Updating sample script and a few changes to models and readService.

Author: denvaar

Examples/Sample.py

@@ -22,7 +22,8 @@
 #connect to database
 #createconnection (dbtype, servername, dbname, username, password)
 #session_factory = dbconnection.createConnection('mysql', 'localhost', 'odm2', 'ODM', 'odm')
-session_factory = dbconnection.createConnection('sqlite', '/Users/stephanie/DEV/DBs/ODM2.sqlite', 2.0)
+#session_factory = dbconnection.createConnection('connection type: sqlite|mysql|mssql|postgresql', '/your/path/to/db/goes/here', 2.0)
+session_factory = dbconnection.createConnection('sqlite', '/Users/denversmith/Downloads/ODM2.sqlite', 2.0)
 # session_factory= dbconnection.createConnection('mssql')
 
 
@@ -73,14 +74,21 @@
 try:
     sf = read.getSamplingFeatureByCode('USU-LBR-Mendon')
     print "\n-------- Information about an individual SamplingFeature ---------"
-    print (
-        "The following are some of the attributes of a SamplingFeature retrieved using getSamplingFeatureByCode(): \n" +
-        "SamplingFeatureCode: " + sf.SamplingFeatureCode + "\n" +
-        "SamplingFeatureName: " + sf.SamplingFeatureName + "\n" +
-        "SamplingFeatureDescription: " + sf.SamplingFeatureDescription + "\n" +
-        "SamplingFeatureGeotypeCV: " + sf.SamplingFeatureGeotypeCV + "\n" +
-        "SamplingFeatureGeometry: " + sf.FeatureGeometry + "\n" +
-        "Elevation_m: " + str(sf.Elevation_m))
+    print "The following are some of the attributes of a SamplingFeature retrieved using getSamplingFeatureByCode(): \n"
+    print "SamplingFeatureCode: " + sf.SamplingFeatureCode
+    print "SamplingFeatureName: " + sf.SamplingFeatureName
+    print "SamplingFeatureDescription: %s" % sf.SamplingFeatureDescription
+    print "SamplingFeatureGeotypeCV: %s" % sf.SamplingFeatureGeotypeCV
+    print "SamplingFeatureGeometry: %s" % sf.FeatureGeometry.geom_wkb
+    print "Elevation_m: %s" % str(sf.Elevation_m)
+    #print (
+    #    "The following are some of the attributes of a SamplingFeature retrieved using getSamplingFeatureByCode(): \n" +
+    #    "SamplingFeatureCode: " + sf.SamplingFeatureCode + "\n" +
+    #    "SamplingFeatureName: " + sf.SamplingFeatureName + "\n" +
+    #    "SamplingFeatureDescription: " + sf.SamplingFeatureDescription + "\n" +
+    #    "SamplingFeatureGeotypeCV: " + sf.SamplingFeatureGeotypeCV + "\n" +
+    #    "SamplingFeatureGeometry: " + sf.FeatureGeometry.geom_wkb + "\n" +
+    #    "Elevation_m: " + str(sf.Elevation_m))
 except Exception as e:
     print "Unable to demo getSamplingFeatureByCode: ", e
 
@@ -127,27 +135,27 @@
 # Now get a particular Result using a ResultID
 print "\n------- Example of Retrieving Attributes of a Time Series Result -------"
 try:
-    tsResult = read.getTimeSeriesResultByResultId(19)
+    tsResult = read.getTimeSeriesResultByResultId(1)
     print (
         "The following are some of the attributes for the TimeSeriesResult retrieved using getTimeSeriesResultByResultID(): \n" +
-        "ResultTypeCV: " + tsResult.ResultTypeCV + "\n" +
+        "ResultTypeCV: " + tsResult.ResultObj.ResultTypeCV + "\n" +
         # Get the ProcessingLevel from the TimeSeriesResult's ProcessingLevel object
-        "ProcessingLevel: " + tsResult.ProcessingLevelObj.Definition + "\n" +
-        "SampledMedium: " + tsResult.SampledMediumCV + "\n" +
+        "ProcessingLevel: " + tsResult.ResultObj.ProcessingLevelObj.Definition + "\n" +
+        "SampledMedium: " + tsResult.ResultObj.SampledMediumCV + "\n" +
         # Get the variable information from the TimeSeriesResult's Variable object
-        "Variable: " + tsResult.VariableObj.VariableCode + ": " + tsResult.VariableObj.VariableNameCV + "\n"
+        "Variable: " + tsResult.ResultObj.VariableObj.VariableCode + ": " + tsResult.ResultObj.VariableObj.VariableNameCV + "\n"
                                                                                                         "AggregationStatistic: " + tsResult.AggregationStatisticCV + "\n" +
         "Elevation_m: " + str(sf.Elevation_m) + "\n" +
         # Get the site information by drilling down
-        "SamplingFeature: " + tsResult.FeatureActionObj.SamplingFeatureObj.SamplingFeatureCode + " - " +
-        tsResult.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName)
+        "SamplingFeature: " + tsResult.ResultObj.FeatureActionObj.SamplingFeatureObj.SamplingFeatureCode + " - " +
+        tsResult.ResultObj.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName)
 except Exception as e:
     print "Unable to demo Example of retrieving Attributes of a time Series Result: ", e
 
