from lenstools.utils import MPIWhirlPool
from lenstools.pipeline.simulation import SimulationBatch
#Get the resource to compress
def shear(model, batch):
full_path = model.collections[0].getCatalog("Shear").storage_subdir
rel_path = os.path.relpath(full_path, batch.environment.storage)
return rel_path
#MPIPool
try:
pool = MPIWhirlPool()
except:
pool = None
#Current simulation batch
batch = SimulationBatch.current()
models = batch.models
archive_names = ["archive/{0}.tar.gz".format(m.cosmo_id) for m in models]
batch.archive(archive_names,
pool=pool,
resource=shear,
chunk_size=1,
batch=batch)
pool.comm.Barrier()
catalog = CatalogSettings.read("../catalog.ini")
zmax = 3.1
box_size_Mpc_over_h = 240.0
nside = 512
lens_thickness_Mpc = 80.0
#NGenIC
ngenic.GlassFile = lenstools.data("dummy_glass_little_endian.dat")
#Gadget
gadget2.NumFilesPerSnapshot = 16
#Init batch
if "--git" in sys.argv:
batch = SimulationBatch.current(syshandler=git)
else:
batch = SimulationBatch.current()
if "--tree" in sys.argv:
#Add all the models,collections and one realization
seed = np.random.randint(10000000)
p = np.load("../../data/Om-si8.npy")
d = list()
for Om,si8 in p:
#Lay down directory tree
cosmo = LensToolsCosmology(Om0=Om,Ode0=1-Om,w0=-1.,sigma8=si8)
#Get the resource to compress
def shear(model,batch,search_string):
full_path = model[search_string].storage
rel_path = os.path.relpath(full_path,batch.environment.storage)
return rel_path
#MPIPool
try:
pool = MPIWhirlPool()
except:
pool = None
#Parse command line arguments
parser = argparse.ArgumentParser()
parser.add_argument("-e","--environment",dest="env_file",action="store",type=str,default="environment.ini",help="environment option file")
parser.add_argument("-a","--archive",dest="archive",action="store",type=str,default="archive/{0}.tar.gz",help="archive name format")
parser.add_argument("-s","--search",dest="search",action="store",type=str,default="c0C0",help="search string that when dialed points to the resource")
cmd_args = parser.parse_args()
#Current simulation batch
batch = SimulationBatch.current(cmd_args.env_file)
models = batch.models
archive_names = [cmd_args.archive.format(m.cosmo_id) for m in models]
batch.archive(archive_names,pool=pool,resource=shear,chunk_size=1,batch=batch,search_string=cmd_args.search)
pool.comm.Barrier()
zmax = 3.1
box_size_Mpc_over_h = 260.0
nside = 512
lens_thickness_Mpc = 120.0
#NGenIC
ngenic.GlassFile = lenstools.data("dummy_glass_little_endian.dat")
#Gadget
gadget2.NumFilesPerSnapshot = 24
#Init batch
if "--git" in sys.argv:
batch = SimulationBatch.current(syshandler=git)
if batch is None:
environment = EnvironmentSettings(home="/Users/andreapetri/Documents/Columbia/Simulations/LSST100parameters/Test/Home",storage="/Users/andreapetri/Documents/Columbia/Simulations/LSST100parameters/Test/Storage")
batch = SimulationBatch(environment,syshandler=git)
else:
batch = SimulationBatch.current()
if batch is None:
environment = EnvironmentSettings(home="/Users/andreapetri/Documents/Columbia/Simulations/LSST100parameters/Test/Home",storage="/Users/andreapetri/Documents/Columbia/Simulations/LSST100parameters/Test/Storage")
batch = SimulationBatch(environment)
if "--tree" in sys.argv:
#Add all the models,collections and one realization
seed = 5616559
#!/usr/bin/env python-mpi import os from lenstools.utils import MPIWhirlPool from lenstools.pipeline.simulation import SimulationBatch #MPIPool try: pool = MPIWhirlPool() except: pool = None #Current simulation batch batch = SimulationBatch.current() batch.unpack(where='/scratch3/scratchdirs/apetri/archive',pool=pool) pool.comm.Barrier()
from operator import add
from functools import reduce
import numpy as np
import astropy.units as u
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
from lenstools.pipeline.simulation import SimulationBatch
from lenstools import ConvergenceMap,GaussianNoiseGenerator,Ensemble
from lenstools.statistics.constraints import FisherAnalysis
#Simulation batch handler
batch = SimulationBatch.current("/Users/andreapetri/Documents/Columbia/Simulations/DEBatch/environment.ini")
batchCov = SimulationBatch.current("/Users/andreapetri/Documents/Columbia/Simulations/CovarianceBatch/environment.ini")
models = batch.models
fiducial = batch.getModel("Om0.260_Ode0.740_w-1.000_wa0.000_si0.800")
variations = (
map(lambda m:batch.getModel(m),["Om0.290_Ode0.710_w-1.000_wa0.000_si0.800","Om0.260_Ode0.740_w-0.800_wa0.000_si0.800","Om0.260_Ode0.740_w-1.000_wa0.000_si0.900"]),
map(lambda m:batch.getModel(m),["Om0.230_Ode0.770_w-1.000_wa0.000_si0.800","Om0.260_Ode0.740_w-1.200_wa0.000_si0.800","Om0.260_Ode0.740_w-1.000_wa0.000_si0.700"])
)
plab = { "Om":r"$\Omega_m$", "w0":r"$w_0$", "wa":r"$w_a$", "si8":r"$\sigma_8$" }
