How to use spawning method in locust

Best Python code snippet using locust

run_svim.py

Source:run_svim.py

1#!/usr/bin/env python2from __future__ import print_function3print(1)4import matplotlib5matplotlib.use('TkAgg')6print(2)7import time8from datetime import datetime, date, time, timedelta9from dateutil.relativedelta import relativedelta10import numpy as np11print(3)12from opendrift.readers import reader_basemap_landmask13from opendrift.readers import reader_ROMS_native14from kino.pelagicplankton import PelagicPlanktonDrift15from opendrift.readers import reader_netCDF_CF_generic16import logging17import gdal18import os19#from netCDF4 import Dataset, datetime, date2num,num2date20print(4)21from numpy.random import RandomState22import matplotlib.pyplot as plt23try:24    import ogr25    import osr26except Exception as e:27    print (e)28    raise ValueError('OGR library is needed to read shapefiles.')29print(5)30def setupSeed(hoursBetweenTimestepInROMSFiles,startTime,endTime,startSpawningTime,endSpawningTime,releaseParticles):31    ##################################################32    # Create seed variation as function of day33    ##################################################34    # Make datetime array from start to end at 3 hour interval35    difference=endTime-startTime36    hoursOfSimulation=divmod(difference.total_seconds(), 3600)37    difference=endSpawningTime-startSpawningTime38    hoursOfSpawning=divmod(difference.total_seconds(), 3600)39    timeStepsSimulation=int(int(hoursOfSimulation[0])/hoursBetweenTimestepInROMSFiles)40		41    print ("\nsvim TIME EVOLUTION:")42    print ("=>SIMULATION: Drift simulation will run for %s simulation hours" %(timeStepsSimulation))43    print ("=>SPAWNING: Simulated spawning will run for %s simulation hours\n initiated on %s and ending on %s"%(timeStepsSimulation,startSpawningTime,endSpawningTime))44    interval = timedelta(hours=24)45    hoursPerSpawning=divmod(interval.total_seconds(), 3600) #hours per spawning event46    timeStepsSpawning=int(int(hoursOfSpawning[0])/int(hoursPerSpawning[0])) #number of spawning timesteps47    spawningTimes = [startSpawningTime + interval*n for n in range(timeStepsSpawning)] #times of spawning48    # Define number of particles released per spawning day, summing to ~releaseParticles and following a gaussian curve49    mu, sigma = 1, 0.25 # mean and standard deviation of the gaussian curve 50    prng = RandomState(1) # random number generator (specify number to ensure the same sequence each time)51    s = prng.normal(mu, sigma, timeStepsSpawning) # random distribution52    num=(s*releaseParticles/timeStepsSpawning).astype(int) # number of particles released per spawning event as releaseParticles/timeStepsSpawning, weighted by random distribution53    num=np.sort(num) #sort particles in increasing order 54    num=np.concatenate((num[len(num)%2::2],num[::-2]),axis=0) #release the highest number of particles at the midpoint of the spawning period55	56    print ("SPAWNING: Simulated spawning will release %s eggs"%(np.sum(num)))57    return num, spawningTimes58print(6)59def createOutputFilenames(startTime,endTime,verticalBehavior,spawning_ground):60    startDate=''61    if startTime.day<10:62        startDate+='0%s'%(startTime.day)63    else:64        startDate+='%s'%(startTime.day)65    if startTime.month<10:66        startDate+='0%s'%(startTime.month)67    else:68        startDate+='%s'%(startTime.month)69    startDate+='%s'%(startTime.year)70    endDate=''71    if endTime.day<10:72        endDate+='0%s'%(endTime.day)73    else:74        endDate+='%s'%(endTime.day)75    if endTime.month<10:76        