tests for CRO/DOT file dimensions

scripts/omPrior.py

@@ -57,3 +57,4 @@
 omWetlandEmis.processEmissions(args.startDate, args.endDate)
 
 omOutputs.sumLayers()
+omPriorVerify.verifyEmis()

tests/conftest.py

@@ -4,4 +4,4 @@
 
 @pytest.fixture(scope="session")
 def root_dir():
-    return Path(__file__).parent.parent
+    return Path(__file__).parent.parent

tests/test_om_prior.py

@@ -15,28 +15,27 @@
 
 root_path = Path(__file__).parent.parent
 sys.path.insert(1, os.path.join(root_path, "scripts"))
-from omDownloadInputs import download_input_files, downloads, remote, sectoralEmissionsPath
+from omDownloadInputs import downloads, remote, sectoralEmissionsPath, download_input_files
 
 
-@pytest.fixture(scope="session")
-def output_domain_file(root_dir,
-                       input_files
-                       ) :
-    subprocess.run(["python", os.path.join(root_dir, "scripts/omCreateDomainInfo.py")], check=True)
-
-    subprocess.run(["python", os.path.join(root_dir, "scripts/omPrior.py"), "2022-07-01", "2022-07-02"], check=True)
-
-    # Generated by scripts/omCreateDomainInfo.py
-    filepath_in_domain = os.path.join(root_dir, "inputs/om-domain-info.nc")
-
-    # Generated by scripts/omPrior.py
-    filepath_out_domain = os.path.join(root_dir, "outputs/out-om-domain-info.nc")
 
-    yield xr.load_dataset(filepath_out_domain)
+@pytest.fixture(scope="session")
+def cro_xr(root_dir) :
+    cmaqExamplePath = getenv("CMAQ_EXAMPLE")
+    croFilePath = os.path.join(root_dir, cmaqExamplePath, getenv("CROFILE"))
+    return xr.open_dataset(croFilePath)
 
-    os.remove(filepath_out_domain)
+@pytest.fixture(scope="session")
+def dot_xr(root_dir) :
+    cmaqExamplePath = getenv("CMAQ_EXAMPLE")
+    dotFilePath = os.path.join(root_dir, cmaqExamplePath, getenv("DOTFILE"))
+    return xr.open_dataset(dotFilePath)
 
-    os.remove(filepath_in_domain)
+@pytest.fixture(scope="session")
+def geom_xr(root_dir) :
+    cmaqExamplePath = getenv("CMAQ_EXAMPLE")
+    geomFilePath = os.path.join(root_dir, cmaqExamplePath, getenv("GEO_EM"))
+    return xr.open_dataset(geomFilePath)
 
 
 # Fixture to download and later remove all input files
@@ -56,6 +55,28 @@ def input_files(root_dir) :
         filepath = os.path.join(input_folder, file)
         os.remove(filepath)
 
+@pytest.fixture(scope="session")
+def input_domain_xr(root_dir, input_files) :
+    subprocess.run(["python", os.path.join(root_dir, "scripts/omCreateDomainInfo.py")], check=True)
+
+    # Generated by scripts/omCreateDomainInfo.py
+    filepath_in_domain = os.path.join(root_dir, "inputs/om-domain-info.nc")
+
+    yield xr.load_dataset(filepath_in_domain)
+
+    os.remove(filepath_in_domain)
+
+
+@pytest.fixture(scope="session")
+def output_domain_xr(root_dir, input_domain_xr) :
+    subprocess.run(["python", os.path.join(root_dir, "scripts/omPrior.py"), "2022-07-01", "2022-07-02"], check=True)
+
+    # Generated by scripts/omPrior.py
+    filepath_out_domain = os.path.join(root_dir, "outputs/out-om-domain-info.nc")
+
+    yield xr.load_dataset(filepath_out_domain)
+
+    os.remove(filepath_out_domain)
 
 def test_001_response_for_download_links() :
     for filename, filepath in downloads :
@@ -75,8 +96,6 @@ def test_002_cdsapi_connection(root_dir, tmpdir) :
 
     assert os.path.exists(filepath)
 
-    os.remove(filepath)
-
 
 def test_003_inputs_folder_is_empty(root_dir) :
     input_folder = os.path.join(root_dir, "inputs")
@@ -121,38 +140,45 @@ def test_005_agriculture_emissions(root_dir, input_files) :
 
 # TODO Update this test when file structure is clear.
 # This test ensures that the grid size for all input files is 10 km.
-def test_006_grid_size_for_geo_files(root_dir, monkeypatch) :
+def test_006_grid_size_for_geo_files(cro_xr, geom_xr, dot_xr) :
     expected_cell_size = 10000
 
-    monkeypatch.chdir(root_dir)
+    assert cro_xr.XCELL == expected_cell_size
+    assert cro_xr.YCELL == expected_cell_size
 
