120 lines
4.2 KiB
Python
120 lines
4.2 KiB
Python
import sys
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import json
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from queue import Queue
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from .database import *
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from .s0_base import get_node_links, get_link_nodes
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sys.path.append('..')
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from epanet.epanet import run_project
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def calculate_service_area(name: str, time_index: int = 0) -> dict[str, Any]:
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inp = json.loads(run_project(name))
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time_count = len(inp['node_results'][0]['result'])
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if time_index >= time_count:
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return {}
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sources : dict[str, list[str]] = {}
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for node_result in inp['node_results']:
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result = node_result['result'][time_index]
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if result['demand'] < 0:
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sources[node_result['node']] = []
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link_flows: dict[str, float] = {}
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for link_result in inp['link_results']:
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result = link_result['result'][time_index]
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link_flows[link_result['link']] = float(result['flow'])
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# build source to nodes map
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for source in sources:
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queue = Queue()
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queue.put(source)
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while not queue.empty():
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cursor = queue.get()
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if cursor not in sources[source]:
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sources[source].append(cursor)
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links = get_node_links(name, cursor)
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for link in links:
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node1, node2 = get_link_nodes(name, link)
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if node1 == cursor and link_flows[link] > 0:
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queue.put(node2)
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elif node2 == cursor and link_flows[link] < 0:
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queue.put(node1)
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# calculation concentration
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concentration_map: dict[str, dict[str, float]] = {}
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node_wip: list[str] = []
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for source, nodes in sources.items():
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for node in nodes:
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if node not in concentration_map:
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concentration_map[node] = {}
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concentration_map[node][source] = 0.0
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if node not in node_wip:
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node_wip.append(node)
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# if only one source, done
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for node, concentrations in concentration_map.items():
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if len(concentrations) == 1:
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node_wip.remove(node)
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for key in concentrations.keys():
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concentration_map[node][key] = 1.0
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node_upstream : dict[str, list[tuple[str, str]]] = {}
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for node in node_wip:
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if node not in node_upstream:
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node_upstream[node] = []
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links = get_node_links(name, node)
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for link in links:
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node1, node2 = get_link_nodes(name, link)
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if node2 == node and link_flows[link] > 0:
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node_upstream[node].append((link, node1))
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elif node1 == node and link_flows[link] < 0:
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node_upstream[node].append((link, node2))
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while len(node_wip) != 0:
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done = []
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for node in node_wip:
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up_link_nodes = node_upstream[node]
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ready = True
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for link_node in up_link_nodes:
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if link_node in node_wip:
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ready = False
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break
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if ready:
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for link_node in up_link_nodes:
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for source, concentration in concentration_map[link_node[1]].items():
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concentration_map[node][source] += concentration * abs(link_flows[link_node[0]])
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# normalize
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sum = 0.0
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for source, concentration in concentration_map[node].items():
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sum += concentration
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for source in concentration_map[node].keys():
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concentration_map[node][source] /= sum
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done.append(node)
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for node in done:
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node_wip.remove(node)
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source_to_main_node: dict[str, list[str]] = {}
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for node, value in concentration_map.items():
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max_source = ''
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max_concentration = 0.0
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for s, c in value.items():
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if c > max_concentration:
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max_concentration = c
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max_source = s
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if max_source not in source_to_main_node:
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source_to_main_node[max_source] = []
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source_to_main_node[max_source].append(node)
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sas: list[dict[str, Any]] = []
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for source, nodes in source_to_main_node.items():
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sas.append({ 'source': source, 'nodes': nodes })
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return { 'service_areas' : sas, 'concentrations': concentration_map }
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