add pints

xadupre · xadupre · commit 449378e782d3 · 2023-10-03T00:34:32.000+02:00
diff --git a/_unittests/ut_mlmodel/test_piecewise_decision_tree_experiment.py b/_unittests/ut_mlmodel/test_piecewise_decision_tree_experiment.py
@@ -67,7 +67,7 @@ def test_criterions(self):
         _test_criterion_init(c2, ys, w, 1.0, ind, 0, y.shape[0])
         i1 = _test_criterion_node_impurity(c1)
         i2 = _test_criterion_node_impurity(c2)
-        self.assertAlmostEqual(i1, i2)
+        self.assertAlmostEqual(i1, i2, atol=1e-8)
         v1 = _test_criterion_node_value(c1)
         v2 = _test_criterion_node_value(c2)
         self.assertEqual(v1, v2)
@@ -91,7 +91,7 @@ def test_criterions(self):
         _test_criterion_check(c1)
         _test_criterion_check(c2)
         assert_criterion_equal(c1, c2)
-        self.assertAlmostEqual(i1, i2)
+        self.assertAlmostEqual(i1, i2, atol=1e-10)
         v1 = _test_criterion_node_value(c1)
         v2 = _test_criterion_node_value(c2)
         _test_criterion_check(c2)
@@ -112,7 +112,7 @@ def test_criterions(self):
             left1, right1 = _test_criterion_node_impurity_children(c1)
             left2, right2 = _test_criterion_node_impurity_children(c2)
             self.assertAlmostEqual(left1, left2)
-            self.assertAlmostEqual(right1, right2)
+            self.assertAlmostEqual(right1, right2, atol=1e-10)
             v1 = _test_criterion_node_value(c1)
             v2 = _test_criterion_node_value(c2)
             self.assertEqual(v1, v2)
@@ -124,7 +124,7 @@ def test_criterions(self):
                 # scikit-learn < 0.24
                 p1 = _test_criterion_impurity_improvement(c1, 0.0)
                 p2 = _test_criterion_impurity_improvement(c2, 0.0)
-            self.assertAlmostEqual(p1, p2)
+            self.assertAlmostEqual(p1, p2, atol=1e-10)
 
         X = numpy.array([[1.0, 2.0, 10.0, 11.0]]).T
         y = numpy.array([0.9, 1.1, 1.9, 2.1])
@@ -137,7 +137,7 @@ def test_criterions(self):
         _test_criterion_init(c2, ys, w, 1.0, ind, 1, y.shape[0])
         i1 = _test_criterion_node_impurity(c1)
         i2 = _test_criterion_node_impurity(c2)
-        self.assertAlmostEqual(i1, i2)
+        self.assertAlmostEqual(i1, i2, atol=1e-10)
         v1 = _test_criterion_node_value(c1)
         v2 = _test_criterion_node_value(c2)
         self.assertEqual(v1, v2)
@@ -175,8 +175,11 @@ def test_decision_tree_criterion(self):
         crit = SimpleRegressorCriterion(
             1 if len(y.shape) <= 1 else y.shape[1], X.shape[0]
         )
+        print("F0")
         clr2 = DecisionTreeRegressor(criterion=crit, max_depth=1)
+        print("F1")
         clr2.fit(X, y)
+        print("F2")
         p2 = clr2.predict(X)
         self.assertEqual(p1, p2)
         self.assertEqual(clr1.tree_.node_count, clr2.tree_.node_count)
diff --git a/mlinsights/mlmodel/piecewise_tree_regression_criterion.pyx b/mlinsights/mlmodel/piecewise_tree_regression_criterion.pyx
@@ -5,7 +5,7 @@ cimport numpy as cnp
 cnp.import_array()
 
 from libc.stdlib cimport calloc, free
-# from libc.stdio cimport printf
+from libc.stdio cimport printf
 
 from sklearn.tree._criterion cimport SIZE_t, DOUBLE_t
 from ._piecewise_tree_regression_common cimport CommonRegressorCriterion
@@ -116,7 +116,9 @@ cdef class SimpleRegressorCriterion(CommonRegressorCriterion):
         self.end = end
         self.weighted_n_samples = weighted_n_samples
         # Fatal Python error: __pyx_fatalerror: Acquisition count is 0
+        printf("init_with_X:A\n")
         self.y = y
+        printf("init_with_X:B\n")
 
         self.sample_sum_wy = 0.
         self.sample_sum_w = 0.
