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Update examples and fixing the Pv2 test #166

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Oct 17, 2024
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Update examples and fixing the Pv2 test #166

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87e0824
Fixing GW150914 Pv2 test
tsunhopang Oct 16, 2024
54cb2e1
Update GW150914 PhenomD example
tsunhopang Oct 16, 2024
ae9204a
Update GW170817 PhenomD
tsunhopang Oct 16, 2024
38de2ac
Fixing the Pv2 test again
tsunhopang Oct 16, 2024
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186 changes: 83 additions & 103 deletions example/GW150914_IMRPhenomD.py
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Original file line number Diff line number Diff line change
@@ -1,22 +1,29 @@
import time

import jax
import jax.numpy as jnp

from jimgw.jim import Jim
from jimgw.jim import Jim
from jimgw.prior import (
CombinePrior,
UniformPrior,
CosinePrior,
SinePrior,
PowerLawPrior,
UniformSpherePrior,
)
from jimgw.single_event.detector import H1, L1
from jimgw.single_event.likelihood import TransientLikelihoodFD
from jimgw.single_event.waveform import RippleIMRPhenomD
from jimgw.transforms import BoundToUnbound
from jimgw.single_event.transforms import (
ComponentMassesToChirpMassSymmetricMassRatioTransform,
SkyFrameToDetectorFrameSkyPositionTransform,
ComponentMassesToChirpMassMassRatioTransform,
SphereSpinToCartesianSpinTransform,
MassRatioToSymmetricMassRatioTransform,
DistanceToSNRWeightedDistanceTransform,
GeocentricArrivalTimeToDetectorArrivalTimeTransform,
GeocentricArrivalPhaseToDetectorArrivalPhaseTransform,
)
from jimgw.single_event.utils import Mc_q_to_m1_m2
from flowMC.strategy.optimization import optimization_Adam
Expand All @@ -27,136 +34,110 @@
########## First we grab data #############
###########################################

total_time_start = time.time()

# first, fetch a 4s segment centered on GW150914
gps = 1126259462.4
duration = 4
post_trigger_duration = 2
start_pad = duration - post_trigger_duration
end_pad = post_trigger_duration
start = gps - 2
end = gps + 2
fmin = 20.0
fmax = 1024.0

ifos = [H1, L1]

for ifo in ifos:
ifo.load_data(gps, start_pad, end_pad, fmin, fmax, psd_pad=16, tukey_alpha=0.2)
H1.load_data(gps, 2, 2, fmin, fmax, psd_pad=16, tukey_alpha=0.2)
L1.load_data(gps, 2, 2, fmin, fmax, psd_pad=16, tukey_alpha=0.2)

waveform = RippleIMRPhenomD(f_ref=20)

###########################################
########## Set up priors ##################
###########################################

prior = []

# Mass prior
M_c_min, M_c_max = 10.0, 80.0
eta_min, eta_max = 0.2, 0.25
# m_1_prior = UniformPrior(Mc_q_to_m1_m2(M_c_min, q_max)[0], Mc_q_to_m1_m2(M_c_max, q_min)[0], parameter_names=["m_1"])
# m_2_prior = UniformPrior(Mc_q_to_m1_m2(M_c_min, q_min)[1], Mc_q_to_m1_m2(M_c_max, q_max)[1], parameter_names=["m_2"])
q_min, q_max = 0.125, 1.0
Mc_prior = UniformPrior(M_c_min, M_c_max, parameter_names=["M_c"])
eta_prior = UniformPrior(eta_min, eta_max, parameter_names=["eta"])
s1z_prior = UniformPrior(-1.0, 1.0, parameter_names=["s1_z"])
s2z_prior = UniformPrior(-1.0, 1.0, parameter_names=["s2_z"])
q_prior = UniformPrior(q_min, q_max, parameter_names=["q"])

prior = prior + [Mc_prior, q_prior]

# Spin prior
s1_prior = UniformPrior(-1.0, 1.0, parameter_names=["s1_z"])
s2_prior = UniformPrior(-1.0, 1.0, parameter_names=["s2_z"])
iota_prior = SinePrior(parameter_names=["iota"])

prior = prior + [
s1_prior,
s2_prior,
iota_prior,
]

# Extrinsic prior
dL_prior = PowerLawPrior(1.0, 2000.0, 2.0, parameter_names=["d_L"])
t_c_prior = UniformPrior(-0.05, 0.05, parameter_names=["t_c"])
phase_c_prior = UniformPrior(0.0, 2 * jnp.pi, parameter_names=["phase_c"])
iota_prior = SinePrior(parameter_names=["iota"])
psi_prior = UniformPrior(0.0, jnp.pi, parameter_names=["psi"])
ra_prior = UniformPrior(0.0, 2 * jnp.pi, parameter_names=["ra"])
dec_prior = CosinePrior(parameter_names=["dec"])

prior = CombinePrior(
[
Mc_prior,
eta_prior,
s1z_prior,
s2z_prior,
dL_prior,
t_c_prior,
phase_c_prior,
iota_prior,
psi_prior,
ra_prior,
dec_prior,
]
)
prior = prior + [
dL_prior,
t_c_prior,
phase_c_prior,
psi_prior,
ra_prior,
dec_prior,
]

prior = CombinePrior(prior)

# Defining Transforms

sample_transforms = [
# ComponentMassesToChirpMassMassRatioTransform,
BoundToUnbound(
name_mapping=(["M_c"], ["M_c_unbounded"]),
original_lower_bound=M_c_min,
original_upper_bound=M_c_max,
),
BoundToUnbound(
name_mapping=(["eta"], ["eta_unbounded"]),
original_lower_bound=eta_min,
original_upper_bound=eta_max,
),
BoundToUnbound(
name_mapping=(["s1_z"], ["s1_z_unbounded"]),
original_lower_bound=-1.0,
original_upper_bound=1.0,
),
BoundToUnbound(
name_mapping=(["s2_z"], ["s2_z_unbounded"]),
original_lower_bound=-1.0,
original_upper_bound=1.0,
),
BoundToUnbound(
name_mapping=(["d_L"], ["d_L_unbounded"]),
original_lower_bound=1.0,
original_upper_bound=2000.0,
),
BoundToUnbound(
name_mapping=(["t_c"], ["t_c_unbounded"]),
original_lower_bound=-0.05,
original_upper_bound=0.05,
),
BoundToUnbound(
name_mapping=(["phase_c"], ["phase_c_unbounded"]),
original_lower_bound=0.0,
original_upper_bound=2 * jnp.pi,
),
BoundToUnbound(
name_mapping=(["iota"], ["iota_unbounded"]),
original_lower_bound=0.0,
original_upper_bound=jnp.pi,
),
BoundToUnbound(
name_mapping=(["psi"], ["psi_unbounded"]),
original_lower_bound=0.0,
original_upper_bound=jnp.pi,
),
DistanceToSNRWeightedDistanceTransform(gps_time=gps, ifos=ifos, dL_min=dL_prior.xmin, dL_max=dL_prior.xmax),
GeocentricArrivalPhaseToDetectorArrivalPhaseTransform(gps_time=gps, ifo=ifos[0]),
GeocentricArrivalTimeToDetectorArrivalTimeTransform(tc_min=t_c_prior.xmin, tc_max=t_c_prior.xmax, gps_time=gps, ifo=ifos[0]),
SkyFrameToDetectorFrameSkyPositionTransform(gps_time=gps, ifos=ifos),
BoundToUnbound(
name_mapping=(["zenith"], ["zenith_unbounded"]),
original_lower_bound=0.0,
original_upper_bound=jnp.pi,
),
BoundToUnbound(
name_mapping=(["azimuth"], ["azimuth_unbounded"]),
original_lower_bound=0.0,
original_upper_bound=2 * jnp.pi,
),
BoundToUnbound(name_mapping = (["M_c"], ["M_c_unbounded"]), original_lower_bound=M_c_min, original_upper_bound=M_c_max),
BoundToUnbound(name_mapping = (["q"], ["q_unbounded"]), original_lower_bound=q_min, original_upper_bound=q_max),
BoundToUnbound(name_mapping = (["s1_z"], ["s1_z_unbounded"]) , original_lower_bound=-1.0, original_upper_bound=1.0),
BoundToUnbound(name_mapping = (["s2_z"], ["s2_z_unbounded"]) , original_lower_bound=-1.0, original_upper_bound=1.0),
BoundToUnbound(name_mapping = (["iota"], ["iota_unbounded"]) , original_lower_bound=0.0, original_upper_bound=jnp.pi),
BoundToUnbound(name_mapping = (["phase_det"], ["phase_det_unbounded"]), original_lower_bound=0.0, original_upper_bound=2 * jnp.pi),
BoundToUnbound(name_mapping = (["psi"], ["psi_unbounded"]), original_lower_bound=0.0, original_upper_bound=jnp.pi),
BoundToUnbound(name_mapping = (["zenith"], ["zenith_unbounded"]), original_lower_bound=0.0, original_upper_bound=jnp.pi),
BoundToUnbound(name_mapping = (["azimuth"], ["azimuth_unbounded"]), original_lower_bound=0.0, original_upper_bound=2 * jnp.pi),
]

likelihood_transforms = [
# ComponentMassesToChirpMassSymmetricMassRatioTransform,
MassRatioToSymmetricMassRatioTransform,
]


likelihood = TransientLikelihoodFD(
ifos,
waveform=RippleIMRPhenomD(),
trigger_time=gps,
duration=4,
post_trigger_duration=2,
[H1, L1], waveform=waveform, trigger_time=gps, duration=4, post_trigger_duration=2
)


mass_matrix = jnp.eye(11)
mass_matrix = mass_matrix.at[1, 1].set(1e-3)
mass_matrix = mass_matrix.at[5, 5].set(1e-3)
local_sampler_arg = {"step_size": mass_matrix * 3e-3}
mass_matrix = jnp.eye(prior.n_dim)
# mass_matrix = mass_matrix.at[1, 1].set(1e-3)
# mass_matrix = mass_matrix.at[9, 9].set(1e-3)
local_sampler_arg = {"step_size": mass_matrix * 1e-3}

Adam_optimizer = optimization_Adam(n_steps=3000, learning_rate=0.01, noise_level=1)

n_epochs = 30
n_loop_training = 20
learning_rate = 1e-4
import optax

n_epochs = 20
n_loop_training = 100
total_epochs = n_epochs * n_loop_training
start = total_epochs // 10
learning_rate = optax.polynomial_schedule(
1e-3, 1e-4, 4.0, total_epochs - start, transition_begin=start
)

jim = Jim(
likelihood,
Expand All @@ -175,13 +156,12 @@
momentum=0.9,
batch_size=30000,
use_global=True,
keep_quantile=0.0,
train_thinning=1,
output_thinning=10,
local_sampler_arg=local_sampler_arg,
strategies=[Adam_optimizer, "default"],
verbose=True,
# strategies=[Adam_optimizer,"default"],
)


jim.sample(jax.random.PRNGKey(42))
# jim.get_samples()
# jim.print_summary()
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