Update algorithm type to compute cut points

samples/sample.cpp

@@ -41,7 +41,7 @@ int main(int argc, char** argv)
         }
         cout << y[i] << endl;
     }
-    mdlp::CPPFImdlp test = mdlp::CPPFImdlp(false);
+    mdlp::CPPFImdlp test = mdlp::CPPFImdlp(0);
     for (auto i = 0; i < attributes.size(); i++) {
         cout << "Cut points for " << get<0>(attributes[i]) << endl;
         cout << "--------------------------" << setprecision(3) << endl;

src/fimdlp/_version.py

@@ -1 +1 @@
-__version__ = "0.9.1"
+__version__ = "0.9.2"

src/fimdlp/cfimdlp.pyx

@@ -6,7 +6,7 @@ from libcpp cimport bool
 cdef extern from "../cppmdlp/CPPFImdlp.h" namespace "mdlp":
     ctypedef float precision_t
     cdef cppclass CPPFImdlp:
-        CPPFImdlp(bool) except + 
+        CPPFImdlp(int) except + 
         CPPFImdlp& fit(vector[precision_t]&, vector[int]&)
         vector[precision_t] getCutPoints()
         

src/fimdlp/mdlp.py

@@ -7,7 +7,7 @@ from joblib import Parallel, delayed
 
 
 class FImdlp(TransformerMixin, BaseEstimator):
-    def __init__(self, n_jobs=-1, proposal=False):
+    def __init__(self, n_jobs=-1, proposal=0):
         self.n_jobs = n_jobs
         self.proposal = proposal
 
@@ -19,6 +19,11 @@ class FImdlp(TransformerMixin, BaseEstimator):
         The number of jobs to run in parallel. :meth:`fit` and
         :meth:`transform`, are parallelized over the features. ``-1`` means
         using all cores available.
+    proposal : int, default=0
+        The type of algorithm to use computing the cut points.
+        0 - Normal implementation
+        1 - JA Proposal
+        2 - Original proposal
 
     Attributes
     ----------