sys.path.append("..")
from barry.config import setup
from barry.models import PowerNoda2019
from barry.datasets import PowerSpectrum_SDSS_DR12_Z061_NGC
from barry.postprocessing import BAOExtractor
from barry.cosmology.camb_generator import getCambGenerator
from barry.samplers import DynestySampler
from barry.fitter import Fitter
if __name__ == "__main__":
pfn, dir_name, file = setup(__file__)
c = getCambGenerator()
r_s = c.get_data()[0]
postprocess = BAOExtractor(r_s)
sampler = DynestySampler(temp_dir=dir_name)
fitter = Fitter(dir_name)
for r in [True, False]:
rt = "Recon" if r else "Prerecon"
data = PowerSpectrum_SDSS_DR12_Z061_NGC(recon=r,
postprocess=postprocess)
n = PowerNoda2019(postprocess=postprocess,
recon=r,
nonlinear_type="spt")
n2 = PowerNoda2019(postprocess=postprocess,
recon=r,
nonlinear_type="halofit")
from barry.utils import weighted_avg_and_std
from barry.datasets.dataset_power_spectrum import PowerSpectrum_DESIMockChallenge0_Z01
from barry.cosmology.camb_generator import getCambGenerator
from barry.postprocessing import BAOExtractor
from barry.config import setup
from barry.models import PowerBeutler2017
from barry.samplers import DynestySampler
from barry.fitter import Fitter
from barry.models.model import Correction
if __name__ == "__main__":
pfn, dir_name, file = setup(__file__)
c = getCambGenerator()
r_s = c.get_data()["r_s"]
p = BAOExtractor(r_s)
sampler = DynestySampler(temp_dir=dir_name, nlive=1000)
fitter = Fitter(dir_name)
cs = ["#262232", "#116A71", "#48AB75", "#D1E05B"]
for r in [False]:
t = "Recon" if r else "Prerecon"
# Fix sigma_nl for one of the Beutler models
model = PowerBeutler2017(recon=r, isotropic=False, correction=Correction.NONE)
model.set_default("sigma_nl_par", 10.9)
model.set_default("sigma_nl_perp", 5.98)
model.set_fix_params(["om", "sigma_nl_par", "sigma_nl_perp"])
from barry.datasets import PowerSpectrum_SDSS_DR12_Z061_NGC
from barry.postprocessing import BAOExtractor
from barry.cosmology.camb_generator import CambGenerator
from barry.samplers import DynestySampler
from barry.fitter import Fitter
if __name__ == "__main__":
pfn, dir_name, file = setup(__file__)
c = CambGenerator()
r_s = c.get_data()[0]
fitter = Fitter(dir_name)
ps = [
BAOExtractor(r_s, extra_ks=(0.095, 0.13)),
BAOExtractor(r_s, extra_ks=(0.095, 0.14)),
BAOExtractor(r_s, extra_ks=(0.095, 0.15)),
BAOExtractor(r_s, extra_ks=(0.095, 0.16)),
BAOExtractor(r_s, extra_ks=(0.095, 0.17)),
BAOExtractor(r_s, extra_ks=(0.095, 0.18)),
BAOExtractor(r_s, extra_ks=(0.095, 0.19)),
BAOExtractor(r_s, extra_ks=(0.095, 0.20)),
BAOExtractor(r_s, extra_ks=(0.095, 0.21)),
BAOExtractor(r_s, extra_ks=(0.095, 0.22)),
BAOExtractor(r_s, extra_ks=(0.095, 0.23)),
BAOExtractor(r_s, extra_ks=(0.095, 0.24)),
]
recon = True
for p in ps:
cov[i, j] = pk_cov[i, j]
return cov
if __name__ == "__main__":
import seaborn as sb
import matplotlib.pyplot as plt
logging.basicConfig(
level=logging.INFO,
format="[%(levelname)7s |%(funcName)18s] %(message)s")
logging.getLogger("matplotlib").setLevel(logging.WARNING)
camb = getCambGenerator()
r_s = c.get_data()[0]
extractor = BAOExtractor(r_s, reorder=False)
extractor2 = PureBAOExtractor(r_s)
step_size = 1
mink = 0.02
maxk = 0.3
data_raw = PowerSpectrum_SDSS_DR12_Z061_NGC(step_size=step_size,
fake_diag=False,
min_k=0.0,
max_k=0.32)
data2 = PowerSpectrum_SDSS_DR12_Z061_NGC(postprocess=extractor,
step_size=step_size,
min_k=mink,
max_k=maxk)
ks = data_raw.ks
import logging
from barry.cosmology.camb_generator import getCambGenerator
from barry.datasets import PowerSpectrum_SDSS_DR12_Z061_NGC
from barry.models import PowerNoda2019
from barry.postprocessing import BAOExtractor
if __name__ == "__main__":
logging.basicConfig(
level=logging.DEBUG,
format="[%(levelname)7s |%(funcName)20s] %(message)s")
logging.getLogger("matplotlib").setLevel(logging.ERROR)
c = getCambGenerator()
r_s = c.get_data()["r_s"]
postprocess = BAOExtractor(r_s, mink=0.15)
for recon in [True, False]:
model1 = PowerNoda2019(recon=recon,
name=f"Noda2019, recon={recon}",
postprocess=postprocess,
fix_params=["om", "f", "gamma"])
dataset1 = PowerSpectrum_SDSS_DR12_Z061_NGC(recon=recon,
postprocess=postprocess,
min_k=0.03,
max_k=0.15)
data1 = dataset1.get_data()
print(list(data1[0].keys()))
print(data1[0]["ks_output"])
exit()
from barry.datasets import PowerSpectrum_SDSS_DR12_Z061_NGC
from barry.postprocessing import BAOExtractor
from barry.cosmology.camb_generator import CambGenerator
from barry.samplers import DynestySampler
from barry.fitter import Fitter
if __name__ == "__main__":
pfn, dir_name, file = setup(__file__)
c = CambGenerator()
r_s = c.get_data()[0]
fitter = Fitter(dir_name)
ps = [
BAOExtractor(r_s, mink=0.03),
BAOExtractor(r_s, mink=0.04),
BAOExtractor(r_s, mink=0.05),
BAOExtractor(r_s, mink=0.06),
BAOExtractor(r_s, mink=0.07)
]
recon = True
for p in ps:
n = f"$k = {p.mink:0.2f}\, h / {{\\rm Mpc}}$"
model = PowerNoda2019(postprocess=p, recon=recon)
data = PowerSpectrum_SDSS_DR12_Z061_NGC(min_k=0.02,
max_k=0.30,
postprocess=p,
recon=recon)
fitter.add_model_and_dataset(model, data, name=n)
pk1d = integrate.simps(pk_smooth * (kaiser_prefac ** 2 + pk_nonlinear), self.mu, axis=0)
else:
# Compute the BAO damping/propagator
propagator = self.get_damping(growth, om, gamma)
pk1d = integrate.simps(pk_smooth * ((1.0 + pk_ratio * propagator) * kaiser_prefac ** 2 + pk_nonlinear), self.mu, axis=0)
return ks, pk1d
if __name__ == "__main__":
import sys
sys.path.append("../..")
from barry.datasets.dataset_power_spectrum import PowerSpectrum_SDSS_DR12_Z061_NGC
from barry.postprocessing import BAOExtractor
from barry.config import setup_logging
setup_logging()
postprocess = BAOExtractor(147.6)
print("Checking pre-recon")
dataset = PowerSpectrum_SDSS_DR12_Z061_NGC(recon=False, postprocess=postprocess)
model_pre = PowerNoda2019(recon=False, postprocess=postprocess)
model_pre.sanity_check(dataset)
print("Checking post-recon")
dataset = PowerSpectrum_SDSS_DR12_Z061_NGC(recon=True, postprocess=postprocess)
model_post = PowerNoda2019(recon=True, postprocess=postprocess)
model_post.sanity_check(dataset)
from barry.config import setup
from barry.models import PowerNoda2019
from barry.datasets import PowerSpectrum_SDSS_DR12_Z061_NGC
from barry.postprocessing import BAOExtractor, PureBAOExtractor
from barry.cosmology.camb_generator import getCambGenerator
from barry.samplers import DynestySampler
from barry.fitter import Fitter
import numpy as np
if __name__ == "__main__":
pfn, dir_name, file = setup(__file__)
c = getCambGenerator()
r_s = c.get_data()["r_s"]
postprocess = BAOExtractor(r_s)
r = True
model = PowerNoda2019(postprocess=postprocess, recon=r, name="")
mink = 0.03
maxk = 0.30
datas = [
PowerSpectrum_SDSS_DR12_Z061_NGC(name="Mock covariance",
recon=r,
min_k=mink,
max_k=maxk,
postprocess=postprocess),
PowerSpectrum_SDSS_DR12_Z061_NGC(name="Nishimichi, full",
recon=r,
min_k=mink,
max_k=maxk,
postprocess=postprocess),
from barry.config import setup
from barry.models import PowerSeo2016, PowerBeutler2017, PowerDing2018
from barry.samplers import DynestySampler, EnsembleSampler
from barry.fitter import Fitter
from barry.models.model import Correction
# Check to see if including the hexadecapole or higher order multipoles gives tighter constraints on BAO parameters
# when fitting the mock average
if __name__ == "__main__":
pfn, dir_name, file = setup(__file__)
# dir_name = dir_name + "nlive_1500/"
c = getCambGenerator()
r_s = c.get_data()["r_s"]
p = BAOExtractor(r_s)
sampler = DynestySampler(temp_dir=dir_name, nlive=500)
# sampler = EnsembleSampler(temp_dir=dir_name, num_steps=5000)
fitter = Fitter(dir_name)
cs = ["#262232", "#116A71", "#48AB75", "#D1E05B"]
for r in [True]:
t = "Recon" if r else "Prerecon"
ls = "-" # if r else "--"
d_quad = PowerSpectrum_Beutler2019(recon=r,
isotropic=False,
fit_poles=[0, 2],
reduce_cov_factor=np.sqrt(2000.0))
d_odd = PowerSpectrum_Beutler2019(recon=r,