From d5928b45556829520e4f97e0c5f2164f0c6f570c Mon Sep 17 00:00:00 2001 From: FelixMau Date: Mon, 15 Apr 2024 10:27:01 +0200 Subject: [PATCH 01/37] remove outdated Bus mapping outdated due to using struct from excel sheet --- data_adapter_oemof/adapters.py | 5 ----- 1 file changed, 5 deletions(-) diff --git a/data_adapter_oemof/adapters.py b/data_adapter_oemof/adapters.py index 8b5c41a..faa6c14 100644 --- a/data_adapter_oemof/adapters.py +++ b/data_adapter_oemof/adapters.py @@ -221,11 +221,6 @@ def get_busses(self) -> dict: struct = self.structure["default"] else: struct = self.structure - warnings.warn( - "Please check structure and provide either one set of inputs/outputs " - "or specify as default Parameter specific busses not implemented yet. " - f"No Bus found for Process {self.process_name} in Adapter {self}" - ) # 2. Check for default busses if bus in ("bus", "from_bus", "to_bus", "fuel_bus"): From 9eb22c258c5a797279f3bf6a3e6576c4ac7a2881 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Mon, 15 Apr 2024 10:29:56 +0200 Subject: [PATCH 02/37] Using np.unique due to future warning for pandas depreciating unique function for lists --- data_adapter_oemof/build_datapackage.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/data_adapter_oemof/build_datapackage.py b/data_adapter_oemof/build_datapackage.py index 266da98..fdee831 100644 --- a/data_adapter_oemof/build_datapackage.py +++ b/data_adapter_oemof/build_datapackage.py @@ -4,6 +4,7 @@ from typing import Optional, Type import pandas as pd +import numpy as np import tsam.timeseriesaggregation as tsam from data_adapter.preprocessing import Adapter from datapackage import Package @@ -515,7 +516,7 @@ def build_datapackage( # Fill with all buses occurring, needed for foreign keys as well! process_busses += list(component_adapter.get_busses().values()) - process_busses = list(pd.unique(process_busses)) + process_busses = list(np.unique(process_busses)) parametrized_elements["bus"] += process_busses # getting foreign keys with last component @@ -532,7 +533,7 @@ def build_datapackage( # Create Bus Element from all unique `busses` found in elements parametrized_elements["bus"] = pd.DataFrame( { - "name": (names := pd.unique(parametrized_elements["bus"])), + "name": (names := np.unique(parametrized_elements["bus"])), "type": ["bus" for i in names], "balanced": [True for i in names], } From 123a832e23914e2ad80cc540483a2e9178bedcf3 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Mon, 15 Apr 2024 14:06:53 +0200 Subject: [PATCH 03/37] Adding `ind_demand` to helper set --- examples/industry/Industriestruktur.xlsx | Bin 423179 -> 423184 bytes examples/industry/data_adapter_industry.py | 11 +++++++---- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git 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zfmCevd^g-ODciu=+W7Bk&5_w!7SxKnG_SKV?Kcp)ZQH*s*oG>(;!48k)YtT%%1c3>X;2p0?3r1#&Jh5q9$7uSI>+y7zBaQLjSW$ynJMu`v$Td4nEgrS&AB@d!^ z+;MpE#I&w34lhJY+;NMfjPA@z8wF`%m)^B>9;eQ&4EA@=cIBwF-vUcTBZt+h0Tm?_bYrzXVHH zk2EaK|NKcnH7??Q6id2K`Z$b(^>Q>w>R+RYf!bfh;l(5QVog_MI9@_xC_w68i=dpT z^z1w?y!dS%mxlj(J$y3^&DZ~?Z9VgiR@&nm?UIkGv=&_niQxZ1o00sDR+ub})Be}= zJYhWQ|48ztgv8j-bN^+}``T}Ok$>qhsp)MWfeTgXR_TAyE_ILE~CEPl(YKo{zXbmCiu(P$E=5_Fa2s%O JKjR>X{|^q14`ToT diff --git a/examples/industry/data_adapter_industry.py b/examples/industry/data_adapter_industry.py index 9e7b9bd..7b7e234 100644 --- a/examples/industry/data_adapter_industry.py +++ b/examples/industry/data_adapter_industry.py @@ -6,14 +6,14 @@ from data_adapter.preprocessing import Adapter # noqa: E402 from data_adapter.structure import Structure # noqa: E402 - from data_adapter_oemof.build_datapackage import DataPackage # noqa: E402 # Download Collection # Due to Nan values in "ind_scalar" type column datapackage.json must be adjusted after download +# from data_adapter.databus import download_collection # download_collection( -# "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/" -# ) +# "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/" +# ) structure = Structure( "Industriestruktur", process_sheet="process_set_steel_casting", @@ -30,7 +30,6 @@ "modex_tech_generator_gas": "ConversionAdapter", "modex_tech_wind_turbine_onshore": "VolatileAdapter", "modex_demand": "LoadAdapter", - "ind_scalars": "LoadAdapter", "pow_combustion_gt_natgas": "ConversionAdapter", "x2x_import_natural_gas": "CommodityAdapter", "x2x_import_crudesteel": "CommodityAdapter", @@ -45,6 +44,10 @@ "excess_co2": "ExcessAdapter", "excess_ch4": "ExcessAdapter", "excess_n2o": "ExcessAdapter", + "helper_sink_exo_steel": "LoadAdapter", + "ind_timeseries": "LoadAdapter", + "helper_sink_exo_steel": "LoadAdapter", + } parameter_map = { From 4af49cebf2b8163cfe654c21524a1c46d2dd93fe Mon Sep 17 00:00:00 2001 From: FelixMau Date: Tue, 14 May 2024 11:20:44 +0200 Subject: [PATCH 04/37] Adding model creation and solving --- examples/industry/data_adapter_industry.py | 37 +++++++++++++++++++--- 1 file changed, 33 insertions(+), 4 deletions(-) diff --git a/examples/industry/data_adapter_industry.py b/examples/industry/data_adapter_industry.py index 6c4b7fb..3b37583 100644 --- a/examples/industry/data_adapter_industry.py +++ b/examples/industry/data_adapter_industry.py @@ -9,12 +9,27 @@ from data_adapter.structure import Structure # noqa: E402 from data_adapter_oemof.build_datapackage import DataPackage # noqa: E402 +from oemof.solph._energy_system import EnergySystem +from oemof.solph import Model + +from oemof.tabular.datapackage import building # noqa F401 +from oemof.tabular.datapackage.reading import deserialize_constraints, deserialize_energy_system + +from oemof.tabular.facades import Excess, Commodity, Conversion, Load, Volatile +from oemof_industry.mimo_converter import MIMO +from oemof.solph.buses import Bus + +EnergySystem.from_datapackage = classmethod(deserialize_energy_system) + +Model.add_constraints_from_datapackage = deserialize_constraints +# # Download Collection # Due to Nan values in "ind_scalar" type column datapackage.json must be adjusted after download -# from data_adapter.databus import download_collection -# download_collection( -# "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/" -# ) + +from data_adapter.databus import download_collection +download_collection( + "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/" + ) structure = Structure( "Industriestruktur", process_sheet="process_set_steel_casting", @@ -76,3 +91,17 @@ ) datapackage_path = pathlib.Path(__file__).parent / "datapackage" dp.save_datapackage_to_csv(str(datapackage_path)) + + +es = EnergySystem.from_datapackage(path = "datapackage/datapackage.json", + typemap= {"bus": Bus, + "excess":Excess, + "commodity": Commodity, + "conversion": Conversion, + "load": Load, + "volatile": Volatile, + "mimo": MIMO}, + ) + +m = Model(es) +m.solve() \ No newline at end of file From 272e87b7956d73b30fca778de1a7fc42715e0d03 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 15 May 2024 12:53:59 +0200 Subject: [PATCH 05/37] Update struct with new x2x --- examples/industry/Industriestruktur.xlsx | Bin 423184 -> 423718 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/examples/industry/Industriestruktur.xlsx b/examples/industry/Industriestruktur.xlsx index c2144d0eb7f2ee95849e8ee0218e94d8b30654d7..0f34fa1e1ccefabaf94efd0686b454110ed46bd4 100644 GIT binary patch delta 115461 zcmZs>1yo$iwl$1Pa1HM6?(PyCg1fuBH16&mEI=T^8h3)bySuylPjb$?|9x+KJw}h- zwX1qn)tqy!s=aE*A7K}tVIwHYfqyMQFN*nq2`tCpVtQouiQx6o+MEPg5AI8!mEk3Nr)C@h*K0K6R&n;G z8t2#SN;^&6%oCC?#-eeGGs7Q>Dl4HsCM18V+3YXL*1{cuH0)h*gBD%>Ek1&({B!^A zKJ55jWf>I}1GeC2r?Yoh$gAU}dZX!!k_nb996Y*_ow;)A=UCD$_BOy`IDl2&ZGmEqm$UDWsSxS`|7T#_%V>u$2@pOB3Ce79xrv;M 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b/examples/industry/data_adapter_industry.py @@ -1,6 +1,8 @@ import os import pathlib +import numpy as np + os.environ["COLLECTIONS_DIR"] = "./collections/" os.environ["STRUCTURES_DIR"] = "" @@ -26,21 +28,27 @@ # Download Collection # Due to Nan values in "ind_scalar" type column datapackage.json must be adjusted after download -from data_adapter.databus import download_collection -download_collection( - "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/" - ) +# from data_adapter.databus import download_collection +# download_collection( +# "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/" +# ) + structure = Structure( - "Industriestruktur", - process_sheet="process_set_steel_casting", - parameter_sheet="parameter_input_output_steel_ca", - helper_sheet="steel_casting_helper", + "SEDOS_Modellstruktur", + process_sheet="Processes_O1", + parameter_sheet="Parameter_O1", + helper_sheet="Helper_O1", ) adapter = Adapter( "steel_industry_test", structure=structure, ) + +# create dicitonary with all found in and outputs + + + process_adapter_map = { "modex_tech_storage_battery": "StorageAdapter", "modex_tech_generator_gas": "ConversionAdapter", From 138bb89f7eda79cd67acbb656baf4bfa110b4576 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 5 Jun 2024 13:36:57 +0200 Subject: [PATCH 07/37] Use Process adaper mapping from excel sheet --- examples/industry/Industriestruktur.xlsx | Bin 301116 -> 0 bytes examples/industry/data_adapter_industry.py | 41 +- poetry.lock | 443 ++++++++++----------- 3 files changed, 233 insertions(+), 251 deletions(-) delete mode 100644 examples/industry/Industriestruktur.xlsx diff --git a/examples/industry/Industriestruktur.xlsx b/examples/industry/Industriestruktur.xlsx deleted file mode 100644 index 6083f157b7d5e623686e992ff71f76ee569551d8..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 301116 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a/examples/industry/data_adapter_industry.py +++ b/examples/industry/data_adapter_industry.py @@ -1,7 +1,7 @@ import os import pathlib -import numpy as np +import pandas as pd os.environ["COLLECTIONS_DIR"] = "./collections/" os.environ["STRUCTURES_DIR"] = "" @@ -36,7 +36,7 @@ structure = Structure( "SEDOS_Modellstruktur", process_sheet="Processes_O1", - parameter_sheet="Parameter_O1", + parameter_sheet="Parameter_Input-Output", helper_sheet="Helper_O1", ) @@ -46,35 +46,20 @@ ) # create dicitonary with all found in and outputs +process_adapter_map = pd.concat([pd.read_excel( + io=structure.structure_file, + sheet_name="Processes_O1", + usecols=("process", "facade adapter (oemof)"), + index_col="process" + ), pd.read_excel( + io=structure.structure_file, + sheet_name="Helper_O1", + usecols=("process", "facade adapter (oemof)"), + index_col="process" + )]).to_dict(orient="dict") -process_adapter_map = { - "modex_tech_storage_battery": "StorageAdapter", - "modex_tech_generator_gas": "ConversionAdapter", - "modex_tech_wind_turbine_onshore": "VolatileAdapter", - "modex_demand": "LoadAdapter", - "ind_scalars": "LoadAdapter", - "pow_combustion_gt_natgas": "ConversionAdapter", - "x2x_import_natural_gas": "CommodityAdapter", - "x2x_import_crudesteel": "CommodityAdapter", - "x2x_import_coke_oven_gas": "CommodityAdapter", - "x2x_import_h2": "CommodityAdapter", - "ind_steel_casting_1": "MIMOAdapter", - "ind_steel_casting_0": "MIMOAdapter", - "ind_steel_hyddri_1": "MIMOAdapter", - "ind_steel_demand": "LoadAdapter", - "x2x_import_elec": "CommodityAdapter", - "ind_steel_boiler_0": "ConversionAdapter", - "excess_co2": "ExcessAdapter", - "excess_ch4": "ExcessAdapter", - "excess_n2o": "ExcessAdapter", - "helper_sink_exo_steel": "LoadAdapter", - "ind_timeseries": "LoadAdapter", - "helper_sink_exo_steel": "LoadAdapter", - -} - parameter_map = { "DEFAULT": {}, "StorageAdapter": { diff --git a/poetry.lock b/poetry.lock index c9d7a28..d2381b3 100644 --- a/poetry.lock +++ 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"sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b"}, + {file = "virtualenv-20.26.2.tar.gz", hash = "sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c"}, ] [package.dependencies] From ab4dac0eebc65b74ad31fadb79ea2073c68bac90 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Mon, 10 Jun 2024 11:33:49 +0200 Subject: [PATCH 08/37] Include nan value handler --- data_adapter_oemof/build_datapackage.py | 19 ++----- data_adapter_oemof/calculations.py | 66 +++++++++++++++++++++++++ 2 files changed, 69 insertions(+), 16 deletions(-) diff --git a/data_adapter_oemof/build_datapackage.py b/data_adapter_oemof/build_datapackage.py index a4c653e..d6532b9 100644 --- a/data_adapter_oemof/build_datapackage.py +++ b/data_adapter_oemof/build_datapackage.py @@ -11,6 +11,7 @@ from data_adapter_oemof.adapters import FACADE_ADAPTERS from data_adapter_oemof.adapters import Adapter as FacadeAdapter +from data_adapter_oemof.calculations import handle_nans from data_adapter_oemof.settings import BUS_MAP, PARAMETER_MAP, PROCESS_ADAPTER_MAP from data_adapter_oemof.utils import convert_mixed_types_to_same_length @@ -48,10 +49,11 @@ def _listify_to_periodic(group_df) -> pd.Series: """ - + handle_nans(group_df) if "year" not in group_df.columns: return group_df unique_values = pd.Series(dtype=object) + for col in group_df.columns: if isinstance(group_df[col][group_df.index[0]], dict): # Unique input/output parameters are not allowed per period @@ -64,21 +66,6 @@ def _listify_to_periodic(group_df) -> pd.Series: ): values = group_df[col].explode().unique() else: - # FIXME: Hotfix "if not" statement to replace nan values from lists: - # in final data only complete datasets are expected. - if not all(group_df[col].isna()) and any(group_df[col].isna()): - group_df.loc[group_df[col].isna(), col] = ( - group_df[col] - .dropna() - .sample( - group_df[col] - .isna() - .sum(), # get the same number of values as are missing - replace=True, - random_state=0, - ) - .values - ) # throw out the index values = group_df[col].unique() if len(values) > 1: if isinstance(group_df[col].iloc[0], list): diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 40934d3..c180d1f 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -3,6 +3,7 @@ import warnings import numpy as np +import pandas as pd from oemof.tools.economics import annuity @@ -188,3 +189,68 @@ def floor_lifetime(mapped_defaults): warnings.warn("Lifetime cannot change in Multi-period modeling") mapped_defaults["lifetime"] = int(np.floor(mapped_defaults["lifetime"][0])) return mapped_defaults + + +def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: + """ + This function should find and fill in missing min and max values in the data + + Missing min value is set to 0. + Missing max value is set to 9999999999999. + + Min values: + capacity_p_min + capacity_e_min + capacity_w_min + flow_share_min_ + + Max values: + potential_annual_max + capacity_p_max + capacity_e_max + capacity_w_max + capacity_p_abs_new_max + capacity_e_abs_new_max + capacity_w_abs_new_max + availability_timeseries_max + capacity_tra_connection_max + flow_share_max_ + sto_cycles_max + sto_max_timeseries + + Returns + ------- + + """ + + max_value = 9999999999999 + min_value = 0 + + min = ["capacity_p_min", "capacity_e_min", "capacity_w_min", "flow_share_min_"] + + max = [ + "potential_annual_max", + "capacity_p_max", + "capacity_e_max", + "capacity_w_max", + "capacity_p_abs_new_max", + "capacity_e_abs_new_max", + "capacity_w_abs_new_max", + "availability_timeseries_max", + "capacity_tra_connection_max", + "flow_share_max_", + "sto_cycles_max", + "sto_max_timeseries", + ] + + for column in group_df.columns: + if column in ["method", "source", "comment", "bandwidth_type"]: + continue + + if group_df[column].nunique(dropna=False) > 1: + if column in max: + group_df[column].fillna(max_value, inplace=True) + elif column in min: + group_df[column].fillna(min_value, inplace=True) + else: + group_df[column].fillna(min_value, inplace=True) From c8e476f18e5343ba0450da1e560e7a42f3c2b05d Mon Sep 17 00:00:00 2001 From: FelixMau Date: Mon, 10 Jun 2024 11:42:20 +0200 Subject: [PATCH 09/37] Adjust test goals --- .../data/elements/modex_tech_chp_steam.csv | 32 +++++++++---------- .../elements/modex_tech_generator_steam.csv | 32 +++++++++---------- .../elements/modex_tech_storage_pumped.csv | 18 +++++------ .../modex_tech_wind_turbine_onshore.csv | 32 +++++++++---------- 4 files changed, 57 insertions(+), 57 deletions(-) diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv index a5f6a69..8641c95 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv @@ -1,17 +1,17 @@ type;carrier;tech;capacity;capacity_potential;marginal_cost;capacity_cost;lifetime;fixed_costs;name;region;year;bus -dispatchable;carrier;tech;[161.2, 161204.0, 161204.0];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[45.14, 45139.0, 45139.0];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[141.24, 141.24, 141.24];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[117.1, 117.1, 117.1];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[204.42, 204422.0, 204422.0];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[14.1, 14.1, 14.1];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[24.28, 24.28, 24.28];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[29.1, 29.1, 29.1];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[232.0, 232.0, 232.0];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[42.5, 42.5, 42.5];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[84.83, 84826.0, 84826.0];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[11.6, 11.6, 11.6];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[15.7, 15.7, 15.7];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[125.44, 125.44, 125.44];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[17.72, 17.72, 17.72];10000.0;[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[161.2, 161204.0, 161204.