endDate+='0%s'%(endTime.month)77    else:78        endDate+='%s'%(endTime.month)79    endDate+='%s'%(endTime.year)80 81    # File naming82    if verticalBehavior:83        outputFilename='results_stock_recruitment/opendrift_%s_%s_to_%s_vertical.nc'%(spawning_ground,startDate,endDate)84        animationFilename='figures/animation_%s_%s_to_%s_vertical.mp4'%(spawning_ground,startDate,endDate)85        plotFilename='figures/plot_%s_%s_to_%s_vertical.png'%(spawning_ground,startDate,endDate)86    else:87        outputFilename='results_stock_recruitment/opendrift_%s_%s_to_%s_novertical.nc'%(spawning_ground,startDate,endDate)88        animationFilename='figures/animation_%s_%s_to_%s_novertical.mp4'%(spawning_ground,startDate,endDate)89        plotFilename='figures/plot_%s_%s_to_%s_novertical.png'%(spawning_ground,startDate,endDate)90    if not os.path.exists('figures'):91        os.makedirs('figures')92    if not os.path.exists('results'):93        os.makedirs('results')94    return outputFilename, animationFilename, plotFilename95print(7)96   97def createAndRunSimulation(lowDepth,highDepth,endTime,shapefile,outputFilename,animationFilename,plotFilename,releaseParticles,pattern_svim,verticalBehavior,spawning_ground):98    # Setup a new simulation99    o = PelagicPlanktonDrift(loglevel=0)  # Set loglevel to 0 for debug information100    #o.max_speed = 10101    #######################102    # Preparing readers103    #######################104    reader_basemap = reader_basemap_landmask.Reader(105                       llcrnrlon=-7, llcrnrlat=50,106                       urcrnrlon=15, urcrnrlat=65,107                       resolution='i', projection='merc')108                       109    o.add_reader([reader_basemap]) #Note: Include because of issue with linearNDfast110    o.set_config('general:basemap_resolution', 'i')111    reader_svim = reader_ROMS_native.Reader(pattern_svim)#SVIM reader used to cover area outside svim reader112    o.add_reader([reader_svim]) #FORCE loaded for wind information113    114    num, spawningTimes = setupSeed(hoursBetweenTimestepInROMSFiles,startTime,endTime,startSpawningTime,endSpawningTime,releaseParticles)115 116    #######################117    #Adjusting configuration118    #######################119    if verticalBehavior:120        o.set_config('processes:turbulentmixing', True)121    else:122        o.set_config('processes:turbulentmixing',  False)123    o.set_config('turbulentmixing:diffusivitymodel','windspeed_Sundby1983')124    o.set_config('turbulentmixing:timestep', 4) # seconds125    o.set_config('turbulentmixing:verticalresolution', 2) # default is 1 meter, but since we have longer timestep we justify it126    if verticalBehavior:127        o.set_config('processes:verticaladvection', False)128    else:129        o.set_config('processes:verticaladvection', False)130    o.set_config('turbulentmixing:TSprofiles', False)131    #o.set_config('turbulentmixing:max_iterations', 400) #200 used in ms version132    o.set_config('drift:scheme', 'euler')133    o.set_config('general:coastline_action', 'previous') #Prevent stranding, jump back to previous position134    135    #######################136    # IBM configuration   137    #######################138    o.set_config('biology:constantIngestion', 0.75)139    o.set_config('biology:activemetabOn', 1)140    o.set_config('biology:cod', True)141    o.set_config('biology:haddock', False)142    o.set_config('biology:attenuationCoefficient',0.18)143    if verticalBehavior:144        o.set_config('biology:fractionOfTimestepSwimming',0.15) # Pause-swim behavior145    else:146        o.set_config('biology:fractionOfTimestepSwimming',0.00) # Pause-swim