First try new cutPoints algorithm

sample.py

@@ -1,10 +1,22 @@
 from sklearn.datasets import load_iris
 from fimdlp.mdlp import FImdlp
 from fimdlp.cppfimdlp import CFImdlp
+import numpy as np
 
 data = load_iris()
 X = data.data
 y = data.target
 features = data.feature_names
 test = FImdlp()
-test.fit(X, y, features=features).transform(X)
+# test.fit(X, y, features=features).transform(X)
+
+X = np.array(
+    [
+        [5.1, 3.5, 1.4, 0.2],
+        [5.2, 3.0, 1.4, 0.2],
+        [5.3, 3.2, 1.3, 0.2],
+        [5.3, 3.1, 1.5, 0.2],
+    ]
+)
+y = np.array([0, 0, 0, 1])
+test.fit(X, y).transform(X)