UTPM/save_results.py at main · lisawink/UTPM · GitHub

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"""Module for saving results for multiple policy options"""

import pandas as pd
from UTPM_Run_Model import __main__

results=pd.DataFrame()

phaseout=[2025,2030,2040]
elec_decarb=[2020,2050,2060]
scrap=[20,18,16,14,12,10]
modal=[20,0,-20,-40,-60,-80,-90]
retro=[0,0.2,0.33]
weights=[1400,1120,840]
china=[0,1]
rate=[3,8,19,28]

for i in phaseout:
    for j in rate:
        for p in elec_decarb:
            for n in retro:
                for l in weights:
                    for m in modal:
                        for k in scrap:
                            for o in china:

                                case=__main__(phase_out_date=i,phase_out_hybrid=i,scrap_age_pre2020=k+5,scrap_age_post2020=k,mass=l,\
                                   fleet_size_projection=m,miles_driven_projection=m,retrofit_percentage=n,manufacture=o,elec=p,rate=j)

                                data = {'Phase-Out:':i,'Net-zero:':p,'Retro-fitting:':n,'Light-weighting:':l,'Modal shift:':m,'Scrap age:':k,'Regulated EV manufacture:':o,'Modal shift rate (years):':j,
                                        'Cumulative Electric Emissions':case['cum_electric'],'Cumulative Tailpipe Emissions':case['cum_tailpipe'],'Cumulative WTT Emissions':case['cum_wtt_emiss'],
                                        'Cumulative EV Production Emissions':case['cum_ev_prod'],'Cumulative ICE Production Emissions':case['cum_ice_prod'],'Cumulative Conversion Production Emissions':case['cum_conv_prod'],
                                        'Cumulative Electric Energy':case['cum_elec'],'Cumulative Tailpipe Energy':case['cum_foss'],'Cumulative WTT Energy':case['cum_wtt_en'],
                                        'Cumulative EV Production Energy':case['cum_ev_en'],'Cumulative ICE Production Energy':case['cum_ice_en'],'Cumulative Conversion Production Energy':case['cum_conv_en']}
                                df=pd.DataFrame(data)
                                results=results.append(df,ignore_index=True)

results.to_csv('figure_4.csv',index=False)
with pd.ExcelWriter('fig4.xlsx') as writer:
    df.to_excel(writer)
print(df)