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[45.14, 45139.0, 45139.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[141.24, 141.24, 141.24];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[117.1, 117.1, 117.1];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[204.42, 204422.0, 204422.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[14.1, 14.1, 14.1];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[24.28, 24.28, 24.28];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[29.1, 29.1, 29.1];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[232.0, 232.0, 232.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[42.5, 42.5, 42.5];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[84.83, 84826.0, 84826.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[11.6, 11.6, 11.6];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[15.7, 15.7, 15.7];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[125.44, 125.44, 125.44];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[17.72, 17.72, 17.72];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv index cad9dac..24a5656 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv @@ -1,17 +1,17 @@ type;carrier;tech;capacity;capacity_potential;marginal_cost;capacity_cost;lifetime;fixed_costs;name;region;year;bus -dispatchable;carrier;tech;[3.6, 3.6, 3.6];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[6.7, 6696.0, 6696.0];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[13.63, 13.63114, 13.63114];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[60.47, 60.46996, 60.46996];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[3.7, 3.7, 3.7];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[5.62, 5.62, 5.62];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[0.0, 0.0, 0.0];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[8.5, 8.5, 8.5];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[48.88, 48.88, 48.88];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[186.53, 186.53, 186.53];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[5.0, 5.0, 5.0];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[1.71, 1.71, 1.71];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[43.24, 43.24, 43.24];10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;10000.0;[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[3.6, 3.6, 3.6];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[6.7, 6696.0, 6696.0];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[13.63, 13.63114, 13.63114];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[60.47, 60.46996, 60.46996];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[3.7, 3.7, 3.7];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[5.62, 5.62, 5.62];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[0.0, 0.0, 0.0];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[8.5, 8.5, 8.5];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[48.88, 48.88, 48.88];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[186.53, 186.53, 186.53];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[5.0, 5.0, 5.0];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[1.71, 1.71, 1.71];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[43.24, 43.24, 43.24];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv index cb124e0..bc1f05b 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv @@ -1,17 +1,17 @@ type;carrier;tech;capacity;capacity_cost;capacity_potential;lifetime;fixed_costs;marginal_cost;name;region;year;invest_relation_output_capacity;inflow_conversion_factor;outflow_conversion_factor;bus storage;carrier;tech;;1500000.0;;10;22500.0;0.0;BB_carrier_tech;BB;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;BE_carrier_tech;BE;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;1873.0;1500000.0;1873.0;10;22500.0;0.0;BW_carrier_tech;BW;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;383.0;1500000.0;383.0;10;22500.0;0.0;BY_carrier_tech;BY;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;1873.0;1500000.0;[0.0, 1873.0, 1873.0];10;22500.0;0.0;BW_carrier_tech;BW;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;383.0;1500000.0;[0.0, 383.0, 383.0];10;22500.0;0.0;BY_carrier_tech;BY;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;HB_carrier_tech;HB;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;625.0;1500000.0;625.0;10;22500.0;0.0;HE_carrier_tech;HE;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;625.0;1500000.0;[0.0, 625.0, 625.0];10;22500.0;0.0;HE_carrier_tech;HE;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;HH_carrier_tech;HH;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;MV_carrier_tech;MV;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;220.0;1500000.0;220.0;10;22500.0;0.0;NI_carrier_tech;NI;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;303.0;1500000.0;303.0;10;22500.0;0.0;NW_carrier_tech;NW;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;220.0;1500000.0;[0.0, 220.0, 220.0];10;22500.0;0.0;NI_carrier_tech;NI;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;303.0;1500000.0;[0.0, 303.0, 303.0];10;22500.0;0.0;NW_carrier_tech;NW;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;RP_carrier_tech;RP;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;119.1;1500000.0;119.1;10;22500.0;0.0;SH_carrier_tech;SH;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;119.1;1500000.0;[0.0, 119.1, 119.1];10;22500.0;0.0;SH_carrier_tech;SH;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;SL_carrier_tech;SL;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;1085.0;1500000.0;1085.0;10;22500.0;0.0;SN_carrier_tech;SN;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;79.7;1500000.0;79.7;10;22500.0;0.0;ST_carrier_tech;ST;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;1509.4;1500000.0;1509.4;10;22500.0;0.0;TH_carrier_tech;TH;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;1085.0;1500000.0;[0.0, 1085.0, 1085.0];10;22500.0;0.0;SN_carrier_tech;SN;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;79.7;1500000.0;[0.0, 79.7, 79.7];10;22500.0;0.0;ST_carrier_tech;ST;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;1509.4;1500000.0;[0.0, 1509.4, 1509.4];10;22500.0;0.0;TH_carrier_tech;TH;[2016, 2030, 2050];5.8;1.0;0.75;electricity diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv index d9d0011..b49b1c7 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv @@ -1,17 +1,17 @@ type;carrier;tech;profile;capacity;capacity_potential;capacity_cost;lifetime;fixed_costs;name;region;year;bus -volatile;carrier;tech;profile_BB;[5700.03, 5700.03375, 5700.03375];[22516.79, 22516.79, 22516.79];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_BE;[11.0, 11.0018, 11.0018];[248.1, 248.1, 248.1];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_BW;[751.03, 751.027686, 751.027686];[29537.65, 29537.65, 29537.65];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_BY;[1854.03, 1854.03049, 1854.03049];[60736.86, 60736.86, 60736.86];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_HB;[171.69, 171689.0, 171689.0];[171.69, 171.69, 171689.0];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_HE;[1316.74, 1316.73603, 1316.73603];[19134.69, 19134.69, 19134.69];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_HH;[54.3, 54296.0, 54296.0];[306.37, 306.37, 306.37];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_MV;[3117.7, 3117.70392, 3117.70392];[19502.13, 19502.13, 19502.13];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_NI;[8007.2, 8007.203624, 8007.203624];[43130.15, 43130.15, 43130.15];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_NW;[3802.77, 3802.77057, 3802.77057];[32372.31, 32372.31, 32372.31];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_RP;[2855.29, 2855.289006, 2855.289006];[19379.97, 19379.97, 19379.97];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_SH;[5309.0, 5309.00481, 5309.00481];[14924.53, 14924.53, 14924.53];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_SL;[279.51, 279.5141, 279.5141];[2079.15, 2079.15, 2079.15];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_SN;[1124.02, 1124.02431, 1124.02431];[18617.69, 18617.69, 18617.69];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_ST;[4515.35, 4515.34775, 4515.34775];[16844.83, 16844.83, 16844.83];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_TH;[1200.56, 1200.564449, 1200.564449];[15716.09, 15716.09, 15716.09];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BB;[5700.03, 5700.03375, 5700.03375];[0.0, 22516.79, 22516.79];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BE;[11.0, 11.0018, 11.0018];[0.0, 248.1, 248.1];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BW;[751.03, 751.027686, 751.027686];[0.0, 29537.65, 29537.65];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BY;[1854.03, 1854.03049, 1854.03049];[0.0, 60736.86, 60736.86];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_HB;[171.69, 171689.0, 171689.0];[0.0, 171.69, 171689.0];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_HE;[1316.74, 1316.73603, 1316.73603];[0.0, 19134.69, 19134.69];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_HH;[54.3, 54296.0, 54296.0];[0.0, 306.37, 306.37];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_MV;[3117.7, 3117.70392, 3117.70392];[0.0, 19502.13, 19502.13];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_NI;[8007.2, 8007.203624, 8007.203624];[0.0, 43130.15, 43130.15];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_NW;[3802.77, 3802.77057, 3802.77057];[0.0, 32372.31, 32372.31];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_RP;[2855.29, 2855.289006, 2855.289006];[0.0, 19379.97, 19379.97];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_SH;[5309.0, 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7a9a27258d8a5e2972381dff203166111f95a34b Mon Sep 17 00:00:00 2001 From: FelixMau Date: Tue, 18 Jun 2024 11:20:35 +0200 Subject: [PATCH 10/37] Updating dependencies --- poetry.lock | 830 +++++++++++++++++++++++-------------------------- pyproject.toml | 1 + 2 files changed, 391 insertions(+), 440 deletions(-) diff --git a/poetry.lock b/poetry.lock index c9d7a28..daa6996 100644 --- a/poetry.lock +++ b/poetry.lock @@ -96,13 +96,13 @@ d = ["aiohttp (>=3.3.2)", "aiohttp-cors"] [[package]] name = "blinker" -version = "1.8.1" +version = "1.8.2" description = "Fast, simple object-to-object and broadcast signaling" optional = false python-versions = ">=3.8" files = [ - {file = "blinker-1.8.1-py3-none-any.whl", hash = "sha256:5f1cdeff423b77c31b89de0565cd03e5275a03028f44b2b15f912632a58cced6"}, - {file = "blinker-1.8.1.tar.gz", hash = "sha256:da44ec748222dcd0105ef975eed946da197d5bdf8bafb6aa92f5bc89da63fa25"}, + {file = "blinker-1.8.2-py3-none-any.whl", hash = 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!=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7" files = [ - {file = "urllib3-1.26.18-py2.py3-none-any.whl", hash = "sha256:34b97092d7e0a3a8cf7cd10e386f401b3737364026c45e622aa02903dffe0f07"}, - {file = "urllib3-1.26.18.tar.gz", hash = "sha256:f8ecc1bba5667413457c529ab955bf8c67b45db799d159066261719e328580a0"}, + {file = "urllib3-1.26.19-py2.py3-none-any.whl", hash = "sha256:37a0344459b199fce0e80b0d3569837ec6b6937435c5244e7fd73fa6006830f3"}, + {file = "urllib3-1.26.19.tar.gz", hash = "sha256:3e3d753a8618b86d7de333b4223005f68720bcd6a7d2bcb9fbd2229ec7c1e429"}, ] [package.extras] @@ -2571,24 +2521,24 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] [[package]] name = "validators" -version = "0.28.1" +version = "0.28.3" description = "Python Data Validation for Humans™" optional = false python-versions = ">=3.8" files = [ - {file = "validators-0.28.1-py3-none-any.whl", hash = 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"sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b"}, + {file = "virtualenv-20.26.2.tar.gz", hash = "sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c"}, ] [package.dependencies] @@ -2622,4 +2572,4 @@ docs = [] [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.11" -content-hash = "1fdae68d1fd816aeff5012460c0dfac7211aa228779e45178b530dd2598a9700" +content-hash = "c20e8c1b158f2417d6e37b7708a4fea2a222fa1f3545062c651d0e9b685dd27c" diff --git a/pyproject.toml b/pyproject.toml index 53131ee..fdf574a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -25,6 +25,7 @@ oemof-industry = { git = "https://github.com/sedos-project/oemof.industry.git", boto3 = "1.26.125" # fix boto3 to fasten up dependency resolution python-dotenv = "^0.21.0" tsam = "^2.3.1" +numpy = "<2" [tool.poetry.dev-dependencies] black = "20.8b1" From c4abeffa22e3b6a871c82ac3d63d277ca4207fd5 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Tue, 18 Jun 2024 13:56:12 +0200 Subject: [PATCH 11/37] Moving utils to utils --- data_adapter_oemof/calculations.py | 37 ++---------------------------- data_adapter_oemof/utils.py | 34 +++++++++++++++++++++++++++ 2 files changed, 36 insertions(+), 35 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index c180d1f..0ba069e 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -2,6 +2,8 @@ import logging import warnings +from utils import divide_two_lists, multiply_two_lists + import numpy as np import pandas as pd from oemof.tools.economics import annuity @@ -72,24 +74,6 @@ def decommission(process_name, adapter_dict: dict) -> dict: ------- """ - - def multiply_two_lists(l1, l2): - """ - Multiplies two lists - - Lists must be same length - - Parameters - ---------- - l1 - l2 - - Returns divided list - ------- - - """ - return [i * j for i, j in zip(l1, l2)] - capacity_column = "capacity" max_column = "max" @@ -134,23 +118,6 @@ def normalize_activity_bonds(adapter): """ - def divide_two_lists(dividend, divisor): - """ - Divides two lists returns quotient, returns 0 if divisor is 0 - - Lists must be same length - - Parameters - ---------- - dividend - divisor - - Returns divided list - ------- - - """ - return [i / j if j != 0 else 0 for i, j in zip(dividend, divisor)] - if "activity_bound_fix" in