, 1, 2, 2, 3, 3, 1, 2, 1, 3, 2, 2, 3, 2, 1, 2, 3, 3, 3, 2, 2, 1, 3, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1 };
EXPECT_EQ(expected, Xt);
auto Xtt = fit_transform(X[0], file.getY());
EXPECT_EQ(expected, Xtt);
auto Xt_t = torch::tensor(X[0], torch::kFloat32);
auto y_t = torch::tensor(file.getY(), torch::kInt32);
auto Xtt_t = fit_transform_t(Xt_t, y_t);
for (int i = 0; i < expected.size(); i++)
EXPECT_EQ(expected[i], Xtt_t[i].item<int>());
}
TEST_F(TestBinDisc4Q, irisQuantile)
{
ArffFiles file;
file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX();
fit(X[0]);
auto Xt = transform(X[0]);
labels_t expected = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 3, 3, 3, 1, 3, 1, 2, 0, 3, 1, 0, 2, 2, 2, 1, 3, 1, 2, 2, 1, 2, 2, 2, 2, 3, 3, 3, 3, 2, 1, 1, 1, 2, 2, 1, 2, 3, 2, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2, 1, 1, 2, 2, 3, 2, 3, 3, 0, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 2, 3, 1, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 2, 2, 3, 2, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 2, 2 };
EXPECT_EQ(expected, Xt);
auto Xtt = fit_transform(X[0], file.getY());
EXPECT_EQ(expected, Xtt);
auto Xt_t = torch::tensor(X[0], torch::kFloat32);
auto y_t = torch::tensor(file.getY(), torch::kInt32);
auto Xtt_t = fit_transform_t(Xt_t, y_t);
for (int i = 0; i < expected.size(); i++)
EXPECT_EQ(expected[i], Xtt_t[i].item<int>());
fit_t(Xt_t, y_t);
auto Xt_t2 = transform_t(Xt_t);
for (int i = 0; i < expected.size(); i++)
EXPECT_EQ(expected[i], Xt_t2[i].item<int>());
}
TEST(TestBinDiscGeneric, Fileset) TEST(TestBinDiscGeneric, Fileset)
{ {
Experiments exps(data_path + "tests.txt"); Experiments exps(data_path + "tests.txt");
int num = 0; int num = 0;
while (exps.is_next()) { while (exps.is_next()) {
++num;
Experiment exp = exps.next(); Experiment exp = exps.next();
std::cout << "Exp #: " << ++num << " From: " << exp.from_ << " To: " << exp.to_ << " Step: " << exp.step_ << " Bins: " << exp.n_bins_ << " Strategy: " << exp.strategy_ << std::endl; BinDisc disc(exp.n_bins_, exp.strategy_[0] == 'Q' ? strategy_t::QUANTILE : strategy_t::UNIFORM);
BinDisc disc(exp.n_bins_, exp.strategy_ == "Q" ? strategy_t::QUANTILE : strategy_t::UNIFORM);
std::vector<float> test; std::vector<float> test;
for (float i = exp.from_; i < exp.to_; i += exp.step_) { if (exp.type_ == experiment_t::RANGE) {
test.push_back(i); for (float i = exp.from_; i < exp.to_; i += exp.step_) {
test.push_back(i);
}
} else {
test = exp.dataset_;
} }
// show_vector(test, "Test"); // show_vector(test, "Test");
auto empty = std::vector<int>(); auto empty = std::vector<int>();
auto Xt = disc.fit_transform(test, empty); auto Xt = disc.fit_transform(test, empty);
auto cuts = disc.getCutPoints(); auto cuts = disc.getCutPoints();
EXPECT_EQ(exp.discretized_data_.size(), Xt.size()); EXPECT_EQ(exp.discretized_data_.size(), Xt.size());
auto flag = false;
size_t n_errors = 0;
for (int i = 0; i < exp.discretized_data_.size(); ++i) { for (int i = 0; i < exp.discretized_data_.size(); ++i) {
if (exp.discretized_data_.at(i) != Xt.at(i)) { if (exp.discretized_data_.at(i) != Xt.at(i)) {
std::cout << "Error at " << i << " Expected: " << exp.discretized_data_.at(i) << " Got: " << Xt.at(i) << std::endl; if (!flag) {
std::cout << "Exp #: " << num << " From: " << exp.from_ << " To: " << exp.to_ << " Step: " << exp.step_ << " Bins: " << exp.n_bins_ << " Strategy: " << exp.strategy_ << std::endl;
std::cout << "Error at " << i << " Expected: " << exp.discretized_data_.at(i) << " Got: " << Xt.at(i) << std::endl;
flag = true;
EXPECT_EQ(exp.discretized_data_.at(i), Xt.at(i));
}
n_errors++;
} }
} }
if (flag) {
std::cout << "*** Found " << n_errors << " mistakes in this experiment dataset" << std::endl;
}
EXPECT_EQ(exp.cutpoints_.size(), cuts.size()); EXPECT_EQ(exp.cutpoints_.size(), cuts.size());
for (int i = 0; i < exp.cutpoints_.size(); ++i) { for (int i = 0; i < exp.cutpoints_.size(); ++i) {
EXPECT_NEAR(exp.cutpoints_.at(i), cuts.at(i), margin); EXPECT_NEAR(exp.cutpoints_.at(i), cuts.at(i), margin);
} }
} }
std::cout << "* Number of experiments tested: " << num << std::endl;
} }
} }

205
tests/Discretizer_unittest.cpp
View File

