SelectGroundMotion.py

# -*- 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.
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# 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 time
import glob
import re
import shutil
import sys
from pathlib import Path
from selenium import webdriver
import json
import random
import numpy as np
import pandas as pd
import zipfile
import csv


def select_ground_motion(target_period, target_ln_sa, gmdb_file, sf_max, sf_min,
                         output_dir, output_file, stations):

    # Loading gmdb
    if gmdb_file == 'NGAWest2':
        cwd = os.path.dirname(os.path.realpath(__file__))
        gmdb = pd.read_csv(cwd+'/database/gmdb/NGAWest2.csv', header = 0, index_col = None)
        # Parsing spectral data
        num_gm = len(gmdb['RecId'])
        tmp = gmdb.keys()[37:147]
        T_db = [float(a.replace('T','').replace('S','')) for a in tmp]
        psa_db = gmdb.iloc[:, 37:147]
        # Scaling factors
        sf_range = np.linspace(sf_min, sf_max, 100)
        # Selected ground motion ID
        gm_id = []
        sf_data = []
        filename = []
        # Processing gmdb spectra
        psa_db_m = [np.interp(target_period, T_db, psa_db.iloc[k, :]) for k in range(num_gm)]
        tmp_scen = 0
        # Looping over all scenarios
        for cur_target in target_ln_sa:
            tmp_scen = tmp_scen + 1
            print('-Scenario #'+str(tmp_scen))
            num_stations, num_periods, num_simu = cur_target.shape
            tmp_id = np.zeros((num_stations, num_simu))
            tmp_sf = np.zeros((num_stations, num_simu))
            tmp_min_err = np.zeros((num_stations, num_simu))
            tmp_filename = []
            for i in range(num_simu):
                print('--Realization #'+str(i+1))
                for j in range(num_stations):
                    #print('---Station #'+str(j+1))
                    tmp_target = [cur_target[j, :, i] for k in range(num_gm)]
                    min_err = 1000000.0
                    for s in sf_range:
                        err = np.linalg.norm(np.exp(tmp_target) - np.exp(np.log(s) + np.log(psa_db_m)),
                                             axis = 1)
                        if np.min(err) < min_err:
                            min_err = np.min(err)
                            tmp_tag = err.argmin()
                            sf = s
                    tmp_min_err[j, i] = min_err
                    tmp_id[j, i] = int(gmdb['RecId'][tmp_tag])
                    tmp_sf[j, i] = sf
                    tmp_filename.append('RSN'+str(int(tmp_id[j,i]))+'_'+gmdb['FileNameHorizontal1'][tmp_tag].replace("\\","_").replace("/","_"))
                    tmp_filename.append('RSN'+str(int(tmp_id[j,i]))+'_'+gmdb['FileNameHorizontal2'][tmp_tag].replace("\\","_").replace("/","_"))
            # Collecting results in one scenario
            gm_id.append(tmp_id)
            sf_data.append(tmp_sf)
            filename.extend(tmp_filename)
            #print(tmp_min_err)
    else:
        print('SelectGroundMotion: currently only supporting NGAWest2.')
        return 1

    # output data
    station_name = ['site'+str(j)+'.csv' for j in range(len(stations))]
    lat = [stations[j]['Latitude'] for j in range(len(stations))]
    lon = [stations[j]['Longitude'] for j in range(len(stations))]
    df = pd.DataFrame({
        'sta': station_name,
        'lon': lon,
        'lat': lat
    })
    output_dir = os.path.join(os.path.dirname(Path(output_dir)),
                              os.path.basename(Path(output_dir)))
    df.to_csv(os.path.join(output_dir, output_file), index = False)
    for cur_scen in range(len(gm_id)):
        if len(gm_id) > 1:
            cur_scen_folder = 'scenario'+str(cur_scen+1)
            try:
                os.mkdir(os.path.join(output_dir, cur_scen_folder))
            except:
                print('SelectGroundMotion: scenario folder already exists.')
            cur_output_dir = os.path.join(output_dir, cur_scen_folder)
        else:
            cur_output_dir = output_dir
        for i, site_id in enumerate(station_name):
            gm_file = ['RSN'+str(int(j)) for j in gm_id[cur_scen][i]]
            factor = [j for j in sf_data[cur_scen][i]]
            df = pd.DataFrame({
                'GM_file': gm_file,
                'factor': factor
            })
            df.to_csv(os.path.join(cur_output_dir, site_id), index = False)
    # return
    return gm_id, filename


def output_all_ground_motion_info(gm_id, gm_file, output_dir, filename):

    # Writing all record names to a csv file
    print(gm_file)
    try:
        with open(os.path.join(output_dir, filename), 'w') as f:
            w = csv.writer(f)
            w.writerow(gm_file)
        with open(os.path.join(output_dir, 'RSN.csv'), 'w') as f:
            w = csv.writer(f)
            w.writerow(gm_id)
        return 1
    except:
        return 0


def download_ground_motion(gm_id, user_name, user_password, output_dir):