behavior147    o.set_config('biology:lowerStomachLim',0.3) #Min. stomach fullness needed to actively swim down148    149 150    #######################151    # Seed particles152    #######################153    #Fixed distribution in depth:154    def eq_div(N, i):155        return [] if i <= 0 else [N / i + 1] * (N % i) + [N / i] * (i - N % i)156    z_levels=range(lowDepth,highDepth+1,10) #levels of depth distribution157    for i, nums in enumerate(num):158        if nums <= 0:159            continue160        z_dist=eq_div(nums,len(z_levels)) #number of particles per level (approx. equal)161        print ("Running i=%s num=%s for spawning ground=%s"%(i,nums,spawning_ground))162        print ("Depths ",np.repeat(z_levels,z_dist))163        o.seed_from_shapefile(shapefile, nums, layername=None,featurenum=[1], z=np.repeat(z_levels,z_dist), time=spawningTimes[i])164    print ("Elements scheduled for %s : %s"%(spawning_ground,o.elements_scheduled))165    #########################166    # Run the model167    #########################168    o.run(end_time=endTime, time_step=timedelta(hours=1),time_step_output=timedelta(hours=12), 169          outfile=outputFilename,export_variables=['lon', 'lat', 'z','sea_water_temperature','length','weight','survival','sea_floor_depth_below_sea_level']) 170    print (o)171    #o.animation(background=['x_sea_water_velocity', 'y_sea_water_velocity'],filename=animationFilename)172print(8)173#########################174# SETUP175#########################176spawning_ground='viking'177lowDepth, highDepth = -50, 0 # in negative meters178verticalBehavior=False179for year in range(2010, 2011):180    print(year)181#Spawning period and number of particles per spawning ground:182    if spawning_ground=='south':183        startTime=datetime(year-1,12,15,1,00,00) 184        endTime=datetime(year,8,15,1,00,00)  185        startSpawningTime=startTime186        endSpawningTime=datetime(year,4,15,1,00,00)187        releaseParticles=32400 # Total number of particles to release (result with be approximately this number)188    elif spawning_ground=='northwest':189        startTime=datetime(year,1,1,1,00,00) 190        endTime=datetime(year,9,29,1,00,00) 191        startSpawningTime=startTime192        endSpawningTime=datetime(year,5,1,1,00,00)193        releaseParticles=22950194    elif spawning_ground=='viking':195        startTime=datetime(year,2,1,1,00,00) 196        endTime=datetime(year,9,29,1,00,00) 197        startSpawningTime=startTime198        endSpawningTime=datetime(year,5,15,1,00,00)199        releaseParticles=27000200    else:201        print ("spawning_ground is not correctly defined")202#Find forcing files needed based on months:203    startDay = datetime(startTime.year,startTime.month,1)204    endDay = datetime(endTime.year,endTime.month,1)205    month_range = [startDay]206    while startDay<endDay:207        startDay = startDay + relativedelta(months=1)208        month_range.append(startDay)209    pattern_svim=[]210    for i in month_range:211        x='/Volumes/Untitled/ROMS_files/SVIM_compressed/'+str(i.year)+'/'+'ocean_avg_'+str(i.year)+str(i.month).zfill(2)+'01.nc4'212        pattern_svim.append(x)213    hoursBetweenTimestepInROMSFiles=24214    shapefile='/Volumes/Untitled/Sustain/Spawning_grounds/Shapefiles_Gio_KINO/'+str(spawning_ground)+'.shp'215    print ("=> Using shapefile %s"%(shapefile))216    outputFilename, animationFilename, plotFilename = createOutputFilenames(startTime,endTime,verticalBehavior,spawning_ground)217    print ("Result files will be stored as:\nnetCDF=> %s\nmp4=> %s"%(outputFilename,animationFilename))218              ...

