test model renames

scripts/bmds-online-33-api.ipynb → scripts/bmds-online-api.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# BMDS online verison 3.3 - API\n",
+    "# BMDS Online API\n",
     "\n",
     "A work in progress to demonstrate how to use the BMDS Online API."
    ]
@@ -16,9 +16,10 @@
    "outputs": [],
    "source": [
     "import json\n",
-    "import requests\n",
+    "import time\n",
     "from pathlib import Path\n",
-    "import time"
+    "\n",
+    "import requests"
    ]
   },
   {
@@ -62,8 +63,8 @@
     "            \"incidences\": [0, 0, 3, 2, 3],\n",
     "            \"model_type\": \"DM\",\n",
     "            \"column_names\": {\n",
-    "                \"ns\": \"N\", \n",
-    "                \"doses\": \"Dose\", \n",
+    "                \"ns\": \"N\",\n",
+    "                \"doses\": \"Dose\",\n",
     "                \"incidences\": \"Incidence\"\n",
     "            },\n",
     "            \"dataset_name\": \"Dataset #1\",\n",
@@ -124,8 +125,7 @@
     "    print(\"Polling...\")\n",
     "    time.sleep(1)\n",
     "    resp = requests.get(poll_url)\n",
-    "    output = resp.json()\n",
-    "    "
+    "    output = resp.json()\n"
    ]
   },
   {
@@ -334,7 +334,7 @@
    "source": [
     "excel_url = root + output['word_url']\n",
     "resp = requests.get(excel_url)\n",
-    "Path('/Users/shapiromatron/Desktop/demo.docx').write_bytes(resp.content)"
+    "Path('~/Desktop/demo.docx').write_bytes(resp.content)"
    ]
   },
   {
@@ -356,7 +356,7 @@
    "source": [
     "word_url = root + output['excel_url']\n",
     "resp = requests.get(word_url)\n",
-    "Path('/Users/shapiromatron/Desktop/demo.xlsx').write_bytes(resp.content)"
+    "Path('~/Desktop/demo.xlsx').write_bytes(resp.content)"
    ]
   },
   {
@@ -393,7 +393,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.10"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,

tests/analysis/test_api.py

@@ -20,7 +20,7 @@ def check_error(response: dict, type: str, loc: list, msg: str):
 
 @pytest.mark.django_db
 class TestAnalysisViewSet:
-    def test_auth(self, bmds3_complete_continuous):
+    def test_auth(self, complete_continuous):
         """
         Check API auth cases.
 
@@ -33,7 +33,7 @@ def test_auth(self, bmds3_complete_continuous):
         read_url = analysis.get_api_url()
         payload = {
             "editKey": analysis.password,
-            "data": bmds3_complete_continuous,
+            "data": complete_continuous,
         }
 
         # client; no CSRF
@@ -142,43 +142,43 @@ def test_patch_partial(self):
         assert response.status_code == 200
         assert response.json()["inputs"] == payload["data"]
 
-    def test_patch_complete_continuous(self, bmds3_complete_continuous):
+    def test_patch_complete_continuous(self, complete_continuous):
         client = APIClient()
         analysis = Analysis.objects.create()
         url = analysis.get_api_patch_inputs_url()
 
-        # complete bmds3 continuous
-        payload = {"editKey": analysis.password, "data": bmds3_complete_continuous}
+        # complete continuous
+        payload = {"editKey": analysis.password, "data": complete_continuous}
         response = client.patch(url, payload, format="json")
         assert response.status_code == 200
         assert response.json()["inputs"] == payload["data"]
 
-    def test_optional_recommender(self, bmds3_complete_continuous):
+    def test_optional_recommender(self, complete_continuous):
         client = APIClient()
         analysis = Analysis.objects.create()
         url = analysis.get_api_patch_inputs_url()
 
-        # complete bmds3 continuous
-        payload = {"editKey": analysis.password, "data": bmds3_complete_continuous}
+        # complete continuous
+        payload = {"editKey": analysis.password, "data": complete_continuous}
         del payload["data"]["recommender"]
         response = client.patch(url, payload, format="json")
         assert response.status_code == 200
         assert response.json()["inputs"] == payload["data"]
 
-    def test_patch_complete_dichotomous(self, bmds3_complete_dichotomous):
+    def test_patch_complete_dichotomous(self, complete_dichotomous):
         client = APIClient()
         analysis = Analysis.objects.create()
         url = analysis.get_api_patch_inputs_url()
 