adapter.data.keys(): adapter.data["activity_bound_fix"] = divide_two_lists( adapter.data["activity_bound_fix"], adapter.get("capacity") diff --git a/data_adapter_oemof/utils.py b/data_adapter_oemof/utils.py index 09f21ab..ff15325 100644 --- a/data_adapter_oemof/utils.py +++ b/data_adapter_oemof/utils.py @@ -53,3 +53,37 @@ def convert_mixed_types_to_same_length(column): ] else: return column + +def divide_two_lists(dividend, divisor): + """ + Divides two lists returns quotient, returns 0 if divisor is 0 + + Lists must be same length + + Parameters + ---------- + dividend + divisor + + Returns divided list + ------- + + """ + return [i / j if j != 0 else 0 for i, j in zip(dividend, divisor)] + +def multiply_two_lists(l1, l2): + """ + Multiplies two lists + + Lists must be same length + + Parameters + ---------- + l1 + l2 + + Returns divided list + ------- + + """ + return [i * j for i, j in zip(l1, l2)] \ No newline at end of file From ea12b6b0a36601333c8b0c2ee81694e9a92db850 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Tue, 18 Jun 2024 14:09:43 +0200 Subject: [PATCH 12/37] Raise Error on nan values --- data_adapter_oemof/calculations.py | 10 ++++++++-- 1 file changed, 8 insertions(+), 2 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 0ba069e..f3204c6 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -214,10 +214,16 @@ def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: if column in ["method", "source", "comment", "bandwidth_type"]: continue - if group_df[column].nunique(dropna=False) > 1: + if group_df.isna().sum>0: if column in max: group_df[column].fillna(max_value, inplace=True) elif column in min: group_df[column].fillna(min_value, inplace=True) else: - group_df[column].fillna(min_value, inplace=True) + if "type" in group_df.columns: + + raise ValueError(f"In column {column} for process {group_df['type']} nan values are found" + f"please make sure to only provide complete datasets") + else: + raise ValueError(f"In column {column} nan values are found" + f"please make sure to only provide complete datasets") From 05d99deddba50c8a581ab7dcf8795a07fdf7eaf6 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Tue, 18 Jun 2024 14:10:05 +0200 Subject: [PATCH 13/37] Linting --- data_adapter_oemof/calculations.py | 17 ++++++++++------- data_adapter_oemof/utils.py | 4 +++- 2 files changed, 13 insertions(+), 8 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index f3204c6..e1ccb36 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -2,11 +2,10 @@ import logging import warnings -from utils import divide_two_lists, multiply_two_lists - import numpy as np import pandas as pd from oemof.tools.economics import annuity +from utils import divide_two_lists, multiply_two_lists class CalculationError(Exception): @@ -214,7 +213,7 @@ def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: if column in ["method", "source", "comment", "bandwidth_type"]: continue - if group_df.isna().sum>0: + if group_df.isna().sum > 0: if column in max: group_df[column].fillna(max_value, inplace=True) elif column in min: @@ -222,8 +221,12 @@ def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: else: if "type" in group_df.columns: - raise ValueError(f"In column {column} for process {group_df['type']} nan values are found" - f"please make sure to only provide complete datasets") + raise ValueError( + f"In column {column} for process {group_df['type']} nan values are found" + f"please make sure to only provide complete datasets" + ) else: - raise ValueError(f"In column {column} nan values are found" - f"please make sure to only provide complete datasets") + raise ValueError( + f"In column {column} nan values are found" + f"please make sure to only provide complete datasets" + ) diff --git a/data_adapter_oemof/utils.py b/data_adapter_oemof/utils.py index ff15325..16af935 100644 --- a/data_adapter_oemof/utils.py +++ b/data_adapter_oemof/utils.py @@ -54,6 +54,7 @@ def convert_mixed_types_to_same_length(column): else: return column + def divide_two_lists(dividend, divisor): """ Divides two lists returns quotient, returns 0 if divisor is 0 @@ -71,6 +72,7 @@ def divide_two_lists(dividend, divisor): """ return [i / j if j != 0 else 0 for i, j in zip(dividend, divisor)] + def multiply_two_lists(l1, l2): """ Multiplies two lists @@ -86,4 +88,4 @@ def multiply_two_lists(l1, l2): ------- """ - return [i * j for i, j in zip(l1, l2)] \ No newline at end of file + return [i * j for i, j in zip(l1, l2)] From fe8693657b2150af687a5880708165c7cdf7c8c9 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 19 Jun 2024 10:11:31 +0200 Subject: [PATCH 14/37] Bugremoval --- data_adapter_oemof/calculations.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index e1ccb36..12cd16b 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -5,7 +5,7 @@ import numpy as np import pandas as pd from oemof.tools.economics import annuity -from utils import divide_two_lists, multiply_two_lists +from .utils import divide_two_lists, multiply_two_lists class CalculationError(Exception): From dd61e4585e0720c44ab164029c346c42beca2255 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 19 Jun 2024 11:35:14 +0200 Subject: [PATCH 15/37] Apply Comments, adjust test --- data_adapter_oemof/calculations.py | 44 ++++++++++++------- .../modex_tech_wind_turbine_onshore.csv | 32 +++++++------- 2 files changed, 43 insertions(+), 33 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 12cd16b..e8f9dc8 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -5,6 +5,7 @@ import numpy as np import pandas as pd from oemof.tools.economics import annuity + from .utils import divide_two_lists, multiply_two_lists @@ -213,20 +214,29 @@ def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: if column in ["method", "source", "comment", "bandwidth_type"]: continue - if group_df.isna().sum > 0: - if column in max: - group_df[column].fillna(max_value, inplace=True) - elif column in min: - group_df[column].fillna(min_value, inplace=True) - else: - if "type" in group_df.columns: - - raise ValueError( - f"In column {column} for process {group_df['type']} nan values are found" - f"please make sure to only provide complete datasets" - ) - else: - raise ValueError( - f"In column {column} nan values are found" - f"please make sure to only provide complete datasets" - ) + """ + Following is a check whether nans can be filled. + + Commented check for columns that are faulty and need to be changed + Commented Error for incomplete columns as we dont know where it may cause errors yet + + """ + # if group_df[column].isna().sum() > 0 and not + # group_df[column].isna().sum()==len(group_df[column]): + if column in max: + group_df[column].fillna(max_value, inplace=True) + elif column in min: + group_df[column].fillna(min_value, inplace=True) + # else: + # if "type" in group_df.columns: + # + # raise ValueError( + # f"In column {column} for process {group_df['type']} nan values are found" + # f"please make sure to only provide complete datasets" + # ) + # else: + # print(group_df) + # raise ValueError( + # f"In column {column} nan values are found \n" + # f"please make sure to only provide complete datasets" + # ) diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv index b49b1c7..f51300b 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_wind_turbine_onshore.csv @@ -1,17 +1,17 @@ type;carrier;tech;profile;capacity;capacity_potential;capacity_cost;lifetime;fixed_costs;name;region;year;bus -volatile;carrier;tech;profile_BB;[5700.03, 5700.03375, 5700.03375];[0.0, 22516.79, 22516.79];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_BE;[11.0, 11.0018, 11.0018];[0.0, 248.1, 248.1];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_BW;[751.03, 751.027686, 751.027686];[0.0, 29537.65, 29537.65];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_BY;[1854.03, 1854.03049, 1854.03049];[0.0, 60736.86, 60736.86];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_HB;[171.69, 171689.0, 171689.0];[0.0, 171.69, 171689.0];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_HE;[1316.74, 1316.73603, 1316.73603];[0.0, 19134.69, 19134.69];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_HH;[54.3, 54296.0, 54296.0];[0.0, 306.37, 306.37];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_MV;[3117.7, 3117.70392, 3117.70392];[0.0, 19502.13, 19502.13];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_NI;[8007.2, 8007.203624, 8007.203624];[0.0, 43130.15, 43130.15];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_NW;[3802.77, 3802.77057, 3802.77057];[0.0, 32372.31, 32372.31];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_RP;[2855.29, 2855.289006, 2855.289006];[0.0, 19379.97, 19379.97];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_SH;[5309.0, 5309.00481, 5309.00481];[0.0, 14924.53, 14924.53];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_SL;[279.51, 279.5141, 279.5141];[0.0, 2079.15, 2079.15];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_SN;[1124.02, 1124.02431, 1124.02431];[0.0, 18617.69, 18617.69];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_ST;[4515.35, 4515.34775, 4515.34775];[0.0, 16844.83, 16844.83];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity -volatile;carrier;tech;profile_TH;[1200.56, 1200.564449, 1200.564449];[0.0, 15716.09, 15716.09];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BB;[5700.03, 5700.03375, 5700.03375];[nan, 22516.79, 22516.79];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BE;[11.0, 11.0018, 11.0018];[nan, 248.1, 248.1];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BW;[751.03, 751.027686, 751.027686];[nan, 29537.65, 29537.65];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_BY;[1854.03, 1854.03049, 1854.03049];[nan, 60736.86, 60736.86];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_HB;[171.69, 171689.0, 171689.0];[nan, 171.69, 171689.0];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_HE;[1316.74, 1316.73603, 1316.73603];[nan, 19134.69, 19134.69];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_HH;[54.3, 54296.0, 54296.0];[nan, 306.37, 306.37];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_MV;[3117.7, 3117.70392, 3117.70392];[nan, 19502.13, 19502.13];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_NI;[8007.2, 8007.203624, 8007.203624];[nan, 43130.15, 43130.15];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_NW;[3802.77, 3802.77057, 3802.77057];[nan, 32372.31, 32372.31];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_RP;[2855.29, 2855.289006, 2855.289006];[nan, 19379.97, 19379.97];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_SH;[5309.0, 5309.00481, 5309.00481];[nan, 14924.53, 14924.53];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_SL;[279.51, 279.5141, 279.5141];[nan, 2079.15, 2079.15];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_SN;[1124.02, 1124.02431, 1124.02431];[nan, 18617.69, 18617.69];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_ST;[4515.35, 4515.34775, 4515.34775];[nan, 16844.83, 16844.83];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity +volatile;carrier;tech;profile_TH;[1200.56, 1200.564449, 1200.564449];[nan, 15716.09, 15716.09];[1288000.0, 1040000.0, 960000.0];10;[23280.0, 12600.0, 11340.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity From 92635d0502895579f4f2a45cc6bca053347fe5f5 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 19 Jun 2024 12:12:30 +0200 Subject: [PATCH 16/37] Adjust test files --- .../data/elements/modex_tech_chp_steam.csv | 32 +++++++++---------- .../elements/modex_tech_generator_steam.csv | 32 +++++++++---------- .../elements/modex_tech_storage_pumped.csv | 18 +++++------ 3 files changed, 41 insertions(+), 41 deletions(-) diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv index 8641c95..5f4ce60 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_chp_steam.csv @@ -1,17 +1,17 @@ type;carrier;tech;capacity;capacity_potential;marginal_cost;capacity_cost;lifetime;fixed_costs;name;region;year;bus -dispatchable;carrier;tech;[161.2, 161204.0, 161204.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[45.14, 45139.0, 45139.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[141.24, 141.24, 141.24];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[117.1, 117.1, 117.1];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[204.42, 204422.0, 204422.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[14.1, 14.1, 14.1];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[24.28, 24.28, 24.28];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[29.1, 29.1, 29.1];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[232.0, 232.0, 232.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[42.5, 42.5, 42.5];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[84.83, 84826.0, 84826.0];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[11.6, 11.6, 11.6];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[15.7, 15.7, 15.7];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[125.44, 125.44, 125.44];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[17.72, 17.72, 17.72];[0.0, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[161.2, 161204.0, 161204.0];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[45.14, 45139.0, 45139.0];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[141.24, 141.24, 141.24];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[117.1, 117.1, 117.1];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[204.42, 204422.0, 204422.0];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[14.1, 14.1, 14.1];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[24.28, 24.28, 24.28];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[29.1, 29.1, 29.1];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[232.0, 232.0, 232.0];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[42.5, 42.5, 42.5];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[84.83, 84826.0, 84826.0];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[11.6, 11.6, 11.6];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[15.7, 15.7, 15.7];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[125.44, 125.44, 125.44];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[17.72, 17.72, 17.72];[nan, 10000.0, 10000.0];[31.8, 31.3, 30.6];[13048000.0, 12200000.0, 10890000.0];10;[518080.0, 470600.0, 406100.