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@@ -33,7 +33,7 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
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ds = ds.drop_sel(source="UNFCCC")
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conv = {}
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- gases = ["CH4"]
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+ gases = ["CO2", "CH4", "N2O"]
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for var in gases:
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conv[var] = cc.Conversion.from_csv(
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f"conversion_FAO_IPPCC2006_PRIMAP_{var}.csv", cats=cats
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@@ -56,7 +56,7 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
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df_all = pd.concat([ds_if, result_if], axis=0, join="outer", ignore_index=True)
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compare = df_all.loc[
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- df_all["entity"] == "CH4"
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+ df_all["entity"] == "CO2"
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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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@@ -81,13 +81,13 @@ def test_conversion_from_FAO_to_IPCC2006_PRIMAP():
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def test_read(tmp_path):
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domains_and_releases_to_read = [
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- ("farm_gate_agriculture_energy", "2024-11-14"),
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+ # ("farm_gate_agriculture_energy", "2024-11-14"),
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("farm_gate_emissions_crops", "2024-11-14"),
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- ("farm_gate_livestock", "2024-11-14"),
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- ("land_use_drained_organic_soils", "2024-11-14"),
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- ("land_use_fires", "2024-11-14"),
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- ("land_use_forests", "2024-11-14"),
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- ("pre_post_agricultural_production", "2024-11-14"),
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+ # ("farm_gate_livestock", "2024-11-14"),
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+ # ("land_use_drained_organic_soils", "2024-11-14"),
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+ # ("land_use_fires", "2024-11-14"),
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+ # ("land_use_forests", "2024-11-14"),
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+ # ("pre_post_agricultural_production", "2024-11-14"),
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]
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read_data(
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