Introduced result object and readapted interface for it.

force_bdss/core_mco_driver.py

@@ -35,6 +35,7 @@ class CoreMCODriver(Plugin):
     def application_started(self):
         workflow = self.application.workflow
         if self.application.evaluate:
+            ds_results = []
             for requested_ds in workflow.data_sources:
                 ds_bundle = self._find_data_source_bundle_by_name(
                     requested_ds.name)
@@ -42,7 +43,7 @@ class CoreMCODriver(Plugin):
                     ds_model = ds_bundle.create_model(requested_ds.model_data)
                     data_source = ds_bundle.create_data_source(
                         self.application, ds_model)
-                    print(data_source.run())
+                    ds_results.append(data_source.run())
                 else:
                     raise Exception("Requested data source {} but don't know "
                                     "to find it.".format(requested_ds.name))

force_bdss/core_plugins/csv_extractor/csv_extractor/csv_extractor_data_source.py

 import csv
+import numpy
 from force_bdss.data_sources.base_data_source import BaseDataSource
+from force_bdss.data_sources.data_source_result import DataSourceResult
 
 
 class CSVExtractorDataSource(BaseDataSource):
@@ -11,9 +13,11 @@ class CSVExtractorDataSource(BaseDataSource):
                     continue
 
                 if rowindex == self.model.row:
-                    return {
-                        self.model.cuba_type: row[self.model.column]
-                    }
+                    return DataSourceResult(
+                        originator=self,
+                        value_types = [self.model.cuba_type],
+                        values=numpy.array(row[self.model.column]).reshape(1,1)
+                    )
 
                 return None
             return None

force_bdss/data_sources/data_source_result.py

-from traits.api import HasTraits, Array, List, String, Instance
+from traits.api import HasTraits, Array, ArrayOrNone, List, String, Instance
 
 from .base_data_source import BaseDataSource
 
@@ -12,9 +12,8 @@ class DataSourceResult(HasTraits):
     quality is the level of accuracy of the (e.g.c omputational) method, as
     the importance and reliability of that value. It should be an enumeration
     value such as HIGH, MEDIUM, POOR"""
-
     originator = Instance(BaseDataSource)
     value_types = List(String)
-    results = Array(shape=(None, None))
-    accuracy = Array(shape=(None, None))
-    quality = Array(shape=(None, None))
+    values = Array(shape=(None, None))
+    accuracy = ArrayOrNone(shape=(None, None))
+    quality = ArrayOrNone(shape=(None, None))

requirements/requirements.txt

@@ -2,3 +2,4 @@ envisage==4.6.0
 click==6.7
 six==1.10.0
 stevedore==1.24.0
+numpy=1.12.0

setup.py

@@ -21,6 +21,7 @@ setup(
         "envisage >= 4.6.0",
         "click >= 6.7",
         "stevedore >= 1.24.0",
-        "six >= 1.10.0"
+        "six >= 1.10.0",
+        "numpy >= 1.12.0",
     ]
 )