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv index 24a5656..bc5fdf3 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_generator_steam.csv @@ -1,17 +1,17 @@ type;carrier;tech;capacity;capacity_potential;marginal_cost;capacity_cost;lifetime;fixed_costs;name;region;year;bus -dispatchable;carrier;tech;[3.6, 3.6, 3.6];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[6.7, 6696.0, 6696.0];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[13.63, 13.63114, 13.63114];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[60.47, 60.46996, 60.46996];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[3.7, 3.7, 3.7];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[5.62, 5.62, 5.62];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[0.0, 0.0, 0.0];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[8.5, 8.5, 8.5];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[48.88, 48.88, 48.88];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[186.53, 186.53, 186.53];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[5.0, 5.0, 5.0];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[1.71, 1.71, 1.71];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;[43.24, 43.24, 43.24];[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity -dispatchable;carrier;tech;;[0.0, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[3.6, 3.6, 3.6];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BB_carrier_tech;BB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[6.7, 6696.0, 6696.0];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BE_carrier_tech;BE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[13.63, 13.63114, 13.63114];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BW_carrier_tech;BW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[60.47, 60.46996, 60.46996];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];BY_carrier_tech;BY;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[3.7, 3.7, 3.7];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HB_carrier_tech;HB;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[5.62, 5.62, 5.62];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HE_carrier_tech;HE;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[0.0, 0.0, 0.0];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];HH_carrier_tech;HH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[8.5, 8.5, 8.5];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];MV_carrier_tech;MV;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[48.88, 48.88, 48.88];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NI_carrier_tech;NI;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[186.53, 186.53, 186.53];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];NW_carrier_tech;NW;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[5.0, 5.0, 5.0];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];RP_carrier_tech;RP;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SH_carrier_tech;SH;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SL_carrier_tech;SL;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[1.71, 1.71, 1.71];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];SN_carrier_tech;SN;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;[43.24, 43.24, 43.24];[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];ST_carrier_tech;ST;[2016, 2030, 2050];electricity +dispatchable;carrier;tech;;[nan, 10000.0, 10000.0];[25.9, 25.4, 24.7];[10640000.0, 9900000.0, 8800000.0];10;[422200.0, 382000.0, 328000.0];TH_carrier_tech;TH;[2016, 2030, 2050];electricity diff --git a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv index bc1f05b..315341d 100644 --- a/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv +++ b/tests/_files/tabular_datapackage_hack_a_thon_goal/data/elements/modex_tech_storage_pumped.csv @@ -1,17 +1,17 @@ type;carrier;tech;capacity;capacity_cost;capacity_potential;lifetime;fixed_costs;marginal_cost;name;region;year;invest_relation_output_capacity;inflow_conversion_factor;outflow_conversion_factor;bus storage;carrier;tech;;1500000.0;;10;22500.0;0.0;BB_carrier_tech;BB;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;BE_carrier_tech;BE;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;1873.0;1500000.0;[0.0, 1873.0, 1873.0];10;22500.0;0.0;BW_carrier_tech;BW;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;383.0;1500000.0;[0.0, 383.0, 383.0];10;22500.0;0.0;BY_carrier_tech;BY;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;1873.0;1500000.0;[nan, 1873.0, 1873.0];10;22500.0;0.0;BW_carrier_tech;BW;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;383.0;1500000.0;[nan, 383.0, 383.0];10;22500.0;0.0;BY_carrier_tech;BY;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;HB_carrier_tech;HB;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;625.0;1500000.0;[0.0, 625.0, 625.0];10;22500.0;0.0;HE_carrier_tech;HE;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;625.0;1500000.0;[nan, 625.0, 625.0];10;22500.0;0.0;HE_carrier_tech;HE;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;HH_carrier_tech;HH;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;MV_carrier_tech;MV;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;220.0;1500000.0;[0.0, 220.0, 220.0];10;22500.0;0.0;NI_carrier_tech;NI;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;303.0;1500000.0;[0.0, 303.0, 303.0];10;22500.0;0.0;NW_carrier_tech;NW;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;220.0;1500000.0;[nan, 220.0, 220.0];10;22500.0;0.0;NI_carrier_tech;NI;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;303.0;1500000.0;[nan, 303.0, 303.0];10;22500.0;0.0;NW_carrier_tech;NW;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;RP_carrier_tech;RP;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;119.1;1500000.0;[0.0, 119.1, 119.1];10;22500.0;0.0;SH_carrier_tech;SH;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;119.1;1500000.0;[nan, 119.1, 119.1];10;22500.0;0.0;SH_carrier_tech;SH;[2016, 2030, 2050];5.8;1.0;0.75;electricity storage;carrier;tech;;1500000.0;;10;22500.0;0.0;SL_carrier_tech;SL;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;1085.0;1500000.0;[0.0, 1085.0, 1085.0];10;22500.0;0.0;SN_carrier_tech;SN;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;79.7;1500000.0;[0.0, 79.7, 79.7];10;22500.0;0.0;ST_carrier_tech;ST;[2016, 2030, 2050];5.8;1.0;0.75;electricity -storage;carrier;tech;1509.4;1500000.0;[0.0, 1509.4, 1509.4];10;22500.0;0.0;TH_carrier_tech;TH;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;1085.0;1500000.0;[nan, 1085.0, 1085.0];10;22500.0;0.0;SN_carrier_tech;SN;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;79.7;1500000.0;[nan, 79.7, 79.7];10;22500.0;0.0;ST_carrier_tech;ST;[2016, 2030, 2050];5.8;1.0;0.75;electricity +storage;carrier;tech;1509.4;1500000.0;[nan, 1509.4, 1509.4];10;22500.0;0.0;TH_carrier_tech;TH;[2016, 2030, 2050];5.8;1.0;0.75;electricity From 4aae4732c0283ec67a38517cdf44edd5b46dd9f9 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Mon, 24 Jun 2024 13:51:02 +0200 Subject: [PATCH 17/37] Extend handling nans Now handeling also other columns than min/max --- data_adapter_oemof/calculations.py | 183 ++++++++++++++------- examples/industry/data_adapter_industry.py | 8 +- 2 files changed, 130 insertions(+), 61 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index e8f9dc8..c9b2392 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -160,73 +160,97 @@ def floor_lifetime(mapped_defaults): def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: """ - This function should find and fill in missing min and max values in the data - - Missing min value is set to 0. - Missing max value is set to 9999999999999. - - Min values: - capacity_p_min - capacity_e_min - capacity_w_min - flow_share_min_ - - Max values: - potential_annual_max - capacity_p_max - capacity_e_max - capacity_w_max - capacity_p_abs_new_max - capacity_e_abs_new_max - capacity_w_abs_new_max - availability_timeseries_max - capacity_tra_connection_max - flow_share_max_ - sto_cycles_max - sto_max_timeseries + This function shall handle found nans in the data. + + Identifiers are set pre-mapping! (Might implement mapping feature later) + + Providing data for one process with changing values and missing some values + cannot be handled by oemof.solph multi period feature. Either a value can be set + or it can be None but cannot be None in some year and be set in another. + + Sometimes data is still missing for some periods. + For most of these occurrences the missing data does not matter: + - The Investment in the invest-object is not allowed in these years + - Existing process is already decommissioned. + For these cases the missing data is marked `irrelevant`. + + The found nans are replaced: + - min/max values replaced by 0 or 9999999999999 (see `handle_min_max()`) + - `irrelevant` data is replaced by mean (arithmetic) + - Other is replaced by mean and warning is issued + + Parameters + ---------- + group_df Returns ------- """ - max_value = 9999999999999 - min_value = 0 - - min = ["capacity_p_min", "capacity_e_min", "capacity_w_min", "flow_share_min_"] - - max = [ - "potential_annual_max", - "capacity_p_max", - "capacity_e_max", - "capacity_w_max", - "capacity_p_abs_new_max", - "capacity_e_abs_new_max", - "capacity_w_abs_new_max", - "availability_timeseries_max", - "capacity_tra_connection_max", - "flow_share_max_", - "sto_cycles_max", - "sto_max_timeseries", - ] - - for column in group_df.columns: - if column in ["method", "source", "comment", "bandwidth_type"]: - continue - + def handle_min_max(group_df: pd.DataFrame) -> pd.DataFrame: """ - Following is a check whether nans can be filled. + This function should find and fill in missing min and max values in the data + + Missing min value is set to 0. + Missing max value is set to 9999999999999. + + Min values: + capacity_p_min + capacity_e_min + capacity_w_min + flow_share_min_ - Commented check for columns that are faulty and need to be changed - Commented Error for incomplete columns as we dont know where it may cause errors yet + Max values: + potential_annual_max + capacity_p_max + capacity_e_max + capacity_w_max + + availability_timeseries_max + capacity_tra_connection_max + flow_share_max_ + sto_cycles_max + sto_max_timeseries + + Returns + ------- """ - # if group_df[column].isna().sum() > 0 and not - # group_df[column].isna().sum()==len(group_df[column]): - if column in max: - group_df[column].fillna(max_value, inplace=True) - elif column in min: - group_df[column].fillna(min_value, inplace=True) + max_value = 9999999999999 + min_value = 0 + + min = ["capacity_p_min", "capacity_e_min", "capacity_w_min", "flow_share_min_"] + + max = [ + "potential_annual_max", + "capacity_p_max", + "capacity_e_max", + "capacity_w_max", + "availability_timeseries_max", + "capacity_tra_connection_max", + "flow_share_max_", + "sto_cycles_max", + "sto_max_timeseries", + ] + + for column in group_df.columns: + if column in ["method", "source", "comment", "bandwidth_type"]: + continue + + """ + Following is a check whether nans can be filled. + + Commented check for columns that are faulty and need to be changed + Commented Error for incomplete columns as we dont know where it may cause errors yet + + """ + # if group_df[column].isna().sum() > 0 and not + # group_df[column].isna().sum()==len(group_df[column]): + if column in max: + group_df[column].fillna(max_value, inplace=True) + elif column in min: + group_df[column].fillna(min_value, inplace=True) # else: # if "type" in group_df.columns: # @@ -240,3 +264,48 @@ def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: # f"In column {column} nan values are found \n" # f"please make sure to only provide complete datasets" # ) + + def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: + """ + Finds and replaces irrelevant Data. + + Searches for where investment is allowed + - If no Investment is allowed and there is no period above where investment was allowed + -> Data is replaced by mean + - If no Investment is allowed and there have been periods with investment before + -> Data is replaced by last value found + + Searches for decomissioned Processes + - If capacity of a process is 0 other nan data is replaced by mean. + + Parameters + ---------- + group_df + + Returns + ------- + + """ + + capacity_columns = ["capacity_p_inst_0", + "capacity_e_inst_0", + "capacity_w_inst_0", + "capacity_tra_inst_0"] + + invest_zero = [ + "capacity_p_abs_new_max", + "capacity_e_abs_new_max", + "capacity_w_abs_new_max", + "capacity_p_max", + "capacity_e_max", + "capacity_w_max" + ] + for capacity_col in capacity_columns: + for row in group_df.iterrows(): + + row['abx'] = np.where(group_df[capacity_col==0], 1, group_df[1]) + + group_df = handle_min_max(group_df) + group_df = find_and_replace_irrelevant_data(group_df) + + diff --git a/examples/industry/data_adapter_industry.py b/examples/industry/data_adapter_industry.py index c126b0b..aa21739 100644 --- a/examples/industry/data_adapter_industry.py +++ b/examples/industry/data_adapter_industry.py @@ -22,10 +22,10 @@ # in `collection.json` structure = Structure( - "Industriestruktur", - process_sheet="process_set_steel_casting", - parameter_sheet="parameter_input_output_steel_ca", - helper_sheet="steel_casting_helper", + "SEDOS_Modellstruktur", + process_sheet="Processes_O1", + parameter_sheet="Parameter_Input-Output", + helper_sheet="Helper_O1", ) adapter = Adapter( From 59e20ad816a16a84b81cf4b3925bec2a4e565878 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Tue, 25 Jun 2024 09:19:12 +0200 Subject: [PATCH 18/37] Linting --- data_adapter_oemof/calculations.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index c9b2392..8fe4250 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -265,7 +265,7 @@ def handle_min_max(group_df: pd.DataFrame) -> pd.DataFrame: # f"please make sure to only provide complete datasets" # ) - def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: + def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: """ Finds and replaces irrelevant Data. @@ -287,10 +287,12 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: """ - capacity_columns = ["capacity_p_inst_0", - "capacity_e_inst_0", - "capacity_w_inst_0", - "capacity_tra_inst_0"] + capacity_columns = [ + "capacity_p_inst_0", + "capacity_e_inst_0", + "capacity_w_inst_0", + "capacity_tra_inst_0", + ] invest_zero = [ "capacity_p_abs_new_max", @@ -298,14 +300,12 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: "capacity_w_abs_new_max", "capacity_p_max", "capacity_e_max", - "capacity_w_max" + "capacity_w_max", ] for capacity_col in capacity_columns: for row in group_df.iterrows(): - row['abx'] = np.where(group_df[capacity_col==0], 1, group_df[1]) + row["abx"] = np.where(group_df[capacity_col == 0], 1, group_df[1]) group_df = handle_min_max(group_df) group_df = find_and_replace_irrelevant_data(group_df) - - From a1a4f626aa8092688f72a0e162e6544013bb63d9 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Mon, 24 Jun 2024 13:51:02 +0200 Subject: [PATCH 19/37] Extend handling nans Now handeling also other columns than min/max --- data_adapter_oemof/calculations.py | 183 ++++++++++++++++++++--------- 1 file changed, 126 insertions(+), 57 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index e8f9dc8..c9b2392 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -160,73 +160,97 @@ def floor_lifetime(mapped_defaults): def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: """ - This function should find and fill in missing min and max values in the data - - Missing min value is set to 0. - Missing max value is set to 9999999999999. - - Min values: - capacity_p_min - capacity_e_min - capacity_w_min - flow_share_min_ - - Max values: - potential_annual_max - capacity_p_max - capacity_e_max - capacity_w_max - capacity_p_abs_new_max - capacity_e_abs_new_max - capacity_w_abs_new_max - availability_timeseries_max - capacity_tra_connection_max - flow_share_max_ - sto_cycles_max - sto_max_timeseries + This function shall handle found nans in the data. + + Identifiers are set pre-mapping! (Might implement mapping feature later) + + Providing data for one process with changing values and missing some values + cannot be handled by oemof.solph multi period feature. Either a value can be set + or it can be None but cannot be None in some year and be set in another. + + Sometimes data is still missing for some periods. + For most of these occurrences the missing data does not matter: + - The Investment in the invest-object is not allowed in these years + - Existing process is already decommissioned. + For these cases the missing data is marked `irrelevant`. + + The found nans are replaced: + - min/max values replaced by 0 or 9999999999999 (see `handle_min_max()`) + - `irrelevant` data is replaced by mean (arithmetic) + - Other is replaced by mean and warning is issued + + Parameters + ---------- + group_df Returns ------- """ - max_value = 9999999999999 - min_value = 0 - - min = ["capacity_p_min", "capacity_e_min", "capacity_w_min", "flow_share_min_"] - - max = [ - "potential_annual_max", - "capacity_p_max", - "capacity_e_max", - "capacity_w_max", - "capacity_p_abs_new_max", - "capacity_e_abs_new_max", - "capacity_w_abs_new_max", - "availability_timeseries_max", - "capacity_tra_connection_max", - "flow_share_max_", - "sto_cycles_max", - "sto_max_timeseries", - ] - - for