-        # complete bmds3 dichotomous
-        payload = {"editKey": analysis.password, "data": bmds3_complete_dichotomous}
+        # complete dichotomous
+        payload = {"editKey": analysis.password, "data": complete_dichotomous}
         response = client.patch(url, payload, format="json")
         assert response.status_code == 200
         assert response.json()["inputs"] == payload["data"]
 
-    def test_execute(self, bmds3_complete_dichotomous):
+    def test_execute(self, complete_dichotomous):
         client = APIClient()
-        analysis = Analysis.objects.create(inputs=bmds3_complete_dichotomous)
+        analysis = Analysis.objects.create(inputs=complete_dichotomous)
         assert analysis.started is None
         url = analysis.get_api_execute_url()
 
@@ -196,9 +196,9 @@ def test_execute(self, bmds3_complete_dichotomous):
         assert response.data["has_errors"] is False
         assert bmd == pytest.approx(164.3, rel=0.05)
 
-    def test_reset_execute(self, bmds3_complete_dichotomous):
+    def test_reset_execute(self, complete_dichotomous):
         client = APIClient()
-        analysis = Analysis.objects.create(inputs=bmds3_complete_dichotomous)
+        analysis = Analysis.objects.create(inputs=complete_dichotomous)
         analysis.execute()
         url = analysis.get_api_execute_reset_url()
 
@@ -215,9 +215,9 @@ def test_reset_execute(self, bmds3_complete_dichotomous):
         assert response.data["has_errors"] is False
         assert response.data["outputs"] == {}
 
-    def test_model_selection(self, bmds3_complete_dichotomous):
+    def test_model_selection(self, complete_dichotomous):
         client = APIClient()
-        analysis = Analysis.objects.create(inputs=bmds3_complete_dichotomous)
+        analysis = Analysis.objects.create(inputs=complete_dichotomous)
         analysis.execute()
 
         url = analysis.get_api_url() + "select-model/"

tests/analysis/test_executor.py

@@ -7,30 +7,30 @@
 
 
 class TestAnalysisSession:
-    def test_default_dichotomous(self, bmds3_complete_dichotomous):
+    def test_default_dichotomous(self, complete_dichotomous):
         # assure a default dataset can be created
-        data = deepcopy(bmds3_complete_dichotomous)
+        data = deepcopy(complete_dichotomous)
         session = AnalysisSession.create(data, 0, 0)
         assert len(session.frequentist.models) == 1
         assert len(session.bayesian.models) == 1
 
-    def test_default_continuous(self, bmds3_complete_continuous):
+    def test_default_continuous(self, complete_continuous):
         # assure a default dataset can be created
-        data = deepcopy(bmds3_complete_continuous)
+        data = deepcopy(complete_continuous)
         session = AnalysisSession.create(data, 0, 0)
         assert len(session.frequentist.models) == 1
         assert len(session.bayesian.models) == 1
 
-    def test_default_continuous_individual(self, bmds3_complete_continuous_individual):
+    def test_default_continuous_individual(self, complete_continuous_individual):
         # assure a default dataset can be created
-        data = deepcopy(bmds3_complete_continuous_individual)
+        data = deepcopy(complete_continuous_individual)
         session = AnalysisSession.create(data, 0, 0)
         assert len(session.frequentist.models) == 1
         assert len(session.bayesian.models) == 1
 
-    def test_prior_classes(self, bmds3_complete_dichotomous):
+    def test_prior_classes(self, complete_dichotomous):
         # assure a default dataset can be created
-        data = deepcopy(bmds3_complete_dichotomous)
+        data = deepcopy(complete_dichotomous)
         data["models"] = {
             "frequentist_restricted": ["Gamma"],
             "frequentist_unrestricted": ["Gamma"],
@@ -50,8 +50,8 @@ def test_prior_classes(self, bmds3_complete_dichotomous):
         )
         assert session.bayesian.models[0].settings.priors.prior_class is PriorClass.bayesian
 
-    def test_exponential_unpacking(self, bmds3_complete_continuous):
-        data = deepcopy(bmds3_complete_continuous)
+    def test_exponential_unpacking(self, complete_continuous):
+        data = deepcopy(complete_continuous)
         data["models"] = {
             "frequentist_restricted": ["Exponential"],
             "bayesian": [{"model": "Exponential", "prior_weight": 1}],
@@ -64,7 +64,7 @@ def test_exponential_unpacking(self, bmds3_complete_continuous):
         assert session.bayesian.models[0].bmd_model_class.id == ContinuousModelIds.c_exp_m3
         assert session.bayesian.models[1].bmd_model_class.id == ContinuousModelIds.c_exp_m5
 
-    def test_multistage_permutations(self, bmds3_complete_dichotomous):
+    def test_multistage_permutations(self, complete_dichotomous):
         def _expected_degree(session, n: int):
             assert session.bayesian is None
             assert len(session.frequentist.models) == n
@@ -74,14 +74,14 @@ def _expected_degree(session, n: int):
             assert degrees == set(list(range(1, n + 1)))
 
         # degree = 1
-        data = deepcopy(bmds3_complete_dichotomous)
+        data = deepcopy(complete_dichotomous)
         data["models"] = {"frequentist_restricted": ["Multistage"]}
         data["dataset_options"][0]["degree"] = 1
         session = AnalysisSession.create(data, 0, 0)
         _expected_degree(session, 1)
 
         # degree = 2
-        data = deepcopy(bmds3_complete_dichotomous)
+        data = deepcopy(complete_dichotomous)
         data["models"] = {"frequentist_restricted": ["Multistage"]}
         data["dataset_options"][0]["degree"] = 2
         session = AnalysisSession.create(data, 0, 0)
@@ -90,7 +90,7 @@ def _expected_degree(session, n: int):
         # 3 dose-groups; degree = N-1; expected 2
         for num_doses in range(3, 8):
             expected_degree = min(max(num_doses - 1, 2), 8)
-            data = deepcopy(bmds3_complete_dichotomous)
+            data = deepcopy(complete_dichotomous)
             data["datasets"] = [
                 {
                     "dtype": "D",
@@ -107,7 +107,7 @@ def _expected_degree(session, n: int):
             _expected_degree(session, expected_degree)
 
         # degree = N -1, bayesian, fixed at degree == 2
-        data = deepcopy(bmds3_complete_dichotomous)
+        data = deepcopy(complete_dichotomous)
         data["models"] = {"bayesian": [{"model": "Multistage", "prior_weight": 1}]}
         data["dataset_options"][0]["degree"] = 0
         session = AnalysisSession.create(data, 0, 0)
@@ -117,9 +117,9 @@ def _expected_degree(session, n: int):
         assert model.bmd_model_class.id == DichotomousModelIds.d_multistage
         assert model.settings.degree == 2
 
-    def test_polynomial_unpacking(self, bmds3_complete_continuous):
+    def test_polynomial_unpacking(self, complete_continuous):
         # test linear; degree 0
-        data = deepcopy(bmds3_complete_continuous)
+        data = deepcopy(complete_continuous)
         data["models"] = {"frequentist_unrestricted": ["Linear"]}
         data["dataset_options"][0]["degree"] = 0
         session = AnalysisSession.create(data, 0, 0)
@@ -128,7 +128,7 @@ def test_polynomial_unpacking(self, bmds3_complete_continuous):
         assert session.bayesian is None
 
         # test polynomial; degree 2
-        data = deepcopy(bmds3_complete_continuous)
+        data = deepcopy(complete_continuous)
         data["models"] = {"frequentist_unrestricted": ["Polynomial"]}
         data["dataset_options"][0]["degree"] = 2
         session = AnalysisSession.create(data, 0, 0)
@@ -137,7 +137,7 @@ def test_polynomial_unpacking(self, bmds3_complete_continuous):
         assert session.bayesian is None
 
         # test polynomial; degree 3
-        data = deepcopy(bmds3_complete_continuous)
+        data = deepcopy(complete_continuous)
         data["models"] = {"frequentist_unrestricted": ["Polynomial"]}
         data["dataset_options"][0]["degree"] = 3
         session = AnalysisSession.create(data, 0, 0)
@@ -147,7 +147,7 @@ def test_polynomial_unpacking(self, bmds3_complete_continuous):
         assert session.bayesian is None
 
         # test linear + polynomial; degree 3
-        data = deepcopy(bmds3_complete_continuous)
+        data = deepcopy(complete_continuous)
         data["models"] = {"frequentist_unrestricted": ["Linear", "Polynomial"]}
         data["dataset_options"][0]["degree"] = 3
         session = AnalysisSession.create(data, 0, 0)
@@ -158,8 +158,8 @@ def test_polynomial_unpacking(self, bmds3_complete_continuous):
         assert session.bayesian is None
 
