vikinganalytics · vnadhan · Mar 28, 2023 · Mar 27, 2023 · Mar 28, 2023 · Mar 27, 2023
diff --git a/mvg/mvg.py b/mvg/mvg.py
@@ -61,8 +61,8 @@ def __init__(self, endpoint: str, token: str):
         self.endpoint = endpoint
         self.token = token
 
-        self.mvg_version = self.parse_version("v0.14.5")
-        self.tested_api_version = self.parse_version("v0.5.6")
+        self.mvg_version = self.parse_version("v0.14.6")
+        self.tested_api_version = self.parse_version("v0.5.12")
 
         # Get API version
         try:
@@ -1075,6 +1075,7 @@ def get_analysis_results(
         request_id: str,
         offset: int = None,
         limit: int = None,
+        result_type: str = None,
     ) -> dict:
         """Retrieves an analysis with given request_id
         The format of the result structure depends on the feature.
@@ -1089,6 +1090,10 @@ def get_analysis_results(
         limit: int
             maximum number of items to be returned from each
             dictionary in the data for "results" key [optional].
+        result_type: str
+            The type of results to return. By default, the type is
+            'full' implying the complete analysis results will be
+            returned. The allowed types varies between features [optional].
 
         Returns
         -------
@@ -1105,6 +1110,8 @@ def get_analysis_results(
             params["offset"] = offset
         if limit is not None:
             params["limit"] = limit
+        if result_type is not None:
+            params["result_type"] = result_type
 
         response = get_paginated_analysis_results(self._request, url, params)
         return response

diff --git a/mvg/utils/response_processing.py b/mvg/utils/response_processing.py
@@ -91,7 +91,10 @@ def get_paginated_analysis_results(request: Callable, url: str, params: Dict) ->
         is_paginated = all(f in results for f in paginator_model_fields)
         if is_paginated:
             # Fields with paginated data
-            paginated_fields = ["timestamps", "labels", "uncertain", "mode_probability"]
+            # We might have to later re-enable this to not make this
+            # automatically paginate list-based values.
+            # paginated_fields = ["timestamps", "labels", "uncertain",
+            # "mode_probability"]
 
             num_items = results["total"]
             limit = results["limit"]
@@ -101,7 +104,7 @@ def get_paginated_analysis_results(request: Callable, url: str, params: Dict) ->
                 params["offset"] = offset
                 _results = request("get", url, params=params).json()["results"]
                 for key in _results:
-                    if key in paginated_fields:
+                    if isinstance(_results[key], list):
                         results[key] += _results[key]
 
         # Construct the response to return

diff --git a/requirements_docs.txt b/requirements_docs.txt
@@ -1,5 +1,6 @@
 papermill
 ipywidgets
+ipykernel
 tqdm
 sphinx
 sphinx-rtd-theme

diff --git a/tests/test_api_analyses.py b/tests/test_api_analyses.py
@@ -275,3 +275,58 @@ def test_get_analysis_info(session: MVG, waveform_source_multiaxial_001):
 
     analysis_info = session.get_analysis_info(request_id)
     assert analysis_info["request_status"] == "successful"
+
+
+def test_get_analysis_results_with_valid_result_type(
+    session: MVG, waveform_source_multiaxial_001
+):
+    source_id, source_info = waveform_source_multiaxial_001
+    timestamps = source_info["timestamps"]
+    pattern = source_info["pattern"]
+
+    parameters = {"n_trials": 1}
+    request = session.request_analysis(source_id, "ModeId", parameters=parameters)
+    request_id = request["request_id"]
+    result_type = "compressed"
+    session.wait_for_analyses([request_id])
+    response = session.get_analysis_results(request_id, result_type=result_type)
+
+    results = response["results"]
+    num_timestamps_in_modes = [6, 14, 5]  # from the pattern
+    assert response["status"] == "successful"
+    assert results["count"] == num_timestamps_in_modes
+    for channel in pattern.keys():
+        assert all(label in pattern[channel] for label in results["label"])
+    assert all(ts in timestamps for ts in results["start_timestamp"])
+    assert all(ts in timestamps for ts in results["end_timestamp"])
+
+
+def test_get_analysis_results_with_noncompliant_result_type(
+    session: MVG, waveform_source_with_measurements
+):
+    source_id = waveform_source_with_measurements
+
+    feature = "KPIDemo"
+    request = session.request_analysis(source_id, feature)
+    request_id = request["request_id"]
+    result_type = "compressed"
+    session.wait_for_analyses([request_id])
+
+    with pytest.raises(MVGAPIError) as exc:
+        session.get_analysis_results(request_id, result_type=result_type)
+    assert f"Feature {feature} supports only result types in" in str(exc)
+
+
+def test_get_analysis_results_with_invalid_result_type(
+    session: MVG, waveform_source_with_measurements
+):
+    source_id = waveform_source_with_measurements
+
+    request = session.request_analysis(source_id, "KPIDemo")
+    request_id = request["request_id"]
+    result_type = "someresultype"
+    session.wait_for_analyses([request_id])
+
+    with pytest.raises(MVGAPIError) as exc:
+        session.get_analysis_results(request_id, result_type=result_type)
+    assert f"Feature result type '{result_type}' does not exist." in str(exc)