slight modifications to python interface and regressor changes

don't reset inds, just don't loop in initial inds.back() < 0

src/descriptor_identifier/SISSO_DI/SISSORegressor.cpp

@@ -92,14 +92,12 @@ void SISSORegressor::l0_norm(std::vector<double>& prop, int n_dim)
 
     for(int rr = 0; rr < n_dim; ++rr)
         inds[rr] = _feat_space->phi_selected().size() - 1 - rr;
-    util_funcs::iterate(inds, inds.size(), _mpi_comm->rank());
-
-    if(inds.back() < 0)
-        for(int rr = 0; rr < n_dim; ++rr)
-            inds[rr] = _feat_space->phi_selected().size() - 1 - rr;
 
+    util_funcs::iterate(inds, inds.size(), _mpi_comm->rank());
     int max_error_ind = 0;
 
+    if(inds.back() >= 0)
+    {
         do {
             int start = 0;
             double error = 0.0;
@@ -120,6 +118,7 @@ void SISSORegressor::l0_norm(std::vector<double>& prop, int n_dim)
                 max_error_ind = std::max_element(min_errors.begin(), min_errors.end()) - min_errors.begin();
             }
         } while(util_funcs::iterate(inds, inds.size(), _mpi_comm->size()));
+    }
 
     std::vector<double> all_min_error(_mpi_comm->size() * n_get_models);
     std::vector<int> all_inds_min(_mpi_comm->size() * n_get_models * n_dim);

src/python/classification/svm.py

@@ -3,7 +3,7 @@ import numpy as np
 from cpp_sisso import ModelClassifier
 
 
-def update_model_svm(model, c=1.0, max_iter=100000, tol=0.01, filename=None):
+def update_model_svm(model, c=1.0, max_iter=-1, tol=0.0001, filename=None):
     """Generate a new model with an updated SVM from sckitlearn
 
     Args: