Update SummaryReview script authored by Nicola De Lillo's avatar Nicola De Lillo
......@@ -72,125 +72,43 @@ for index in params:
which outputs
```
luminosity_distance [194.16 282.01]
phi_12 [0.33 5.94]
#### Obtained using PESummary
chirp_mass_source [6.03 6.15]
cos_tilt_1 [-0.97 0.85]
phi_jl [0.36 5.83]
total_mass_source [24.31 26.73]
mass_ratio [0.1 0.13]
chirp_mass [6.39 6.43]
comoving_distance [186.24 265.82]
V1_matched_filter_snr_abs [3.69 4.49]
H1_matched_filter_snr_angle [-0.11 0.1 ]
mass_2 [2.64 2.86]
tilt_2 [0.62 2.64]
tilt_1 [0.55 2.89]
chi_p [0.01 0.11]
mass_1 [22.68 25.56]
L1_matched_filter_snr_abs [21.99 22.32]
geocent_time [1.24985226e+09 1.24985226e+09]
mass_1_source [21.58 24.23]
symmetric_mass_ratio [0.08 0.1 ]
mass_2_source [2.5 2.73]
cos_tilt_2 [-0.88 0.81]
phi_2 [0.36 5.95]
psi [0.06 3.05]
V1_matched_filter_snr_angle [-0.31 0.39]
theta_jn [0.63 2.39]
ra [0.2 0.4]
dec [-0.57 -0.4 ]
cos_theta_jn [-0.73 0.81]
a_2 [0.06 0.94]
total_mass [25.54 28.2 ]
phase [0.4 5.88]
H1_matched_filter_snr_abs [10.51 10.76]
chi_eff [-0.09 0.04]
log_likelihood [-45774.32 302.36]
phi_1 [0.34 5.93]
L1_matched_filter_snr_angle [-0.07 0.06]
chi_p [0.01 0.11]
a_1 [0. 0.11]
luminosity_distance [194.16 282.01]
theta_jn [0.63 2.39]
L1_matched_filter_snr_abs [21.99 22.32]
H1_matched_filter_snr_abs [10.51 10.76]
V1_matched_filter_snr_abs [3.69 4.49]
```
These numbers have been compared to the reviewed results for GW190814 `combinedPHM` at the bottom of this page [1]
* upper value `mass ratio`
* lower value `total_mass_source`
* lower value `mass_1_source`
* lower limit `theta_jn `
* both limits for `L1_matched_filter_snr_abs ` (0.05 difference for the lower limit)
* Same for `H1_matched_filter_snr_abs `
* Same for `V1_matched_filter_snr_abs` , with a 0.13 difference.
My guess is that this is due to different versions of `np.percentile` (pesummary uses ). To cross-check this, I have personally run the script at the page linked [1]:
```python
import numpy as np
from pesummary.gw.file.read import read
parameter_dict = {
"chirp_mass_source": "Chirp mass $\mathcal{M}/M_{\odot}$",
"total_mass_source": "Total mass $M/M_{\odot}$",
"mass_ratio": "Mass ratio $q$",
"mass_1_source": "Primary mass $m_{1}/M_{\odot}$",
"mass_2_source": "Secondary mass ${m_{2}/M_{\odot}}$",
"chi_eff": "Effective inspiral spin parameter $\chi_{eff}$",
"chi_p": "Effective precession parameter $\chi_{p}$",
"a_1": "Dimensionless primary spin magnitude $a_{1}$",
"luminosity_distance": "Luminosity Distance $D_{L}/\text{Mpc}$",
"redshift": "Source redshift $z$",
"theta_jn": "Inclination angle $\\theta_{\mathrm{JN}}$",
"L1_matched_filter_snr_abs": "Signal to Noise ratio in \\llo $\\rho_{\mathrm{L}}$",
"H1_matched_filter_snr_abs": "Signal to Noise ratio in \\lho $\\rho_{\mathrm{H}}$",
"V1_matched_filter_snr_abs": "Signal to Noise ratio in \\virgo $\\rho_{\mathrm{V}}$",
"network_matched_filter_snr": "Network Signal to Noise ratio $\\rho_{\mathrm{HLV}}$",
}
waveform_model = "combinedPHM"
print("---------- {} ----------\n".format(waveform_model))
f = read('/home/nicola.delillo/pesummary-review/summaryreview/combined_PHM.dat')
f.generate_all_posterior_samples()
params = parameter_dict.keys()
for param in params:
samples = f.samples_dict[param]
print(
"{} = {}^{}_{} [{} {}]".format(
param, np.round(np.median(samples), 2),
np.round(np.percentile(samples, 95) - np.median(samples), 2),
np.round(np.median(samples) - np.percentile(samples, 5), 2),
np.round(np.percentile(samples, 5), 2),
np.round(np.percentile(samples, 95), 2)
)
)
```
I have adapted the script to run only on `combinedPHM` data. I had also to change `matched_filter_snr` tag in `matched_filter_snr_abs`. Plus I have added two lines that print the intervals in the form [min, max]
The output of the script is:
These numbers have been compared to the reviewed results for GW190814 `combinedPHM` at the bottom of this page [1], which correspond to numbers cited in the discovery paper [2], which we report her:
```
chirp_mass_source = 6.09^0.06_0.06
total_mass_source = 25.52^1.21_1.22
mass_ratio = 0.11^0.01_0.01
mass_1_source = 22.91^1.32_1.32
mass_2_source = 2.62^0.11_0.12
chi_eff = -0.02^0.06_0.07
chi_p = 0.05^0.06_0.04
a_1 = 0.03^0.08_0.03
luminosity_distance = 237.97^44.04_43.81
redshift = 0.05^0.01_0.01
theta_jn = 0.9^1.49_0.28
L1_matched_filter_snr_abs = 22.2^0.13_0.21
H1_matched_filter_snr_abs = 10.66^0.1_0.15
V1_matched_filter_snr_abs = 4.27^0.22_0.58
network_matched_filter_snr = 24.98^0.14_0.22
#### GW190814 reviewed numbers
chirp_mass_source = 6.09^0.06_0.06 | [6.03 6.15]
total_mass_source = 25.52^1.21_1.22 | [24.31 26.73]
mass_ratio = 0.11^0.01_0.01 | [0.1 0.13]
mass_1_source = 22.91^1.32_1.32 | [21.58 24.23]
mass_2_source = 2.62^0.11_0.12 | [2.5 2.73]
chi_eff = -0.02^0.06_0.07 | [-0.09 0.04]
chi_p = 0.05^0.06_0.04 | [0.01 0.11]
a_1 = 0.03^0.08_0.03 | [0.0 0.11]
luminosity_distance = 237.97^44.04_43.81 | [194.16 282.01]
redshift = 0.05^0.01_0.01 | [0.04 0.06]
theta_jn = 0.9^1.49_0.28 | [0.63 2.39]
L1_matched_filter_snr_abs = 22.2^0.13_0.21 | [21.99 22.32]
H1_matched_filter_snr_abs = 10.66^0.1_0.15 | [10.51 10.76]
V1_matched_filter_snr_abs = 4.27^0.22_0.58 | [3.69 4.49]
network_matched_filter_snr = 24.98^0.14_0.22 | [24.76 25.12]
```
[1]: [https://git.ligo.org/publications/gw190814/gw190814-discovery/-/wikis/PE-result-table](https://git.ligo.org/publications/gw190814/gw190814-discovery/-/wikis/PE-result-table) . There are sum difference in the following parameters
[2] [https://dcc.ligo.org/LIGO-P190814-v2](https://dcc.ligo.org/LIGO-P190814-v2)
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