Delete build_biomass_potentials.py

describe biomass

scripts/build_biomass_potentials.py

@@ -1,54 +0,0 @@
-
-import pandas as pd
-
-idx = pd.IndexSlice
-
-def build_biomass_potentials():
-
-    #delete empty column C from this sheet first before reading it in
-    df = pd.read_excel(snakemake.input.jrc_potentials,
-                       "Potentials (PJ)",
-                       index_col=[0,1])
-
-    df.rename(columns={"Unnamed: 18":"Municipal waste"},inplace=True)
-    df.drop(columns="Total",inplace=True)
-    df.replace("-",0.,inplace=True)
-
-    df_dict = {}
-
-    for i in range(36):
-        df_dict[df.iloc[i*16,1]] = df.iloc[1+i*16:(i+1)*16].astype(float)
-
-    df_new = pd.concat(df_dict)
-
-    us_type = pd.Series(index=df_new.columns)
-    us_type.iloc[0:7] = "not included"
-    us_type.iloc[7:8] = "biogas"
-    us_type.iloc[8:9] = "solid biomass"
-    us_type.iloc[9:11] = "not included"
-    us_type.iloc[11:16] = "solid biomass"
-    us_type.iloc[16:17] = "biogas"
-
-
-    #convert from PJ to MWh
-    biomass_potentials = df_new.loc[idx[:,snakemake.config['biomass']['year'],snakemake.config['biomass']['scenario']],:].groupby(us_type,axis=1).sum().groupby(level=0).sum().rename({"UK" : "GB", "BH" : "BA"})/3.6*1e6
-    biomass_potentials.to_csv(snakemake.output.biomass_potentials)
-
-
-
-if __name__ == "__main__":
-
-
-    # Detect running outside of snakemake and mock snakemake for testing
-    if 'snakemake' not in globals():
-        from vresutils import Dict
-        import yaml
-        snakemake = Dict()
-        snakemake.input = Dict()
-        snakemake.input['jrc_potentials'] = "data/biomass/JRC Biomass Potentials.xlsx"
-        snakemake.output = Dict()
-        snakemake.output['biomass_potentials'] = 'data/biomass_potentials.csv'
-        with open('config.yaml') as f:
-            snakemake.config = yaml.load(f)
-
-    build_biomass_potentials()