Expand test of .ssp.transport.main()

message_ix_models/tests/project/ssp/test_transport.py

@@ -1,8 +1,10 @@
 from typing import TYPE_CHECKING
 
+import pandas as pd
 import pytest
 
 from message_ix_models.project.ssp.transport import main
+from message_ix_models.tests.tools.iea.test_web import user_local_data  # noqa: F401
 from message_ix_models.util import package_data_path
 
 if TYPE_CHECKING:
@@ -33,19 +35,109 @@ def input_xlsx_path(tmp_path_factory, input_csv_path) -> "pathlib.Path":
     return result
 
 
+# Enumeration/flags for codes appearing in VARIABLE
+IN_ = 1  # Data appears in the input file only
+OUT = 2  # Data appears in the output file *and* with a modified magnitude
+I_O = IN_ | OUT  # Both
+
+edt = "Energy|Demand|Transportation"
+
+#: IAMC 'Variable' codes appearing in the input file and/or output file.
+VARIABLE = {
+    (0, f"Emissions|CH4|{edt}"),
+    (OUT, f"Emissions|CH4|{edt}|Aviation"),
+    (0, f"Emissions|CH4|{edt}|Aviation|International"),
+    (I_O, f"Emissions|CH4|{edt}|Road Rail and Domestic Shipping"),
+    # No emissions factors available for BC
+    (IN_, f"Emissions|BC|{edt}"),
+    (IN_, f"Emissions|BC|{edt}|Aviation"),
+    (IN_, f"Emissions|BC|{edt}|Aviation|International"),
+    #
+    (I_O, f"Emissions|CO|{edt}|Aviation"),
+    (I_O, f"Emissions|CO|{edt}|Road Rail and Domestic Shipping"),
+    #
+    (OUT, f"Emissions|N2O|{edt}|Aviation"),
+    (I_O, f"Emissions|N2O|{edt}|Road Rail and Domestic Shipping"),
+    #
+    (IN_, f"Emissions|NH3|{edt}"),
+    (IN_, f"Emissions|NH3|{edt}|Aviation"),
+    (IN_, f"Emissions|NH3|{edt}|Aviation|International"),
+    #
+    (I_O, f"Emissions|NOx|{edt}|Aviation"),
+    (I_O, f"Emissions|NOx|{edt}|Road Rail and Domestic Shipping"),
+    #
+    (IN_, f"Emissions|OC|{edt}"),
+    (IN_, f"Emissions|OC|{edt}|Aviation"),
+    (IN_, f"Emissions|OC|{edt}|Aviation|International"),
+    # FIXME Should be OUT
+    (0, f"Emissions|Sulfur|{edt}|Aviation"),
+    #
+    (IN_, f"Emissions|VOC|{edt}"),
+    (I_O, f"Emissions|VOC|{edt}|Aviation"),
+    (IN_, f"Emissions|VOC|{edt}|Aviation|International"),
+    (I_O, f"Emissions|VOC|{edt}|Road Rail and Domestic Shipping"),
+}
+
+
 @main.minimum_version
-def test_main(tmp_path, input_csv_path) -> None:
+# @pytest.mark.usefixtures("user_local_data")
+@pytest.mark.parametrize("method", ("A", "B"))
+def test_main(tmp_path, test_context, input_csv_path, method) -> None:
     """Code can be called from Python."""
     # Locate a temporary data file
     path_in = input_csv_path
     path_out = tmp_path.joinpath("output.csv")
 
     # Code runs
-    main(path_in=path_in, path_out=path_out)
+    main(path_in=path_in, path_out=path_out, method=method)
 
     # Output path exists
     assert path_out.exists()
 
+    # Read input file
+    df_in = pd.read_csv(path_in)
+
+    # Identify dimension columns
+    dims_wide = list(df_in.columns)[:5]  # …in 'wide' layout
+    dims = dims_wide + ["Year"]  # …in 'long' layout
+
+    # Convert wide to long; sort
+    df_in = df_in.melt(dims_wide, var_name="Year").sort_values(dims)
+
+    # Input data already contains the variable names to be modified
+    exp = {v[1] for v in VARIABLE if IN_ & v[0]}
+    assert exp <= set(df_in["Variable"].unique())
+    region = set(df_in["Region"].unique())
+
+    # Read output file
+    df_out = pd.read_csv(path_out).melt(dims_wide, var_name="Year")
+
+    # Data have the same length
+    assert len(df_in) == len(df_out)
+
+    # Output has the same set of region codes as input
+    assert region == set(df_out["Region"].unique())
+
+    # Diff data:
+    # - Outer merge.
+    # - Compute diff and select rows where diff is larger than a certain value
+    df = df_in.merge(df_out, how="outer", on=dims).query(
+        "abs(value_y - value_x) > 1e-16"
+    )
+
+    # df.to_csv("debug0.csv")  # DEBUG Dump to file
+    # print(df.to_string(max_rows=50))  # DEBUG Show in test output
+
+    # All of the expected 'variable' codes have been modified
+    exp = {v[1] for v in VARIABLE if OUT & v[0]}
+    assert exp == set(df["Variable"].unique())
+
+    cond = df.query("value_y < 0")
+    if len(cond):
+        msg = "Negative emissions totals after processing"
+        print(f"\n{msg}:", cond.to_string(), sep="\n")
+        assert False, msg
+
 
 @main.minimum_version
 def test_cli(tmp_path, mix_models_cli, input_xlsx_path) -> None: