[DATALAD] Recorded changes

tests/unit/conversion_FAO_IPPCC2006_PRIMAP_CH4.csv

@@ -0,0 +1 @@
+../../.git/annex/objects/kP/qf/MD5E-s1719--3fc215dd7a8ed206f63cb0033d134499.csv/MD5E-s1719--3fc215dd7a8ed206f63cb0033d134499.csv

tests/unit/conversion_FAO_IPPCC2006_PRIMAP_CO2.csv

@@ -0,0 +1 @@
+../../.git/annex/objects/vv/6m/MD5E-s419--709f2af8c935768407b0a7c793383c3b.csv/MD5E-s419--709f2af8c935768407b0a7c793383c3b.csv

tests/unit/conversion_FAO_IPPCC2006_PRIMAP_N2O.csv

@@ -0,0 +1 @@
+../../.git/annex/objects/9g/2P/MD5E-s973--bbe2aec96494664a3a4dd5cf3bcaf229.csv/MD5E-s973--bbe2aec96494664a3a4dd5cf3bcaf229.csv

tests/unit/test_conversion.py

@@ -20,12 +20,9 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
     cats = {
         "FAOSTAT": categorisation_a,
         "IPCC2006_PRIMAP": categorisation_b,
-        "gas": cc.cats["gas"],
+        # "gas": cc.cats["gas"],
     }
 
-    # make conversion from csv
-    conv = cc.Conversion.from_csv("conversion_FAO_IPPCC2006_PRIMAP.csv", cats=cats)
-
     ds_fao = (
         extracted_data_path
         / "v2024-11-14/FAOSTAT_Agrifood_system_emissions_v2024-11-14.nc"
@@ -35,26 +32,33 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
     # drop UNFCCC data
     ds = ds.drop_sel(source="UNFCCC")
 
+    conv = {}
+    gases = ["CH4"]
+    for var in gases:
+        conv[var] = cc.Conversion.from_csv(
+            f"conversion_FAO_IPPCC2006_PRIMAP_{var}.csv", cats=cats
+        )
+
     ds_if = ds.pr.to_interchange_format()
 
     da_dict = {}
-    for var in ds.data_vars:
+    for var in gases:
         da_dict[var] = ds[var].pr.convert(
             dim="category (FAOSTAT)",
-            conversion=conv,
-            auxiliary_dimensions={"gas": "entity"},
+            conversion=conv[var],
+            # auxiliary_dimensions={"gas": "entity"},
         )
-    result = xr.Dataset(da_dict)
 
-    # ds = ds.set_coords(("lat", "lon"))
+    result = xr.Dataset(da_dict)
 
     result_if = result.pr.to_interchange_format()
 
     df_all = pd.concat([ds_if, result_if], axis=0, join="outer", ignore_index=True)
 
     compare = df_all.loc[
-        (df_all["category (IPCC2006_PRIMAP)"] == "3.A")
-        | (df_all["category (FAOSTAT)"] == "3")
+        df_all["entity"] == "CH4"
+        # (df_all["category (IPCC2006_PRIMAP)"] == "3.A")
+        # | (df_all["category (FAOSTAT)"] == "3")
     ].sort_values(by="area (ISO3)")
 
     compare_short = compare[