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@@ -24,6 +24,7 @@ from .UNFCCC_DI_reader_config import di_query_filters
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from .UNFCCC_DI_reader_config import di_processing_info
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from .UNFCCC_DI_reader_config import cat_conversion
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from .UNFCCC_DI_reader_config import gas_baskets
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+from .UNFCCC_DI_reader_config import cat_code_regexp
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from .util import NoDIDataError, nAI_countries, AI_countries
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from .util import DI_date_format, regex_date
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@@ -413,14 +414,14 @@ def read_UNFCCC_DI_for_country_df(
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}
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# find country group
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- if country_code in list(reader.non_annex_one_reader.parties["code"]):
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+ if country_code in nAI_countries:
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ai_country = False
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- elif country_code in list(reader.annex_one_reader.parties["code"]):
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+ elif country_code in AI_countries:
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ai_country = True
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#di_data = reader.annex_one_reader.query(**query)
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else:
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raise ValueError(f"Country code {country_code} found neither in AnnexI nor "
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- f"non-AnnexI countrz lists.")
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+ f"non-AnnexI country lists.")
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if category_groups is None:
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# no category defs given, so use default which is all categories,
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@@ -558,27 +559,6 @@ def convert_DI_data_to_pm2_if(
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print("Convert data to PRIMAP2 interchange format")
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- # regular expression to match category code in category label
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- cat_code_regexp = r'(?P<code>^(([0-9][A-Za-z0-9\.]{0,10}[0-9A-Za-z]))|([0-9]))[' \
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- r'\s\.].*'
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-
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- # the activity data and emissions factors have a structure that is incompatible
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- # with PRIMAP2.
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- # To read it into a primap2 dataframe the information in classification / measure
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- # has to be put into "entity" which is currently always "No gas". I's possible,
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- # but takes some time, so I have omitted it here
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- filter_activity_factors = {
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- "entity": {"gas": ["No gas"]},
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- "unit": {"unit": [
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- 'no unit', 'kg/TJ', 't/TJ', '%', 'kg/t',
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- 'kg/kt', 't/t', 'kg/head/year', 'kg N2O/kg N handled', 'kg N2O/kg N',
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- 'kg N2O-N/kg N handled', 'g/m^2', 'kg N2O-N/kg N', 'kg N2O-N/ha', 'kg/t dm',
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- 't CO2-C/t', 't/unit', 't C/ha', 'kg CH4/ha', 'kg CO2/ha',
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- 'g/kg', 'kg/kg DC',
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- ]
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- },
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- }
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-
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# create a copy of the data to avoid data altering the original data
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# this will be done inside the *convert_to_long_dataframe* function
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# in the future. Thus it can be removed here once the category column
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@@ -587,12 +567,10 @@ def convert_DI_data_to_pm2_if(
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# check which country group we have
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reader = unfccc_di_api.UNFCCCApiReader()
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- ai_parties = list(reader.annex_one_reader.parties["code"])
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- nai_parties = list(reader.non_annex_one_reader.parties["code"])
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parties_present_ai = [party for party in data_temp["party"].unique() if party
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- in ai_parties]
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+ in AI_countries]
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parties_present_nai = [party for party in data_temp["party"].unique() if party
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- in nai_parties]
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+ in nAI_countries]
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if len(parties_present_ai) > 0:
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if len(parties_present_nai) > 0:
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raise ValueError("AnnexI and non-AnnexI parties present in one dataset. "
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@@ -857,7 +835,6 @@ def read_UNFCCC_DI_for_country_group(
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) -> xr.Dataset:
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'''
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This function reads DI data for all countries in a group (annexI or non-AnnexI)
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- TODO: currently only non-annexI is implemented
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The function reads all data in one go using datalad run. as the output data file
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names are unknown beforehand datalad run uses explicit=false
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'''
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@@ -865,6 +842,66 @@ def read_UNFCCC_DI_for_country_group(
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today = date.today()
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date_str = today.strftime(DI_date_format)
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+ if annexI:
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+ countries = AI_countries
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+ else:
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+ countries = nAI_countries
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+
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+ # read the data
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+ data_all = None
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+ for country in countries[0:5]:
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+ print(f"reading DI data for country {country}")
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+
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+ try:
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+ data_country = read_UNFCCC_DI_for_country(
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+ country_code=country,
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+ category_groups=None, # read all categories
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+ read_subsectors=False, # not applicable as we read all categories
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+ date_str=date_str,
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+ pm2if_specifications=None,
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+ # automatically use the right specs for AI and NAI
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+ default_gwp=None, # automatically uses right default GWP for AI and NAI
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+ debug=False)
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+
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+ if data_all is None:
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+ data_all = data_country
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+ else:
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+ data_all = data_all.pr.merge(data_country)
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+ except unfccc_di_api.NoDataError as err:
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+ print(f"No data for {country}.")
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+ print(err)
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+
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+ # TODO: add more info to metadata? (like list of covered countries)
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+ if annexI:
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+ data_all.attrs["comment"] = data_all.attrs["comment"] + " Data for AnnexI " \
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+ "countries."
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+ else:
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+ data_all.attrs["comment"] = data_all.attrs["comment"] + " Data for non-AnnexI " \
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+ "countries."
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+
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+ # save the data
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+ save_DI_dataset(data_all, raw=True, annexI=annexI)
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+
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+ return data_all
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+
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+
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+def process_UNFCCC_DI_for_country_group(
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+ annexI: bool=False,
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+) -> xr.Dataset:
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+ '''
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+ This function processes DI data for all countries in a group (annexI or non-AnnexI)
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+ TODO: currently only non-annexI is implemented
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+ The function processes all data in one go using datalad run. as the output data file
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+ names are unknown beforehand datalad run uses explicit=false
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+
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+ TODO: use the latest
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+
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+
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+ '''
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+
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+ today = date.today()
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+ date_str = today.strftime(DI_date_format)
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+
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if annexI:
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raise ValueError("Bulk reading for AnnexI countries not implemented yet")
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else:
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