@@ -30,34 +30,187 @@ namespace mdlp {
EXPECT_EQ("1.2.3", version); EXPECT_EQ("1.2.3", version);
} }
TEST(Discretizer, BinIrisUniform) // TEST(Discretizer, BinIrisUniform)
{ // {
ArffFiles file; // ArffFiles file;
Discretizer* disc = new BinDisc(4, strategy_t::UNIFORM); // Discretizer* disc = new BinDisc(4, strategy_t::UNIFORM);
file.load(data_path + "iris.arff", true); // file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX(); // vector<samples_t>& X = file.getX();
auto y = labels_t(); // auto y = labels_t();
disc->fit(X[0], y); // disc->fit(X[0], y);
auto Xt = disc->transform(X[0]); // auto Xt = disc->transform(X[0]);
labels_t expected = { 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 2, 2, 1, 2, 1, 2, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 0, 1, 1, 1, 2, 0, 1, 2, 1, 3, 2, 2, 3, 0, 3, 2, 3, 2, 2, 2, 1, 1, 2, 2, 3, 3, 1, 2, 1, 3, 2, 2, 3, 2, 1, 2, 3, 3, 3, 2, 2, 1, 3, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1 }; // labels_t expected = { 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 2, 2, 1, 2, 1, 2, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 2, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 0, 1, 1, 1, 2, 0, 1, 2, 1, 3, 2, 2, 3, 0, 3, 2, 3, 2, 2, 2, 1, 1, 2, 2, 3, 3, 1, 2, 1, 3, 2, 2, 3, 2, 1, 2, 3, 3, 3, 2, 2, 1, 3, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1 };
delete disc; // delete disc;
EXPECT_EQ(expected, Xt); // EXPECT_EQ(expected, Xt);
} // }
TEST(Discretizer, BinIrisQuantile) // TEST(Discretizer, BinIrisQuantile)
{ // {
ArffFiles file; // ArffFiles file;
Discretizer* disc = new BinDisc(4, strategy_t::QUANTILE); // Discretizer* disc = new BinDisc(4, strategy_t::QUANTILE);
file.load(data_path + "iris.arff", true); // file.load(data_path + "iris.arff", true);
vector<samples_t>& X = file.getX(); // vector<samples_t>& X = file.getX();
auto y = labels_t(); // auto y = labels_t();
disc->fit(X[0], y); // disc->fit(X[0], y);
auto Xt = disc->transform(X[0]); // auto Xt = disc->transform(X[0]);
labels_t expected = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 3, 3, 3, 1, 3, 1, 2, 0, 3, 1, 0, 2, 2, 2, 1, 3, 1, 2, 2, 1, 2, 2, 2, 2, 3, 3, 3, 3, 2, 1, 1, 1, 2, 2, 1, 2, 3, 2, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2, 1, 1, 2, 2, 3, 2, 3, 3, 0, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 2, 3, 1, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 2, 2, 3, 2, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 2, 2 }; // labels_t expected = { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 3, 3, 3, 1, 3, 1, 2, 0, 3, 1, 0, 2, 2, 2, 1, 3, 1, 2, 2, 1, 2, 2, 2, 2, 3, 3, 3, 3, 2, 1, 1, 1, 2, 2, 1, 2, 3, 2, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2, 1, 1, 2, 2, 3, 2, 3, 3, 0, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 2, 3, 1, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 2, 2, 3, 2, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 2, 2 };
delete disc; // delete disc;
EXPECT_EQ(expected, Xt); // EXPECT_EQ(expected, Xt);
} // }
TEST(Discretizer, FImdlpIris) TEST(Discretizer, FImdlpIris)
{ {
auto labelsq = {
1,
0,
0,
0,
0,
1,
0,
0,
0,
0,
1,
0,
0,
0,
2,
1,
1,
1,
1,
1,
1,
1,
0,
1,
0,
0,
0,
1,
1,
0,
0,
1,
1,
1,
0,
0,
1,
0,
0,
1,
0,
0,
0,
0,
1,
0,
1,
0,
1,
0,
3,
3,
3,
1,
3,
1,
2,
0,
3,
1,
0,
2,
2,
2,
1,
3,
1,
2,
2,
1,
2,
2,
2,
2,
3,
3,
3,
3,
2,
1,
1,
1,
2,
2,
1,
2,
3,
2,
1,
1,
1,
2,
2,
0,
1,
1,
1,
2,
1,
1,
2,
2,
3,
2,
3,
3,
0,
3,
3,
3,
3,
3,
3,
1,
2,
3,
3,
3,
3,
2,
3,
1,
3,
2,
3,
3,
2,
2,
3,
3,
3,
3,
3,
2,
2,
3,
2,
3,
2,
3,
3,
3,
2,
3,
3,
3,
2,
3,
2,
2,
};
labels_t expected = { labels_t expected = {
5, 3, 4, 4, 5, 5, 5, 5, 2, 4, 5, 5, 3, 3, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3, 4, 4, 5, 5, 5, 5, 2, 4, 5, 5, 3, 3, 5, 5, 5, 5, 5, 5, 5, 5,
5, 4, 5, 3, 5, 5, 5, 4, 4, 5, 5, 5, 4, 4, 5, 4, 3, 5, 5, 0, 4, 5, 5, 4, 5, 3, 5, 5, 5, 4, 4, 5, 5, 5, 4, 4, 5, 4, 3, 5, 5, 0, 4, 5,

73
tests/Experiments.hpp
View File

@@ -7,13 +7,39 @@
#include<vector> #include<vector>
#include<tuple> #include<tuple>
#include "../typesFImdlp.h" #include "../typesFImdlp.h"
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;
}
enum class experiment_t {
RANGE,
VECTOR
};
class Experiment { class Experiment {
