def run_with_base_class():
    client = IncoreClient(INCORE_API_DEV_URL)

    # Memphis Earthquake damage
    # New madrid earthquake using Atkinson Boore 1995
    hazard_type = "earthquake"
    hazard_id = "5b902cb273c3371e1236b36b"

    # Building dataset
    # 5a284f0bc7d30d13bc081a28  5kb
    # 5bcf2fcbf242fe047ce79dad 300kb
    # 5a284f37c7d30d13bc08219c 20mb
    bldg_dataset_id = "5a284f0bc7d30d13bc081a28"

    bldg_dmg = BuildingDamage(client)
    bldg_dmg.load_remote_input_dataset("buildings", bldg_dataset_id)

    # Earthquake mapping
    mapping_id = "5b47b350337d4a3629076f2c"
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    bldg_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    result_name = "memphis_eq_bldg_dmg_result"
    bldg_dmg.set_parameter("result_name", result_name)
    bldg_dmg.set_parameter("hazard_type", hazard_type)
    bldg_dmg.set_parameter("hazard_id", hazard_id)
    bldg_dmg.set_parameter("num_cpu", 4)

    # Run Analysis
    bldg_dmg.run_analysis()

    # TSUNAMI

    hazard_type = "tsunami"
    hazard_id = "5bc9e25ef7b08533c7e610dc"

    # Seaside building dataset
    bldg_dataset_id = "5bcf2fcbf242fe047ce79dad"

    # Run seaside tsunami building damage
    bldg_dmg = BuildingDamage(client)
    bldg_dmg.load_remote_input_dataset("buildings", bldg_dataset_id)

    # Tsunami mapping
    mapping_id = "5b48fb1f337d4a478e7bd54d"
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    bldg_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    result_name = "seaside_tsunami_dmg_result"
    bldg_dmg.set_parameter("result_name", result_name)
    bldg_dmg.set_parameter("hazard_type", hazard_type)
    bldg_dmg.set_parameter("hazard_id", hazard_id)
    bldg_dmg.set_parameter("num_cpu", 4)
    bldg_dmg.run_analysis()
예제 #2
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def run_with_base_class():
    client = IncoreClient(INCORE_API_DEV_URL)

    hazard_type = "earthquake"

    hazard_id = "5eebcbb08f80fe3899ad6039"

    epf_dataset_id = "5eebcaa17a00803abc85ec11"

    # Earthquake mapping
    mapping_id = "5eebcc13e7226233ce4ef0d7"

    # Run epf damage
    epf_dmg = EpfDamage(client)

    epf_dmg.load_remote_input_dataset("epfs", epf_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    epf_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    epf_dmg.set_parameter("result_name", "earthquake_epf_dmg_result")
    epf_dmg.set_parameter("hazard_type", hazard_type)
    epf_dmg.set_parameter("hazard_id", hazard_id)
    epf_dmg.set_parameter("num_cpu", 1)

    # Run Analysis
    epf_dmg.run_analysis()

    hazard_type = "tsunami"

    hazard_id = "5bc9eaf7f7b08533c7e610e1"

    epf_dataset_id = "5eebcaa17a00803abc85ec11"

    # Tsunami mapping
    mapping_id = "5eebce11e7226233ce4ef305"

    # Run epf damage
    epf_dmg = EpfDamage(client)
    epf_dmg.load_remote_input_dataset("epfs", epf_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    epf_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    epf_dmg.set_parameter("fragility_key", "Non-Retrofit inundationDepth Fragility ID Code")
    epf_dmg.set_parameter("result_name", "tsunami_epf_dmg_result")
    epf_dmg.set_parameter("hazard_type", hazard_type)
    epf_dmg.set_parameter("hazard_id", hazard_id)
    epf_dmg.set_parameter("num_cpu", 1)

    # Run Analysis
    epf_dmg.run_analysis()
예제 #3
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def test_pipeline_dmg():
    client = IncoreClient(service_url=INCORE_API_DEV_URL, token_file_name=".incrtesttoken")
    pipeline_dmg = PipelineDamage(client)

    # test tsunami pipeline
    pipeline_dmg.load_remote_input_dataset("pipeline",
                                           "5ef1171b2367ff111d082f0c")

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping("5ef11888da15730b13b84353"))
    pipeline_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    pipeline_dmg.set_parameter("result_name",
                               "seaside_tsunami_pipeline_result")
    pipeline_dmg.set_parameter("hazard_type", "tsunami")
    pipeline_dmg.set_parameter("fragility_key",
                               "Non-Retrofit inundationDepth Fragility ID Code")
    pipeline_dmg.set_parameter("hazard_id", "5bc9eaf7f7b08533c7e610e1")
    pipeline_dmg.set_parameter("num_cpu", 4)

    # Run pipeline damage analysis
    result = pipeline_dmg.run_analysis()

    assert result is True
def run_with_base_class():
    client = IncoreClient(INCORE_API_DEV_URL)
    hazard_type = "earthquake"
    hazard_id = "5b902cb273c3371e1236b36b"
    facility_datasetid = "5a284f2ac7d30d13bc081e52"

    mapping_id = "5b47c3b1337d4a387e85564b"  # Hazus Potable Water Facility Fragility Mapping - Only PGA

    liq_geology_dataset_id = "5a284f53c7d30d13bc08249c"

    uncertainty = False
    liquefaction = False
    liq_fragility_key = "pgd"

    wf_dmg = WaterFacilityDamage(client)
    wf_dmg.load_remote_input_dataset("water_facilities", facility_datasetid)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    wf_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    result_name = "wf-dmg-results.csv"
    wf_dmg.set_parameter("result_name", result_name)
    wf_dmg.set_parameter("hazard_type", hazard_type)
    wf_dmg.set_parameter("hazard_id", hazard_id)
    wf_dmg.set_parameter("fragility_key", "pga")
    wf_dmg.set_parameter("use_liquefaction", liquefaction)
    wf_dmg.set_parameter("liquefaction_geology_dataset_id",
                         liq_geology_dataset_id)
    wf_dmg.set_parameter("liquefaction_fragility_key", liq_fragility_key)
    wf_dmg.set_parameter("use_hazard_uncertainty", uncertainty)
    wf_dmg.set_parameter("num_cpu", 4)

    wf_dmg.run_analysis()
예제 #5
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def run_with_base_class():
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)
    pipeline_dmg = PipelineDamage(client)

    # test tsunami pipeline
    pipeline_dmg.load_remote_input_dataset("pipeline",
                                           "5ef1171b2367ff111d082f0c")

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(
        fragility_service.get_mapping(
            "60b124e01f2b7d4a916ba456"))  # new format fragility curves
    # mapping_set = MappingSet(fragility_service.get_mapping("5ef11888da15730b13b84353")) # legacy fragility curves
    pipeline_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    pipeline_dmg.set_parameter("result_name",
                               "seaside_tsunami_pipeline_result")
    pipeline_dmg.set_parameter("hazard_type", "tsunami")
    pipeline_dmg.set_parameter(
        "fragility_key", "Non-Retrofit inundationDepth Fragility ID Code")
    pipeline_dmg.set_parameter("hazard_id", "5bc9eaf7f7b08533c7e610e1")
    pipeline_dmg.set_parameter("num_cpu", 4)

    # Run pipeline damage analysis
    result = pipeline_dmg.run_analysis()
예제 #6
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def test_road_failure():
    client = IncoreClient(INCORE_API_DEV_URL, token_file_name=".incrtesttoken")

    # road inventory for Galveston island
    road_dataset_id = "5f0dd5ecb922f96f4e962caf"
    # distance table for Galveston island
    distance_dataset_id = "5f1883abfeef2d758c4e857d"
    # road damage by hurricane inundation mapping
    mapping_id = "5f0cb04fe392b24d4800f316"
    # Galveston Deterministic Hurricane - Kriging inundationDuration
    hazard_type = "hurricane"
    hazard_id = "5f10837c01d3241d77729a4f"

    # Create road damage
    road_failure = RoadFailure(client)
    # Load input datasets
    road_failure.load_remote_input_dataset("roads", road_dataset_id)
    road_failure.load_remote_input_dataset("distance_table",
                                           distance_dataset_id)
    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    road_failure.set_input_dataset('dfr3_mapping_set', mapping_set)
    # Specify the result name
    result_name = "road_result"
    # Set analysis parameters
    road_failure.set_parameter("result_name", result_name)
    road_failure.set_parameter("hazard_type", hazard_type)
    road_failure.set_parameter("hazard_id", hazard_id)
    road_failure.set_parameter("num_cpu", 4)

    # Run road damage by hurricane inundation analysis
    result = road_failure.run_analysis()

    assert result is True
예제 #7
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def run_with_base_class():
    client = IncoreClient(INCORE_API_DEV_URL)

    # EQ Road Dataset - Seaside roads
    road_dataset_id = "5ee7af50772cf80008577ae3"

    hazard_type = "tsunami"
    liq_geology_dataset_id = None

    if hazard_type == 'earthquake':
        # Seaside Earthquake
        hazard_id = "5ba8f379ec2309043520906f"

        # Earthquake mapping
        mapping_id = "5ee7b145c54361000148dcc5"

        fragility_key = "pgd"
        liquefaction = False
    elif hazard_type == 'tsunami':
        # Seaside Tsunami
        hazard_id = "5bc9eaf7f7b08533c7e610e1"

        # Tsunami Mapping for Seaside
        mapping_id = "5ee7b2c9c54361000148de37"

        fragility_key = "Non-Retrofit inundationDepth Fragility ID Code"
        liquefaction = False
    else:
        raise ValueError(
            "Earthquake and tsunami are the only testable hazards with road damage currently"
        )

    uncertainty = False

    # Run Seaside earthquake road damage
    road_dmg = RoadDamage(client)
    road_dmg.load_remote_input_dataset("roads", road_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    road_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    road_dmg.set_parameter("result_name", "seaside_road_dmg_" + hazard_type)
    road_dmg.set_parameter("hazard_type", hazard_type)
    road_dmg.set_parameter("hazard_id", hazard_id)
    if fragility_key is not None:
        road_dmg.set_parameter("fragility_key", fragility_key)
    road_dmg.set_parameter("num_cpu", 1)
    road_dmg.set_parameter("use_liquefaction", liquefaction)
    if liquefaction and liq_geology_dataset_id is not None:
        road_dmg.set_parameter("liquefaction_geology_dataset_id",
                               liq_geology_dataset_id)
    road_dmg.set_parameter("use_hazard_uncertainty", uncertainty)

    # Run Analysis
    road_dmg.run_analysis()
def run_with_base_class():
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)

    # Joplin tornado building damage
    bldg_dataset_id = "5df7d0de425e0b00092d0082"  # joplin building v6

    bldg_dmg = BuildingDamage(client)
    bldg_dmg.load_remote_input_dataset("buildings", bldg_dataset_id)

    mapping_id = "5e8e3a21eaa8b80001f04f1c"  # 19 archetype, non-retrofit
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    bldg_dmg.set_input_dataset("dfr3_mapping_set", mapping_set)
    bldg_dmg.set_parameter("fragility_key", "Non-Retrofit Fragility ID Code")

    # The simulated EF-5 tornado shows geographical locations and the range of wind speed
    # of tornado hazard in Joplin.
    hazard_type = "tornado"
    hazard_id = "5dfa32bbc0601200080893fb"

    result_name = "joplin_tornado_dmg_result"
    bldg_dmg.set_parameter("result_name", result_name)
    bldg_dmg.set_parameter("hazard_type", hazard_type)
    bldg_dmg.set_parameter("hazard_id", hazard_id)
    bldg_dmg.set_parameter("num_cpu", 4)
    bldg_dmg.set_parameter("seed", 1000)
    bldg_dmg.run_analysis()
    # end of Building damage analysis

    # get csv results from Building damage analysis
    building_dmg_result = bldg_dmg.get_output_dataset("ds_result")
    building_dmg_result.get_dataframe_from_csv()

    restoration = JoplinEmpiricalRestoration(client)
    # Building final target level dataset defining custom final restoration values
    building_fl_id = "61a68979d5b02930aa43ae39"

    restoration.load_remote_input_dataset("buildings", bldg_dataset_id)
    # restoration.load_remote_input_dataset("building_dmg", building_dmg_result)
    restoration.set_input_dataset("building_dmg", building_dmg_result)
    restoration.load_remote_input_dataset("building_functionality_level", building_fl_id)

    result_name = "Joplin_empirical_restoration_result"
    restoration.set_parameter("result_name", result_name)
    restoration.set_parameter("target_functionality_level", 0)
    # restoration.set_parameter("seed", 1234)

    # Run Analysis
    restoration.run_analysis()
예제 #9
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def run_with_base_class():
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)

    # Memphis 7.9 AB-95
    hazard_type = "earthquake"
    hazard_id = "5b902cb273c3371e1236b36b"

    # Shelby County Essential Facilities
    building_dataset_id = "5a284f42c7d30d13bc0821ba"

    # Default Building Fragility Mapping v1.0
    mapping_id = "5b47b350337d4a3629076f2c"

    non_structural_building_dmg = NonStructBuildingDamage(client)

    # Load input datasets
    non_structural_building_dmg.load_remote_input_dataset(
        "buildings", building_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    non_structural_building_dmg.set_input_dataset('dfr3_mapping_set',
                                                  mapping_set)

    # Specify the result name
    result_name = "non_structural_building_dmg_result"

    # Set analysis parameters
    non_structural_building_dmg.set_parameter("result_name", result_name)
    non_structural_building_dmg.set_parameter("hazard_type", hazard_type)
    non_structural_building_dmg.set_parameter("hazard_id", hazard_id)
    non_structural_building_dmg.set_parameter("num_cpu", 4)

    # use liquefaction (slow)
    # Shelby County Liquefaction Susceptibility
    use_liquefaction = True
    liq_geology_dataset_id = "5a284f55c7d30d13bc0824ba"

    non_structural_building_dmg.set_parameter("use_liquefaction",
                                              use_liquefaction)
    non_structural_building_dmg.set_parameter("liq_geology_dataset_id",
                                              liq_geology_dataset_id)

    # Run analysis
    non_structural_building_dmg.run_analysis()
def test_pipeline_dmg_w_repair_rate():
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)

    # This is the Memphis Water Buried Pipeline with Topology dataset the Ergo repository
    pipeline_dataset_id = "5a284f28c7d30d13bc081d14"
    # pipeline mapping
    mapping_id = "5b47c227337d4a38464efea8"

    # New madrid earthquake using Atkinson Boore 1995
    hazard_type = "earthquake"
    hazard_id = "5b902cb273c3371e1236b36b"

    # Geology dataset
    liq_geology_dataset_id = "5a284f53c7d30d13bc08249c"

    # Create pipeline damage
    test_pipeline_dmg_w_rr = PipelineDamageRepairRate(client)
    # Load input datasets
    test_pipeline_dmg_w_rr.load_remote_input_dataset("pipeline",
                                                     pipeline_dataset_id)
    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    test_pipeline_dmg_w_rr.set_input_dataset('dfr3_mapping_set', mapping_set)
    # Specify the result name
    result_name = "pipeline_result"
    # Set analysis parameters
    test_pipeline_dmg_w_rr.set_parameter("result_name", result_name)
    test_pipeline_dmg_w_rr.set_parameter("hazard_type", hazard_type)
    test_pipeline_dmg_w_rr.set_parameter("hazard_id", hazard_id)
    test_pipeline_dmg_w_rr.set_parameter("liquefaction_fragility_key", "pgd")
    # test_pipeline_dmg_w_rr.set_parameter("use_liquefaction", False)
    test_pipeline_dmg_w_rr.set_parameter(
        "use_liquefaction", True)  # toggle on and off to see liquefaction
    test_pipeline_dmg_w_rr.set_parameter("num_cpu", 4)
    test_pipeline_dmg_w_rr.set_parameter("liquefaction_geology_dataset_id",
                                         liq_geology_dataset_id)
    # Run pipeline damage analysis
    result = test_pipeline_dmg_w_rr.run_analysis()

    assert result is True
예제 #11
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def run_with_base_class():
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)

    # EQ Road Dataset - Seaside roads
    road_dataset_id = "5ee7af50772cf80008577ae3"

    hazard_type = "tsunami"
    # hazard_type = "earthquake"
    liq_geology_dataset_id = None

    if hazard_type == 'earthquake':
        # Seaside Earthquake
        hazard_id = "5ba8f379ec2309043520906f"

        # Earthquake mapping
        mapping_id = "5d545b0bb9219c0689f1f3f4"

        fragility_key = "pgd"
        liquefaction = False
    elif hazard_type == 'tsunami':
        # Seaside Tsunami
        hazard_id = "5bc9eaf7f7b08533c7e610e1"

        # Tsunami Mapping for Seaside
        mapping_id = "5ee7b2c9c54361000148de37"

        fragility_key = "Non-Retrofit inundationDepth Fragility ID Code"
        liquefaction = False
    else:
        raise ValueError(
            "Earthquake and tsunami are the only testable hazards with road damage currently"
        )

    uncertainty = False

    # Run road damage
    road_dmg = RoadDamage(client)
    road_dmg.load_remote_input_dataset("roads", road_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    road_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    road_dmg.set_parameter("result_name", "seaside_road_dmg_" + hazard_type)
    road_dmg.set_parameter("hazard_type", hazard_type)
    road_dmg.set_parameter("hazard_id", hazard_id)
    if fragility_key is not None:
        road_dmg.set_parameter("fragility_key", fragility_key)
    road_dmg.set_parameter("num_cpu", 1)
    road_dmg.set_parameter("use_liquefaction", liquefaction)
    if liquefaction and liq_geology_dataset_id is not None:
        road_dmg.set_parameter("liquefaction_geology_dataset_id",
                               liq_geology_dataset_id)
    road_dmg.set_parameter("use_hazard_uncertainty", uncertainty)

    # Run Analysis
    road_dmg.run_analysis()

    ######################################################################
    # test galveston hurricane road failure

    # road inventory for Galveston island
    road_dataset_id = "60ba5ee94219ee25a56b6999"
    # road damage by hurricane inundation mapping
    mapping_id = "60ba583b1f2b7d4a916faf03"
    # Galveston Deterministic Hurricane - Kriging inundationDuration
    hazard_type = "hurricane"
    hazard_id = "5f10837c01d3241d77729a4f"

    # Create road damage
    hurr_road_dmg = RoadDamage(client)
    # Load input datasets
    hurr_road_dmg.load_remote_input_dataset("roads", road_dataset_id)
    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    hurr_road_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)
    # Specify the result name
    result_name = "galveston_hurricane_road_result"
    # Set analysis parameters
    hurr_road_dmg.set_parameter("result_name", result_name)
    hurr_road_dmg.set_parameter("hazard_type", hazard_type)
    hurr_road_dmg.set_parameter(
        "fragility_key", "Non-Retrofit inundationDepth Fragility ID Code")
    hurr_road_dmg.set_parameter("hazard_id", hazard_id)
    hurr_road_dmg.set_parameter("num_cpu", 4)

    # Run road damage by hurricane inundation analysis
    hurr_road_dmg.run_analysis()
예제 #12
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def run_with_base_class():
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)

    # New madrid earthquake using Atkinson Boore 1995
    hazard_type = "earthquake"
    hazard_id = "5b902cb273c3371e1236b36b"

    # NBSR bridges
    bridge_dataset_id = "5a284f2dc7d30d13bc082040"

    # Default Bridge Fragility Mapping on incore-service
    mapping_id = "5b47bcce337d4a37755e0cb2"

    # Use hazard uncertainty for computing damage
    use_hazard_uncertainty = False
    # Use liquefaction (LIQ) column of bridges to modify fragility curve
    use_liquefaction = False

    # Create bridge damage
    bridge_dmg = BridgeDamage(client)

    # Load input datasets
    bridge_dmg.load_remote_input_dataset("bridges", bridge_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    bridge_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    # Set analysis parameters
    bridge_dmg.set_parameter("result_name", "bridge_result")
    bridge_dmg.set_parameter("hazard_type", hazard_type)
    bridge_dmg.set_parameter("hazard_id", hazard_id)
    bridge_dmg.set_parameter("num_cpu", 4)

    # Run bridge damage analysis
    bridge_dmg.run_analysis()

    ###################################################################
    # Test liquefaction

    # south carolina eq damage
    hazard_type = "earthquake"
    hazard_id = "5ee9309bc9f1b70008fdbd26"

    # south carolina bridges
    bridge_dataset_id = "5ee92f884210b80008f9377e"

    # Default Bridge Fragility Mapping on incore-service
    mapping_id = "5b47bcce337d4a37755e0cb2"

    # Use hazard uncertainty for computing damage
    use_hazard_uncertainty = False
    # Use liquefaction (LIQ) column of bridges to modify fragility curve
    use_liquefaction = True

    # Create bridge damage
    bridge_dmg = BridgeDamage(client)

    # Load input datasets
    bridge_dmg.load_remote_input_dataset("bridges", bridge_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    bridge_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    # Set analysis parameters
    bridge_dmg.set_parameter("result_name", "bridge_result_w_liquefaction")
    bridge_dmg.set_parameter("hazard_type", hazard_type)
    bridge_dmg.set_parameter("hazard_id", hazard_id)
    bridge_dmg.set_parameter("use_liquefaction", use_liquefaction)
    bridge_dmg.set_parameter("num_cpu", 1)

    # Run bridge damage analysis
    bridge_dmg.run_analysis()

    ###################################################################
    # test Galveston Bridge Damage
    hazard_type = "hurricane"
    hazard_id = "5f11e50cc6491311a814584c"

    # Galveston bridge
    bridge_dataset_id = "6062058ac57ada48e48c31e3"

    # Galveston hurricane bridge mapping
    refactored_mapping_id = "6062254b618178207f66226c"

    # Create bridge damage
    bridge_dmg = BridgeDamage(client)

    # Load input datasets
    bridge_dmg.load_remote_input_dataset("bridges", bridge_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    refactored_mapping_set = MappingSet(
        fragility_service.get_mapping(refactored_mapping_id))
    bridge_dmg.set_input_dataset('dfr3_mapping_set', refactored_mapping_set)

    # Set analysis parameters
    bridge_dmg.set_parameter(
        "fragility_key",
        "Hurricane SurgeLevel and WaveHeight Fragility ID Code")
    bridge_dmg.set_parameter("result_name", "galveston_bridge_dmg_result")
    bridge_dmg.set_parameter("hazard_type", hazard_type)
    bridge_dmg.set_parameter("hazard_id", hazard_id)
    bridge_dmg.set_parameter("num_cpu", 4)

    # Run bridge damage analysis
    bridge_dmg.run_analysis()
예제 #13
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def run_with_base_class():
    client = IncoreClient(INCORE_API_DEV_URL)

    # New madrid earthquake using Atkinson Boore 1995
    hazard_type = "earthquake"
    hazard_id = "5b902cb273c3371e1236b36b"

    # NBSR bridges
    bridge_dataset_id = "5a284f2dc7d30d13bc082040"

    # Default Bridge Fragility Mapping on incore-service
    mapping_id = "5b47bcce337d4a37755e0cb2"

    # Use hazard uncertainty for computing damage
    use_hazard_uncertainty = False
    # Use liquefaction (LIQ) column of bridges to modify fragility curve
    use_liquefaction = False

    # Create bridge damage
    bridge_dmg = BridgeDamage(client)

    # Load input datasets
    bridge_dmg.load_remote_input_dataset("bridges", bridge_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    bridge_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    # Set analysis parameters
    bridge_dmg.set_parameter("result_name", "bridge_result")
    bridge_dmg.set_parameter("hazard_type", hazard_type)
    bridge_dmg.set_parameter("hazard_id", hazard_id)
    bridge_dmg.set_parameter("num_cpu", 4)

    # Run bridge damage analysis
    bridge_dmg.run_analysis()

    ###################################################################
    # Test liquefaction

    # south carolina eq damage
    hazard_type = "earthquake"
    hazard_id = "5ee9309bc9f1b70008fdbd26"

    # south carolina bridges
    bridge_dataset_id = "5ee92f884210b80008f9377e"

    # Default Bridge Fragility Mapping on incore-service
    mapping_id = "5b47bcce337d4a37755e0cb2"

    # Use hazard uncertainty for computing damage
    use_hazard_uncertainty = False
    # Use liquefaction (LIQ) column of bridges to modify fragility curve
    use_liquefaction = True

    # Create bridge damage
    bridge_dmg = BridgeDamage(client)

    # Load input datasets
    bridge_dmg.load_remote_input_dataset("bridges", bridge_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    bridge_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

    # Set analysis parameters
    bridge_dmg.set_parameter("result_name", "bridge_result_w_liquefaction")
    bridge_dmg.set_parameter("hazard_type", hazard_type)
    bridge_dmg.set_parameter("hazard_id", hazard_id)
    bridge_dmg.set_parameter("use_liquefaction", use_liquefaction)
    bridge_dmg.set_parameter("num_cpu", 1)

    # Run bridge damage analysis
    bridge_dmg.run_analysis()
예제 #14
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def run_with_base_class(chained):
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)

    if chained:
        # *************************************************************
        # Set up and run Building damage, Galveston, TX analysis
        # *************************************************************
        hazard_type = "hurricane"
        # Galveston deterministic Hurricane, 3 datasets - Kriging
        # hazard_id = "5fa5a228b6429615aeea4410"  # prod
        hazard_id = "5fa472033c1f0c73fe81461a"

        # Galveston, TX Building inventory
        # bldg_inv_id = "60354b6c123b4036e6837ef7"  # prod 19k buildings with age_group
        bldg_inv_id = "602eba8bb1db9c28aef01358"

        # Hurricane building mapping (with equation)
        mapping_id = "602c381a1d85547cdc9f0675" # dev & prod
        fragility_service = FragilityService(client)
        mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))

        bldg_dmg = BuildingDamage(client)
        bldg_dmg.load_remote_input_dataset("buildings", bldg_inv_id)
        bldg_dmg.set_input_dataset("dfr3_mapping_set", mapping_set)

        result_name = "Galveston_bldg_dmg_result"

        bldg_dmg.set_parameter("fragility_key", "Hurricane SurgeLevel and WaveHeight Fragility ID Code")
        bldg_dmg.set_parameter("result_name", result_name)
        bldg_dmg.set_parameter("hazard_type", hazard_type)
        bldg_dmg.set_parameter("hazard_id", hazard_id)
        bldg_dmg.set_parameter("num_cpu", 4)

        # Run Building damage
        bldg_dmg.run_analysis()

        # Retrieve result dataset
        building_dmg_result = bldg_dmg.get_output_dataset("ds_result")

        # Convert dataset to Pandas DataFrame
        # bdmg_df = building_dmg_result.get_dataframe_from_csv(low_memory=False)
        # print(bdmg_df[["guid", "DS_0", "DS_1", "DS_2", "DS_3", "haz_expose"]])

        # *************************************************************
        # Set up and run Housing Unit Allocation (HUA) analysis
        # *************************************************************
        # Housing unit inventory
        # housing_unit_inv = "5fc6ab1cd2066956f49e7a03" # prod
        housing_unit_inv = "5fc6a757eba0eb743dc7739f"
        # Address point inventory
        # address_point_inv = "5fc6aadcc38a0722f563392e"
        address_point_inv = "5fc6a4ddeba0eb743dc77301"

        # Create housing allocation
        hua = HousingUnitAllocation(client)

        # Load input dataset
        hua.load_remote_input_dataset("housing_unit_inventory", housing_unit_inv)
        hua.load_remote_input_dataset("address_point_inventory", address_point_inv)
        hua.load_remote_input_dataset("buildings", bldg_inv_id)

        # Specify the result name
        result_name = "Galveston_HUA"

        seed = 1238
        iterations = 1

        # Set analysis parameters
        hua.set_parameter("result_name", result_name)
        hua.set_parameter("seed", seed)
        hua.set_parameter("iterations", iterations)

        # Run Housing unit allocation analysis
        hua.run_analysis()

        # Retrieve result dataset
        hua_result = hua.get_output_dataset("result")

        # Convert dataset to Pandas DataFrame
        # hua_df = hua_result.get_dataframe_from_csv(low_memory=False)
        # Display top 5 rows of output data
        # print(hua_df[["guid", "numprec", "incomegroup"]].head())

        # *************************************************************
        # Set up and run Population Dislocation analysis
        # *************************************************************

        # Block group data, IN-CORE_BGMAP_2021-01-19_GalvestonTX
        # bg_data = "603545f2dcda03378087e708" # prod
        bg_data = "6035445b1e456929c86094c8"
        # Value loss parameters DS 0-3
        # value_loss = "60354810e379f22e16560dbd"
        value_loss = "613901d9ca423a005e422feb"

        pop_dis = PopulationDislocation(client)

        pop_dis.load_remote_input_dataset("block_group_data", bg_data)
        pop_dis.load_remote_input_dataset("value_loss_param", value_loss)

        pop_dis.set_input_dataset("building_dmg", building_dmg_result)
        pop_dis.set_input_dataset("housing_unit_allocation", hua_result)

        result_name = "galveston-pop-disl-results"
        seed = 1111

        pop_dis.set_parameter("result_name", result_name)
        pop_dis.set_parameter("seed", seed)

        pop_dis.run_analysis()

        # Retrieve result dataset
        pd_result = pop_dis.get_output_dataset("result")

        # Convert dataset to Pandas DataFrame
        # pd_df = pd_result.get_dataframe_from_csv(low_memory=False)
        # Display top 5 rows of output data
        # print(pd_df[["guid", "dislocated"]].head())

        # *************************************************************
        # Set up and run Housing Recovery analysis
        # *************************************************************

        # Additional inventory data (assessed damage, square area)
        bldg_sqft_id = "62193c19a42a3e546ae2d9f8"
        # Census block groups data (required)
        census_bg_id = "62193b7ca42a3e546ae2d9f2"

        # Census appraisal file; id of external Census json
        census_appr_id = "6241fbd153302c512d685181" # dev
        result_name = "Galveston_building_values_chained"

        housing_rec = HousingRecovery(client)

        housing_rec.set_input_dataset("population_dislocation", pd_result)
        housing_rec.load_remote_input_dataset("building_area", bldg_sqft_id)
        housing_rec.load_remote_input_dataset("census_block_groups_data", census_bg_id)
        # Census appraisal data
        housing_rec.load_remote_input_dataset("census_appraisal_data", census_appr_id)

        housing_rec.set_parameter("result_name", result_name)

        housing_rec.run_analysis()

    else:
        # Run Housing Recovery analysis without chaining

        # Additional inventory data (assessed damage, square area)
        bldg_add_id = "62193c19a42a3e546ae2d9f8"
        # bldg_add_id = "6243638e89dbb809c6432501" # no dmg, uses value_loss
        # Census block groups data (required)
        census_bg_id = "62193b7ca42a3e546ae2d9f2"

        # Census appraisal file; id of external Census json
        census_appr_id = "6241fbd153302c512d685181"
        result_name = "Galveston_building_values"

        housing_rec = HousingRecovery(client)

        pop_disl_id = "623d1e1ca42a3e546aeba25f"  # dev
        housing_rec.load_remote_input_dataset("population_dislocation", pop_disl_id)
        housing_rec.load_remote_input_dataset("building_area", bldg_add_id)
        housing_rec.load_remote_input_dataset("census_block_groups_data", census_bg_id)
        # Census appraisal data
        housing_rec.load_remote_input_dataset("census_appraisal_data", census_appr_id)

        housing_rec.set_parameter("result_name", result_name)

        housing_rec.run_analysis()
예제 #15
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def run_with_base_class():
    client = IncoreClient()

    # New madrid earthquake using Atkinson Boore 1995
    hazard_type = "earthquake"
    hazard_id = "5b902cb273c3371e1236b36b"

    # mmsa highway bridges
    highway_bridges_id_list = {
        "Highway_Bridges": "60e86d6b544e944c3ce622d2"
    }

    # mmsa railway bridges
    railway_bridges_id_list = {
        "Railway_Bridges_BNSF": "60e86e6f60b3f41243fb9df3",
        "Railway_Bridges_CN": "60e86e91544e944c3ce62376",
        "Railway_Bridges_CSXT": "60e86eab60b3f41243fb9e44",
        "Railway_Bridges_NS": "60e86ed1544e944c3ce6241a",
        "Railway_Bridges_UP": "60e86ee960b3f41243fb9ee8"
    }

    # Default Bridge Fragility Mapping on incore-service
    highway_bridge_mapping_id_list = {
        "ABP": "60f89fce52e10319df8086c4",
        "ABA": "60f89fd647290977c8994353",
        "EBL": "60f89fd7a0c8a24d7eedf916",
        "EBT": "60f89fd96fb1bc236b68d3f7",
        "Col": "60f89fdc47290977c8994578",
        "FBL": "60f89fdda0c8a24d7eedfa9f",
        "ABT": "60f89fdf6fb1bc236b68d61c",
        "FBT": "60f89fdf52e10319df808b5f"
    }

    railway_bridge_mapping_id_list = {
        "ABT": "60f89fc947290977c8994215",
        "FBL": "60f89fcba0c8a24d7eedf6a0",
        "FBT": "60f89fcd6fb1bc236b68d049",
        "Col": "60f89fd047290977c8994302",
        "EBL": "60f89fd2a0c8a24d7eedf6f1",
        "EBT": "60f89fd36fb1bc236b68d3a6",
        "ABA": "60f89fd452e10319df8088e9",
        "ABP": "60f89fda52e10319df808a72"
    }

    # Use hazard uncertainty for computing damage
    use_hazard_uncertainty = False
    # Use liquefaction (LIQ) column of bridges to modify fragility curve
    use_liquefaction = False

    # Create bridge damage
    bridge_dmg = BridgeDamage(client)

    # Load input datasets
    for bridge_name, highway_bridge_id in highway_bridges_id_list.items():
        bridge_dmg.load_remote_input_dataset("bridges", highway_bridge_id)

        # Load fragility mapping
        fragility_service = FragilityService(client)
        for component_name, highway_bridge_mapping_id in highway_bridge_mapping_id_list.items():
            mapping_set = MappingSet(fragility_service.get_mapping(highway_bridge_mapping_id))
            bridge_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

            # Set analysis parameters
            bridge_dmg.set_parameter("result_name", bridge_name + "_" + component_name)
            bridge_dmg.set_parameter("hazard_type", hazard_type)
            bridge_dmg.set_parameter("hazard_id", hazard_id)
            bridge_dmg.set_parameter("num_cpu", 4)

            # Run bridge damage analysis
            bridge_dmg.run_analysis()

    # Load input datasets
    for bridge_name, railway_bridge_id in railway_bridges_id_list.items():
        bridge_dmg.load_remote_input_dataset("bridges", railway_bridge_id)

        # Load fragility mapping
        fragility_service = FragilityService(client)
        for component_name, railway_bridge_mapping_id in railway_bridge_mapping_id_list.items():
            mapping_set = MappingSet(fragility_service.get_mapping(railway_bridge_mapping_id))
            bridge_dmg.set_input_dataset('dfr3_mapping_set', mapping_set)

            # Set analysis parameters
            bridge_dmg.set_parameter("result_name", bridge_name + "_" + component_name)
            bridge_dmg.set_parameter("hazard_type", hazard_type)
            bridge_dmg.set_parameter("hazard_id", hazard_id)
            bridge_dmg.set_parameter("num_cpu", 4)

            # Run bridge damage analysis
            bridge_dmg.run_analysis()
예제 #16
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def run_with_base_class():
    client = IncoreClient(pyglobals.INCORE_API_DEV_URL)

    # ## Memphis EPF Damage with Earthquake ##
    hazard_type_eq = "earthquake"
    hazard_id_eq = "5b902cb273c3371e1236b36b"
    epf_dataset_id = "6189c103d5b02930aa3efc35"
    # mapping_id = "61980b11e32da63f4b9d86f4"
    mapping_id = "61980cf5e32da63f4b9d86f5"  # PGA and PGD

    use_liquefaction = True
    use_hazard_uncertainty = False
    liquefaction_geology_dataset_id = "5a284f53c7d30d13bc08249c"

    # Run epf damage
    epf_dmg_eq_memphis = EpfDamage(client)
    epf_dmg_eq_memphis.load_remote_input_dataset("epfs", epf_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    epf_dmg_eq_memphis.set_input_dataset('dfr3_mapping_set', mapping_set)

    epf_dmg_eq_memphis.set_parameter("result_name",
                                     "memphis_eq_epf_dmg_result")
    epf_dmg_eq_memphis.set_parameter("hazard_type", hazard_type_eq)
    epf_dmg_eq_memphis.set_parameter("hazard_id", hazard_id_eq)
    epf_dmg_eq_memphis.set_parameter("use_liquefaction", use_liquefaction)
    epf_dmg_eq_memphis.set_parameter("use_hazard_uncertainty",
                                     use_hazard_uncertainty)
    epf_dmg_eq_memphis.set_parameter("liquefaction_geology_dataset_id",
                                     liquefaction_geology_dataset_id)
    epf_dmg_eq_memphis.set_parameter("num_cpu", 1)
    # Run Analysis
    epf_dmg_eq_memphis.run_analysis()

    # ##  Seaside EPF Damage with Earthquake ##
    hazard_type_eq = "earthquake"
    hazard_id_eq = "5eebcbb08f80fe3899ad6039"
    epf_dataset_id = "5eebcaa17a00803abc85ec11"
    # Earthquake mapping
    mapping_id = "5eebcc13e7226233ce4ef0d7"  # only PGA

    # Run epf damage
    epf_dmg_eq = EpfDamage(client)
    epf_dmg_eq.load_remote_input_dataset("epfs", epf_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    epf_dmg_eq.set_input_dataset('dfr3_mapping_set', mapping_set)
    epf_dmg_eq.set_parameter("result_name", "seaside_eq_epf_dmg_result")
    epf_dmg_eq.set_parameter("hazard_type", hazard_type_eq)
    epf_dmg_eq.set_parameter("hazard_id", hazard_id_eq)
    epf_dmg_eq.set_parameter("num_cpu", 1)
    epf_dmg_eq.run_analysis()

    # ## Seaside Tsunami EPF Damage ##
    hazard_type_tsu = "tsunami"
    hazard_id_tsu = "5bc9eaf7f7b08533c7e610e1"
    epf_dataset_id = "5eebcaa17a00803abc85ec11"
    # Tsunami mapping
    mapping_id = "605bf9e1618178207f6475c6"

    # Run epf damage
    epf_dmg_tsu_re = EpfDamage(client)
    epf_dmg_tsu_re.load_remote_input_dataset("epfs", epf_dataset_id)
    epf_dmg_eq = EpfDamage(client)
    epf_dmg_eq.load_remote_input_dataset("epfs", epf_dataset_id)

    # Load fragility mapping
    fragility_service = FragilityService(client)
    mapping_set = MappingSet(fragility_service.get_mapping(mapping_id))
    epf_dmg_tsu_re.set_input_dataset('dfr3_mapping_set', mapping_set)

    epf_dmg_tsu_re.set_parameter(
        "fragility_key", "Non-Retrofit inundationDepth Fragility ID Code")
    epf_dmg_tsu_re.set_parameter("result_name",
                                 "seaside_tsunami_epf_dmg_result")
    epf_dmg_tsu_re.set_parameter("hazard_type", hazard_type_tsu)
    epf_dmg_tsu_re.set_parameter("hazard_id", hazard_id_tsu)
    epf_dmg_tsu_re.set_parameter("num_cpu", 1)

    epf_dmg_tsu_re.set_input_dataset('dfr3_mapping_set', mapping_set)
    # Run Analysis
    epf_dmg_tsu_re.run_analysis()