column in group_df.columns: - if column in ["method", "source", "comment", "bandwidth_type"]: - continue - + def handle_min_max(group_df: pd.DataFrame) -> pd.DataFrame: """ - Following is a check whether nans can be filled. + This function should find and fill in missing min and max values in the data + + Missing min value is set to 0. + Missing max value is set to 9999999999999. + + Min values: + capacity_p_min + capacity_e_min + capacity_w_min + flow_share_min_ - Commented check for columns that are faulty and need to be changed - Commented Error for incomplete columns as we dont know where it may cause errors yet + Max values: + potential_annual_max + capacity_p_max + capacity_e_max + capacity_w_max + + availability_timeseries_max + capacity_tra_connection_max + flow_share_max_ + sto_cycles_max + sto_max_timeseries + + Returns + ------- """ - # if group_df[column].isna().sum() > 0 and not - # group_df[column].isna().sum()==len(group_df[column]): - if column in max: - group_df[column].fillna(max_value, inplace=True) - elif column in min: - group_df[column].fillna(min_value, inplace=True) + max_value = 9999999999999 + min_value = 0 + + min = ["capacity_p_min", "capacity_e_min", "capacity_w_min", "flow_share_min_"] + + max = [ + "potential_annual_max", + "capacity_p_max", + "capacity_e_max", + "capacity_w_max", + "availability_timeseries_max", + "capacity_tra_connection_max", + "flow_share_max_", + "sto_cycles_max", + "sto_max_timeseries", + ] + + for column in group_df.columns: + if column in ["method", "source", "comment", "bandwidth_type"]: + continue + + """ + Following is a check whether nans can be filled. + + Commented check for columns that are faulty and need to be changed + Commented Error for incomplete columns as we dont know where it may cause errors yet + + """ + # if group_df[column].isna().sum() > 0 and not + # group_df[column].isna().sum()==len(group_df[column]): + if column in max: + group_df[column].fillna(max_value, inplace=True) + elif column in min: + group_df[column].fillna(min_value, inplace=True) # else: # if "type" in group_df.columns: # @@ -240,3 +264,48 @@ def handle_nans(group_df: pd.DataFrame) -> pd.DataFrame: # f"In column {column} nan values are found \n" # f"please make sure to only provide complete datasets" # ) + + def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: + """ + Finds and replaces irrelevant Data. + + Searches for where investment is allowed + - If no Investment is allowed and there is no period above where investment was allowed + -> Data is replaced by mean + - If no Investment is allowed and there have been periods with investment before + -> Data is replaced by last value found + + Searches for decomissioned Processes + - If capacity of a process is 0 other nan data is replaced by mean. + + Parameters + ---------- + group_df + + Returns + ------- + + """ + + capacity_columns = ["capacity_p_inst_0", + "capacity_e_inst_0", + "capacity_w_inst_0", + "capacity_tra_inst_0"] + + invest_zero = [ + "capacity_p_abs_new_max", + "capacity_e_abs_new_max", + "capacity_w_abs_new_max", + "capacity_p_max", + "capacity_e_max", + "capacity_w_max" + ] + for capacity_col in capacity_columns: + for row in group_df.iterrows(): + + row['abx'] = np.where(group_df[capacity_col==0], 1, group_df[1]) + + group_df = handle_min_max(group_df) + group_df = find_and_replace_irrelevant_data(group_df) + + From 3cd5dd0f12cc4b5d553f7b35db2b375dac9152a6 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Tue, 25 Jun 2024 09:19:12 +0200 Subject: [PATCH 20/37] Linting --- data_adapter_oemof/calculations.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index c9b2392..8fe4250 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -265,7 +265,7 @@ def handle_min_max(group_df: pd.DataFrame) -> pd.DataFrame: # f"please make sure to only provide complete datasets" # ) - def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: + def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: """ Finds and replaces irrelevant Data. @@ -287,10 +287,12 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: """ - capacity_columns = ["capacity_p_inst_0", - "capacity_e_inst_0", - "capacity_w_inst_0", - "capacity_tra_inst_0"] + capacity_columns = [ + "capacity_p_inst_0", + "capacity_e_inst_0", + "capacity_w_inst_0", + "capacity_tra_inst_0", + ] invest_zero = [ "capacity_p_abs_new_max", @@ -298,14 +300,12 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame)->pd.DataFrame: "capacity_w_abs_new_max", "capacity_p_max", "capacity_e_max", - "capacity_w_max" + "capacity_w_max", ] for capacity_col in capacity_columns: for row in group_df.iterrows(): - row['abx'] = np.where(group_df[capacity_col==0], 1, group_df[1]) + row["abx"] = np.where(group_df[capacity_col == 0], 1, group_df[1]) group_df = handle_min_max(group_df) group_df = find_and_replace_irrelevant_data(group_df) - - From 5185b6005d57657738257d4243556a192ada87f5 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Fri, 5 Jul 2024 11:58:02 +0200 Subject: [PATCH 21/37] Add Documentation --- data_adapter_oemof/calculations.py | 52 +++++++++++++++++------------- 1 file changed, 29 insertions(+), 23 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 8fe4250..9812738 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -232,6 +232,9 @@ def handle_min_max(group_df: pd.DataFrame) -> pd.DataFrame: "flow_share_max_", "sto_cycles_max", "sto_max_timeseries", + "capacity_p_abs_new_max", + "capacity_e_abs_new_max", + "capacity_w_abs_new_max", ] for column in group_df.columns: @@ -245,25 +248,12 @@ def handle_min_max(group_df: pd.DataFrame) -> pd.DataFrame: Commented Error for incomplete columns as we dont know where it may cause errors yet """ - # if group_df[column].isna().sum() > 0 and not - # group_df[column].isna().sum()==len(group_df[column]): if column in max: - group_df[column].fillna(max_value, inplace=True) + group_df[column] = group_df[column].fillna(max_value) elif column in min: - group_df[column].fillna(min_value, inplace=True) - # else: - # if "type" in group_df.columns: - # - # raise ValueError( - # f"In column {column} for process {group_df['type']} nan values are found" - # f"please make sure to only provide complete datasets" - # ) - # else: - # print(group_df) - # raise ValueError( - # f"In column {column} nan values are found \n" - # f"please make sure to only provide complete datasets" - # ) + group_df[column] = group_df[column].fillna(min_value) + + return group_df def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: """ @@ -271,9 +261,9 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: Searches for where investment is allowed - If no Investment is allowed and there is no period above where investment was allowed - -> Data is replaced by mean + -> Data is replaced by pandas ffil/bfill - If no Investment is allowed and there have been periods with investment before - -> Data is replaced by last value found + -> Data is replaced by pandas ffil/bfill Searches for decomissioned Processes - If capacity of a process is 0 other nan data is replaced by mean. @@ -302,10 +292,26 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: "capacity_e_max", "capacity_w_max", ] - for capacity_col in capacity_columns: - for row in group_df.iterrows(): + # no investment in decommissioning processes + # no capacity can be set on investment objects + if not any([x in capacity_columns for x in group_df.columns]): + for invest_column in invest_zero: + if invest_column in group_df.columns: + non_investment_indices = group_df[invest_column] == 0 + # In Case the first values are missing we have to bfill and in case the last values are missing + # we have to ffil which is why we cannot use interpolate reliably since + # in most cases boundary values are missing + group_df.loc[non_investment_indices] = group_df.bfill().loc[non_investment_indices] + group_df.loc[non_investment_indices] = group_df.ffill().loc[non_investment_indices] + else: + for capacity_c in capacity_columns: + if capacity_c in group_df.columns: + zero_capacity_columns_indices = group_df[capacity_c] == 0 + group_df.loc[zero_capacity_columns_indices] = group_df.bfill().loc[zero_capacity_columns_indices] + group_df.loc[zero_capacity_columns_indices] = group_df.ffill().loc[zero_capacity_columns_indices] + + return group_df - row["abx"] = np.where(group_df[capacity_col == 0], 1, group_df[1]) group_df = handle_min_max(group_df) - group_df = find_and_replace_irrelevant_data(group_df) + return find_and_replace_irrelevant_data(group_df) From f494cc875267b62c75a2b82f6a9a39982a103c39 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Fri, 5 Jul 2024 11:58:17 +0200 Subject: [PATCH 22/37] Bugfix --- examples/industry/data_adapter_industry.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/examples/industry/data_adapter_industry.py b/examples/industry/data_adapter_industry.py index 5e64bbe..45e9736 100644 --- a/examples/industry/data_adapter_industry.py +++ b/examples/industry/data_adapter_industry.py @@ -56,7 +56,7 @@ sheet_name="Helper_O1", usecols=("process", "facade adapter (oemof)"), index_col="process" - )]).to_dict(orient="dict") + )]).to_dict(orient="dict")['facade adapter (oemof)'] From faaca01a5b9e2283d7aa343c57280e77c8da1c72 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Fri, 5 Jul 2024 11:58:27 +0200 Subject: [PATCH 23/37] Dependencies --- poetry.lock | 86 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"pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"] [[package]] name = "shellingham" @@ -2532,13 +2532,13 @@ files = [ [[package]] name = "virtualenv" -version = "20.26.2" +version = "20.26.3" description = "Virtual Python Environment builder" optional = false python-versions = ">=3.7" files = [ - {file = "virtualenv-20.26.2-py3-none-any.whl", hash = "sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b"}, - {file = "virtualenv-20.26.2.tar.gz", hash = "sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c"}, + {file = "virtualenv-20.26.3-py3-none-any.whl", hash = "sha256:8cc4a31139e796e9a7de2cd5cf2489de1217193116a8fd42328f1bd65f434589"}, + {file = "virtualenv-20.26.3.tar.gz", hash = "sha256:4c43a2a236279d9ea36a0d76f98d84bd6ca94ac4e0f4a3b9d46d05e10fea542a"}, ] [package.dependencies] From 4d017e011ce8bb333fa25b8cda7d5c2d7fc2cc5d Mon Sep 17 00:00:00 2001 From: FelixMau Date: Fri, 5 Jul 2024 12:02:42 +0200 Subject: [PATCH 24/37] Linting --- data_adapter_oemof/adapters.py | 1 - data_adapter_oemof/build_datapackage.py | 1 - data_adapter_oemof/calculations.py | 23 +++++---- examples/industry/data_adapter_industry.py | 56 ++++++++++++---------- 4 files changed, 47 insertions(+), 34 deletions(-) diff --git a/data_adapter_oemof/adapters.py b/data_adapter_oemof/adapters.py index 8f78bbb..9f719a8 100644 --- a/data_adapter_oemof/adapters.py +++ b/data_adapter_oemof/adapters.py @@ -4,7 +4,6 @@ import itertools import json import logging -import warnings from typing import Optional, Type, Union import pandas as pd diff --git a/data_adapter_oemof/build_datapackage.py b/data_adapter_oemof/build_datapackage.py index 0adbc19..d6532b9 100644 --- a/data_adapter_oemof/build_datapackage.py +++ b/data_adapter_oemof/build_datapackage.py @@ -5,7 +5,6 @@ import numpy as np import pandas as pd -import numpy as np import tsam.timeseriesaggregation as tsam from data_adapter.preprocessing import Adapter from datapackage import Package diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 9812738..707f2eb 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -298,20 +298,27 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: for invest_column in invest_zero: if invest_column in group_df.columns: non_investment_indices = group_df[invest_column] == 0 - # In Case the first values are missing we have to bfill and in case the last values are missing - # we have to ffil which is why we cannot use interpolate reliably since - # in most cases boundary values are missing - group_df.loc[non_investment_indices] = group_df.bfill().loc[non_investment_indices] - group_df.loc[non_investment_indices] = group_df.ffill().loc[non_investment_indices] + # In Case first values are missing bfil is used in case last values missed + # ffil is used. In most cases boundary values are missing + # therefore interpolation is no viable option. + group_df.loc[non_investment_indices] = group_df.bfill().loc[ + non_investment_indices + ] + group_df.loc[non_investment_indices] = group_df.ffill().loc[ + non_investment_indices + ] else: for capacity_c in capacity_columns: if capacity_c in group_df.columns: zero_capacity_columns_indices = group_df[capacity_c] == 0 - group_df.loc[zero_capacity_columns_indices] = group_df.bfill().loc[zero_capacity_columns_indices] - group_df.loc[zero_capacity_columns_indices] = group_df.ffill().loc[zero_capacity_columns_indices] + group_df.loc[zero_capacity_columns_indices] = group_df.bfill().loc[ + zero_capacity_columns_indices + ] + group_df.loc[zero_capacity_columns_indices] = group_df.ffill().loc[ + zero_capacity_columns_indices + ] return group_df - group_df = handle_min_max(group_df) return find_and_replace_irrelevant_data(group_df) diff --git a/examples/industry/data_adapter_industry.py b/examples/industry/data_adapter_industry.py index 45e9736..06ff1db 100644 --- a/examples/industry/data_adapter_industry.py +++ b/examples/industry/data_adapter_industry.py @@ -9,17 +9,18 @@ from data_adapter.databus import download_collection # noqa from data_adapter.preprocessing import Adapter # noqa: E402 from data_adapter.structure import Structure # noqa: E402 -from data_adapter_oemof.build_datapackage import DataPackage # noqa: E402 - -from oemof.solph._energy_system import EnergySystem from oemof.solph import Model - +from oemof.solph._energy_system import EnergySystem +from oemof.solph.buses import Bus from oemof.tabular.datapackage import building # noqa F401 -from oemof.tabular.datapackage.reading import deserialize_constraints, deserialize_energy_system - -from oemof.tabular.facades import Excess, Commodity, Conversion, Load, Volatile +from oemof.tabular.datapackage.reading import ( + deserialize_constraints, + deserialize_energy_system, +) +from oemof.tabular.facades import Commodity, Conversion, Excess, Load, Volatile from oemof_industry.mimo_converter import MIMO -from oemof.solph.buses import Bus + +from data_adapter_oemof.build_datapackage import DataPackage # noqa: E402 EnergySystem.from_datapackage = classmethod(deserialize_energy_system) @@ -46,18 +47,22 @@ ) # create dicitonary with all found in and outputs -process_adapter_map = pd.concat([pd.read_excel( +process_adapter_map = pd.concat( + [ + pd.read_excel( io=structure.structure_file, sheet_name="Processes_O1", usecols=("process", "facade adapter (oemof)"), - index_col="process" - ), pd.read_excel( + index_col="process", + ), + pd.read_excel( io=structure.structure_file, sheet_name="Helper_O1", usecols=("process", "facade adapter (oemof)"), - index_col="process" - )]).to_dict(orient="dict")['facade adapter (oemof)'] - + index_col="process", + ), + ] +).to_dict(orient="dict")["facade adapter (oemof)"] parameter_map = { @@ -86,15 +91,18 @@ dp.save_datapackage_to_csv(str(datapackage_path)) -es = EnergySystem.from_datapackage(path = "datapackage/datapackage.json", - typemap= {"bus": Bus, - "excess":Excess, - "commodity": Commodity, - "conversion": Conversion, - "load": Load, - "volatile": Volatile, - "mimo": MIMO}, - ) +es = EnergySystem.from_datapackage( + path="datapackage/datapackage.json", + typemap={ + "bus": Bus, + "excess": Excess, + "commodity": Commodity, + "conversion": Conversion, + "load": Load, + "volatile": Volatile, + "mimo": MIMO, + }, +) m = Model(es) -m.solve() \ No newline at end of file +m.solve() From