fix #290

feat/feat.py

@@ -302,7 +302,7 @@ def predict(self,X,Z=None):
         else:
             return self.cfeat_.predict(X)
 
-    def predict_archive(self,X,Z=None):
+    def predict_archive(self,X,Z=None,front=False):
         """Returns a list of dictionary predictions for all models."""
         if not self.is_fitted_:
             raise ValueError("Call fit before calling predict.")
@@ -313,9 +313,11 @@ def predict_archive(self,X,Z=None):
             raise NotImplementedError('longitudinal not implemented')
             return
 
-        archive = self.cfeat_.get_archive(False)
+        archive = self.cfeat_.get_archive(front)
         preds = []
         for ind in archive:
+            if ind['id'] == 9234:
+                print('individual:',json.dumps(ind,indent=2))
             tmp = {}
             tmp['id'] = ind['id']
             tmp['y_pred'] = self.cfeat_.predict_archive(ind['id'], X) 

feat/versionstr.py

@@ -1 +1 @@
-__version__="0.5.2.post115"
+__version__="0.5.2.post116"

src/feat.cc

@@ -1203,17 +1203,29 @@ VectorXf Feat::predict_archive(int id, MatrixXf& X, LongData& Z)
     Data tmp_data(X,empty_y,Z);
 
     /* cout << "individual prediction id " << id << "\n"; */
+    if (id == best_ind.id)
+    {
+        return best_ind.predict_vector(tmp_data);
+    }
     for (int i = 0; i < this->archive.individuals.size(); ++i)
     {
         Individual& ind = this->archive.individuals.at(i);
 
         if (id == ind.id)
             return ind.predict_vector(tmp_data);
 
+    }
+    for (int i = 0; i < this->pop.individuals.size(); ++i)
+    {
+        Individual& ind = this->pop.individuals.at(i);
+
+        if (id == ind.id)
+            return ind.predict_vector(tmp_data);
+
     }
 
     THROW_INVALID_ARGUMENT("Could not find id = "
-            + to_string(id) + "in archive.");
+            + to_string(id) + "in archive or population.");
     return VectorXf();
 }