Generate.py

"""
    This script generates random water distribution networks as INP files.
"""

from RWDN_core import RandomWaterDistributionNetwork
import pandas as pd
import random
import sys
import os.path
import osmnx as ox
import networkx as nx
import csv

gmap_key = input("Enter gmap_key (Google maps API): \n")

# Creating the ouput directory
output_dir = os.getcwd() + '/ouput'
while True:    
    try:
        os.makedirs(output_dir)
    except FileExistsError:
        break
    except OSError:
        raise Exception('Creation of the project directory failed! Aborting...')
    break

# number_of_WDN =  int(input("Enter the number of WDNs you wish to be generated: \n"))
number_of_WDN = 1

# Loading cities data from which the location of the streets will be generated
world_cities = pd.read_csv("data/simplemaps_worldcities_basicv1.73/worldcities.csv")

# the minimal population for the cities to be used for the generation of the Virtual Water Network
min_population = 100000

# Average demand values in gal/day/acre from Water Distribution Systems Handbook - McGraw Hill (2000)
demand_values = {'Low_density_residential': 1670, 'Med_density_residential': 2610, 'High_density_residential': 4160, 'Single_family_residential ': 2300, 'Multifamily residential': 4160, 'Office_commercial': 2030, 'Retail_commercial': 2040, 'Light_industrial': 1620, 'Heavy_industrial': 2270, 'Parks': 2020, 'Schools': 1700}

# Average hourly demand values in m3/h/hectare
demand_values = {key: v*0.00039 for key,v in demand_values.items()}

# Roughness
roughness_values = [100, 110, 130]

# Reservoir's elevation over the highest point
reservoir_heads = [30, 40, 50]

# Possible pipes diameters values in m
pipes_diameters = [0.04, 0.06, 0.08, 0.1, 0.13, 0.15, 0.18, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]

# pipes_diameters = [0.08, 0.1, 0.11, 0.13, 0.15, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]

sf = 0.01

j=0
while j < number_of_WDN:
    distance = random.randint(1000, 1500)

    # Instantiating the class RandomWaterDistributionNetwork
    rd = RandomWaterDistributionNetwork(gmap_key, world_cities, min_population, distance, demand_values, roughness_values, reservoir_heads, pipes_diameters)

    # Generate the layout from street network data 
    while True:
        try:
            G = rd.generate_random_graph()
            # Add elevation values to the nodes 
            rd.add_elevation(G)
            if len(G) < 200: 
                print ('Number of nodes < 200, this graph will be discarded') 
                continue
            else: break
        except Exception:
            continue
    print('Graph n: {} generated' .format(j))

    # Project the layout UTM-WGS84
    G = ox.project_graph(G)
    print('Graph n: {} projected UTM-WGS84' .format(j))
    G = nx.Graph(G)

    # Clean the graph from clustered nodes, self loops and parallel edges
    G = rd.clean_graph(G, 15)
    print('Graph n: {} cleaned from too closely clustered nodes' .format(j))

    # Add demands to nodes
    rd.add_node_demands(G)
    print('Demand values added to nodes' .format(j))

    # Create main distribution network
    subG = rd.main_network(G)
    subG = rd.clean_cycles(subG)
    print('Main distribution network created')

    # Add reservoirs as nodes and connecting them to the graph
    subG = rd.add_reservoirs(subG)
    print('Reservoirs added')
    F = nx.compose(G, subG)

    # Add edge roughness
    rd.add_edge_roughness(F)
    print('Roughness added to the Graph {}'.format(j))

    # Create WaterNetworkModel object for wntr
    wn = rd.create_wn(F, subG)

    # Run simulation for pipe sizing
    wn = rd.pipe_sizing(wn)
    print('Pipe sizing performed')

    # Divide the network to sectors and add valves between sectors
    wn = rd.add_valves(wn, subG, n_sectors=5)
    print('Valves have been added to the network')
    stats = rd.stats(wn)

    # If the minimum pressure is above zero save the network and the stats
    if min(stats['Pressure']) > 0:
        filename = os.path.join(output_dir, 'WDN{}' .format(j) + '.inp')
        rd.save_wn(wn, filename)
        
        print('File n: {} ' .format(j) + 'was generated successfully')

        print('Main valves list:')
        print(rd._main_valves)
        
        closed_valves = pd.DataFrame(dict([ (k,pd.Series(v, dtype=object)) for k,v in stats['Valves per sector'].items() ]))
        open_valves = pd.DataFrame(dict([ (k,pd.Series(v, dtype=object)) for k,v in stats['Main valves'].items() ]))
        
        closed_valves.to_csv(os.path.join(output_dir, 'valves_to_be_closed{}' .format(j) + '.csv'))
        open_valves.to_csv(os.path.join(output_dir, 'main_valves{}' .format(j) + '.csv'))

        out = os.path.join(output_dir, 'WDN_stats{}' .format(j) + '.csv')
        w = csv.writer(open(out, "w"))
        for key, val in stats.items():
            w.writerow([key, val])
        
        j+=1

    else:
        continue