pp/dynesty.md

@@ -2,7 +2,21 @@
 
 All runs can be found [on cit](https://ldas-jobs.ligo.caltech.edu/~gregory.ashton/bilby_tests/dynesty/). 
 
-Runs are generated by drawing simulated signals in Gaussian (aLIGO noise curve) data for H1 and L1. The prior distribution from which simulation values are selected is
+Runs are generated by drawing simulated signals in Gaussian (aLIGO noise curve) data for H1 and L1. 
+
+
+
+Then, for the analysis the same prior is used **except** that the `geocent_time` prior is set to
+
+```
+geocent_time = Uniform(minimum=-0.05, maximum=0.05, name='geocent_time', latex_label='$t_c$', unit='$s$')
+```
+
+in all cases we use the `bilby.gw.likelihood.GravitationalWaveTransientLikelihood` with no marginalisation.
+
+## Run 1: `nlive=2000` and `walks=50`
+
+For the first run, we doa  no-spin run, i.e. the prior is given by
 
 ```python
 chirp_mass = Uniform(name='chirp_mass', minimum=25, maximum=100, unit='$M_{\\odot}$')
@@ -21,17 +35,6 @@ phase =  Uniform(name='phase', minimum=0, maximum=2 * np.pi)
 luminosity_distance = PowerLaw(alpha=2, minimum=100, maximum=5000, name='luminosity_distance')
 geocent_time = 0
 ```
-
-Then, for the analysis the same prior is used **except** that the `geocent_time` prior is set to
-
-```
-geocent_time = Uniform(minimum=-0.05, maximum=0.05, name='geocent_time', latex_label='$t_c$', unit='$s$')
-```
-
-in all cases we use the `bilby.gw.likelihood.GravitationalWaveTransientLikelihood` with no marginalisation.
-
-## Run 1: `nlive=2000` and `walks=50`
-
 Here is the full set of sampler kwargs:
 
 ```python
@@ -50,6 +53,43 @@ Here is the full set of sampler kwargs:
 
 ![image](uploads/966793dc31433597902bd919570192cc/image.png)
 
+## Run 2
+
+```python
+chirp_mass = Uniform(name='chirp_mass', minimum=25, maximum=100, unit='$M_{\\odot}$')
+mass_ratio =  Uniform(name='mass_ratio', minimum=0.125, maximum=1)
+a_1 =  Uniform(name='a_1', minimum=0, maximum=0.8)
+a_2 =  Uniform(name='a_2', minimum=0, maximum=0.8)
+tilt_1 =  Sine(name='tilt_1')
+tilt_2 =  Sine(name='tilt_2')
+phi_12 =  Uniform(name='phi_12', minimum=0, maximum=2 * np.pi)
+phi_jl =  Uniform(name='phi_jl', minimum=0, maximum=2 * np.pi)
+dec =  Cosine(name='dec')
+ra =  Uniform(name='ra', minimum=0, maximum=2 * np.pi)
+iota =  Sine(name='iota')
+psi =  Uniform(name='psi', minimum=0, maximum=np.pi)
+phase =  Uniform(name='phase', minimum=0, maximum=2 * np.pi)
+luminosity_distance = PowerLaw(alpha=2, minimum=100, maximum=5000, name='luminosity_distance')
+geocent_time = 0
+```
+
+The set of kwargs are
+
+```
+{'bound': 'multi', 'sample': 'rwalk', 'verbose': True, 'check_point_delta_t': 600, 'nlive': 2000, 'first_update': None, 'npdim': None, 'rstate': None, 'queue_size': None, 'pool': None, 'use_pool': None, 'live_points': None, 'logl_args': None, 'logl_kwargs': None, 'ptform_args': None, 'ptform_kwargs': None, 'enlarge': None, 'bootstrap': None, 'vol_dec': 0.5, 'vol_check': 2.0, 'facc': 0.5, 'slices': 5, 'walks': 50, 'update_interval': 1200, 'print_func': <bound method Dynesty._print_func of <bilby.core.sampler.dynesty.Dynesty object at 0x2b07df2b4358>>, 'dlogz': 0.1, 'maxiter': None, 'maxcall': None, 'logl_max': inf, 'add_live': True, 'print_progress': True, 'save_bounds': True}
+```
+
+### PP plot
+
+![image](uploads/3acfb087ead9680b9c69c82ba55d961c/image.png)
+
+### Sampling time
+
+![image](uploads/407be4a9d232a86801a0146dd38e39b3/image.png)
+
+### SNR distribition
+
+![image](uploads/e5278c2e1610a1a3fde624e14ce4e2e9/image.png)
 ## Old runs
 
 The following are some old results, leaving here in case we want to come back to them.