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lscsoft
bilby
Commits
7a033493
Commit
7a033493
authored
6 years ago
by
Colm Talbot
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Merge branch 'master' into update_examples
parents
f9a0b82c
7c8fe044
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!228
Update examples
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2 changed files
bilby/core/result.py
+9
-3
9 additions, 3 deletions
bilby/core/result.py
examples/injection_examples/australian_detector.py
+104
-0
104 additions, 0 deletions
examples/injection_examples/australian_detector.py
with
113 additions
and
3 deletions
bilby/core/result.py
+
9
−
3
View file @
7a033493
...
...
@@ -9,7 +9,7 @@ import matplotlib.pyplot as plt
from
collections
import
OrderedDict
from
.
import
utils
from
.utils
import
logger
from
.utils
import
logger
,
infer_parameters_from_function
from
.prior
import
PriorSet
,
DeltaFunction
...
...
@@ -502,16 +502,22 @@ class Result(dict):
from the outdir and label attributes.
"""
# Determine model_posterior, the subset of the full posterior which
# should be passed into the model
model_keys
=
infer_parameters_from_function
(
model
)
model_posterior
=
self
.
posterior
[
model_keys
]
xsmooth
=
np
.
linspace
(
np
.
min
(
x
),
np
.
max
(
x
),
npoints
)
fig
,
ax
=
plt
.
subplots
()
logger
.
info
(
'
Plotting {} draws
'
.
format
(
ndraws
))
for
_
in
range
(
ndraws
):
s
=
self
.
posterior
.
sample
().
to_dict
(
'
records
'
)[
0
]
s
=
model_
posterior
.
sample
().
to_dict
(
'
records
'
)[
0
]
ax
.
plot
(
xsmooth
,
model
(
xsmooth
,
**
s
),
alpha
=
0.25
,
lw
=
0.1
,
color
=
'
r
'
,
label
=
draws_label
)
if
all
(
~
np
.
isnan
(
self
.
posterior
.
log_likelihood
)):
logger
.
info
(
'
Plotting maximum likelihood
'
)
s
=
self
.
posterior
.
ix
[
self
.
posterior
.
log_likelihood
.
idxmax
()]
s
=
model_
posterior
.
ix
[
self
.
posterior
.
log_likelihood
.
idxmax
()]
ax
.
plot
(
xsmooth
,
model
(
xsmooth
,
**
s
),
lw
=
1
,
color
=
'
k
'
,
label
=
maxl_label
)
...
...
This diff is collapsed.
Click to expand it.
examples/injection_examples/australian_detector.py
0 → 100644
+
104
−
0
View file @
7a033493
#!/bin/python
"""
Tutorial to demonstrate a new interferometer
We place a new instrument in Gingin, with an A+ sensitivity in a network of A+
interferometers at Hanford and Livingston
"""
from
__future__
import
division
,
print_function
import
numpy
as
np
import
bilby
,
gwinc
# Set the duration and sampling frequency of the data segment that we're going to inject the signal into
duration
=
4.
sampling_frequency
=
2048.
# Specify the output directory and the name of the simulation.
outdir
=
'
outdir
'
label
=
'
australian_detector
'
bilby
.
core
.
utils
.
setup_logger
(
outdir
=
outdir
,
label
=
label
)
# Set up a random seed for result reproducibility. This is optional!
np
.
random
.
seed
(
88170232
)
# create a new detector using a PyGwinc sensitivity curve
frequencies
=
np
.
logspace
(
0
,
3
,
1000
)
gwinc_detector
=
gwinc
.
load_ifo
(
'
A+
'
)
gwinc_detector
=
gwinc
.
precompIFO
(
frequencies
,
gwinc_detector
)
gwinc_noises
=
gwinc
.
noise_calc
(
frequencies
,
gwinc_detector
)
Aplus_psd
=
gwinc_noises
[
'
Total
'
]
# Set up the detector as a four-kilometer detector in Gingin
# The location of this detector is not defined in Bilby, so we need to add it
AusIFO
=
bilby
.
gw
.
detector
.
