Merge pull request #125 from ODM2/sfdataset

Sfdataset

odm2api/ODM2/services/readService.py

@@ -72,6 +72,43 @@ def __init__(self, affiliation, person, org):
         self.Organization = '(' + org.OrganizationCode + ') ' + org.OrganizationName
 
 
+class SamplingFeatureDataSet():
+    datasets={}
+    def __init__(self, samplingfeature, datasetresults):
+        sf = samplingfeature
+
+        self.SamplingFeatureID = sf.SamplingFeatureID
+        self.SamplingFeatureUUID = sf.SamplingFeatureUUID
+        self.SamplingFeatureTypeCV = sf.SamplingFeatureTypeCV
+        self.SamplingFeatureCode = sf.SamplingFeatureCode
+        self.SamplingFeatureName = sf.SamplingFeatureName
+        self.SamplingFeatureDescription = sf.SamplingFeatureDescription
+        self.SamplingFeatureGeotypeCV = sf.SamplingFeatureGeotypeCV
+        self.Elevation_m = sf.Elevation_m
+        self.ElevationDatumCV = sf.ElevationDatumCV
+        self.FeatureGeometryWKT = sf.FeatureGeometryWKT
+        self.assignDatasets(datasetresults)
+
+        print(self.datasets)
+
+
+    def assignDatasets(self, datasetresults):
+        for dsr in datasetresults:
+            if dsr.DataSetObj not in self.datasets:
+                #if the dataset is not in the dictionary, add it and the first result
+                self.datasets[dsr.DataSetObj]=[]
+                res = dsr.ResultObj
+                # res.FeatureActionObj = None
+                self.datasets[dsr.DataSetObj].append(res)
+            else:
+                #if the dataset is in the dictionary, append the result object to the list
+                res = dsr.ResultObj
+                # res.FeatureActionObj = None
+                self.datasets[dsr.DataSetObj].append(res)
+
+
+
+
 class ReadODM2(serviceBase):
     # Exists functions
     def resultExists(self, result):
@@ -871,7 +908,6 @@ def getSamplingFeatureDatasets(self, ids=None, codes=None, uuids=None, dstype=No
             raise ValueError('Expected samplingFeatureID OR samplingFeatureUUID OR samplingFeatureCode argument')
 
         sf_query = self._session.query(SamplingFeatures)
-
         if ids:
             sf_query = sf_query.filter(SamplingFeatures.SamplingFeatureID.in_(ids))
         if codes:
@@ -880,21 +916,29 @@ def getSamplingFeatureDatasets(self, ids=None, codes=None, uuids=None, dstype=No
             sf_query = sf_query.filter(SamplingFeatures.SamplingFeatureUUID.in_(uuids))
         sf_list = []
         for sf in sf_query.all():
-            sf_list.append(sf.SamplingFeatureID)
+            sf_list.append(sf)
 
-        q = self._session.query(DataSetsResults)\
-            .join(Results)\
-            .join(FeatureActions)\
-            .filter(FeatureActions.SamplingFeatureID.in_(sf_list))
+        sfds = None
+        try:
+            sfds=[]
+            for sf in sf_list:
 
-        if dstype:
-            q = q.filter_by(DatasetTypeCV=dstype)
+                q = self._session.query(DataSetsResults)\
+                    .join(Results)\
+                    .join(FeatureActions)\
+                    .filter(FeatureActions.SamplingFeatureID == sf.SamplingFeatureID)
 
-        try:
-            return q.all()
+                if dstype:
+                    q = q.filter_by(DatasetTypeCV=dstype)
+
+
+                vals = q.all()
+
+                sfds.append(SamplingFeatureDataSet(sf, vals))
         except Exception as e:
             print('Error running Query: {}'.format(e))
             return None
+        return sfds
 
     # Data Quality
     def getDataQuality(self):

tests/test_odm2/test_readservice.py

@@ -130,42 +130,51 @@ def test_getDataSetsValues(self):
 
 
     def test_getSamplingFeatureDataSets(self):
+        try:
+            #find a sampling feature that is associated with a dataset
+            sf = self.engine.execute(
+                'SELECT * from SamplingFeatures as sf '
+                'inner join FeatureActions as fa on fa.SamplingFeatureID == sf.SamplingFeatureID '
+                'inner join Results as r on fa.FeatureActionID == r.FeatureActionID  '
+                'inner join DataSetsResults as ds on r.ResultID == ds.ResultID '
+            ).fetchone()
+            assert len(sf) > 0
+
+            #get the dataset associated with the sampling feature
+            ds = self.engine.execute(
+                'SELECT * from DataSetsResults as ds '
+                'inner join Results as r on r.ResultID == ds.ResultID '
+                'inner join FeatureActions as fa on fa.FeatureActionID == r.FeatureActionID '
+                'where fa.SamplingFeatureID = ' + str(sf[0])
+            ).fetchone()
+            assert len(ds) > 0
 
-        #find a sampling feature that is associated with a dataset
-        sf = self.engine.execute(
-            'SELECT * from SamplingFeatures as sf '
-            'inner join FeatureActions as fa on fa.SamplingFeatureID == sf.SamplingFeatureID '
-            'inner join Results as r on fa.FeatureActionID == r.FeatureActionID  '
-            'inner join DataSetsResults as ds on r.ResultID == ds.ResultID '
-        ).fetchone()
-        assert len(sf) > 0
+            print (sf[0])
+            # get the dataset associated with the sampling feature using hte api
+            dsapi = self.reader.getSamplingFeatureDatasets(ids=[sf[0]])
 
-        #get the dataset associated with the sampling feature
-        ds = self.engine.execute(
-            'SELECT * from DataSetsResults as ds '
-            'inner join Results as r on r.ResultID == ds.ResultID '
-            'inner join FeatureActions as fa on fa.FeatureActionID == r.FeatureActionID '
-            'where fa.SamplingFeatureID = ' + str(sf[0])
-        ).fetchone()
-        assert len(ds) > 0
+            assert dsapi is not None
+            assert len(dsapi) > 0
+            assert dsapi[0].datasets is not None
+            assert dsapi[0].SamplingFeatureID == sf[0]
+            # assert ds[0] == dsapi[0]
+        except Exception as ex:
+            assert False
+        finally:
+            self.reader._session.rollback()
 
-        print (sf[0])
-        # get the dataset associated with the sampling feature using hte api
-        dsapi = self.reader.getSamplingFeatureDatasets(ids=[sf[0]])
-
-        assert dsapi is not None
-        assert len(dsapi) > 0
-        assert ds[1] == dsapi[0].DataSetID
 
     # Results
     def test_getAllResults(self):
+
         # get all results from the database
         res = self.engine.execute('SELECT * FROM Results').fetchall()
         print(res)
         # get all results using the api
         resapi = self.reader.getResults()
         assert len(res) == len(resapi)
 
+
     def test_getResultsByID(self):
         # get a result from the database
         res = self.engine.execute('SELECT * FROM Results').fetchone()