refactor: get bsyncr config from analysis config

seed/analysis_pipelines/bsyncr.py

@@ -43,6 +43,36 @@
 
 logger = logging.getLogger(__name__)
 
+# map for translating SEED's model names into bsyncr's model names
+# used for communicating with bsyncr service
+BSYNCR_MODEL_TYPE_MAP = {
+    'Simple Linear Regression': 'SLR',
+    'Three Parameter Linear Model Cooling': '3PC',
+    'Three Parameter Linear Model Heating': '3PH',
+    'Four Parameter Linear Model': '4P',
+}
+
+
+def _validate_bsyncr_config(analysis):
+    """Performs basic validation of the analysis for running bsyncr. Returns any
+    errors
+
+    :param analysis: Analysis
+    :returns: list[str], list of validation error messages
+    """
+    config = analysis.configuration
+    if not isinstance(config, dict):
+        return ['Analysis configuration must be a dictionary/JSON']
+
+    if 'model_type' not in config:
+        return ['Analysis configuration missing required property "model_type"']
+
+    model_type = config['model_type']
+    if model_type not in BSYNCR_MODEL_TYPE_MAP:
+        return [f'Analysis configuration.model_type "{model_type}" is invalid. '
+                f'Must be one of the following: {", ".join(BSYNCR_MODEL_TYPE_MAP.keys())}']
+
+    return []
 
 class BsyncrPipeline(AnalysisPipeline):
     """
@@ -58,6 +88,10 @@ def _prepare_analysis(self, analysis_id, property_view_ids):
             self.fail(message, logger)
             raise AnalysisPipelineException(message)
 
+        validation_errors = _validate_bsyncr_config(Analysis.objects.get(id=self._analysis_id))
+        if validation_errors:
+            raise AnalysisPipelineException(f'Unexpected error(s) while validating analysis configuration: {"; ".join(validation_errors)}')
+
         progress_data = ProgressData('prepare-analysis-bsyncr', analysis_id)
 
         # Steps:
@@ -317,10 +351,11 @@ def _start_analysis(self, analysis_id, progress_data_key):
     progress_data = ProgressData.from_key(progress_data_key)
     progress_data.step('Sending requests to bsyncr service')
 
+    bsyncr_model_type = BSYNCR_MODEL_TYPE_MAP[analysis.configuration['model_type']]
     output_xml_file_ids = []
     for input_file in analysis.input_files.all():
         analysis_property_view_id = _parse_analysis_property_view_id(input_file.file.path)
-        results_dir, errors = _run_bsyncr_analysis(input_file.file)
+        results_dir, errors = _run_bsyncr_analysis(input_file.file, bsyncr_model_type)
 
         if errors:
             for error in errors:
@@ -435,10 +470,11 @@ def elem2dict(node):
     return {'models': parsed_models}
 
 
-def _bsyncr_service_request(file_):
+def _bsyncr_service_request(file_, model_type):
     """Makes request to bsyncr service using the provided file
 
     :param file_: File
+    :param model_type: str
     :returns: requests.Response
     """
     files = [
@@ -449,22 +485,23 @@ def _bsyncr_service_request(file_):
         method='POST',
         url=f'http://{settings.BSYNCR_SERVER_HOST}:{settings.BSYNCR_SERVER_PORT}/',
         files=files,
-        params={'model_type': 'SLR'},
+        params={'model_type': model_type},
         timeout=60 * 2,  # timeout after two minutes
     )
 
 
-def _run_bsyncr_analysis(file_):
+def _run_bsyncr_analysis(file_, model_type):
     """Runs the bsyncr analysis by making a request to a bsyncr server with the
     provided file. Returns a tuple, an object representing a temporary directory
     created with tempfile.TemporaryDirectory which contains the files returned by bsyncr
     followed by a list of error messages.
 
     :param file_: File
+    :param model_type: str
     :returns: tuple, (object, list[str])
     """
     try:
-        response = _bsyncr_service_request(file_)
+        response = _bsyncr_service_request(file_, model_type)
     except requests.exceptions.Timeout:
         return None, ['Request to bsyncr server timed out.']
     except Exception as e:

seed/static/seed/js/controllers/inventory_detail_analyses_modal_controller.js

@@ -25,11 +25,10 @@ angular.module('BE.seed.controller.inventory_detail_analyses_modal', [])
       inventory_ids,
     ) {
       $scope.bsyncr_models = [
-        {model_type:'Simple Linear Regression'},
-        {model_type:'Three Parameter Linear Model Cooling'},
-        {model_type:'Three Parameter Linear Model Heating'},
-        {model_type:'Four Parameter Linear Model'},
-        {model_type:'Five Parameter Linear Model'}
+        {model_type: 'Simple Linear Regression'},
+        {model_type: 'Three Parameter Linear Model Cooling'},
+        {model_type: 'Three Parameter Linear Model Heating'},
+        {model_type: 'Four Parameter Linear Model'}
       ];
 
       function initialize_new_analysis () {

seed/tests/test_analysis_pipelines.py

@@ -517,7 +517,8 @@ def setUp(self):
             FakeAnalysisFactory(organization=self.org, user=self.user)
             .get_analysis(
                 name='Good Analysis',
-                service=Analysis.BSYNCR
+                service=Analysis.BSYNCR,
+                configuration={'model_type': 'Simple Linear Regression'}
             )
         )
 
@@ -573,8 +574,12 @@ def _build_bsyncr_output(file_):
             result.seek(0)
             return result
 
-        def _mock_request(file_):
+        def _mock_request(file_, model_type):
             # mock the call to _bsyncr_service_request by returning a constructed Response
+
+            # ignore model_type
+            _ = model_type
+
             the_response = Response()
             if error_messages is not None:
                 the_response.status_code = 400

seed/tests/test_analysis_property_views.py

@@ -34,9 +34,11 @@ def setUp(self):
         cycle_b = FakeCycleFactory(organization=self.org_b, user=self.user).get_cycle(name="Cycle Org B")
 
         self.analysis_a = (
-            FakeAnalysisFactory(organization=self.org_a, user=self.user).get_analysis(
+            FakeAnalysisFactory(organization=self.org_a, user=self.user)
+            .get_analysis(
                 name='Quite neat',
                 service=Analysis.BSYNCR,
+                configuration={'model_type': 'Simple Linear Regression'}
             )
         )