b3402f9f67e39c2a45d0acde6a2cf185ae657079 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Fri, 5 Jul 2024 12:05:30 +0200 Subject: [PATCH 25/37] Addin .env for example --- examples/industry/.env | 2 ++ examples/industry/data_adapter_industry.py | 5 ----- 2 files changed, 2 insertions(+), 5 deletions(-) create mode 100644 examples/industry/.env diff --git a/examples/industry/.env b/examples/industry/.env new file mode 100644 index 0000000..2a764b6 --- /dev/null +++ b/examples/industry/.env @@ -0,0 +1,2 @@ +COLLECTIONS_DIR = ./collections/ +STRUCTURES_DIR= "" diff --git a/examples/industry/data_adapter_industry.py b/examples/industry/data_adapter_industry.py index 06ff1db..356c3f6 100644 --- a/examples/industry/data_adapter_industry.py +++ b/examples/industry/data_adapter_industry.py @@ -1,11 +1,6 @@ -import os import pathlib import pandas as pd - -os.environ["COLLECTIONS_DIR"] = "./collections/" -os.environ["STRUCTURES_DIR"] = "" - from data_adapter.databus import download_collection # noqa from data_adapter.preprocessing import Adapter # noqa: E402 from data_adapter.structure import Structure # noqa: E402 From 18328d305a8a73a54989530b24055a3a1703d569 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Fri, 5 Jul 2024 12:36:33 +0200 Subject: [PATCH 26/37] More docu --- data_adapter_oemof/calculations.py | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 707f2eb..fde72b3 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -297,10 +297,14 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: if not any([x in capacity_columns for x in group_df.columns]): for invest_column in invest_zero: if invest_column in group_df.columns: + # Get rows where allowed investment is 0 non_investment_indices = group_df[invest_column] == 0 + # In Case first values are missing bfil is used in case last values missed # ffil is used. In most cases boundary values are missing # therefore interpolation is no viable option. + + # Fill all nans in rows where no investment is allowed group_df.loc[non_investment_indices] = group_df.bfill().loc[ non_investment_indices ] @@ -310,7 +314,10 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: else: for capacity_c in capacity_columns: if capacity_c in group_df.columns: + # Get rows where capacity is decommissioned zero_capacity_columns_indices = group_df[capacity_c] == 0 + + # Fill nan values for rows where capacity is decommissioned group_df.loc[zero_capacity_columns_indices] = group_df.bfill().loc[ zero_capacity_columns_indices ] From 98e072582cd1040bf56c083c5b87cc93a025fdcf Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 10 Jul 2024 13:04:08 +0200 Subject: [PATCH 27/37] Using pd.DataFrame.where --- data_adapter_oemof/calculations.py | 43 ++++++++++++------------------ 1 file changed, 17 insertions(+), 26 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index fde72b3..00db76c 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -300,32 +300,23 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: # Get rows where allowed investment is 0 non_investment_indices = group_df[invest_column] == 0 - # In Case first values are missing bfil is used in case last values missed - # ffil is used. In most cases boundary values are missing - # therefore interpolation is no viable option. - - # Fill all nans in rows where no investment is allowed - group_df.loc[non_investment_indices] = group_df.bfill().loc[ - non_investment_indices - ] - group_df.loc[non_investment_indices] = group_df.ffill().loc[ - non_investment_indices - ] - else: - for capacity_c in capacity_columns: - if capacity_c in group_df.columns: - # Get rows where capacity is decommissioned - zero_capacity_columns_indices = group_df[capacity_c] == 0 - - # Fill nan values for rows where capacity is decommissioned - group_df.loc[zero_capacity_columns_indices] = group_df.bfill().loc[ - zero_capacity_columns_indices - ] - group_df.loc[zero_capacity_columns_indices] = group_df.ffill().loc[ - zero_capacity_columns_indices - ] - - return group_df + group_df.mask( + group_df[invest_column] == 0, + group_df.fillna(group_df.mean(numeric_only=True)), + axis=1, + inplace=True, + ) + return group_df + for capacity_c in capacity_columns: + if capacity_c in group_df.columns: + # Fill rows where capacity is decommissioned + group_df.mask( + group_df[capacity_c] == 0, + group_df.fillna(group_df.mean(numeric_only=True)), + axis=1, + inplace=True, + ) + return group_df group_df = handle_min_max(group_df) return find_and_replace_irrelevant_data(group_df) From 90c55be82727ea9b97e61c04d4998608a84ec86b Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 10 Jul 2024 13:04:34 +0200 Subject: [PATCH 28/37] Remove unnecessary checks update doc --- data_adapter_oemof/calculations.py | 18 +++++++----------- 1 file changed, 7 insertions(+), 11 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 00db76c..0780133 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -260,13 +260,9 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: Finds and replaces irrelevant Data. Searches for where investment is allowed - - If no Investment is allowed and there is no period above where investment was allowed - -> Data is replaced by pandas ffil/bfill - - If no Investment is allowed and there have been periods with investment before - -> Data is replaced by pandas ffil/bfill - + - If allowed Investmet is 0, nan data is replaced by mean. Searches for decomissioned Processes - - If capacity of a process is 0 other nan data is replaced by mean. + - If capacity of a process is 0, nan data is replaced by mean. Parameters ---------- @@ -294,11 +290,11 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: ] # no investment in decommissioning processes # no capacity can be set on investment objects - if not any([x in capacity_columns for x in group_df.columns]): - for invest_column in invest_zero: - if invest_column in group_df.columns: - # Get rows where allowed investment is 0 - non_investment_indices = group_df[invest_column] == 0 + for invest_column in invest_zero: + if invest_column in group_df.columns and not any( + [cap_col in capacity_columns for cap_col in group_df.columns] + ): + # Fill rows where allowed investment is 0 group_df.mask( group_df[invest_column] == 0, From ff1b1e926d2c826c83d0cd67b0be97011dbf0cd6 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 10 Jul 2024 13:04:48 +0200 Subject: [PATCH 29/37] Add test skript --- tests/test_build_datapackage.py | 53 +++++++++++++++++++++++++++++++++ 1 file changed, 53 insertions(+) diff --git a/tests/test_build_datapackage.py b/tests/test_build_datapackage.py index 99a1fbb..dfff5c8 100644 --- a/tests/test_build_datapackage.py +++ b/tests/test_build_datapackage.py @@ -228,4 +228,57 @@ def test_decomissioning(): data_adapter_industry +def test_filling_nans(): + """ + Test to fill nan values on rows where Investment is 0 or capacity is 0 + Returns + ------- + + """ + structure = Structure( + "test_fill_nans", + process_sheet="Processes_O1", + parameter_sheet="Parameter_Input-Output", + helper_sheet="Helper_O1", + ) + adapter = Adapter( + "test_fill_nans", + structure=structure, + ) + + process_adapter_map = { + "ind_steel_casting_0": "MIMOAdapter", + "ind_steel_hyddri_1": "MIMOAdapter", + } + + parameter_map = { + "DEFAULT": {"capacity_w_inst_0": "capacity", "capacity": "capacity_w_inst_0"} + } + + data_package = DataPackage.build_datapackage( + adapter, process_adapter_map, parameter_map + ) + + assert ( + data_package.parametrized_elements["ind_steel_casting_0"][ + "conversion_factor_sec_methane" + ][0] + == 1.5774000000000008 + ) + assert data_package.parametrized_elements["ind_steel_hyddri_1"][ + "conversion_factor_sec_elec_ind" + ][0] == [ + 0.7000000000000001, + 0.7000000000000001, + 0.7000000000000001, + 0.7000000000000001, + 0.7, + 0.7, + 0.7, + 0.7, + 0.7, + 0.7, + ] + + # Check wheter result would be correct From e2596f4d82d9712d73dd7e32c9bfdede4a6c9be2 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 10 Jul 2024 13:04:57 +0200 Subject: [PATCH 30/37] bugfix --- data_adapter_oemof/build_datapackage.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data_adapter_oemof/build_datapackage.py b/data_adapter_oemof/build_datapackage.py index d6532b9..6c9fc0d 100644 --- a/data_adapter_oemof/build_datapackage.py +++ b/data_adapter_oemof/build_datapackage.py @@ -49,7 +49,7 @@ def _listify_to_periodic(group_df) -> pd.Series: """ - handle_nans(group_df) + group_df = handle_nans(group_df) if "year" not in group_df.columns: return group_df unique_values = pd.Series(dtype=object) From f125bc5cc0d3aa24520e52226ee021995cbd99cc Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 10 Jul 2024 13:06:59 +0200 Subject: [PATCH 31/37] Add test collection and struct --- .../srd_range_draft/ind_steel_casting_0.csv | 11 ++++ .../srd_range_draft/ind_steel_casting_0.json | 1 + .../srd_range_draft/ind_steel_hyddri_1.csv | 11 ++++ .../srd_range_draft/ind_steel_hyddri_1.json | 1 + .../test_fill_nans/collection.json | 50 ++++++++++++++++++ tests/structures/test_fill_nans.xlsx | Bin 0 -> 79091 bytes 6 files changed, 74 insertions(+) create mode 100644 tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv create mode 100644 tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.json create mode 100644 tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.csv create mode 100644 tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json create mode 100644 tests/collections/test_fill_nans/collection.json create mode 100644 tests/structures/test_fill_nans.xlsx diff --git a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv new file mode 100644 index 0000000..96f12a5 --- /dev/null +++ b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv @@ -0,0 +1,11 @@ +"id","region","year","type","conversion_factor_exo_steel","conversion_factor_iip_heat_proc","conversion_factor_sec_elec_ind","conversion_factor_iip_steel_crudesteel","ef_sec_methane_emi_ch4_f_ind","ef_sec_methane_emi_co2_f_ind","ef_sec_methane_emi_n2o_f_ind","flow_share_max_sec_hydrogen","capacity_w_abs_new_max","lifetime","capacity_w_inst_0","conversion_factor_sec_methane","conversion_factor_sec_hydrogen","wacc","bandwidth_type","version","method","source","comment" +1,"DE",2021,"ind_steel_casting_0",1.0,0.345,0.7749,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,0.0,0.0,30.0,42.6,1.5774000000000008,1.5774000000000008,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +2,"DE",2024,"ind_steel_casting_0",1.0,0.345,0.7749,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,0.0,0.0,30.0,39.4444,1.5774000000000008,1.5774000000000008,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +3,"DE",2027,"ind_steel_casting_0",1.0,0.345,0.7749,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,0.0,0.0,30.0,31.5556,1.5774000000000008,1.5774000000000008,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +4,"DE",2030,"ind_steel_casting_0",1.0,0.345,0.7749,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,50.0,0.0,30.0,23.6667,1.5774000000000008,1.5774000000000008,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +5,"DE",2035,"ind_steel_casting_0",1.0,0.345,0.7749,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,100.0,0.0,30.0,15.7778,1.5774000000000008,1.5774000000000008,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +6,"DE",2040,"ind_steel_casting_0",1.0,0.345,0.7749,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,100.0,0.0,30.0,7.8889,1.5774000000000008,1.5774000000000008,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +7,"DE",2045,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +8,"DE",2050,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +9,"DE",2060,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +10,"DE",2070,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" \ No newline at end of file diff --git a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.json b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.json new file mode 100644 index 0000000..1756a8d --- /dev/null +++ b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.json @@ -0,0 +1 @@ +{"id": "https://openenergy-platform.org/dataedit/view/model_draft/ind_steel_casting_0", "@id": null, "name": "ind_steel_casting_0", "title": "sedos_ind_steel_casting_0", "review": {"path": null, "badge": null}, "context": {"contact": "ulrich.fahl@ier.uni-stuttgart.de", "grantNo": null, "homepage": "https://sedos-project.github.io/.github/", "sourceCode": "https://github.com/sedos-project", "documentation": "https://sedos-project.github.io/.github/", "fundingAgency": "Bundesministerium f\u00c3\u00bcr Wirtschaft und Klimaschutz (BMWK)", "publisherLogo": null, "fundingAgencyLogo": "https://en.wikipedia.org/wiki/Federal_Ministry_for_Economic_Affairs_and_Climate_Action#/media/File:BMWi_Logo_2021.svg"}, "sources": [{"path": "https://github.com/sedos-project/oedatamodel/tree/main/oedatamodel-parameter", "title": "OEDatamodel-parameter", "licenses": [{"name": "CC0-1.0", "path": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", "title": "Creative Commons Zero v1.0 Universal", "attribution": null, "instruction": "You are free: To Share, To Create, To Adapt"}], "description": "Parameter data model for secondary input scalars and timeseries"}, {"path": null, "title": "TAM Industry Model", "licenses": [{"name": "Creative Commons Attribution 4.0 International", "path": "https://creativecommons.org/licenses/by/4.0/", "title": "CC BY 4.0", "attribution": "@Energy Economics and Social Analysis(ESA), IER, University of Stuttgart", "instruction": null}], "description": "TAM Industry is based on TIMES and focuses on German industry energy system"}], "spatial": {"extent": "DE", "location": "Germany", "resolution": "NUTS-0"}, "subject": [{"name": "Industry Sector", "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227/"}, {"name": "Industry Sub-sector", "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227"}], "@context": "https://raw.githubusercontent.com/OpenEnergyPlatform/oemetadata/develop/metadata/latest/context.json", "_comment": {"null": "If not applicable use: null", "todo": "If a value is not yet available, use: todo", "dates": "Dates and time must follow the ISO8601 including time zone (YYYY-MM-DD or YYYY-MM-DDThh:mm:ss\u00b1hh)", "units": "Use a space between numbers and units (100 m)", "review": "Following the OEP Data Review (https://github.com/OpenEnergyPlatform/data-preprocessing/blob/master/data-review/manual/review_manual.md)", "licenses": "License name must follow the SPDX License List (https://spdx.org/licenses/)", "metadata": "Metadata documentation and explanation (https://github.com/OpenEnergyPlatform/oemetadata)", "languages": "Languages must follow the IETF (BCP47) format (en-GB, en-US, de-DE)"}, "keywords": ["SEDOS", "input_data", "AP7", "Industry", "oedatamodel-parameter", "steel"], "language": ["en-GB"], "licenses": [{"name": "CC-BY-4.0", "path": "https://creativecommons.org/licenses/by/4.0/?ref=chooser-v1", "title": "Creative Commons Attribution 4.0 International", "attribution": null, "instruction": "You are free to: Share- copy and redistribute the material in any medium or format for any purpose, even commercially. Adapt - remix, transform, and build upon the material for any purpose, even commercially."