runspawningserver.py

Source:runspawningserver.py

1#!/usr/bin/env python2# Licensed to Cloudera, Inc. under one3# or more contributor license agreements.  See the NOTICE file4# distributed with this work for additional information5# regarding copyright ownership.  Cloudera, Inc. licenses this file6# to you under the Apache License, Version 2.0 (the7# "License"); you may not use this file except in compliance8# with the License.  You may obtain a copy of the License at9#10#     http://www.apache.org/licenses/LICENSE-2.011#12# Unless required by applicable law or agreed to in writing, software13# distributed under the License is distributed on an "AS IS" BASIS,14# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.15# See the License for the specific language governing permissions and16# limitations under the License.17import desktop.lib.eventlet_util18import logging19import os20import sys21from django.core.management.base import BaseCommand22from desktop import conf23import spawning.spawning_controller24from desktop.lib.daemon_utils import drop_privileges_if_necessary25from django.utils.translation import ugettext as _26SPAWNING_SERVER_HELP = r"""27  Run Hue using the Spawning WSGI server in asynchronous mode.28"""29SPAWNING_SERVER_OPTIONS = {30  'access_log_file': os.devnull,31  'backdoor': None,32  'chuid': None,33  'coverage': None,34  'daemonize': None,35  'deadman_timeout': 1,36  'factory': 'spawning.django_factory.config_factory',37  'host': conf.HTTP_HOST.get(),38  'max_age': None,39  'max_memory': 0,40  'no_keepalive': None,41  'pidfile': None,42  'port': conf.HTTP_PORT.get(),43  'processes': 1,44  'reload': None,45  'restart_args': None,46  'server_user': conf.SERVER_USER.get(),47  'server_group': conf.SERVER_GROUP.get(),48  'ssl_certificate': conf.SSL_CERTIFICATE.get(),49  'ssl_private_key': conf.SSL_PRIVATE_KEY.get(),50  'status_host': '',51  'status_port': 0,52  'stderr': None,53  'stdout': None,54  'sysinfo': None,55  'threads': 0,56  'verbose': None,57  'watch': None58}59LOG = logging.getLogger(__name__)60class Command(BaseCommand):61    help = _("Spawning Server for Hue.")62    def handle(self, *args, **options):63        from django.conf import settings64        from django.utils import translation65        if not conf.ENABLE_SERVER.get():66            LOG.info("Hue is configured to not start its own web server.")67            sys.exit(0)68        # Activate the current language, because it won't get activated later.69        try:70            translation.activate(settings.LANGUAGE_CODE)71        except AttributeError:72            pass73        runspawningserver()74    def usage(self, subcommand):75        return SPAWNING_SERVER_HELP76def runspawningserver():77  try:78    sock = spawning.spawning_controller.bind_socket(SPAWNING_SERVER_OPTIONS)79  except Exception, ex:80    LOG.error('Could not bind port %s: %s. Exiting' % (str(SPAWNING_SERVER_OPTIONS['port']), ex,))81    return82  drop_privileges_if_necessary(SPAWNING_SERVER_OPTIONS)83  factory = SPAWNING_SERVER_OPTIONS['factory']84  pos_args = ['desktop.settings']85  argv_str_format = '--factory=%s %s --port %s -s %d -t %d'86  argv_str =  argv_str_format % (SPAWNING_SERVER_OPTIONS['factory'],87                                 pos_args[0],88                                 SPAWNING_SERVER_OPTIONS['port'],89                                 SPAWNING_SERVER_OPTIONS['processes'],90                                 SPAWNING_SERVER_OPTIONS['threads'])91  factory_args = {92    'access_log_file': SPAWNING_SERVER_OPTIONS['access_log_file'],93    'args': pos_args,94    'argv_str': argv_str,95    'coverage': SPAWNING_SERVER_OPTIONS['coverage'],96    'deadman_timeout': SPAWNING_SERVER_OPTIONS['deadman_timeout'],97    'host': SPAWNING_SERVER_OPTIONS['host'],98    'max_age' : SPAWNING_SERVER_OPTIONS['max_age'],99    'no_keepalive' : SPAWNING_SERVER_OPTIONS['no_keepalive'],100    'num_processes': SPAWNING_SERVER_OPTIONS['processes'],101    'pidfile': SPAWNING_SERVER_OPTIONS['pidfile'],102    'port': SPAWNING_SERVER_OPTIONS['port'],103    'reload': SPAWNING_SERVER_OPTIONS['reload'],104    'ssl_certificate': SPAWNING_SERVER_OPTIONS['ssl_certificate'],105    'ssl_private_key': SPAWNING_SERVER_OPTIONS['ssl_private_key'],106    'status_host': SPAWNING_SERVER_OPTIONS['status_host'] or SPAWNING_SERVER_OPTIONS['host'],107    'status_port': SPAWNING_SERVER_OPTIONS['status_port'],108    'sysinfo': SPAWNING_SERVER_OPTIONS['sysinfo'],109    'threadpool_workers': SPAWNING_SERVER_OPTIONS['threads'],110    'verbose': SPAWNING_SERVER_OPTIONS['verbose'],111    'watch': SPAWNING_SERVER_OPTIONS['watch']112  }113  os.environ['HUE_SPAWNING'] = 'yes'114  spawning.spawning_controller.start_controller(sock, factory, factory_args)115if __name__ == '__main__':...

