Multi Link Redundancy

The multi-link redundancy analysis returns the same types of results as the single-link redundancy analysis, but it considers multiple links failing simultaneously. This is particularly useful for assessing the resilience of a network to natural disasters that may affect several links at once.

Run Multi-Link Redundancy Analysis

The workflow is therefore very similar to the single-link redundancy analysis, with the difference being that a hazard map must be specified. See the Single Link Redundancy tutorial for more details on the workflow.

We select the analysis type as AnalysisLossesEnum.MULTI_LINK_REDUNDANCY, for which we can also set a threshold for the water depth. The threshold defines the hazard value above which a link is considered impassable/disrupted.

Step 1: Import Libraries and Set Paths

We start by importing the required libraries and defining the root directory and network path.

from pathlib import Path
import geopandas as gpd
from IPython.core.display_functions import display

from ra2ce.analysis.analysis_config_data.analysis_config_data import AnalysisSectionLosses, AnalysisConfigData
from ra2ce.analysis.analysis_config_data.enums.analysis_losses_enum import AnalysisLossesEnum
from ra2ce.analysis.analysis_config_data.enums.weighing_enum import WeighingEnum
from ra2ce.network.network_config_data.enums.aggregate_wl_enum import AggregateWlEnum
from ra2ce.network.network_config_data.network_config_data import NetworkSection, NetworkConfigData, HazardSection
from ra2ce.network.network_config_data.enums.source_enum import SourceEnum
from ra2ce.ra2ce_handler import Ra2ceHandler

root_dir = Path('data', 'multi_link_redundancy')

network_path = root_dir / "network"
hazard_path = root_dir / "hazard"

Step 2: Define Network and Analysis Configuration

network_section = NetworkSection(
    source=SourceEnum.SHAPEFILE,
    primary_file=network_path.joinpath("base_shapefile.shp"),
    file_id="ID",
    save_gpkg=True,
    reuse_network_output=True,
    )

hazard_section = HazardSection(
    hazard_map=[hazard_path.joinpath("max_flood_depth.tif")],
    hazard_id='Flood',
    hazard_field_name="waterdepthtt",
    aggregate_wl=AggregateWlEnum.MIN,
    hazard_crs="EPSG:32736",
    )

network_config_data = NetworkConfigData(
    root_path= root_dir,
    static_path=root_dir.joinpath('static'),
    network=network_section,
    hazard=hazard_section,
    )

analyse_section = AnalysisSectionLosses(
    name="tutorial_multi_link_redundancy",
    analysis=AnalysisLossesEnum.MULTI_LINK_REDUNDANCY,
    threshold=0.3,  # roads with a flood depth above this value are considered impassable
    weighing=WeighingEnum.LENGTH,
    save_csv=True,
    save_gpkg=True,
)

analysis_config_data = AnalysisConfigData(
    output_path=root_dir.joinpath("output"),
    static_path=root_dir.joinpath('static'),
    analyses=[analyse_section],
    aggregate_wl=AggregateWlEnum.MIN,
)

handler = Ra2ceHandler.from_config(network=network_config_data, analysis=analysis_config_data)
handler.configure()
handler.run_analysis()

Inspect Results

analysis_output_folder = root_dir.joinpath("output", "multi_link_redundancy")
redundancy_gdf = gpd.read_file(analysis_output_folder/"tutorial_multi_link_redundancy.gpkg") # specify the name of the geopackage holding your results (can be found in the analysis output folder)
redundancy_gdf.head() # display the attributes of the file

import matplotlib.pyplot as plt

fig, ax = plt.subplots(figsize=(10, 10))
redundancy_gdf.plot(column='alt_length', ax=ax, legend=False, cmap='viridis')
plt.title('Multi Link Redundancy Analysis Results')
plt.xlabel('Longitude')
plt.ylabel('Latitude')
plt.grid(True)
plt.show()