public: public:
Experiment(float from_, float to_, float step_, int n_bins, std::string strategy, std::vector<int> data_discretized, std::vector<float> cutpoints) : Experiment(float from_, float to_, float step_, int n_bins, std::string strategy, std::vector<int> data_discretized, std::vector<float> cutpoints) :
from_{ from_ }, to_{ to_ }, step_{ step_ }, n_bins_{ n_bins }, strategy_{ strategy }, discretized_data_{ data_discretized }, cutpoints_{ cutpoints } from_{ from_ }, to_{ to_ }, step_{ step_ }, n_bins_{ n_bins }, strategy_{ strategy }, discretized_data_{ data_discretized }, cutpoints_{ cutpoints }, type_{ experiment_t::RANGE }
{ {
if (strategy != "Q" && strategy != "U") { validate_strategy();
throw std::invalid_argument("Invalid strategy " + strategy);
}
Experiment(std::vector<float> dataset, int n_bins, std::string strategy, std::vector<int> data_discretized, std::vector<float> cutpoints) :
n_bins_{ n_bins }, strategy_{ strategy }, dataset_{ dataset }, discretized_data_{ data_discretized }, cutpoints_{ cutpoints }, type_{ experiment_t::VECTOR }
{
validate_strategy();
}
void validate_strategy()
{
if (strategy_ != "Q" && strategy_ != "U") {
throw std::invalid_argument("Invalid strategy " + strategy_);
} }
} }
float from_; float from_;
@@ -21,8 +47,10 @@ public:
float step_; float step_;
int n_bins_; int n_bins_;
std::string strategy_; std::string strategy_;
std::vector<float> dataset_;
std::vector<int> discretized_data_; std::vector<int> discretized_data_;
std::vector<float> cutpoints_; std::vector<float> cutpoints_;
experiment_t type_;
}; };
class Experiments { class Experiments {
public: public:
@@ -76,33 +104,30 @@ private:
} }
Experiment parse_experiment(std::string& line) Experiment parse_experiment(std::string& line)
{ {
// Read experiment lines
std::string experiment, data, cuts, strategy;
std::getline(test_file, experiment);
std::getline(test_file, data);
std::getline(test_file, cuts);
// split data into variables
float from_, to_, step_;
int n_bins;
std::vector<float> dataset;
auto data_discretized = parse_vector<int>(data);
auto cutpoints = parse_vector<float>(cuts);
if (line == "RANGE") { if (line == "RANGE") {
std::getline(test_file, line); tie(from_, to_, step_, n_bins, strategy) = parse_header(experiment);
auto [from_, to_, step_, n_bins, strategy] = parse_header(line); return Experiment{ from_, to_, step_, n_bins, strategy, data_discretized, cutpoints };
} else {
std::getline(test_file, line);
} }
std::getline(test_file, line); strategy = experiment.substr(0, 1);
auto data_discretized = parse_vector<int>(line); n_bins = std::stoi(experiment.substr(1, 1));
std::getline(test_file, line); data = experiment.substr(3, experiment.size() - 4);
auto cutpoints = parse_vector<float>(line); dataset = parse_vector<float>(data);
return Experiment{ from_, to_, step_, n_bins, strategy, data_discretized, cutpoints }; return Experiment(dataset, n_bins, strategy, data_discretized, cutpoints);
} }
std::ifstream test_file; std::ifstream test_file;
std::string filename; std::string filename;
std::string line; std::string line;
bool exp_end; bool exp_end;
}; };
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;
}
#endif #endif

73
tests/datasets/tests.txt
View File

@@ -3,6 +3,9 @@
# discretized data # discretized data
# cut points # cut points
# #
#
# Range experiments
#
RANGE RANGE
0, 100, 1, 4, Q 0, 100, 1, 4, Q
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3
@@ -91,6 +94,9 @@ RANGE
1, 15, 1, 3, U 1, 15, 1, 3, U
0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2 0, 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 2
1.0, 5.33333, 9.66667, 14.0 1.0, 5.33333, 9.66667, 14.0
#
# Vector experiments
#
VECTOR VECTOR
Q3[3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0] Q3[3.0, 1.0, 1.0, 3.0, 1.0, 1.0, 3.0, 1.0, 1.0]
1, 0, 0, 1, 0, 0, 1, 0, 0 1, 0, 0, 1, 0, 0, 1, 0, 0
@@ -147,3 +153,70 @@ VECTOR
U3[0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0] U3[0.0, 1.0, 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 3.0, 4.0]
0, 0, 0, 0, 1, 1, 2, 2, 2, 2 0, 0, 0, 0, 1, 1, 2, 2, 2, 2
0.0, 1.33333, 2.66667, 4.0 0.0, 1.33333, 2.66667, 4.0
#
# Vector experiments with iris
#
VECTOR
