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@@ -31,6 +31,9 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
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)
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ds = pm2.open_dataset(ds_fao)
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+ # drop UNFCCC data
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+ ds = ds.drop_sel(source="UNFCCC")
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+
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ds_if = ds.pr.to_interchange_format()
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da_dict = {}
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@@ -38,7 +41,7 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
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da_dict[var] = ds[var].pr.convert(
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dim="category (FAOSTAT)",
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conversion=conv,
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- # auxiliary_dimensions={"gas" : "source (gas)"},
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+ # auxiliary_dimensions={"gas" : "entity"},
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)
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result = xr.Dataset(da_dict)
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result_if = result.pr.to_interchange_format()
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@@ -48,9 +51,24 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
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compare = df_all.loc[
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(df_all["category (IPCC2006_PRIMAP)"] == "3.A")
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| (df_all["category (FAOSTAT)"] == "3")
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+ ].sort_values(by="area (ISO3)")
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+
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+ compare_short = compare[
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+ [
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+ "source",
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+ "scenario (FAO)",
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+ "area (ISO3)",
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+ "entity",
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+ "unit",
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+ "category (FAOSTAT)",
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+ "2021",
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+ "2022",
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+ "2023",
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+ "category (IPCC2006_PRIMAP)",
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+ ]
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]
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- assert compare
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+ assert compare_short
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def test_read(tmp_path):
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