From 2d71127695fb08e9b71963f36f8e3a5332285dc5 Mon Sep 17 00:00:00 2001
From: Rayne Liu <rayne.liu@atlas1>
Date: Fri, 14 Aug 2020 13:45:09 +0000
Subject: [PATCH] Most recent pyscript

---
 code/RDGW150914_ptemcee4.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/code/RDGW150914_ptemcee4.py b/code/RDGW150914_ptemcee4.py
index f0a99d1..848d6a7 100755
--- a/code/RDGW150914_ptemcee4.py
+++ b/code/RDGW150914_ptemcee4.py
@@ -33,17 +33,17 @@ from scipy.optimize import minimize
 #tshift: time shift after the strain peak
 #vary_fund: whether you vary the fundamental frequency. Works in the model_dv function.
 
-rootpath= "/Users/RayneLiu"#"/work/rayne.liu"
+rootpath="/work/rayne.liu"# "/Users/RayneLiu"
 nmax=1
 tshift=19
 vary_fund = False
 
 #sampler parameters
-npoints=1002 
+npoints=1000000 
 nwalkers = 42
 ntemps=12
 ndim = int(4*(nmax+1))
-burnin = 200 #How many points do you burn before doing the corner plot. You need to watch the convergence of the chain plot a bit.
+burnin = 420000 #How many points do you burn before doing the corner plot. You need to watch the convergence of the chain plot a bit.
             #This is trivial but often forgotten: this cannot be more than npoints! Usually 1/5~1/4 npoints is what I observe.
 numbins = 42 #corner plot parameter - how many bins you want
 datacolor = '#105670' #'#4fa3a7'
@@ -172,8 +172,8 @@ def log_probability(theta):
 
 #Fit with ptemcee
 #Set the number of cores of your processors
-pool = choose_pool(6)
-pool.size = 6
+pool = choose_pool(12)
+pool.size = 12
 vary_param = float(vary_fund)
 pos = np.array([[random.uniform(-0.1,0.1), random.uniform(-0.1,0.1), 4.28313743e-01, random.uniform(2.5, 2.6) + (1-vary_param) * np.pi]])
 for i in range (1,nmax+1):
-- 
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