# -*- coding: utf-8 -*-
"""
This file collects results from grid use model scenarios and collates them for 
summarising results

@author: theot
"""
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import itertools

out_fn="C:/Users/theot/Dropbox (Sense.)/2018-19 EA TPM CBA (Shared)/Step 3/AoB model/Output/Results/"

# Check that the following has been completed

# Read the first file, add a scenario description column and append... 
#File paths
main_fn="C:/Users/theot/Dropbox (Sense.)/2018-19 EA TPM CBA (Shared)/Step 3/AoB model/Output/"
scenarios = ['All_major_capex',
                'Demand',
                'Demand_and_DG_investment',
             'Demand_and_gen_investment',
             'All_major_capex_alternative',
             'WUNI',
             'No_AoB_on_existing',
             'Demand_no_aob_on_existing',
             'All_major_capex_tiwai_off',
             'Demand_major_capex',
             'MWh_Demand_major_capex',
             'All_major_capex_2024',
             'All_major_capex_gen_benefits',
             'All_Major_Capex_30_70']

gen_scenarios = ['All_major_capex',
                'Demand_and_gen_investment',
             'All_major_capex_alternative',
             'WUNI',
             'No_AoB_on_existing',
             'All_major_capex_tiwai_off',
             'All_major_capex_2024',
             'All_major_capex_gen_benefits',
             'All_Major_Capex_30_70']

#Make sure welfare values are up to date. Either run one 


# Function to get totals of output variables
def get_totals(variable,output_folder=main_fn,scenarios=scenarios):
    for i, s in enumerate(scenarios):
        if i == 0:
            results = pd.read_csv(main_fn+s+'/'+variable)
            results['scenario']=s
        else:
            temp=pd.read_csv(main_fn+s+'/'+ variable)
            temp['scenario']=s
            results = results.append(temp,ignore_index=True)
    return results


# Welfare
welfare = get_totals(variable='cv_results.csv')
welfare.to_csv(out_fn+'welfare.csv')

welfare_cs = get_totals(variable='cs_results.csv')
welfare_cs.to_csv(out_fn+'welfare_cs.csv')

#Transmission investment costs
transmission_costs= get_totals(variable='transmission_costs.csv')
transmission_costs.to_csv(out_fn+'transmission_costs.csv')

#Plant investment
plant_investment = get_totals(variable='plant_investment.csv',scenarios=gen_scenarios)
plant_investment.to_csv(out_fn+'plant_investment.csv')

# Investment in generation by year
generation_investment = get_totals(variable='generation_investment.csv',scenarios=gen_scenarios)
generation_investment.to_csv(out_fn+'generation_investment.csv')

# All results - load
for i, s in enumerate(scenarios):
    if i ==0:
        all_results=pd.read_csv(main_fn+s+'/rcpd.csv')
        all_results['scenario']=s
        all_results['policy']="status quo"
        temp=pd.read_csv(main_fn+s+'/aob.csv')
        temp['scenario']=s
        temp['policy']="proposal"
        all_results=all_results.append(temp,ignore_index=True)
    else:
        add=pd.read_csv(main_fn+s+'/rcpd.csv')
        add['scenario']=s
        add['policy']="status quo"
        aob=pd.read_csv(main_fn+s+'/aob.csv')
        aob['scenario']=s
        aob['policy']="proposal"
        add=add.append(aob,ignore_index=True)
        all_results=all_results.append(add,ignore_index=True)

all_results.to_csv(out_fn+'load_results.csv')



# Revenue
revenue = get_totals(variable='total_revenue.csv')
revenue.to_csv(out_fn+'revenue.csv')

# Distributed generation
dg = get_totals(variable='total_dg.csv')
dg.to_csv(out_fn+'dg.csv')

# Demand
load = get_totals(variable='total_load.csv')
load.to_csv(out_fn+'load.csv')

# Grid generation 
grid_generation = get_totals(variable='total_generation.csv')
grid_generation.to_csv(out_fn+'grid_generation.csv')

# Total average prices 
prices = get_totals(variable='total_average_prices.csv')
prices.to_csv(out_fn+'total_average_prices.csv')

# Generation investment
for i, s in enumerate(gen_scenarios):
    if i ==0:
        plant_results=pd.read_csv(main_fn+s+'/exist_g_rcpd.csv')
        plant_results['scenario']=s
        plant_results['policy']="status quo"
        temp=pd.read_csv(main_fn+s+'/exist_g_aob.csv')
        temp['scenario']=s
        temp['policy']="proposal"
        plant_results=plant_results.append(temp,ignore_index=True)
    else:
        add=pd.read_csv(main_fn+s+'/exist_g_rcpd.csv')
        add['scenario']=s
        add['policy']="status quo"
        aob=pd.read_csv(main_fn+s+'/exist_g_aob.csv')
        aob['scenario']=s
        aob['policy']="proposal"
        add=add.append(aob,ignore_index=True)
        plant_results=plant_results.append(add,ignore_index=True)

plant_results.to_csv(out_fn+'plant_results.csv')


# All results - generation
for i, s in enumerate(gen_scenarios):
    if i ==0:
        gen_results=pd.read_csv(main_fn+s+'/gen_rcpd.csv')
        gen_results['scenario']=s
        gen_results['policy']="status quo"
        temp=pd.read_csv(main_fn+s+'/gen_aob.csv')
        temp['scenario']=s
        temp['policy']="proposal"
        gen_results=gen_results.append(temp,ignore_index=True)
    else:
        add=pd.read_csv(main_fn+s+'/gen_rcpd.csv')
        add['scenario']=s
        add['policy']="status quo"
        aob=pd.read_csv(main_fn+s+'/gen_aob.csv')
        aob['scenario']=s
        aob['policy']="proposal"
        add=add.append(aob,ignore_index=True)
        gen_results=gen_results.append(add,ignore_index=True)

gen_results.to_csv(out_fn+'gen_results.csv')