Interferometer
(
power_spectral_density
=
bilby
.
gw
.
detector
.
PowerSpectralDensity
(
frequency_array
=
frequencies
,
psd_array
=
Aplus_psd
),
name
=
'
AusIFO
'
,
length
=
4
,
minimum_frequency
=
min
(
frequencies
),
maximum_frequency
=
max
(
frequencies
),
latitude
=-
31.34
,
longitude
=
115.91
,
elevation
=
0.
,
xarm_azimuth
=
2.
,
yarm_azimuth
=
125.
)
# Set up two other detectors at Hanford and Livingston
interferometers
=
bilby
.
gw
.
detector
.
InterferometerList
([
'
H1
'
,
'
L1
'
])
for
interferometer
in
interferometers
:
interferometer
.
power_spectral_density
=
bilby
.
gw
.
detector
.
PowerSpectralDensity
(
frequency_array
=
frequencies
,
psd_array
=
Aplus_psd
)
# append the Australian detector to the list of other detectors
interferometers
.
append
(
AusIFO
)
# Inject a gravitational-wave signal into the network
# as we're using a three-detector network of A+, we inject a GW150914-like
# signal at 4 Gpc
injection_parameters
=
dict
(
mass_1
=
36.
,
mass_2
=
29.
,
a_1
=
0.4
,
a_2
=
0.3
,
tilt_1
=
0.5
,
tilt_2
=
1.0
,
phi_12
=
1.7
,
phi_jl
=
0.3
,
luminosity_distance
=
4000.
,
iota
=
0.4
,
psi
=
2.659
,
phase
=
1.3
,
geocent_time
=
1126259642.413
,
ra
=
1.375
,
dec
=
0.2108
)
# Fixed arguments passed into the source model
waveform_arguments
=
dict
(
waveform_approximant
=
'
IMRPhenomPv2
'
,
reference_frequency
=
50.
)
# Create the waveform_generator using a LAL BinaryBlackHole source function
waveform_generator
=
bilby
.
gw
.
WaveformGenerator
(
duration
=
duration
,
sampling_frequency
=
sampling_frequency
,
frequency_domain_source_model
=
bilby
.
gw
.
source
.
lal_binary_black_hole
,
waveform_arguments
=
waveform_arguments
)
start_time
=
injection_parameters
[
'
geocent_time
'
]
+
2
-
duration
# inject the signal into the interferometers
for
interferometer
in
interferometers
:
interferometer
.
set_strain_data_from_power_spectral_density
(
sampling_frequency
=
sampling_frequency
,
duration
=
duration
)
interferometer
.
inject_signal
(
parameters
=
injection_parameters
,
waveform_generator
=
waveform_generator
)
## plot the data for sanity
signal
=
interferometer
.
get_detector_response
(
waveform_generator
.
frequency_domain_strain
(),
injection_parameters
)
interferometer
.
plot_data
(
signal
=
signal
,
outdir
=
outdir
,
label
=
label
)
# set up priors
priors
=
bilby
.
gw
.
prior
.
BBHPriorSet
()
for
key
in
[
'
a_1
'
,
'
a_2
'
,
'
tilt_1
'
,
'
tilt_2
'
,
'
phi_12
'
,
'
phi_jl
'
,
'
psi
'
,
'
geocent_time
'
,
'
phase
'
]:
priors
[
key
]
=
injection_parameters
[
key
]
# Initialise the likelihood by passing in the interferometer data (IFOs) and the waveoform generator
likelihood
=
bilby
.
gw
.
GravitationalWaveTransient
(
interferometers
=
interferometers
,
waveform_generator
=
waveform_generator
,
time_marginalization
=
False
,
phase_marginalization
=
False
,
distance_marginalization
=
False
,
prior
=
priors
)
result
=
bilby
.
run_sampler
(
likelihood
=
likelihood
,
priors
=
priors
,
npoints
=
1000
,
injection_parameters
=
injection_parameters
,
outdir
=
outdir
,
label
=
label
)
# make some plots of the outputs
result
.
plot_corner
()
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