Response params and available columns from operations api

cognitive/app/models.py

@@ -15,6 +15,7 @@
 from django.db import models
 from django.core.validators import validate_email
 from django.core.exceptions import ValidationError
+from jsonfield import JSONField
 import string
 import random
 
@@ -54,6 +55,8 @@ class Data_operation_type(models.Model):
     function_arg = models.CharField(max_length=50, choices=FUNCTION_ARG)
     function_arg_id = models.CharField(max_length=50, blank=True, null=True)
     function_subtype = models.CharField(max_length=50, choices=FUNCTION_SUBTYPE)
+
+    # This should be JSON format
     function_subtype_arg = models.CharField(max_length=50, blank=True, null=True)
 
     def __str__(self):
@@ -167,6 +170,7 @@ class Component(models.Model):
     execution_end_time = models.DateField(blank=True, null=True)
     data_location = models.CharField(max_length=50, blank=True, null=True)
     preferred_data_location = models.CharField(max_length=50, blank=True, null=True)
+    outputs = JSONField()
     # component_id = models.IntegerField(blank=True, null=True)
 
 

cognitive/app/serializers.py

@@ -12,8 +12,10 @@
 # License for the specific language governing permissions and limitations
 # under the License.
 
+import json
+
 from rest_framework import serializers
-from .models import User, Experiment, Component, Workflow
+from .models import User, Experiment, Component, Workflow, Data_operation_type
 
 
 class UserSerializer(serializers.ModelSerializer):
@@ -35,11 +37,32 @@ class Meta:
         #        'execution_start_time', 'execution_end_time', 'component_start_id')
 
 
+class ComponentOutputValue(serializers.ModelSerializer):
+    class Meta:
+        fields = ('function_subtype', 'function_subtype_arg')
+        model = Data_operation_type
+
+
 class ComponentSerializer(serializers.ModelSerializer):
+    type = serializers.SerializerMethodField('component_type')
+    params = serializers.SerializerMethodField('component_params')
 
     class Meta:
         model = Component
 
+    def component_type(self, obj):
+        return obj.operation_type.function_subtype
+
+    def component_params(self, obj):
+        data = obj.operation_type.function_subtype_arg
+        if data is None:
+            return ''
+        elif data.startswith(('[', '{')):
+            return json.loads(data)
+        else:
+            # TODO(|Less Priority| All Data_operation_type.function_subtype_arg values should be JSON)
+            return data
+
 
 class WorkflowSerializer(serializers.ModelSerializer):
 

cognitive/app/static/app/whiteboard/experiment/directive/node.directive.js

@@ -63,8 +63,8 @@
                         .on("dragend", finishDrawingConnection));
 
                 g.append('text')
-                    .attr('x', '{{node.x - 15}}')
-                    .attr('y', '{{node.y - 5}}')
+                    .attr('ng-attr-x', '{{node.x - 15}}')
+                    .attr('ng-attr-y', '{{node.y - 5}}')
                     .attr('font-family', 'FontAwesome')
                     .attr('class', 'node close-icon')
                     .attr('node', '{{node.id}}')

cognitive/app/view/view_operation.py

@@ -19,10 +19,19 @@
 from rest_framework.renderers import JSONRenderer
 from pandas import read_csv, datetime
 import json
+import re
 import urllib2
 
 MAX_COMPONENTS_PER_EXP = 100
 
+def get_csv_fields(csv_data):
+    for line in re.split('\n|\r', csv_data):
+        if line == '':
+            continue
+        parsed_line = line.split(',')
+        return [{'id': i,'name': parsed_line[i]} for i in range(len(parsed_line))]
+    return []
+
 #####
 # Operation      function_type function_arg function_subtype function_arg_id function_subtype_arg
 # mathformula       Update      {comp_type}  {op_type}        {comp_id}       {op_constant}
@@ -35,7 +44,6 @@
 # input             Create      Table        Input            -               {filename}
 # machine learning  Create      Model        {model_type}     {Train-test}    {ML arguments}
 
-
 class OperationViewSet(viewsets.ViewSet):
 
     def set_operation(self, operation, data):
@@ -178,9 +186,14 @@ def create(self, request, operation):
         print "Experiment ", exp_id, " Operation ", operation
         op = self.set_operation(operation, data)
 
+        outputs = []
+        if operation == 'input' and data["input_file_type"] == "csv":
+            outputs = get_csv_fields(data["data_values"])
+
         component = Component(
             experiment=exp, created_time=datetime.now(),
-            modified_time=datetime.now(), operation_type=op)
+            modified_time=datetime.now(), operation_type=op, outputs=outputs)
+
         component.save()
         serializer = ComponentSerializer(component)
         return send_response("GET", serializer)

cognitive/app/view/view_result_local.py

@@ -112,10 +112,10 @@ def run(self):
                                 input_data, model_type, train_data_percentage,
                                 input_features, target_feature)
                             output_data = classifier.learn()
-                        except ValueError as e:
+                        except ValueError:
                             status = "failure"
                             err_msg = " Invalid input for the model training"
-                        except KeyError as e:
+                        except KeyError:
                             status = "failure"
                             err_msg = target_feature + " column is not available for Model Training"
 