Q3[5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5.0, 5.0, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5.0, 5.5, 4.9, 4.4, 5.1, 5.0, 4.5, 4.4, 5.0, 5.1, 4.8, 5.1, 4.6, 5.3, 5.0, 7.0, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5.0, 5.9, 6.0, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6.0, 5.7, 5.5, 5.5, 5.8, 6.0, 5.4, 6.0, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5.0, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6.0, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6.0, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9]
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 1, 2, 1, 2, 0, 2, 0, 0, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 2, 1, 2, 2, 2, 2, 0, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1
4.3, 5.4, 6.3, 7.9
VECTOR
U3[5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5.0, 5.0, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5.0, 5.5, 4.9, 4.4, 5.1, 5.0, 4.5, 4.4, 5.0, 5.1, 4.8, 5.1, 4.6, 5.3, 5.0, 7.0, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5.0, 5.9, 6.0, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6.0, 5.7, 5.5, 5.5, 5.8, 6.0, 5.4, 6.0, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5.0, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6.0, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6.0, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9]
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 2, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 0, 1, 2, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 2, 1, 1, 2, 0, 2, 2, 2, 1, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 1, 1, 2, 2, 2, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1
4.3, 5.5, 6.7, 7.9
VECTOR
Q4[5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5.0, 5.0, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5.0, 5.5, 4.9, 4.4, 5.1, 5.0, 4.5, 4.4, 5.0, 5.1, 4.8, 5.1, 4.6, 5.3, 5.0, 7.0, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5.0, 5.9, 6.0, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6.0, 5.7, 5.5, 5.5, 5.8, 6.0, 5.4, 6.0, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5.0, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6.0, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6.0, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9]
1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 3, 3, 3, 1, 3, 1, 2, 0, 3, 1, 0, 2, 2, 2, 1, 3, 1, 2, 2, 1, 2, 2, 2, 2, 3, 3, 3, 3, 2, 1, 1, 1, 2, 2, 1, 2, 3, 2, 1, 1, 1, 2, 2, 0, 1, 1, 1, 2, 1, 1, 2, 2, 3, 2, 3, 3, 0, 3, 3, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 2, 3, 1, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 2, 2, 3, 2, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 2, 2
4.3, 5.1, 5.8, 6.4, 7.9
VECTOR
U4[5.1, 4.9, 4.7, 4.6, 5.0, 5.4, 4.6, 5.0, 4.4, 4.9, 5.4, 4.8, 4.8, 4.3, 5.8, 5.7, 5.4, 5.1, 5.7, 5.1, 5.4, 5.1, 4.6, 5.1, 4.8, 5.0, 5.0, 5.2, 5.2, 4.7, 4.8, 5.4, 5.2, 5.5, 4.9, 5.0, 5.5, 4.9, 4.4, 5.1, 5.0, 4.5, 4.4, 5.0, 5.1, 4.8, 5.1, 4.6, 5.3, 5.0, 7.0, 6.4, 6.9, 5.5, 6.5, 5.7, 6.3, 4.9, 6.6, 5.2, 5.0, 5.9, 6.0, 6.1, 5.6, 6.7, 5.6, 5.8, 6.2, 5.6, 5.9, 6.1, 6.3, 6.1, 6.4, 6.6, 6.8, 6.7, 6.0, 5.7, 5.5, 5.5, 5.8, 6.0, 5.4, 6.0, 6.7, 6.3, 5.6, 5.5, 5.5, 6.1, 5.8, 5.0, 5.6, 5.7, 5.7, 6.2, 5.1, 5.7, 6.3, 5.8, 7.1, 6.3, 6.5, 7.6, 4.9, 7.3, 6.7, 7.2, 6.5, 6.4, 6.8, 5.7, 5.8, 6.4, 6.5, 7.7, 7.7, 6.0, 6.9, 5.6, 7.7, 6.3, 6.7, 7.2, 6.2, 6.1, 6.4, 7.2, 7.4, 7.9, 6.4, 6.3, 6.1, 7.7, 6.3, 6.4, 6.0, 6.9, 6.7, 6.9, 5.8, 6.8, 6.7, 6.7, 6.3, 6.5, 6.2, 5.9]
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 3, 2, 2, 1, 2, 1, 2, 0, 2, 1, 0, 1, 1, 2, 1, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 1, 0, 1, 1, 1, 2, 0, 1, 2, 1, 3, 2, 2, 3, 0, 3, 2, 3, 2, 2, 2, 1, 1, 2, 2, 3, 3, 1, 2, 1, 3, 2, 2, 3, 2, 2, 2, 3, 3, 3, 2, 2, 2, 3, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1
4.3, 5.2, 6.1, 7.0, 7.9
VECTOR