spawningTypes.py

Source:spawningTypes.py

1from AdaptivePELE.constants import blockNames2class SPAWNING_TYPES:3    sameWeight, inverselyProportional, epsilon, simulatedAnnealing, FAST, variableEpsilon, UCB, independent, REAP, null, independentMetric, ProbabilityMSMCalculator, MetastabilityMSMCalculator, UncertaintyMSMCalculator, IndependentMSMCalculator = list(range(15))4SPAWNING_TYPE_TO_STRING_DICTIONARY = {5    SPAWNING_TYPES.independent: blockNames.StringSpawningTypes.independent,6    SPAWNING_TYPES.sameWeight: blockNames.StringSpawningTypes.sameWeight,7    SPAWNING_TYPES.inverselyProportional: blockNames.StringSpawningTypes.inverselyProportional,8    SPAWNING_TYPES.epsilon: blockNames.StringSpawningTypes.epsilon,9    SPAWNING_TYPES.FAST: blockNames.StringSpawningTypes.fast,10    SPAWNING_TYPES.variableEpsilon: blockNames.StringSpawningTypes.variableEpsilon,11    SPAWNING_TYPES.simulatedAnnealing: blockNames.StringSpawningTypes.simulatedAnnealing,12    SPAWNING_TYPES.UCB: blockNames.StringSpawningTypes.UCB,13    SPAWNING_TYPES.REAP: blockNames.StringSpawningTypes.REAP,14    SPAWNING_TYPES.null: blockNames.StringSpawningTypes.null,15    SPAWNING_TYPES.independentMetric: blockNames.StringSpawningTypes.independentMetric,16    SPAWNING_TYPES.ProbabilityMSMCalculator: blockNames.StringSpawningTypes.ProbabilityMSMCalculator,17    SPAWNING_TYPES.MetastabilityMSMCalculator: blockNames.StringSpawningTypes.MetastabilityMSMCalculator,18    SPAWNING_TYPES.UncertaintyMSMCalculator: blockNames.StringSpawningTypes.UncertaintyMSMCalculator,19    SPAWNING_TYPES.IndependentMSMCalculator: blockNames.StringSpawningTypes.IndependentMSMCalculator20}21MSMSpawning = set([blockNames.StringSpawningTypes.ProbabilityMSMCalculator, blockNames.StringSpawningTypes.MetastabilityMSMCalculator, blockNames.StringSpawningTypes.UncertaintyMSMCalculator, blockNames.StringSpawningTypes.IndependentMSMCalculator])22class EPSILON_VARIATION_TYPES:23    linearVariation, contactsVariation = list(range(2))24EPSILON_VARIATION_TYPE_TO_STRING_DICTIONARY = {25    EPSILON_VARIATION_TYPES.linearVariation: blockNames.VariableEpsilonTypes.linearVariation,26    EPSILON_VARIATION_TYPES.contactsVariation: blockNames.VariableEpsilonTypes.contactsVariation,27}...

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