@@ -132,72 +132,72 @@ def run(self):
                         column_id = float(op.function_arg_id)
                         column_name = feature_names[column_id]
                         if column_name not in input_data:
-                            #print "Column name ", column_name, " not present. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " not present. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
                             err_msg = column_name + " column is not available for current operation"
                         elif input_data[column_name].dtype == 'object':
-                            #print "Column name ", column_name, " is not integer/float. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " is not integer/float. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
-                            err_msg = " Invalid input in column "+ column_name+ " for the current operation"
+                            err_msg = " Invalid input in column " + column_name + " for the current operation"
                         else:
                             input_data[column_name] += constant_value
                     if op.function_subtype == 'Sub':
                         constant_value = float(op.function_subtype_arg)
                         column_id = float(op.function_arg_id)
                         column_name = feature_names[column_id]
                         if column_name not in input_data:
-                            #print "Column name ", column_name, " not present. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " not present. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
                             err_msg = column_name + " column is not available for current operation"
                         elif input_data[column_name].dtype == 'object':
-                            #print "Column name ", column_name, " is not integer/float. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " is not integer/float. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
-                            err_msg = " Invalid input in column "+ column_name+ " for the current operation"
+                            err_msg = " Invalid input in column " + column_name + " for the current operation"
                         else:
                             input_data[column_name] -= constant_value
                     if op.function_subtype == 'Mult':
                         constant_value = float(op.function_subtype_arg)
                         column_id = float(op.function_arg_id)
                         column_name = feature_names[column_id]
                         if column_name not in input_data:
-                            #print "Column name ", column_name, " not present. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " not present. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
                             err_msg = column_name + " column is not available for current operation"
                         elif input_data[column_name].dtype == 'object':
-                            #print "Column name ", column_name, " is not integer/float. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " is not integer/float. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
-                            err_msg = " Invalid input in column "+ column_name+ " for the current operation"
+                            err_msg = " Invalid input in column " + column_name + " for the current operation"
                         else:
                             input_data[column_name] *= constant_value
                     if op.function_subtype == 'Div':
                         constant_value = float(op.function_subtype_arg)
                         column_id = float(op.function_arg_id)
                         column_name = feature_names[column_id]
                         if column_name not in input_data:
-                            #print "Column name ", column_name, " not present. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " not present. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
                             err_msg = column_name + " column is not available for current operation"
                         elif input_data[column_name].dtype == 'object':
-                            #print "Column name ", column_name, " is not integer/float. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " is not integer/float. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
-                            err_msg = " Invalid input in column "+ column_name+ " for the current operation"
+                            err_msg = " Invalid input in column " + column_name + " for the current operation"
                         else:
                             input_data[column_name] /= constant_value
                     if op.function_subtype == 'Normalize':
                         column_id = float(op.function_arg_id)
                         column_name = feature_names[column_id]
                         sum_array = input_data.sum(axis=0)
                         if column_name not in sum_array:
-                            #print "Column name ", column_name, " not present. Skipping"
-                            #continue  # throw error in module status
+                            # print "Column name ", column_name, " not present. Skipping"
+                            # continue  # throw error in module status
                             status = "failure"
                             err_msg = column_name + " column is not available for current operation"
                         else:
@@ -222,8 +222,8 @@ def run(self):
                         for elem in column_id_list:
                             column_name = feature_names[elem]
                             if column_name not in input_data:
-                                #print "Column name ", column_name, " not present. Skipping"
-                                #continue  # throw error in module status
+                                # print "Column name ", column_name, " not present. Skipping"
+                                # continue  # throw error in module status
                                 status = "failure"
                                 err_msg = column_name + " column is not available for current operation"
                             else:
@@ -330,7 +330,7 @@ def run(self):
                 if self.cache_results is True:
                     CACHE[self.experiment] = input_data
 
-                #print self.result
+                # print self.result
                 print self.result["status"]
                 print self.result["message"]
                 break

requirements.txt

@@ -1,14 +1,15 @@
-Django==1.7.1
+Django>=1.7.1
 django-rest-swagger>=0.2.9
 Markdown==2.5.1
 Pygments==2.0.1
-django-bower==5.0.1
+django-bower>=5.0.1
 django-mptt==0.6.1
 django-treebeard==2.0
 djangorestframework==2.4.4
-hamlpy==0.82.2
+hamlpy>=0.82.2
 jasmine==2.3.0
 jasmine-core==2.3.4
+jsonfield>=1.0.3
 numpy==1.9.1
 pandas==0.15.1
 python-dateutil==2.2