Q3[3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3.0, 3.0, 4.0, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3.0, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3.0, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3.0, 3.8, 3.2, 3.7, 3.3, 3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2.0, 3.0, 2.2, 2.9, 2.9, 3.1, 3.0, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3.0, 2.8, 3.0, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3.0, 3.4, 3.1, 2.3, 3.0, 2.5, 2.6, 3.0, 2.6, 2.3, 2.7, 3.0, 2.9, 2.9, 2.5, 2.8, 3.3, 2.7, 3.0, 2.9, 3.0, 3.0, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3.0, 2.5, 2.8, 3.2, 3.0, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3.0, 2.8, 3.0, 2.8, 3.8, 2.8, 2.8, 2.6, 3.0, 3.4, 3.1, 3.0, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3.0, 2.5, 3.0, 3.4, 3.0]
2, 1, 2, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 0, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 0, 0, 0, 2, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 2, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 2, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 2, 0, 1, 1, 1, 1, 0, 1, 0, 2, 2, 0, 1, 0, 0, 2, 1, 2, 0, 0, 2, 0, 0, 0, 2, 2, 0, 1, 0, 1, 0, 2, 0, 0, 0, 1, 2, 1, 1, 1, 1, 1, 0, 2, 2, 1, 0, 1, 2, 1
2.0, 2.9, 3.2, 4.4
VECTOR
U3[3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3.0, 3.0, 4.0, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3.0, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3.0, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3.0, 3.8, 3.2, 3.7, 3.3, 3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2.0, 3.0, 2.2, 2.9, 2.9, 3.1, 3.0, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3.0, 2.8, 3.0, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3.0, 3.4, 3.1, 2.3, 3.0, 2.5, 2.6, 3.0, 2.6, 2.3, 2.7, 3.0, 2.9, 2.9, 2.5, 2.8, 3.3, 2.7, 3.0, 2.9, 3.0, 3.0, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3.0, 2.5, 2.8, 3.2, 3.0, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3.0, 2.8, 3.0, 2.8, 3.8, 2.8, 2.8, 2.6, 3.0, 3.4, 3.1, 3.0, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3.0, 2.5, 3.0, 3.4, 3.0]
1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 2, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 1, 1, 2, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 2, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1
2.0, 2.8, 3.6, 4.4
VECTOR
Q4[3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3.0, 3.0, 4.0, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3.0, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3.0, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3.0, 3.8, 3.2, 3.7, 3.3, 3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2.0, 3.0, 2.2, 2.9, 2.9, 3.1, 3.0, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3.0, 2.8, 3.0, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3.0, 3.4, 3.1, 2.3, 3.0, 2.5, 2.6, 3.0, 2.6, 2.3, 2.7, 3.0, 2.9, 2.9, 2.5, 2.8, 3.3, 2.7, 3.0, 2.9, 3.0, 3.0, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3.0, 2.5, 2.8, 3.2, 3.0, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3.0, 2.8, 3.0, 2.8, 3.8, 2.8, 2.8, 2.6, 3.0, 3.4, 3.1, 3.0, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3.0, 2.5, 3.0, 3.4, 3.0]
3, 2, 2, 2, 3, 3, 3, 3, 1, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 2, 2, 3, 3, 3, 2, 2, 3, 3, 2, 3, 3, 0, 2, 3, 3, 2, 3, 2, 3, 3, 2, 2, 2, 0, 1, 1, 3, 0, 1, 0, 0, 2, 0, 1, 1, 2, 2, 0, 0, 0, 2, 1, 0, 1, 1, 2, 1, 2, 1, 0, 0, 0, 0, 0, 2, 3, 2, 0, 2, 0, 0, 2, 0, 0, 0, 2, 1, 1, 0, 1, 3, 0, 2, 1, 2, 2, 0, 1, 0, 3, 2, 0, 2, 0, 1, 2, 2, 3, 0, 0, 2, 1, 1, 0, 3, 2, 1, 2, 1, 2, 1, 3, 1, 1, 0, 2, 3, 2, 2, 2, 2, 2, 0, 2, 3, 2, 0, 2, 3, 2
2.0, 2.8, 3.0, 3.3, 4.4
VECTOR
U4[3.5, 3.0, 3.2, 3.1, 3.6, 3.9, 3.4, 3.4, 2.9, 3.1, 3.7, 3.4, 3.0, 3.0, 4.0, 4.4, 3.9, 3.5, 3.8, 3.8, 3.4, 3.7, 3.6, 3.3, 3.4, 3.0, 3.4, 3.5, 3.4, 3.2, 3.1, 3.4, 4.1, 4.2, 3.1, 3.2, 3.5, 3.6, 3.0, 3.4, 3.5, 2.3, 3.2, 3.5, 3.8, 3.0, 3.8, 3.2, 3.7, 3.3, 3.2, 3.2, 3.1, 2.3, 2.8, 2.8, 3.3, 2.4, 2.9, 2.7, 2.0, 3.0, 2.2, 2.9, 2.9, 3.1, 3.0, 2.7, 2.2, 2.5, 3.2, 2.8, 2.5, 2.8, 2.9, 3.0, 2.8, 3.0, 2.9, 2.6, 2.4, 2.4, 2.7, 2.7, 3.0, 3.4, 3.1, 2.3, 3.0, 2.5, 2.6, 3.0, 2.6, 2.3, 2.7, 3.0, 2.9, 2.9, 2.5, 2.8, 3.3, 2.7, 3.0, 2.9, 3.0, 3.0, 2.5, 2.9, 2.5, 3.6, 3.2, 2.7, 3.0, 2.5, 2.8, 3.2, 3.0, 3.8, 2.6, 2.2, 3.2, 2.8, 2.8, 2.7, 3.3, 3.2, 2.8, 3.0, 2.8, 3.0, 2.8, 3.8, 2.8, 2.8, 2.6, 3.0, 3.4, 3.1, 3.0, 3.1, 3.1, 3.1, 2.7, 3.2, 3.3, 3.0, 2.5, 3.0, 3.4, 3.0]
