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CreateScenario.py
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CreateScenario.py
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# -*- coding: utf-8 -*-
#
# Copyright (c) 2018 Leland Stanford Junior University
# Copyright (c) 2018 The Regents of the University of California
#
# This file is part of the SimCenter Backend Applications
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice,
# this list of conditions and the following disclaimer.
#
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# 3. Neither the name of the copyright holder nor the names of its contributors
# may be used to endorse or promote products derived from this software without
# specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
# POSSIBILITY OF SUCH DAMAGE.
#
# You should have received a copy of the BSD 3-Clause License along with
# this file. If not, see <http://www.opensource.org/licenses/>.
#
# Contributors:
# Kuanshi Zhong
#
import os
import subprocess
import json
import random
import numpy as np
import pandas as pd
from FetchOpenSHA import *
def create_earthquake_scenarios(scenario_info, stations, input_dir=[], output_dir=[], output_format='SimCenterEvent'):
# Number of scenarios
source_num = scenario_info.get('Number', 1)
if source_num == 'All':
# Large number to consider all sources in the ERF
source_num = 10000000
# Directly defining earthquake ruptures
if scenario_info['Generator'] == 'Simulation':
# TODO:
print('Physics-based earthquake simulation is under development.')
return 1
# Searching earthquake ruptures that fulfill the request
elif scenario_info['Generator'] == 'Selection':
# Collecting all possible earthquake scenarios
lat = []
lon = []
for s in stations['Stations']:
lat.append(s['Latitude'])
lon.append(s['Longitude'])
# Reference location
lat = np.mean(lat)
lon = np.mean(lon)
ref_station = [lat, lon]
# Getting earthquake rupture forecast data
source_type = scenario_info['EqRupture']['Type']
if source_type == 'ERF':
source_model = scenario_info['EqRupture']['Model']
source_name = scenario_info['EqRupture'].get('Name', None)
min_M = scenario_info['EqRupture'].get('min_Mag', 5.0)
max_M = scenario_info['EqRupture'].get('max_Mag', 9.0)
max_R = scenario_info['EqRupture'].get('max_Dist', 1000.0)
eq_source = getERF(source_model, True)
erf_data = export_to_json(eq_source, ref_station, outfile = None, \
EqName = source_name, minMag = min_M, \
maxMag = max_M, maxDistance = max_R, \
maxSources = np.max([500, source_num]))
# Parsing data
feat = erf_data['features']
tag = []
for i, cur_f in enumerate(feat):
if source_name and (source_name not in cur_f['properties']['Name']):
continue
if min_M > cur_f['properties']['Magnitude']:
continue
tag.append(i)
# Abstracting desired ruptures
s_tag = random.sample(tag, min(source_num, len(tag)))
erf_data['features'] = list(feat[i] for i in s_tag)
scenario_data = dict()
for i, rup in enumerate(erf_data['features']):
scenario_data.update({i: {
'Type': source_type,
'RuptureForecast': source_model,
'SourceIndex': rup['properties']['Source'],
'RuptureIndex': rup['properties']['Rupture']
}})
# Cleaning tmp outputs
del erf_data
elif source_type == 'PointSource':
scenario_data = dict()
try:
magnitude = scenario_info['EqRupture']['Magnitude']
location = scenario_info['EqRupture']['Location']
average_rake = scenario_info['EqRupture']['AverageRake']
average_dip = scenario_info['EqRupture']['AverageDip']
scenario_data.update({0: {
'Type': source_type,
'Magnitude': magnitude,
'Location': location,
'AverageRake': average_rake,
'AverageDip': average_dip
}})
except:
print('Please check point-source inputs.')
# Simulating the earthquake
elif scenario_info['Generator'] == 'ShakerMaker':
from imm.ShakerMakerSimulation import ShakerMakerModel
# initialization
sm_model = ShakerMakerModel(scenario_info['SimuConfig'], stations['Stations'], input_dir)
# configuration
sm_model.model_configuration()
scenario_data = sm_model
sm_model.run_simulation(output_dir, output_format)
# return
return scenario_data
def create_wind_scenarios(scenario_info, event_info, stations, data_dir):
# Number of scenarios
source_num = scenario_info.get('Number', 1)
# Directly defining earthquake ruptures
if scenario_info['Generator'] == 'Simulation':
# Collecting site locations
lat = []
lon = []
for s in stations['Stations']:
lat.append(s['Latitude'])
lon.append(s['Longitude'])
# Station list
station_list = {
'Latitude': lat,
'Longitude': lon
}
# Track data
try:
track_file = scenario_info['Storm'].get('Track')
df = pd.read_csv(os.path.join(data_dir, track_file), header = None, index_col = None)
track = {
'Latitude': df.iloc[:, 0].values.tolist(),
'Longitude': df.iloc[:, 1].values.tolist()
}
except:
print('CreateScenario: no storm track provided or file format not accepted.')
# Save Lat_w.csv
track_simu_file = scenario_info['Storm'].get('TrackSimu', None)
if track_simu_file:
df = pd.read_csv(os.path.join(data_dir, track_simu_file), header = None, index_col = None)
track_simu = df.iloc[:, 0].values.tolist()
else:
track_simu = track['Latitude']
# Reading Terrain info (if provided)
terrain_file = scenario_info.get('Terrain', None)
if terrain_file:
with open(os.path.join(data_dir, terrain_file)) as f:
terrain_data = json.load(f)
else:
terrain_data = []
# Parsing storm properties
param = []
param.append(scenario_info['Storm']['Landfall']['Latitude'])
param.append(scenario_info['Storm']['Landfall']['Longitude'])
param.append(scenario_info['Storm']['LandingAngle'])
param.append(scenario_info['Storm']['Pressure'])
param.append(scenario_info['Storm']['Speed'])
param.append(scenario_info['Storm']['Radius'])
# Monte-Carlo
#del_par = [0, 0, 0] # default
# Parsing mesh configurations
mesh_info = [1000., scenario_info['Mesh']['DivRad'], 1000000.]
mesh_info.extend([0., scenario_info['Mesh']['DivDeg'], 360.])
# Wind speed measuring height
measure_height = event_info['IntensityMeasure']['MeasureHeight']
# Saving results
scenario_data = dict()
for i in range(source_num):
scenario_data.update({i: {
'Type': 'Wind',
'CycloneParam': param,
'StormTrack': track,
'StormMesh': mesh_info,
'Terrain': terrain_data,
'TrackSimu': track_simu,
'StationList': station_list,
'MeasureHeight': measure_height
}})
# return
return scenario_data
else:
print('Currently only supporting Simulation generator.')