-    cmaqExamplePath = getenv("CMAQ_EXAMPLE")
+    assert geom_xr.DX == expected_cell_size
+    assert geom_xr.DY == expected_cell_size
+
+    assert dot_xr.XCELL == expected_cell_size
+    assert dot_xr.YCELL == expected_cell_size
+
+
+def test_007_compare_in_domain_with_cro_dot_files(input_domain_xr, cro_xr, dot_xr):
+
+    assert dot_xr.NCOLS == input_domain_xr.COL_D.size
+    assert dot_xr.NROWS == input_domain_xr.ROW_D.size
+
+    assert cro_xr.NCOLS == input_domain_xr.COL.size
+    assert cro_xr.NROWS == input_domain_xr.ROW.size
 
-    croFilePath = os.path.join(cmaqExamplePath, getenv("CROFILE"))
-    dotFilePath = os.path.join(cmaqExamplePath, getenv("DOTFILE"))
-    geomFilePath = os.path.join(cmaqExamplePath, getenv("GEO_EM"))
+def test_008_compare_out_domain_with_cro_dot_files(input_domain_xr, output_domain_xr, cro_xr, dot_xr):
 
-    with xr.open_dataset(geomFilePath) as geomXr :
-        assert geomXr.DX == expected_cell_size
-        assert geomXr.DY == expected_cell_size
+    assert dot_xr.NCOLS == output_domain_xr.COL_D.size
+    assert dot_xr.NROWS == output_domain_xr.ROW_D.size
 
-    with xr.open_dataset(dotFilePath) as dotXr :
-        assert dotXr.XCELL == expected_cell_size
-        assert dotXr.YCELL == expected_cell_size
+    assert cro_xr.NCOLS == output_domain_xr.COL.size
+    assert cro_xr.NROWS == output_domain_xr.ROW.size
 
-    with xr.open_dataset(croFilePath) as croXr :
-        assert croXr.XCELL == expected_cell_size
-        assert croXr.YCELL == expected_cell_size
 
 
-def test_007_output_domain_file(output_domain_file, num_regression) :
-    mean_values = {key : output_domain_file[key].mean().item() for key in output_domain_file.keys()}
+def test_009_output_domain_xr(output_domain_xr, num_regression) :
+    mean_values = {key : output_domain_xr[key].mean().item() for key in output_domain_xr.keys()}
 
     num_regression.check(mean_values)
 
 
-def test_008_emission_discrepancy(root_dir, output_domain_file, input_files) :
-    modelAreaM2 = output_domain_file.DX * output_domain_file.DY
+def test_010_emission_discrepancy(root_dir, output_domain_xr, input_files) :
+    modelAreaM2 = output_domain_xr.DX * output_domain_xr.DY
 
     filepath_sector = os.path.join(root_dir, sectoralEmissionsPath)
     sector_data = pd.read_csv(filepath_sector).to_dict(orient="records")[0]
@@ -163,11 +189,11 @@ def test_008_emission_discrepancy(root_dir, output_domain_file, input_files) :
         sectorVal = float(sector_data[sector]) * 1e9
 
         # Check each layer in the output sums up to the input
-        if layerName in output_domain_file :
-            layerVal = np.sum(output_domain_file[layerName][0].values * modelAreaM2 * secsPerYear)
+        if layerName in output_domain_xr :
+            layerVal = np.sum(output_domain_xr[layerName][0].values * modelAreaM2 * secsPerYear)
 
             if sector == "agriculture" :
-                layerVal += np.sum(output_domain_file["OCH4_LIVESTOCK"][0].values * modelAreaM2 * secsPerYear)
+                layerVal += np.sum(output_domain_xr["OCH4_LIVESTOCK"][0].values * modelAreaM2 * secsPerYear)
 
             diff = round(layerVal - sectorVal)
             perectenageDifference = diff / sectorVal * 100

tests/test_om_prior/test_009_output_domain_xr.csv

@@ -0,0 +1,2 @@
+,LAT,LON,LANDMASK,LATD,LOND,OCH4_AGRICULTURE,OCH4_LULUCF,OCH4_WASTE,OCH4_LIVESTOCK,OCH4_INDUSTRIAL,OCH4_STATIONARY,OCH4_TRANSPORT,OCH4_ELECTRICITY,OCH4_FUGITIVE,OCH4_TERMITE,OCH4_FIRE,OCH4_WETLANDS,OCH4_TOTAL
+0,-26.983160018920898,133.302001953125,0.39128163456916809,-26.980266571044922,133.302001953125,3.8221794892533283e-13,8.2839841777071689e-13,7.6806688034203811e-13,3.3252710482543991e-12,4.6406982245152562e-15,8.5852921845127254e-14,1.8562792898061025e-14,2.3204437472569127e-14,1.9068246493083643e-12,8.1061502996138124e-13,2.6130391795643748e-13,1.8596938045956645e-11,2.7011896889060713e-11