2, 1, 2, 1, 2, 3, 2, 2, 1, 1, 2, 2, 1, 1, 3, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 3, 3, 1, 2, 2, 2, 1, 2, 2, 0, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 0, 1, 1, 2, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 2, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 2, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 2, 1, 1, 1, 1, 1, 0, 1, 0, 2, 2, 1, 1, 0, 1, 2, 1, 2, 1, 0, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 0, 1, 2, 1
2.0, 2.6, 3.2, 3.8, 4.4
VECTOR
Q3[1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1.0, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4, 4.7, 4.5, 4.9, 4.0, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4.0, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4.0, 4.9, 4.7, 4.3, 4.4, 4.8, 5.0, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4.0, 4.4, 4.6, 4.0, 3.3, 4.2, 4.2, 4.2, 4.3, 3.0, 4.1, 6.0, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5.0, 5.1, 5.3, 5.5, 6.7, 6.9, 5.0, 5.7, 4.9, 6.7, 4.9, 5.7, 6.0, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5.0, 5.2, 5.4, 5.1]
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
1.0, 2.63333, 4.9, 6.9
VECTOR
U3[1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1.0, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4, 4.7, 4.5, 4.9, 4.0, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4.0, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4.0, 4.9, 4.7, 4.3, 4.4, 4.8, 5.0, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4.0, 4.4, 4.6, 4.0, 3.3, 4.2, 4.2, 4.2, 4.3, 3.0, 4.1, 6.0, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5.0, 5.1, 5.3, 5.5, 6.7, 6.9, 5.0, 5.7, 4.9, 6.7, 4.9, 5.7, 6.0, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5.0, 5.2, 5.4, 5.1]
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
1.0, 2.96667, 4.93333, 6.9
VECTOR
Q4[1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1.0, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4, 4.7, 4.5, 4.9, 4.0, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4.0, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4.0, 4.9, 4.7, 4.3, 4.4, 4.8, 5.0, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4.0, 4.4, 4.6, 4.0, 3.3, 4.2, 4.2, 4.2, 4.3, 3.0, 4.1, 6.0, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5.0, 5.1, 5.3, 5.5, 6.7, 6.9, 5.0, 5.7, 4.9, 6.7, 4.9, 5.7, 6.0, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5.0, 5.2, 5.4, 5.1]
0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 2, 2, 2, 1, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2, 2, 1, 2, 2, 2, 2, 1, 1, 1, 1, 3, 2, 2, 2, 2, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 2, 3, 2, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3
1.0, 1.6, 4.35, 5.1, 6.9
VECTOR
U4[1.4, 1.4, 1.3, 1.5, 1.4, 1.7, 1.4, 1.5, 1.4, 1.5, 1.5, 1.6, 1.4, 1.1, 1.2, 1.5, 1.3, 1.4, 1.7, 1.5, 1.7, 1.5, 1.0, 1.7, 1.9, 1.6, 1.6, 1.5, 1.4, 1.6, 1.6, 1.5, 1.5, 1.4, 1.5, 1.2, 1.3, 1.4, 1.3, 1.5, 1.3, 1.3, 1.3, 1.6, 1.9, 1.4, 1.6, 1.4, 1.5, 1.4, 4.7, 4.5, 4.9, 4.0, 4.6, 4.5, 4.7, 3.3, 4.6, 3.9, 3.5, 4.2, 4.0, 4.7, 3.6, 4.4, 4.5, 4.1, 4.5, 3.9, 4.8, 4.0, 4.9, 4.7, 4.3, 4.4, 4.8, 5.0, 4.5, 3.5, 3.8, 3.7, 3.9, 5.1, 4.5, 4.5, 4.7, 4.4, 4.1, 4.0, 4.4, 4.6, 4.0, 3.3, 4.2, 4.2, 4.2, 4.3, 3.0, 4.1, 6.0, 5.1, 5.9, 5.6, 5.8, 6.6, 4.5, 6.3, 5.8, 6.1, 5.1, 5.3, 5.5, 5.0, 5.1, 5.3, 5.5, 6.7, 6.9, 5.0, 5.7, 4.9, 6.7, 4.9, 5.7, 6.0, 4.8, 4.9, 5.6, 5.8, 6.1, 6.4, 5.6, 5.1, 5.6, 6.1, 5.6, 5.5, 4.8, 5.4, 5.6, 5.1, 5.1, 5.9, 5.7, 5.2, 5.0, 5.2, 5.4, 5.1]
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 3, 2, 3, 3, 3, 3, 2, 3, 3, 3, 2, 2, 3, 2, 2, 2, 3, 3, 3, 2, 3, 2, 3, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 2, 2, 3, 2, 2, 3, 3, 2, 2, 2, 2, 2
1.0, 2.475, 3.95, 5.425, 6.9
VECTOR
Q3[0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1.0, 1.3, 1.4, 1.0, 1.5, 1.0, 1.4, 1.3, 1.4, 1.5, 1.0, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1.0, 1.1, 1.0, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1.0, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2.0, 1.9, 2.1, 2.0, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2.0, 2.0, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2.0, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2.0, 2.3, 1.8]
