Expand knowledge search with reconstruction step.

cml/usecases/query.py

@@ -3,6 +3,7 @@ from os.path import expanduser, join
 from datetime import datetime
 from logging import getLogger, FileHandler, StreamHandler
 
+from cml.shared.errors import NoModelReconstructedError
 from cml.shared.parameter import PROTOCOL_LEVEL
 from cml.usecases.usecase import Usecase
 from cml.domain import (
@@ -44,24 +45,31 @@ class FeatureSelectionUsecase(Usecase):
 
 class ReconstructionUsecase(Usecase):
     def process(self, request):
-        return Reconstructor()
+        return Reconstructor(request.settings,
+                             request.ml_models,
+                             request.knowledge_domain)
 
 
 class KnowledgeSearchUsecase(Usecase):
     def process(self, request):
         source, constr, f_selectr, reconstr = self._init_loggers(request)
+        reconstr.category = constr.construction_type
 
         for learnblock in source.learnblocks:
             for complete_learnblock in constr.construct(learnblock):
                 try:
                     reduced_learnblock = f_selectr.select(complete_learnblock)
+                    pragmatic_model = reconstr.reconstruct(reduced_learnblock)
                 except ValueError as error:
                     # Can't reduce learnblock
                     # log
                     continue
+                except NoModelReconstructedError:
+                    continue
                 else:
                     # process with reconstruction
-                    pass
+                    if pragmatic_model:
+                        print(pragmatic_model.model.mean_error)
 
     def _init_loggers(self, request):
         log_dir = create_log_dir()