     # disttype 3 Linear and power are not added
-    def test_disttype(self, bmds3_complete_continuous):
-        data = deepcopy(bmds3_complete_continuous)
+    def test_disttype(self, complete_continuous):
+        data = deepcopy(complete_continuous)
         data["models"] = {
             "frequentist_restricted": ["Exponential", "Hill", "Linear", "Power"],
         }

tests/analysis/test_models.py

@@ -14,9 +14,9 @@ def write_excel(data: dict, path: Path):
 
 
 @pytest.mark.django_db()
-class TestBmds3Execution:
-    def test_continuous(self, bmds3_complete_continuous, data_path, rewrite_data_files):
-        analysis = Analysis.objects.create(inputs=bmds3_complete_continuous)
+class TestExecution:
+    def test_continuous(self, complete_continuous, data_path, rewrite_data_files):
+        analysis = Analysis.objects.create(inputs=complete_continuous)
 
         assert analysis.is_finished is False
         assert analysis.has_errors is False
@@ -38,13 +38,13 @@ def test_continuous(self, bmds3_complete_continuous, data_path, rewrite_data_fil
         assert len(df) == 3
 
         if rewrite_data_files:
-            write_excel(df, data_path / "continuous.xlsx")
-            (data_path / "continuous.docx").write_bytes(docx.getvalue())
+            write_excel(df, data_path / "reports/continuous.xlsx")
+            (data_path / "reports/continuous.docx").write_bytes(docx.getvalue())
 
     def test_continuous_individual(
-        self, bmds3_complete_continuous_individual, data_path, rewrite_data_files
+        self, complete_continuous_individual, data_path, rewrite_data_files
     ):
-        analysis = Analysis.objects.create(inputs=bmds3_complete_continuous_individual)
+        analysis = Analysis.objects.create(inputs=complete_continuous_individual)
 
         assert analysis.is_finished is False
         assert analysis.has_errors is False
@@ -66,11 +66,11 @@ def test_continuous_individual(
         assert len(df) == 3
 
         if rewrite_data_files:
-            write_excel(df, data_path / "continuous_individual.xlsx")
-            (data_path / "continuous_individual.docx").write_bytes(docx.getvalue())
+            write_excel(df, data_path / "reports/continuous_individual.xlsx")
+            (data_path / "reports/continuous_individual.docx").write_bytes(docx.getvalue())
 
-    def test_dichotomous(self, bmds3_complete_dichotomous, data_path, rewrite_data_files):
-        analysis = Analysis.objects.create(inputs=bmds3_complete_dichotomous)
+    def test_dichotomous(self, complete_dichotomous, data_path, rewrite_data_files):
+        analysis = Analysis.objects.create(inputs=complete_dichotomous)
 
         assert analysis.is_finished is False
         assert analysis.has_errors is False
@@ -92,8 +92,8 @@ def test_dichotomous(self, bmds3_complete_dichotomous, data_path, rewrite_data_f
         assert len(df) == 3
 
         if rewrite_data_files:
-            write_excel(df, data_path / "dichotomous.xlsx")
-            (data_path / "dichotomous.docx").write_bytes(docx.getvalue())
+            write_excel(df, data_path / "reports/dichotomous.xlsx")
+            (data_path / "reports/dichotomous.docx").write_bytes(docx.getvalue())
 
     def test_nested_dichotomous(self, bmds_complete_nd, data_path, rewrite_data_files):
         analysis = Analysis.objects.create(inputs=bmds_complete_nd)
@@ -118,8 +118,8 @@ def test_nested_dichotomous(self, bmds_complete_nd, data_path, rewrite_data_file
         assert len(df) == 3
 
         if rewrite_data_files:
-            write_excel(df, data_path / "nested_dichotomous.xlsx")
-            (data_path / "nested_dichotomous.docx").write_bytes(docx.getvalue())
+            write_excel(df, data_path / "reports/nested_dichotomous.xlsx")
+            (data_path / "reports/nested_dichotomous.docx").write_bytes(docx.getvalue())
 
     def test_multitumor(self, bmds_complete_mt, data_path, rewrite_data_files):
         analysis = Analysis.objects.create(inputs=bmds_complete_mt)
@@ -144,5 +144,5 @@ def test_multitumor(self, bmds_complete_mt, data_path, rewrite_data_files):
         assert len(df) == 3
 
         if rewrite_data_files:
-            write_excel(df, data_path / "multitumor.xlsx")
-            (data_path / "multitumor.docx").write_bytes(docx.getvalue())
+            write_excel(df, data_path / "reports/multitumor.xlsx")
+            (data_path / "reports/multitumor.docx").write_bytes(docx.getvalue())