 # Get the values for a particular TimeSeriesResult
 print "\n-------- Example of Retrieving Time Series Result Values ---------"
 
-tsValues = read.getTimeSeriesResultValuesByResultId(19)  # Return type is a pandas dataframe
+tsValues = read.getTimeSeriesResultValuesByResultId(1)  # Return type is a pandas dataframe
 
 # Print a few Time Series Values to the console
 # tsValues.set_index('ValueDateTime', inplace=True)
@@ -162,9 +170,9 @@
     fig = plt.figure()
     ax = fig.add_subplot(111)
     tsValues.plot(x='ValueDateTime', y='DataValue', kind='line',
-                  title=tsResult.VariableObj.VariableNameCV + " at " + tsResult.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName,
+                  title=tsResult.ResultObj.VariableObj.VariableNameCV + " at " + tsResult.ResultObj.FeatureActionObj.SamplingFeatureObj.SamplingFeatureName,
                   ax=ax)
-    ax.set_ylabel(tsResult.VariableObj.VariableNameCV + " (" + tsResult.UnitObj.UnitsAbbreviation + ")")
+    ax.set_ylabel(tsResult.ResultObj.VariableObj.VariableNameCV + " (" + tsResult.ResultObj.UnitsObj.UnitsAbbreviation + ")")
     ax.set_xlabel("Date/Time")
     ax.xaxis.set_minor_locator(dates.MonthLocator())
     ax.xaxis.set_minor_formatter(dates.DateFormatter('%b'))

odm2api/ODM2/models.py

@@ -559,17 +559,17 @@ class SamplingFeatures(Base):
                                       index=True)
     Elevation_m = Column('elevation_m', Float(53))
     ElevationDatumCV = Column('elevationdatumcv', ForeignKey(CVElevationDatum.Name), index=True)
-    #FeatureGeometry = Column('featuregeometry', Geometry) # Geoalchemy 2
-    FeatureGeometry = GeometryColumn('featuregeometry', Geometry) #Geoalchemy 1, #wkb.loads(str(self.FeatureGeometry.geom_wkb)).wkt if self.FeatureGeometry is not None else None
+    FeatureGeometry = Column('featuregeometry', Geometry) # Geoalchemy 2
+    #FeatureGeometry = GeometryColumn('featuregeometry', Geometry) #Geoalchemy 1, #wkb.loads(str(self.FeatureGeometry.geom_wkb)).wkt if self.FeatureGeometry is not None else None
     # FeatureGeometry = Column('featuregeometry', BLOB)# custom geometry queries
 
 
     def __repr__(self):
-        from shapely import wkb
-        return "<SamplingFeatures('%s', '%s', '%s', '%s', '%s')>" % (
-            self.SamplingFeatureCode, self.SamplingFeatureName, self.SamplingFeatureDescription,
-            self.Elevation_m, wkb.loads(str(self.FeatureGeometry.geom_wkb)).wkt if self.FeatureGeometry is not None else None)#self.FeatureGeometry)
-
+        #from shapely import wkb
+        #return "<SamplingFeatures('%s', '%s', '%s', '%s', '%s')>" % (
+        #    self.SamplingFeatureCode, self.SamplingFeatureName, self.SamplingFeatureDescription,
+        #    self.Elevation_m, wkb.loads(str(self.FeatureGeometry.geom_wkb)).wkt if self.FeatureGeometry is not None else None)#self.FeatureGeometry)
+        return "<SamplingFeatures('%s', '%s', '%s', '%s', '%s')>" % (self.SamplingFeatureCode, self.SamplingFeatureName, self.SamplingFeatureDescription, self.Elevation_m, self.FeatureGeometry)
 GeometryDDL(SamplingFeatures.__table__) #Geoalchemy1
 
 class FeatureActions(Base):

odm2api/ODM2/services/readService.py

@@ -764,13 +764,14 @@ def getTimeSeriesResultValuesByResultId(self, resultId):
             :type Timeseriesresultvalue:
         """
         try:
-            q = self._session.query(TimeSeriesResults).filter_by(ResultID=resultId).all()
-
+            q = self._session.query(TimeSeriesResultValues).filter_by(ResultID=resultId).all()
+            print type(q[0]), q[0]
             df = pd.DataFrame([dv.list_repr() for dv in q])
             df.columns = q[0].get_columns()
             return df
             # return self._session.query(Timeseriesresultvalue).filter_by(ResultID=resultId).all()
         except Exception as e:
+            print e
             return None
 
     def getTimeSeriesResultValuesByCode(self, timeSeriesCode):