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
0.1, 0.86667, 1.6, 2.5
VECTOR
U3[0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1.0, 1.3, 1.4, 1.0, 1.5, 1.0, 1.4, 1.3, 1.4, 1.5, 1.0, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1.0, 1.1, 1.0, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1.0, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2.0, 1.9, 2.1, 2.0, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2.0, 2.0, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2.0, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2.0, 2.3, 1.8]
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2
0.1, 0.9, 1.7, 2.5
VECTOR
Q4[0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1.0, 1.3, 1.4, 1.0, 1.5, 1.0, 1.4, 1.3, 1.4, 1.5, 1.0, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1.0, 1.1, 1.0, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1.0, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2.0, 1.9, 2.1, 2.0, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2.0, 2.0, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2.0, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2.0, 2.3, 1.8]
0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 2, 1, 3, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3
0.1, 0.3, 1.3, 1.8, 2.5
VECTOR
U4[0.2, 0.2, 0.2, 0.2, 0.2, 0.4, 0.3, 0.2, 0.2, 0.1, 0.2, 0.2, 0.1, 0.1, 0.2, 0.4, 0.4, 0.3, 0.3, 0.3, 0.2, 0.4, 0.2, 0.5, 0.2, 0.2, 0.4, 0.2, 0.2, 0.2, 0.2, 0.4, 0.1, 0.2, 0.2, 0.2, 0.2, 0.1, 0.2, 0.2, 0.3, 0.3, 0.2, 0.6, 0.4, 0.3, 0.2, 0.2, 0.2, 0.2, 1.4, 1.5, 1.5, 1.3, 1.5, 1.3, 1.6, 1.0, 1.3, 1.4, 1.0, 1.5, 1.0, 1.4, 1.3, 1.4, 1.5, 1.0, 1.5, 1.1, 1.8, 1.3, 1.5, 1.2, 1.3, 1.4, 1.4, 1.7, 1.5, 1.0, 1.1, 1.0, 1.2, 1.6, 1.5, 1.6, 1.5, 1.3, 1.3, 1.3, 1.2, 1.4, 1.2, 1.0, 1.3, 1.2, 1.3, 1.3, 1.1, 1.3, 2.5, 1.9, 2.1, 1.8, 2.2, 2.1, 1.7, 1.8, 1.8, 2.5, 2.0, 1.9, 2.1, 2.0, 2.4, 2.3, 1.8, 2.2, 2.3, 1.5, 2.3, 2.0, 2.0, 1.8, 2.1, 1.8, 1.8, 1.8, 2.1, 1.6, 1.9, 2.0, 2.2, 1.5, 1.4, 2.3, 2.4, 1.8, 1.8, 2.1, 2.4, 2.3, 1.9, 2.3, 2.5, 2.3, 1.9, 2.0, 2.3, 1.8]
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 2, 2, 2, 1, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 3, 3, 3, 2, 3, 3, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 2, 3, 2, 2, 2, 3, 2, 3, 3, 3, 2, 2, 3, 3, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2
0.1, 0.7, 1.3, 1.9, 2.5

13
tests/tests_do.py
View File

@@ -6,6 +6,7 @@ with open("datasets/tests.txt") as f:
data = [x.strip() for x in data if x[0] != "#"] data = [x.strip() for x in data if x[0] != "#"]
errors = False
for i in range(0, len(data), 4): for i in range(0, len(data), 4):
experiment_type = data[i] experiment_type = data[i]
print("Experiment:", data[i + 1]) print("Experiment:", data[i + 1])
@@ -31,20 +32,28 @@ for i in range(0, len(data), 4):
result = disc.transform(X) result = disc.transform(X)
result = [int(x) for x in result.flatten()] result = [int(x) for x in result.flatten()]
expected = [int(x) for x in expected_data.split(",")] expected = [int(x) for x in expected_data.split(",")]
#
# Check the Results
#
assert len(result) == len(expected) assert len(result) == len(expected)
for j in range(len(result)): for j in range(len(result)):
if result[j] != expected[j]: if result[j] != expected[j]:
print("Error at", j, "Expected=", expected[j], "Result=", result[j]) print("* Error at", j, "Expected=", expected[j], "Result=", result[j])
errors = True
expected_cuts = disc.bin_edges_[0] expected_cuts = disc.bin_edges_[0]
computed_cuts = [float(x) for x in cuts_data.split(",")] computed_cuts = [float(x) for x in cuts_data.split(",")]
assert len(expected_cuts) == len(computed_cuts) assert len(expected_cuts) == len(computed_cuts)
for j in range(len(expected_cuts)): for j in range(len(expected_cuts)):
if round(expected_cuts[j], 5) != computed_cuts[j]: if round(expected_cuts[j], 5) != computed_cuts[j]:
print( print(
"Error at", "* Error at",
j, j,
"Expected=", "Expected=",
expected_cuts[j], expected_cuts[j],
"Result=", "Result=",
computed_cuts[j], computed_cuts[j],
) )
errors = True
if errors:
raise Exception("There were errors!")