    # Setting chrome options
    if sys.platform.startswith('win'):
        chromedriver = os.path.dirname(__file__) + '/bin/chromedriver/chromedriver.exe'
    elif sys.platform.startswith('linux'):
        chromedriver = os.path.dirname(__file__) + '/bin/chromedriver/chromedriver_linux'
    elif sys.platform.startswith('darwin'):
        chromedriver = os.path.dirname(__file__) + '/bin/chromedriver/chromedriver_mac'
        os.chmod(chromedriver, 755)
    else:
        print('Currently supoorting win32, linux, and mac.')
    chromeOptions = webdriver.ChromeOptions()
    output_dir = os.path.join(os.path.dirname(Path(output_dir)),
                              os.path.basename(Path(output_dir)))
    prefs = {"download.default_directory" : output_dir, "directory_upgrade": True}
    chromeOptions.add_experimental_option("prefs", prefs)
    # Ground motion record numbers
    num_gm = len(gm_id)
    # Accessing NGA West-2 website
    gm_driver = webdriver.Chrome(executable_path=chromedriver, chrome_options=chromeOptions)
    gm_driver.get("https://ngawest2.berkeley.edu/users/sign_in?unauthenticated=true")
    try:
        gm_driver.find_element_by_id("user_email").send_keys(user_name)
        gm_driver.find_element_by_id("user_password").send_keys(user_password)
        gm_driver.find_element_by_id("user_submit").click()
        gm_driver.find_element_by_xpath('//a[@href="/spectras/new?sourceDb_flag=1"]').click()
        gm_driver.find_element_by_xpath('//button[@onclick="OnSubmit();"]').click()
        time.sleep(1)
    except:
        gm_driver.close()
        print('Please provide valid account name and password.')
        return 0

    # Grouping every 100 records (NGA West website allows 100 records/time)
    for r in range(num_gm//100 + 1):
        cur_id = [f"{c}" for c in gm_id[r*100:min(r*100+100, num_gm)]]
        s = ","
        s = s.join(cur_id)
        gm_driver.find_element_by_id("search_search_nga_number").clear()
        gm_driver.find_element_by_id("search_search_nga_number").send_keys(s)
        gm_driver.find_element_by_xpath('//button[@onclick="uncheck_plot_selected();reset_selectedResult();OnSubmit();"]').click()
        time.sleep(20)
        gm_driver.find_element_by_xpath('//button[@onclick="getSelectedResult(true)"]').click()
        gm_driver.switch_to_alert().accept()
        gm_driver.switch_to_alert().accept()
        time.sleep(40)
    # Closing
    gm_driver.close()

    record_path = output_dir
    record_files = os.listdir(record_path)
    raw_record_folder = 'raw'
    try:
        os.mkdir(os.path.join(record_path, raw_record_folder))
    except:
        print('SelectGroundMotion: the /record/raw folder already exists.')
    for cur_file in record_files:
        if 'zip' in cur_file:
            with zipfile.ZipFile(os.path.join(record_path, cur_file), 'r') as zip_ref:
                zip_ref.extractall(os.path.join(record_path, raw_record_folder))
            os.remove(os.path.join(record_path, cur_file))
    # return
    return os.path.join(record_path, raw_record_folder)

def readNGAWest2record(ngaW2FilePath):
    series = []
    dt = 0.0
    with open(ngaW2FilePath, 'r') as recordFile:
        data_flag = False
        for line in recordFile:
            if(data_flag):
                # seismogram
                series.extend([float(value) for value in line.split()])
            elif("NPTS=" in line):
                # sampling rate
                dt = float(re.match(r"NPTS=.+, DT=\s+([0-9\.]+)\s+SEC", line).group(1))
                data_flag = True
    # return
    return series, dt


def parse_record(gm_file, raw_dir, output_dir, input_format, output_format):
    gm_file = np.reshape(gm_file, (-1, 2))
    for cur_id in gm_file:
        # Reading raw data
        if input_format == 'NGAWest2':
            if(len(cur_id) != 2):
                print('Error finding NGA West 2 files.\n'\
                'Please download the files for record {} '\
                .format(cur_id))
                exit(-1)
            acc_1, dt_1 = readNGAWest2record(os.path.join(raw_dir, cur_id[0]))
            acc_2, dt_2 = readNGAWest2record(os.path.join(raw_dir, cur_id[1]))
        else:
            print('Currently only supporting NGAWest2')
        # Parsing output files
        rsn = cur_id[0].split('_')[0]
        if output_format == 'SimCenterEvent':
            tmp = {
                "name": str(rsn),
                "dT": dt_1,
                "data_x": acc_1,
                "data_y": acc_2,
                "PGA_x": max(abs(np.array(acc_1))),
                "PGA_y": max(abs(np.array(acc_2)))
            }
            with open(output_dir+str(rsn)+'.json', 'w') as f:
                json.dump(tmp, f, indent = 2)
        else:
            print('Currently only supporting SimCenterEvent')

    # removing raw files
    shutil.rmtree(raw_dir)
    # return
    return output_dir