Source code for atra.analysis.adaptation_analysis

# -*- coding: utf-8 -*-
"""Assess national adaptation options
"""
import os
import sys
import numpy as np
from atra.adaptation_options import *

def main():
    """
    (i) estimated cost to upgrade to a climate-resilient bituminous 2L 
        (applied to unpaved, gravel and bituminous 2L roads), 
    (ii) estimated cost to upgrade to a climate-resilient bituminous 4L 
        (applied to bituminous 4L roads), 
    (iii) estimated cost to upgrade to a climate-resilient concrete 2L 
        (applied to concrete 2L roads), 
    (iv) estimated cost to upgrade to a climate-resilient concrete 4L 
        (applied to concrete 4L roads).
    """
    read_from_file = False
    if len(sys.argv) == 2:
        if sys.argv[1] == '--read_from_file':
            read_from_file = True

    if read_from_file:
        print('Reading param values from file')
    else:
        print('Running with fixed param values,  --read_from_file to use file')

    config = load_config()
    data_path = config['paths']['data']
    calc_path = config['paths']['calc']
    output_path = config['paths']['output']

    adapt_results = os.path.join(output_path,'adaptation_results')
    if os.path.exists(adapt_results) == False:
        os.mkdir(adapt_results)

    duration_list = np.arange(10,110,10)
    discount_rate = 12
    growth_rates = np.arange(-2,4,0.2)

    modes = ['road','bridge']
    modes_id_cols = ['edge_id','bridge_id']
    result_types = ['combined_climate','hazard_and_climate']
    index_columns = [['climate_scenario'],['hazard_type','climate_scenario']]
    start_year = 2016
    end_year = 2050
    min_periodic_year = 4
    max_periodic_year = 8

    for r_t in range(len(result_types)):
        result_type = result_types[r_t]
        adapt_results = os.path.join(output_path,'adaptation_results',result_type)
        if os.path.exists(adapt_results) == False:
            os.mkdir(adapt_results)
        for m in range(len(modes)):
            costs_df = get_adaptation_options_costs(
                    modes[m], 
                    data_path,
                    output_path,
                    result_type, 
                    discount_rate=discount_rate,
                    start_year=start_year,
                    end_year=end_year,
                    min_period=min_periodic_year,
                    max_period=max_periodic_year,  
                    read_from_file=read_from_file)

            # for dur in duration_list:
            #     for growth_rate in growth_rates:
            #         run_adaptation_calculation(
            #             costs_df,
            #             modes[m],
            #             output_path,
            #             modes_id_cols[m],
            #             index_columns[r_t],
            #             result_type, 
            #             duration_max=dur, 
            #             discount_rate=discount_rate,
            #             growth_rate=round(growth_rate,1),
            #             start_year=start_year,
            #             end_year=end_year,
            #             min_period=min_periodic_year,
            #             max_period=max_periodic_year,  
            #             read_from_file=read_from_file)


if __name__ == '__main__':
    main()