}], "temporal": {"timeseries": [{"end": "2070-12-31", "start": "2021-01-01", "alignment": null, "resolution": "yearly", "aggregationType": null}], "referenceDate": "2021"}, "resources": [{"name": "model_draft.ind_steel_casting_0", "path": "https://openenergy-platform.org/dataedit/view/model_draft/ind_steel_casting_0", "format": "PostgreSQL", "schema": {"fields": [{"name": "id", "type": "bigint", "unit": null, "isAbout": [], "description": "Unique identifier", "valueReference": []}, {"name": "region", "type": "text", "unit": null, "isAbout": [], "description": "Country or regionx", "valueReference": []}, {"name": "year", "type": "integer", "unit": "a", "isAbout": [], "description": "Year", "valueReference": []}, {"name": "type", "type": "text", "unit": null, "isAbout": [], "description": "Type of process", "valueReference": []}, {"name": "conversion_factor_exo_steel", "type": "float", "unit": "Mt", 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"valueReference": []}, {"name": "conversion_factor_iip_steel_crudesteel", "type": "float", "unit": "Mt/Mt", "isAbout": [{"name": "energy conversion efficiency", "path": "http://openenergyplatform.org/ontology/oeo/OEO_00140049/"}], "description": "Commodity-specific conversion factor (multiplication of input and output factors yields the efficiency of the process).", "valueReference": []}, {"name": "ef_sec_methane_emi_ch4_f_ind", "type": "float", "unit": "Kt/PJ", "isAbout": [{"name": "emission factor", "path": "http://openenergyplatform.org/ontology/oeo/OEO_00000148/"}], "description": "Emission factor for a process flow per output.", "valueReference": []}, {"name": "ef_sec_methane_emi_co2_f_ind", "type": "text", "unit": "Kt/PJ", "isAbout": [{"name": "emission factor", "path": "http://openenergyplatform.org/ontology/oeo/OEO_00000148/"}], "description": "Emission factor for a process flow per output.", "valueReference": []}, {"name": "ef_sec_methane_emi_n2o_f_ind", "type": "float", "unit": "Kt/PJ", "isAbout": [{"name": "emission factor", "path": "http://openenergyplatform.org/ontology/oeo/OEO_00000148/"}], "description": "Emission factor for a process flow per output.", "valueReference": []}, {"name": "flow_share_max_sec_hydrogen", "type": "float", "unit": "%", "isAbout": [{"name": "flow potential", "path": "http://openenergyplatform.org/ontology/oeo/OEO_00140056/"}], "description": "Maximum share of flow commodity c based upon the sum of individual flows defined by the commodity group cg belonging to process p.", "valueReference": []}, {"name": "capacity_w_abs_new_max", "type": "float", "unit": "Mt", "isAbout": [{"name": null, "path": null}], "description": "Absolute upper bound on level of investment in new weight capacity for a period.", "valueReference": []}, {"name": "lifetime", "type": "float", "unit": "a", "isAbout": [{"name": "operational life time", "path": "http://openenergyplatform.org/ontology/oeo/OEO_00020178/"}], "description": "Technical lifetime 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Casting Plant & Hot Rolling Mill", "contributors": [{"date": "2024-06-26", "email": "md-anik.islam@ier.uni-stuttgart.de", "title": "Anik Islam", "object": "data and metadata for industry", "comment": "Created data and metadata in specific format based on provided data"}, {"date": "2024-06-26", "email": "isela.bailey@ier.uni-stuttgart.de", "title": "Isela Bailey", "object": "data and metadata for industry", "comment": "Prepared and Provided data and necessary details of cement, glass, steel, aluminium and paper industry"}], "metaMetadata": {"metadataLicense": {"name": "CC0-1.0", "path": "https://creativecommons.org/publicdomain/zero/1.0/", "title": "Creative Commons Zero v1.0 Universal"}, "metadataVersion": "OEP-1.5.2"}, "publicationDate": "2024-06-26"} \ No newline at end of file diff --git a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.csv b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.csv new file mode 100644 index 0000000..755637b --- /dev/null +++ b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.csv @@ -0,0 +1,11 @@ +"id","region","year","type","conversion_factor_iip_steel_crudesteel","conversion_factor_sec_elec_ind","conversion_factor_sec_hydrogen","availability_constant","capacity_w_abs_new_max","cost_inv_w","cost_fix_w","lifetime","wacc","bandwidth_type","version","method","source","comment" +1,"DE",2021,"ind_steel_hyddri_1","","","","",0.0,"","","","global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +2,"DE",2024,"ind_steel_hyddri_1","","","","",0.0,"","","","global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +3,"DE",2027,"ind_steel_hyddri_1","","","","",0.0,"","","","global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +4,"DE",2030,"ind_steel_hyddri_1","","","","",0.0,"","","","global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +5,"DE",2035,"ind_steel_hyddri_1",1.0,0.7,17.0,85.0,"",400.0,10.0,40.0,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +6,"DE",2040,"ind_steel_hyddri_1",1.0,0.7,17.0,85.0,"",400.0,10.0,40.0,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +7,"DE",2045,"ind_steel_hyddri_1",1.0,0.7,17.0,85.0,"",400.0,10.0,40.0,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +8,"DE",2050,"ind_steel_hyddri_1",1.0,0.7,17.0,85.0,"",400.0,10.0,40.0,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +9,"DE",2060,"ind_steel_hyddri_1",1.0,0.7,17.0,85.0,"",400.0,10.0,40.0,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" +10,"DE",2070,"ind_steel_hyddri_1",1.0,0.7,17.0,85.0,"",400.0,10.0,40.0,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" diff --git a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json new file mode 100644 index 0000000..e76ce7a --- /dev/null +++ b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json @@ -0,0 +1 @@ +{"id": "https://openenergy-platform.org/dataedit/view/model_draft/ind_steel_hyddri_1", "@id": null, "name": "ind_steel_hyddri_1", "title": "sedos_ind_steel_hyddri_1", "review": {"path": null, "badge": null}, "context": {"contact": "ulrich.fahl@ier.uni-stuttgart.de", "grantNo": null, "homepage": "https://sedos-project.github.io/.github/", "sourceCode": "https://github.com/sedos-project", "documentation": "https://sedos-project.github.io/.github/", "fundingAgency": "Bundesministerium f\u00c3\u00bcr Wirtschaft und Klimaschutz (BMWK)", "publisherLogo": null, "fundingAgencyLogo": "https://en.wikipedia.org/wiki/Federal_Ministry_for_Economic_Affairs_and_Climate_Action#/media/File:BMWi_Logo_2021.svg"}, "sources": [{"path": "https://github.com/sedos-project/oedatamodel/tree/main/oedatamodel-parameter", "title": "OEDatamodel-parameter", "licenses": [{"name": "CC0-1.0", "path": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", "title": "Creative Commons Zero v1.0 Universal", "attribution": null, "instruction": "You are free: To Share, To Create, To Adapt"}], "description": "Parameter data model for secondary input scalars and timeseries"}, {"path": null, "title": "TAM Industry Model", "licenses": [{"name": "Creative Commons Attribution 4.0 International", "path": "https://creativecommons.org/licenses/by/4.0/", "title": "CC BY 4.0", "attribution": "@Energy Economics and Social Analysis(ESA), IER, University of Stuttgart", "instruction": null}], "description": "TAM Industry is based on TIMES and focuses on German industry energy system"}], "spatial": {"extent": "DE", "location": "Germany", "resolution": "NUTS-0"}, "subject": [{"name": "Industry Sector", "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227/"}, {"name": "Industry Sub-sector", "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227"}], "@context": "https://raw.githubusercontent.com/OpenEnergyPlatform/oemetadata/develop/metadata/latest/context.json", "_comment": {"null": "If not applicable use: null", "todo": "If a value is not yet available, use: todo", "dates": "Dates and time must follow the ISO8601 including time zone (YYYY-MM-DD or YYYY-MM-DDThh:mm:ss\u00b1hh)", "units": "Use a space between numbers and units (100 m)", "review": "Following the OEP Data Review (https://github.com/OpenEnergyPlatform/data-preprocessing/blob/master/data-review/manual/review_manual.md)", "licenses": "License name must follow the SPDX License List (https://spdx.org/licenses/)", "metadata": "Metadata documentation and explanation 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z^rRae9=BlrZmz#F--@>NjswhJI3N(_L(Gmx518#d+}s@8eUJxtX8Dy{ZFu!J3t9+7 z{Z9zw_#tj-nged658BlMNv>f@3a!yg3=jz05ClR>qx$FQJn=tL|D04MNe;!WmX1N> z6a=#L?N<~_9|QJo$ke@GQIHqOqDYfN z$yqa}E&$3n1#Bnqk5WKM#PU~^zn$VhNwOp?vhL9~BAH4aP{8V601wnn7EtMJ{KZ#5 zp8Wq$LawX-0(js+WC43Wj$6DW3kbXRFMtPGc4PtL?QoCDcUcATFMtR3APd;N*&Blg z-8E+W)hKe-{{nd6Y-9m7;|mzy06(t}rTE4BU9SHM_>X;m9e$AoCbOGh3~4_4)#H4< z$)d=S^SDtSnyh`Geu`tj>%jS+qblS8W2=@*l1CJNMiI3BzJ;|WADdv9AmXLm>Be+y*e!MiQ)s^5VOHXwNY_D@GZ z2^)48#n;XC!rzFJFi`%#i^Cjw80bH8kqs=G4zWQkK%Da+E*}2Z--4yhdDs`uc^su zrQn5U#9hGs9dLs&@Y7Ke4}sWw*cp0zcp@e2JiHyq`D-ookE2w8{Rwy+Zrm;LCw5y; zPjcKUX&OU%fU^c@ll7;jA&~NvNCWZYr^7StKzT?fTW<$@6CZDqyOTrsIXU_8SfT4YK=?Hwne4^; h=gG)nl)(+MDE}F^R3J`3Ag94!Eg0#)ive9g{vX6TSy2E0 literal 0 HcmV?d00001 From d276d805310f48bfb82eef489b702a4d49fadce3 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Wed, 10 Jul 2024 13:08:56 +0200 Subject: [PATCH 32/37] Also return df if no values missing --- data_adapter_oemof/calculations.py | 1 + 1 file changed, 1 insertion(+) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 0780133..477ac78 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -313,6 +313,7 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: inplace=True, ) return group_df + return group_df group_df = handle_min_max(group_df) return find_and_replace_irrelevant_data(group_df) From 69889e0a3d48975545864780f0a5fae6077ae962 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Thu, 18 Jul 2024 11:36:41 +0200 Subject: [PATCH 33/37] Simplify Logic to old approach --- data_adapter_oemof/calculations.py | 51 +++++++++++++++++------------- 1 file changed, 29 insertions(+), 22 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 477ac78..5ab5b89 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -290,29 +290,36 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: ] # no investment in decommissioning processes # no capacity can be set on investment objects - for invest_column in invest_zero: - if invest_column in group_df.columns and not any( - [cap_col in capacity_columns for cap_col in group_df.columns] - ): - # Fill rows where allowed investment is 0 - - group_df.mask( - group_df[invest_column] == 0, - group_df.fillna(group_df.mean(numeric_only=True)), - axis=1, - inplace=True, - ) - return group_df - for capacity_c in capacity_columns: - if capacity_c in group_df.columns: - # Fill rows where capacity is decommissioned - group_df.mask( - group_df[capacity_c] == 0, - group_df.fillna(group_df.mean(numeric_only=True)), - axis=1, - inplace=True, - ) + invest_col = [d for d in invest_zero if d in group_df.columns] + capacity_c = [d for d in capacity_columns if d in group_df.columns] + if len(invest_col) == 1 and len(capacity_c) == 0: + # Get rows where allowed investment is 0 + non_investment_indices = group_df[invest_col[0]] == 0 + # In Case first values are missing bfil is used in case last values missed + # ffil is used. In most cases boundary values are missing + # therefore interpolation is no viable option. + group_df.loc[non_investment_indices] = group_df.bfill().loc[ + non_investment_indices + ] + group_df.loc[non_investment_indices] = group_df.ffill().loc[ + non_investment_indices + ] + return group_df + if len(capacity_c) == 1: + # Fill rows where capacity is decommissioned + zero_capacity_columns_indices = group_df[capacity_c[0]] == 0 + group_df.loc[zero_capacity_columns_indices] = group_df.bfill().loc[ + zero_capacity_columns_indices + ] + group_df.loc[zero_capacity_columns_indices] = group_df.ffill().loc[ + zero_capacity_columns_indices + ] + return group_df + else: + warnings.warn("Multiple Investment Columns found - nans cannot be filled automatically" + f" for DataFrame {group_df}") + return group_df group_df = handle_min_max(group_df) From 825334d43bb08465dc03f1515151e665a26bd6ea Mon Sep 17 00:00:00 2001 From: FelixMau Date: Thu, 18 Jul 2024 11:37:00 +0200 Subject: [PATCH 34/37] Simplify Logic to old approach --- data_adapter_oemof/calculations.py | 28 +- .../srd_range_draft/ind_steel_casting_0.csv | 2 +- .../srd_range_draft/ind_steel_casting_0.json | 410 +++++++++++++++++- .../srd_range_draft/ind_steel_hyddri_1.json | 345 ++++++++++++++- .../test_fill_nans/collection.json | 16 +- 5 files changed, 777 insertions(+), 24 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 5ab5b89..cdc8c8a 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -293,19 +293,19 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: invest_col = [d for d in invest_zero if d in group_df.columns] capacity_c = [d for d in capacity_columns if d in group_df.columns] if len(invest_col) == 1 and len(capacity_c) == 0: - # Get rows where allowed investment is 0 - non_investment_indices = group_df[invest_col[0]] == 0 - # In Case first values are missing bfil is used in case last values missed - # ffil is used. In most cases boundary values are missing - # therefore interpolation is no viable option. - group_df.loc[non_investment_indices] = group_df.bfill().loc[ + # Get rows where allowed investment is 0 + non_investment_indices = group_df[invest_col[0]] == 0 + # In Case first values are missing bfil is used in case last values missed + # ffil is used. In most cases boundary values are missing + # therefore interpolation is no viable option. + group_df.loc[non_investment_indices] = group_df.bfill().loc[ non_investment_indices - ] - group_df.loc[non_investment_indices] = group_df.ffill().loc[ - non_investment_indices - ] + ] + group_df.loc[non_investment_indices] = group_df.ffill().loc[ + non_investment_indices + ] - return group_df + return group_df if len(capacity_c) == 1: # Fill rows where capacity is decommissioned zero_capacity_columns_indices = group_df[capacity_c[0]] == 0 @@ -317,8 +317,10 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: ] return group_df else: - warnings.warn("Multiple Investment Columns found - nans cannot be filled automatically" - f" for DataFrame {group_df}") + warnings.warn( + "Multiple Investment Columns found - nans cannot be filled automatically" + f" for DataFrame {group_df}" + ) return group_df diff --git a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv index 96f12a5..66d7324 100644 --- a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv +++ b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.csv @@ -8,4 +8,4 @@ 7,"DE",2045,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" 8,"DE",2050,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" 9,"DE",2060,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" -10,"DE",2070,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" \ No newline at end of file +10,"DE",2070,"ind_steel_casting_0",1.0,,,1.0,0.0012,"global_emission_factors.natural_gas",0.0006,,0.0,30.0,0.0,,,"global_scalars.wacc","{}","srd_range_draft","{}","{}","{}" diff --git a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.json b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.json index 1756a8d..768e11f 100644 --- a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_casting_0/srd_range_draft/ind_steel_casting_0.json +++ 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Used to calculate annuity factor for investment costs.", + "isAbout": [ + { + "name": null, + "path": null + } + ], + "name": "wacc", + "type": "text", + "unit": "%", + "valueReference": [] + }, + { + "description": "Bandwidth Type", + "isAbout": [], + "name": "bandwidth_type", + "type": "json", + "unit": null, + "valueReference": [] + }, + { + "description": "Version", + "isAbout": [], + "name": "version", + "type": "text", + "unit": null, + "valueReference": [] + }, + { + "description": "Method", + "isAbout": [], + "name": "method", + "type": "json", + "unit": null, + "valueReference": [] + }, + { + "description": "Source", + "isAbout": [], + "name": "source", + "type": "json", + "unit": null, + "valueReference": [] + }, + { + "description": "Comment", + "isAbout": [], + "name": "comment", + "type": "json", + "unit": null, + "valueReference": [] + } + ], + "foreignKeys": [], + "primaryKey": [ + "id" + ] + } + } + ], + "review": { + "badge": null, + "path": null + }, + "sources": [ + { + "description": "Parameter data model for secondary input scalars and timeseries", + "licenses": [ + { + "attribution": null, + "instruction": "You are free: To Share, To Create, To Adapt", + "name": "CC0-1.0", + "path": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", + "title": "Creative Commons Zero v1.0 Universal" + } + ], + "path": "https://github.com/sedos-project/oedatamodel/tree/main/oedatamodel-parameter", + "title": "OEDatamodel-parameter" + }, + { + "description": "TAM Industry is based on TIMES and focuses on German industry energy system", + "licenses": [ + { + "attribution": "@Energy Economics and Social Analysis(ESA), IER, University of Stuttgart", + "instruction": null, + "name": "Creative Commons Attribution 4.0 International", + "path": "https://creativecommons.org/licenses/by/4.0/", + "title": "CC BY 4.0" + } + ], + "path": null, + "title": "TAM Industry Model" + } + ], + "spatial": { + "extent": "DE", + "location": "Germany", + "resolution": "NUTS-0" + }, + "subject": [ + { + "name": "Industry Sector", + "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227/" + }, + { + "name": "Industry Sub-sector", + "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227" + } + ], + "temporal": { + "referenceDate": "2021", + "timeseries": [ + { + "aggregationType": null, + "alignment": null, + "end": "2070-12-31", + "resolution": "yearly", + "start": "2021-01-01" + } + ] + }, + "title": "sedos_ind_steel_casting_0" +} diff --git a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json index e76ce7a..db6cdb1 100644 --- a/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json +++ b/tests/collections/test_fill_nans/SEDOS_industry_sector/ind_steel_hyddri_1/srd_range_draft/ind_steel_hyddri_1.json @@ -1 +1,344 @@ -{"id": "https://openenergy-platform.org/dataedit/view/model_draft/ind_steel_hyddri_1", "@id": null, "name": "ind_steel_hyddri_1", "title": "sedos_ind_steel_hyddri_1", "review": {"path": null, "badge": null}, "context": {"contact": "ulrich.fahl@ier.uni-stuttgart.de", "grantNo": null, "homepage": "https://sedos-project.github.io/.github/", "sourceCode": "https://github.com/sedos-project", "documentation": "https://sedos-project.github.io/.github/", "fundingAgency": "Bundesministerium f\u00c3\u00bcr Wirtschaft und Klimaschutz (BMWK)", "publisherLogo": null, "fundingAgencyLogo": "https://en.wikipedia.org/wiki/Federal_Ministry_for_Economic_Affairs_and_Climate_Action#/media/File:BMWi_Logo_2021.svg"}, "sources": [{"path": "https://github.com/sedos-project/oedatamodel/tree/main/oedatamodel-parameter", "title": "OEDatamodel-parameter", "licenses": [{"name": 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Electric Arc Furnace for DRI + Hydrogen", + "id": "https://openenergy-platform.org/dataedit/view/model_draft/ind_steel_hyddri_1", + "keywords": [ + "SEDOS", + "input_data", + "AP7", + "Industry", + "oedatamodel-parameter", + "steel" + ], + "language": [ + "en-GB" + ], + "licenses": [ + { + "attribution": null, + "instruction": "You are free to: Share- copy and redistribute the material in any medium or format for any purpose, even commercially. Adapt - remix, transform, and build upon the material for any purpose, even commercially.", + "name": "CC-BY-4.0", + "path": "https://creativecommons.org/licenses/by/4.0/?ref=chooser-v1", + "title": "Creative Commons Attribution 4.0 International" + } + ], + "metaMetadata": { + "metadataLicense": { + "name": "CC0-1.0", + "path": "https://creativecommons.org/publicdomain/zero/1.0/", + "title": "Creative Commons Zero v1.0 Universal" + }, + "metadataVersion": "OEP-1.5.2" + }, + "name": "ind_steel_hyddri_1", + "publicationDate": "2024-06-26", + "resources": [ + { + "dialect": { + "decimalSeparator": ".", + "delimiter": ";" + }, + "encoding": "UTF-8", + "format": "PostgreSQL", + "name": "model_draft.ind_steel_hyddri_1", + "path": "https://openenergy-platform.org/dataedit/view/model_draft/ind_steel_hyddri_1", + "profile": "tabular-data-resource", + "schema": { + "fields": [ + { + "description": "Unique identifier", + "isAbout": [], + "name": "id", + "type": "bigint", + "unit": null, + "valueReference": [] + }, + { + "description": "Country or regionx", + "isAbout": [], + "name": "region", + "type": "text", + "unit": null, + "valueReference": [] + }, + { + "description": "Year", + "isAbout": [], + "name": "year", + "type": "integer", + "unit": "a", + "valueReference": [] + }, + { + "description": "Type of process", + "isAbout": [], + "name": "type", + "type": "text", + "unit": null, + "valueReference": [] + }, + { + "description": "Commodity-specific conversion factor (multiplication of input and output factors yields the efficiency of the process).", + "isAbout": [ + { + "name": "energy conversion efficiency", + "path": "http://openenergyplatform.org/ontology/oeo/OEO_00140049/" + } + ], + "name": "conversion_factor_iip_steel_crudesteel", + "type": "float", + "unit": "Mt", + "valueReference": [] + }, + { + "description": "Commodity-specific conversion factor (multiplication of input and output factors yields the efficiency of the process).", + "isAbout": [ + { + "name": "energy conversion efficiency", + "path": "http://openenergyplatform.org/ontology/oeo/OEO_00140049/" + } + ], + "name": "conversion_factor_sec_elec_ind", + "type": "float", + "unit": "PJ/Mt", + "valueReference": [] + }, + { + "description": "Commodity-specific conversion factor (multiplication of input and output factors yields the efficiency of the process).", + "isAbout": [ + { + "name": "energy conversion efficiency", + "path": "http://openenergyplatform.org/ontology/oeo/OEO_00140049/" + } + ], + "name": "conversion_factor_sec_hydrogen", + "type": "float", + "unit": "PJ/Mt", + "valueReference": [] + }, + { + "description": "Constant output ratio in relation to installed capacity. (= h/a)", + "isAbout": [ + { + "name": "unplanned availability", + "path": "http://openenergyplatform.org/ontology/oeo/OEO_00140129/" + } + ], + "name": "availability_constant", + "type": "float", + "unit": "%", + "valueReference": [] + }, + { + "description": "Absolute upper bound on level of investment in new weight capacity for a period.", + "isAbout": [ + { + "name": null, + "path": null + } + ], + "name": "capacity_w_abs_new_max", + "type": "float", + "unit": "Mt", + "valueReference": [] + }, + { + "description": "Investment costs for new capacity per unit weight.", + "isAbout": [ + { + "name": "investment cost", + "path": "http://openenergyplatform.org/ontology/oeo/OEO_00020167/" + } + ], + "name": "cost_inv_w", + "type": "float", + "unit": "M\u20ac/Mt", + "valueReference": [] + }, + { + "description": "Operation independent costs for capacity per unit weight.", + "isAbout": [ + { + "name": "fixed cost ", + "path": "http://openenergyplatform.org/ontology/oeo/OEO_00020168/" + } + ], + "name": "cost_fix_w", + "type": "float", + "unit": "M\u20ac/Mt", + "valueReference": [] + }, + { + "description": "Technical lifetime of a process.", + "isAbout": [ + { + "name": "operational life time", + "path": "http://openenergyplatform.org/ontology/oeo/OEO_00020178/" + } + ], + "name": "lifetime", + "type": "float", + "unit": "a", + "valueReference": [] + }, + { + "description": "Percentage of costs for capital after taxes. Used to calculate annuity factor for investment costs.", + "isAbout": [ + { + "name": null, + "path": null + } + ], + "name": "wacc", + "type": "text", + "unit": "%", + "valueReference": [] + }, + { + "description": "Bandwidth Type", + "isAbout": [], + "name": "bandwidth_type", + "type": "json", + "unit": null, + "valueReference": [] + }, + { + "description": "Version", + "isAbout": [], + "name": "version", + "type": "text", + "unit": null, + "valueReference": [] + }, + { + "description": "Method", + "isAbout": [], + "name": "method", + "type": "json", + "unit": null, + "valueReference": [] + }, + { + "description": "Source", + "isAbout": [], + "name": "source", + "type": "json", + "unit": null, + "valueReference": [] + }, + { + "description": "Comment", + "isAbout": [], + "name": "comment", + "type": "json", + "unit": null, + "valueReference": [] + } + ], + "foreignKeys": [], + "primaryKey": [ + "id" + ] + } + } + ], + "review": { + "badge": null, + "path": null + }, + "sources": [ + { + "description": "Parameter data model for secondary input scalars and timeseries", + "licenses": [ + { + "attribution": null, + "instruction": "You are free: To Share, To Create, To Adapt", + "name": "CC0-1.0", + "path": "https://creativecommons.org/publicdomain/zero/1.0/legalcode", + "title": "Creative Commons Zero v1.0 Universal" + } + ], + "path": "https://github.com/sedos-project/oedatamodel/tree/main/oedatamodel-parameter", + "title": "OEDatamodel-parameter" + }, + { + "description": "TAM Industry is based on TIMES and focuses on German industry energy system", + "licenses": [ + { + "attribution": "@Energy Economics and Social Analysis(ESA), IER, University of Stuttgart", + "instruction": null, + "name": "Creative Commons Attribution 4.0 International", + "path": "https://creativecommons.org/licenses/by/4.0/", + "title": "CC BY 4.0" + } + ], + "path": null, + "title": "TAM Industry Model" + } + ], + "spatial": { + "extent": "DE", + "location": "Germany", + "resolution": "NUTS-0" + }, + "subject": [ + { + "name": "Industry Sector", + "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227/" + }, + { + "name": "Industry Sub-sector", + "path": "http://openenergy-platform.org/ontology/oeo/OEO_00000227" + } + ], + "temporal": { + "referenceDate": "2021", + "timeseries": [ + { + "aggregationType": null, + "alignment": null, + "end": "2070-12-31", + "resolution": "yearly", + "start": "2021-01-01" + } + ] + }, + "title": "sedos_ind_steel_hyddri_1" +} diff --git a/tests/collections/test_fill_nans/collection.json b/tests/collections/test_fill_nans/collection.json index caa2983..f2fa348 100644 --- a/tests/collections/test_fill_nans/collection.json +++ b/tests/collections/test_fill_nans/collection.json @@ -1,9 +1,8 @@ { - "name": "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/", - "version": "v3", "artifacts": { "SEDOS_industry_sector": { "ind_steel_casting_0": { + "datatype": 0, "latest_version": "srd_range_draft", "multiple_types": true, "names": [ @@ -21,10 +20,10 @@ ], "subjects": [ "Industry Sector_Industry Sub-sector" - ], - "datatype": 0 + ] }, "ind_steel_hyddri_1": { + "datatype": 0, "latest_version": "srd_range_draft", "multiple_types": true, "names": [ @@ -42,9 +41,10 @@ ], "subjects": [ "Industry Sector_Industry Sub-sector" - ], - "datatype": 0 + ] } } - } -} \ No newline at end of file + }, + "name": "https://databus.openenergyplatform.org/felixmaur/collections/steel_industry_test/", + "version": "v3" +} From 7137b82d33778e43ab62ac7a4e9c8a637085ac81 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Thu, 18 Jul 2024 12:21:56 +0200 Subject: [PATCH 35/37] Super Easy, super Readable, super Performance --- data_adapter_oemof/calculations.py | 60 +++++++++++++----------------- 1 file changed, 25 insertions(+), 35 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index cdc8c8a..a625e77 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -284,43 +284,33 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: "capacity_p_abs_new_max", "capacity_e_abs_new_max", "capacity_w_abs_new_max", - "capacity_p_max", - "capacity_e_max", - "capacity_w_max", ] - # no investment in decommissioning processes - # no capacity can be set on investment objects + + max_zero = ["capacity_p_max", "capacity_e_max", "capacity_w_max"] + + # Get relevant columns that appear in dataframe + max_col = [d for d in max_zero if d in group_df.columns] invest_col = [d for d in invest_zero if d in group_df.columns] - capacity_c = [d for d in capacity_columns if d in group_df.columns] - if len(invest_col) == 1 and len(capacity_c) == 0: - # Get rows where allowed investment is 0 - non_investment_indices = group_df[invest_col[0]] == 0 - # In Case first values are missing bfil is used in case last values missed - # ffil is used. In most cases boundary values are missing - # therefore interpolation is no viable option. - group_df.loc[non_investment_indices] = group_df.bfill().loc[ - non_investment_indices - ] - group_df.loc[non_investment_indices] = group_df.ffill().loc[ - non_investment_indices - ] - - return group_df - if len(capacity_c) == 1: - # Fill rows where capacity is decommissioned - zero_capacity_columns_indices = group_df[capacity_c[0]] == 0 - group_df.loc[zero_capacity_columns_indices] = group_df.bfill().loc[ - zero_capacity_columns_indices - ] - group_df.loc[zero_capacity_columns_indices] = group_df.ffill().loc[ - zero_capacity_columns_indices - ] - return group_df - else: - warnings.warn( - "Multiple Investment Columns found - nans cannot be filled automatically" - f" for DataFrame {group_df}" - ) + capacity_col = [d for d in capacity_columns if d in group_df.columns] + + # Set all indices to "not be filled" (False) + fill_indices = pd.Series([False] * len(group_df), index=group_df.index) + + # Capacity and Investment cannot be set in parallel. If both columns appear in dataframe + # Fill the ones where capacity is set to 0 (decomissioned) + if len(capacity_col) == 1 and (len(invest_col) != 0 or len(max_col) != 0): + # Add Indices where capacity is 0 + fill_indices += group_df[capacity_col[0]] == 0 + elif len(invest_col) == 1: + # Add indices where capacity max == 0 (making investment impossible) + fill_indices += group_df[max_col[0]] == 0 + elif len(max_col) == 1: + # Add indices where investment is not allowed + fill_indices += group_df[invest_col[0]] == 0 + + # Fill indices + group_df.loc[fill_indices] = group_df.bfill().loc[fill_indices] + group_df.loc[fill_indices] = group_df.ffill().loc[fill_indices] return group_df From 6e07cfc8eb5a0f6ee5a57810733bf2b4686fd9d3 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Thu, 18 Jul 2024 12:31:50 +0200 Subject: [PATCH 36/37] Super Easy, super Readable, super Performance --- data_adapter_oemof/calculations.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index a625e77..7f477be 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -301,16 +301,15 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: if len(capacity_col) == 1 and (len(invest_col) != 0 or len(max_col) != 0): # Add Indices where capacity is 0 fill_indices += group_df[capacity_col[0]] == 0 - elif len(invest_col) == 1: + elif len(max_col) == 1: # Add indices where capacity max == 0 (making investment impossible) fill_indices += group_df[max_col[0]] == 0 - elif len(max_col) == 1: + elif len(invest_col) == 1: # Add indices where investment is not allowed fill_indices += group_df[invest_col[0]] == 0 # Fill indices - group_df.loc[fill_indices] = group_df.bfill().loc[fill_indices] - group_df.loc[fill_indices] = group_df.ffill().loc[fill_indices] + group_df.loc[fill_indices] = group_df.fillna(group_df.mean(numeric_only=True)) return group_df From 91b6efd195e55e5836f3d47a4cbe7fe03d993ec9 Mon Sep 17 00:00:00 2001 From: FelixMau Date: Thu, 18 Jul 2024 12:32:59 +0200 Subject: [PATCH 37/37] Linting --- data_adapter_oemof/calculations.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/data_adapter_oemof/calculations.py b/data_adapter_oemof/calculations.py index 7f477be..c190b60 100644 --- a/data_adapter_oemof/calculations.py +++ b/data_adapter_oemof/calculations.py @@ -309,7 +309,9 @@ def find_and_replace_irrelevant_data(group_df: pd.DataFrame) -> pd.DataFrame: fill_indices += group_df[invest_col[0]] == 0 # Fill indices - group_df.loc[fill_indices] = group_df.fillna(group_df.mean(numeric_only=True)) + group_df.loc[fill_indices] = group_df.fillna( + group_df.mean(numeric_only=True) + ).loc[fill_indices] return group_df