Fix shakemap, edits to allow updated HAZUS Bridges

modules/Workflow/WorkflowApplications.json

@@ -285,12 +285,12 @@
         "ApplicationSpecificInputs": [
           {
             "id": "Directory",
-            "type": "path",
+            "type": "string",
             "description": "Path to file containing folder of shake maps"
           },
           {
             "id": "EventPath",
-            "type": "string",
+            "type": "path",
             "description": "Path to the shake map event"
           },
           {

modules/createEVENT/IsolatedBuildingCFD/post_process_output.py

@@ -259,7 +259,7 @@ def read_pressure_data(file_names):
                 # index += 1
 
             except:  # noqa: E722
-                # sys.exit('Fatal Error!: the pressure filese have time gap')
+                # sys.exit('Fatal Error!: the pressure files have time gap')
                 index = 0  # Joint them even if they have a time gap
 
             connected_time = np.concatenate((connected_time, time2[index:]))

modules/createEVENT/shakeMapEvent/shakeMapEvent.py

@@ -44,12 +44,17 @@
 from pathlib import Path
 
 
+class IntensityMeasureTypeError(Exception):
+    def __init__(self, im_type):
+        super().__init__(f'Intensity measure type {im_type} not found in grid data')
+
+
 def create_shakemap_event(eventDirectory, eventPath, IMTypes):  # noqa: D103, N803
     IMTypesList = eval(IMTypes)  # noqa: S307, N806
 
     print('Creating shakemap event')  # noqa: T201
 
-    xml_file_path = Path(eventDirectory) / eventPath / 'grid.xml'
+    xml_file_path = Path(eventPath) / 'grid.xml'
 
     # Parse the XML file
     tree = ET.parse(xml_file_path)  # noqa: S314
@@ -62,6 +67,19 @@ def create_shakemap_event(eventDirectory, eventPath, IMTypes):  # noqa: D103, N8
     points = []
     attributes = []
 
+    # Get the attribute_mapping
+    namespace = {'ns': 'http://earthquake.usgs.gov/eqcenter/shakemap'}
+    grid_fields = {}
+    for grid_field in root.findall('ns:grid_field', namespace):
+        index = grid_field.get('index')
+        name = grid_field.get('name')
+        units = grid_field.get('units')
+        grid_fields[name] = {'index': index, 'units': units}
+    attribute_mapping = {}
+    for im_type in ['PGA', 'PGV', 'MMI', 'PSA03', 'PSA10', 'PSA30']:
+        if im_type not in grid_fields:
+            raise IntensityMeasureTypeError(im_type)
+        attribute_mapping[im_type] = int(grid_fields[im_type]['index']) - 1
     # Parse the grid data
     for line in grid_data.text.strip().split('\n'):
         values = line.split()
@@ -71,15 +89,6 @@ def create_shakemap_event(eventDirectory, eventPath, IMTypes):  # noqa: D103, N8
 
         # Store only the specified attributes
         attr = {}
-        attribute_mapping = {
-            'PGA': 2,
-            'PGV': 3,
-            'MMI': 4,
-            'PSA03': 5,
-            'PSA10': 6,
-            'PSA30': 7,
-        }
-
         for im_type in IMTypesList:
             if im_type in attribute_mapping:
                 attr[im_type] = float(values[attribute_mapping[im_type]])
@@ -89,11 +98,21 @@ def create_shakemap_event(eventDirectory, eventPath, IMTypes):  # noqa: D103, N8
     # Create GeoDataFrame
     gdf = gpd.GeoDataFrame(attributes, geometry=points, crs='EPSG:4326')
 
+    if 'PGA' in gdf.columns:
+        gdf['PGA'] = gdf['PGA'] / 100 # convert from pct g to g
+
+    if 'PSA03' in gdf.columns:
+        gdf['PSA03'] = gdf['PSA03'] / 100 # convert from pct g to g
+        gdf = gdf.rename(columns={'PSA03': 'SA_0.3'})
+    if 'PSA10' in gdf.columns:
+        gdf['PSA10'] = gdf['PSA10'] / 100 # convert from pct g to g
+        gdf = gdf.rename(columns={'PSA10': 'SA_1.0'})
+
     # Display the first few rows
     print('Saving shakemap to gpkg')  # noqa: T201
 
     # Save as a GeoPackage file
-    gdf_path = Path(eventDirectory) / 'EventGrid.gpkg'
+    gdf_path = Path(eventPath) / 'EventGrid.gpkg'
     gdf.to_file(gdf_path, driver='GPKG')
 
     return  # noqa: PLR1711

modules/performRegionalMapping/NearestNeighborEvents/NNE.py

@@ -321,7 +321,8 @@ def find_neighbors(  # noqa: C901, D103
                 for col in grid_df.columns
                 if col not in ['geometry', 'Longitude', 'Latitude']
             ]
-            event_count = len(im_columns)
+            # event_count = len(im_columns)
+            event_count = 1
 
             # for each neighbor
             for sample_j, nbr in enumerate(nbr_samples):
@@ -332,26 +333,28 @@ def find_neighbors(  # noqa: C901, D103
                 nbr_index = ind_list[nbr]
 
                 # For GIS files, create a new CSV file
-                csv_filename = f'Site_{sample_j}.csv'
+                csv_filename = f'Site_{nbr_index}.csv'
 
                 csv_path = event_dir / csv_filename
 
-                # Create a CSV file with data from the GIS file
-                # Use actual data from the GIS file if available, otherwise use dummy data
-                im_columns = [
-                    col
-                    for col in grid_df.columns
-                    if col not in ['geometry', 'Longitude', 'Latitude']
-                ]
-
-                im_data = pd.DataFrame(
-                    {
-                        col: [grid_df.iloc[nbr_index][col]] * event_count
-                        for col in im_columns
-                    }
-                )
+                if not csv_path.exists():
+
+                    # Create a CSV file with data from the GIS file
+                    # Use actual data from the GIS file if available, otherwise use dummy data
+                    im_columns = [
+                        col
+                        for col in grid_df.columns
+                        if col not in ['geometry', 'Longitude', 'Latitude']
+                    ]
+
+                    im_data = pd.DataFrame(
+                        {
+                            col: [grid_df.iloc[nbr_index][col]] * event_count
+                            for col in im_columns
+                        }
+                    )
 
-                im_data.to_csv(csv_path, index=False)
+                    im_data.to_csv(csv_path, index=False)
                 # save the collection file name and the IM row id
                 event_list.append(csv_filename + f'x{event_j}')
 

modules/performSIMULATION/capacitySpectrum/CapacityModels.py

@@ -88,6 +88,7 @@ def convert_story_rise(structureType, stories):  # noqa: N803
         rise = None
 
     else:
+        rise = None
         # First, check if we have valid story information
         try:
             stories = int(stories)
@@ -340,7 +341,7 @@ def __init__(self, general_info, dD=0.001):  # noqa: N803
             self.Dy = self.capacity_data[self.design_level][self.HAZUS_type]['Dy']
             self.Ay = self.capacity_data[self.design_level][self.HAZUS_type]['Ay']
         except KeyError:
-            msg = f'No capacity data for {self.HAZUS_type} and {self.design_level}'
+            msg = f'No capacity data for build class {self.HAZUS_type} and design level {self.design_level}'
             raise KeyError(msg)  # noqa: B904
         self.cao_peterson_2006 = cao_peterson_2006(
             self.Dy, self.Ay, self.Du, self.Au, dD

modules/performSIMULATION/capacitySpectrum/DampingModels.py

@@ -256,6 +256,8 @@ def get_beta(self, Dp, Ap):  # noqa: N803
                 f'The base model {self.base_model} does not have a useful'
                 'get_kappa method.'
             )
+        if Dp <= 0 or Ap <= 0:
+            return beta_elastic
         Du = self.capacity.Du  # noqa: N806
         Ax = self.capacity.Ax  # noqa: N806
         B = self.capacity.B  # noqa: N806

modules/performSIMULATION/capacitySpectrum/runCMS.py

@@ -97,10 +97,8 @@ def find_performance_point(cap_x, cap_y, dem_x, dem_y, dd=0.001):
     elif dem_y_interp[0] < cap_y_interp[0]:
         perf_x = 0.001  # x_interp[0]
         perf_y = 0.001  # cap_y_interp[0]
-    # except IndexError as err:
-    #   print('No performance point found; curves do not intersect.')
-    #   print('IndexError: ')
-    #   print(err)
+    else:
+      print('No performance point found; curves do not intersect.')
 
     return perf_x, perf_y
 

modules/systemPerformance/ResidualDemand/run_residual_demand.py

@@ -868,6 +868,8 @@ def run_residual_demand(  # noqa: C901
     edges_gdf['capacity'] = edges_gdf['lanes'] * 1800
     edges_gdf['normal_capacity'] = edges_gdf['capacity']
     edges_gdf['normal_maxspeed'] = edges_gdf['maxspeed']
+    edges_gdf['start_nid'] = edges_gdf['start_nid'].astype(int)
+    edges_gdf['end_nid'] = edges_gdf['end_nid'].astype(int)
     # edges_gdf['fft'] = edges_gdf['length']/edges_gdf['maxspeed'] * 2.23694
     edges_gdf.to_csv('edges.csv', index=False)
     nodes_gdf = gpd.read_file(node_geojson)

modules/tools/BRAILS/runBrailsTransp.py

@@ -72,6 +72,7 @@ def runBrails(  # noqa: N802, D103
     minimumHAZUS,  # noqa: N803
     maxRoadLength,  # noqa: N803
     lengthUnit,  # noqa: N803
+    saveTrafficSimulationAttr,  # noqa: N803
 ):
     # Initialize TranspInventoryGenerator:
     invGenerator = TranspInventoryGenerator(  # noqa: N806
@@ -83,7 +84,8 @@ def runBrails(  # noqa: N802, D103
 
     # Combine and format the generated inventory to SimCenter transportation network inventory json format
     invGenerator.combineAndFormat_HWY(
-        minimumHAZUS=minimumHAZUS, maxRoadLength=maxRoadLength, lengthUnit=lengthUnit
+        minimumHAZUS=minimumHAZUS, maxRoadLength=maxRoadLength, lengthUnit=lengthUnit,
+        connectivity=saveTrafficSimulationAttr
     )
 
 
@@ -99,6 +101,7 @@ def main(args):  # noqa: D103
     )
     parser.add_argument('--maxRoadLength', default=100, type=float)
     parser.add_argument('--lengthUnit', default='m', type=str)
+    parser.add_argument('--saveTrafficSimulationAttr', default=False, type=str2bool, nargs='?', const=True)
 
     args = parser.parse_args(args)
 
@@ -115,6 +118,7 @@ def main(args):  # noqa: D103
         args.minimumHAZUS,
         args.maxRoadLength,
         args.lengthUnit,
+        args.saveTrafficSimulationAttr,
     )
 
     log_msg('BRAILS successfully generated the requested transportation inventory')