reeds-visualizer/multiply_emit_by_scc.py at main · ucsusa/reeds-visualizer · GitHub

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import pandas as pd
from pathlib import Path
from os import listdir
from glob import glob
from tqdm import tqdm

if __name__ == "__main__":
    dollar_year = 2020
    scenarios = listdir('results/fy25')
    scc = pd.read_csv("data/scc_mult.csv")
    deflator = pd.read_csv(("https://raw.githubusercontent.com/"
                            "ucsusa/ReEDS-2.0/"
                            "0b57ae128bf9295dee0cf0218fe5f5fc800d26d9/"
                            "inputs/financials/deflator.csv"),
                            index_col="*Dollar.Year")

    for i, scenario in tqdm(enumerate(scenarios)):
        emit_irt_path = Path(f'results/fy25/{scenario}/emit_irt.csv')
        try:
            temp_file = pd.read_csv(emit_irt_path)
        except FileNotFoundError:
            print(f"File not found: {emit_irt_path}")
            continue
        df = temp_file.drop(columns=['i']).groupby(['eall', 'r','t']).sum().reset_index()


        # Estimate non-modeled years according to NREL's method, centering modeled years.
        df = df.set_index(pd.to_datetime(df['t'], format='%Y')).drop(columns=["t"])
        df = df.groupby(['eall','r'])\
            .resample("YE")\
                .ffill(limit=2)\
                    .bfill(limit=2)\
                        .drop(columns=['eall','r'])\
                            .reset_index()
        df['t'] = df['t'].dt.year

        # Merge on 'eall' and 't' columns
        merged = pd.merge(
            df,
            scc,
            on=['eall', 't'],
            suffixes=('_emit', '_scc')
        )
        # Multiply the values and discount them back to the analysis year
        merged['Value'] = merged['Value_emit'] * merged['Value_scc'] * merged['dtau']
        # merged = merged.drop(columns=['Value_emit','Value_scc','dtau'])

        # Deflate to 2004$
        merged['Value'] = merged['Value'] * deflator.at[dollar_year, 'Deflator']

        # Output the result
        scc_path = Path(f'results/fy25/{scenario}/scc_values.csv')
        merged.to_csv(scc_path, index=False)