print("*** All tests run succesfully! ***")

93
tests/tests_generate.ipynb
View File

@@ -6,7 +6,8 @@
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"from sklearn.preprocessing import KBinsDiscretizer" "from sklearn.preprocessing import KBinsDiscretizer\n",
"from sklearn.datasets import load_iris"
] ]
}, },
{ {
@@ -84,6 +85,12 @@
" file.write(\"# discretized data\\n\")\n", " file.write(\"# discretized data\\n\")\n",
" file.write(\"# cut points\\n\")\n", " file.write(\"# cut points\\n\")\n",
" file.write(\"#\\n\")\n", " file.write(\"#\\n\")\n",
" #\n",
" # Range experiments\n",
" #\n",
" file.write(\"#\\n\")\n",
" file.write(\"# Range experiments\\n\")\n",
" file.write(\"#\\n\")\n",
" for experiment in experiments_range:\n", " for experiment in experiments_range:\n",
" file.write(\"RANGE\\n\")\n", " file.write(\"RANGE\\n\")\n",
" (from_, to_, step_, bins_, strategy) = experiment\n", " (from_, to_, step_, bins_, strategy) = experiment\n",
@@ -93,6 +100,12 @@
" result = disc.transform(data)\n", " result = disc.transform(data)\n",
" file.write(f\"{from_}, {to_}, {step_}, {bins_}, {strategy}\\n\")\n", " file.write(f\"{from_}, {to_}, {step_}, {bins_}, {strategy}\\n\")\n",
" write_lists(file, result, disc.bin_edges_[0])\n", " write_lists(file, result, disc.bin_edges_[0])\n",
" #\n",
" # Vector experiments\n",
" #\n",
" file.write(\"#\\n\")\n",
" file.write(\"# Vector experiments\\n\")\n",
" file.write(\"#\\n\")\n",
" for n_bins, experiment in experiments_vectors:\n", " for n_bins, experiment in experiments_vectors:\n",
" for strategy in [\"Q\", \"U\"]:\n", " for strategy in [\"Q\", \"U\"]:\n",
" file.write(\"VECTOR\\n\")\n", " file.write(\"VECTOR\\n\")\n",
@@ -105,8 +118,84 @@
" )\n", " )\n",
" data = [[x] for x in experiment]\n", " data = [[x] for x in experiment]\n",
" result = disc.fit_transform(data)\n", " result = disc.fit_transform(data)\n",
" write_lists(file, result, disc.bin_edges_[0])" " write_lists(file, result, disc.bin_edges_[0])\n",
" #\n",
" # Vector experiments iris\n",
" #\n",
" file.write(\"#\\n\");\n",
" file.write(\"# Vector experiments with iris\\n\");\n",
" file.write(\"#\\n\");\n",
" X, y = load_iris(return_X_y=True)\n",
" for i in range(X.shape[1]):\n",
" for n_bins in [3, 4]:\n",
" for strategy in [\"Q\", \"U\"]:\n",
" file.write(\"VECTOR\\n\")\n",
" experiment = X[:, i]\n",
" file.write(f\"{strategy}{n_bins}{experiment.tolist()}\\n\")\n",
" disc = KBinsDiscretizer(\n",
" n_bins=n_bins,\n",
" encode=\"ordinal\",\n",
" strategy=\"quantile\" if strategy.strip() == \"Q\" else \"uniform\")\n",
" data = [[x] for x in experiment]\n",
" result = disc.fit_transform(data)\n",
" write_lists(file, result, disc.bin_edges_[0])"
] ]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Cut points [array([ 0., 33., 66., 99.])]\n",
"i=32 X[32]=[32] result[32]=[0.]\n",
"i=33 X[33]=[33] result[33]=[1.]\n",
"i=34 X[34]=[34] result[34]=[1.]\n",
"i=65 X[65]=[65] result[65]=[1.]\n",
"i=66 X[66]=[66] result[66]=[2.]\n",
"i=67 X[67]=[67] result[67]=[2.]\n"
]
}
],
"source": [
"X = [[x] for x in range(100)]\n",
"disc = KBinsDiscretizer(n_bins=3, encode=\"ordinal\", strategy=\"uniform\")\n",
"result = disc.fit_transform(X)\n",
"print(\"Cut points\", disc.bin_edges_)\n",
"test = [32, 33, 34, 65, 66, 67]\n",
"for i in test:\n",
" print(f\"{i=} X[{i}]={X[i]} result[{i}]={result[i]}\")"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"right [0 1 1 1 2 2]\n",
"left [0 0 1 1 1 2]\n"
]
}
],
"source": [
"import numpy as np\n",
"print(\"right\", np.searchsorted(disc.bin_edges_[0][1:-1],test, side=\"right\"))\n",
"print(\"left \", np.searchsorted(disc.bin_edges_[0][1:-1],test))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {