Adjustments from atlas

code/NR_Interpolate-0001_t_10M_wandt.py

@@ -42,14 +42,14 @@ tshift=10
 vary_fund = True
 
 #sampler parameters
-npoints = 10
-nwalkers = 20
+npoints = 1200
+nwalkers = 256
 ntemps=12
 dim = nmax+1
 ndim = 4*dim
-burnin = 5  #How many points do you burn before doing the corner plot. You need to watch the convergence of the chain plot a bit.
+burnin = 600  #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! I usually use half the points.
-numbins = 42 #corner plot parameter - how many bins you want
+numbins = 32 #corner plot parameter - how many bins you want
 datacolor = '#105670' #'#4fa3a7'
 pkcolor = '#f2c977' #'#ffb45f'
 mediancolor = '#f7695c' #'#9b2814'
@@ -180,8 +180,8 @@ def log_prior(theta):
             return 0.0
     
     elif tshift == 10:
-        if all([0.56 <= omega0 <= 0.64, 0.4 <= omega1 <= 0.56, 6.45 <= tau0 <= 13.6, 1.94 <= tau1 <= 10., \
-            0. <= xvar0 <= 1.5, 0. <= xvar1 <= 1.2, 0 <= yvar0 <= 2*np.pi, 0. <= yvar1 <= 2*np.pi]):        
+        if all([0.54 <= omega0 <= 0.6, 0.4 <= omega1 <= 0.58, 8.8 <= tau0 <= 14.2, 3.7 <= tau1 <= 10., \
+            0. <= xvar0 <= 1.0, 0. <= xvar1 <= 1.2, 0 <= yvar0 <= 2*np.pi, -np.pi <= yvar1 <= np.pi]):        
             return 0.0
     
     return -np.inf
@@ -213,7 +213,7 @@ def log_probability(theta):
 #pool = choose_pool(1)
 #pool.size = 1
 np.random.seed(42)
-pos = np.array([random.uniform(0.58,0.62), random.uniform(0.42,0.54), random.uniform(7., 12.),                 random.uniform(2.,4.), random.uniform(0.5,1.), random.uniform(0.5, 1.), random.uniform(1., 2.),                 random.uniform(1., 2.)])
+pos = np.array([random.uniform(0.55,0.57), random.uniform(0.5,0.52), random.uniform(9., 12.),                 random.uniform(4.,7.), random.uniform(0.3,0.5), random.uniform(0.3, 0.5), random.uniform(1., 5.),                 random.uniform(-2., 2.)])
 pos = list(pos)
 pos += 1e-5 * np.random.randn(ntemps, nwalkers, ndim)
 with Pool() as pool:

code/condor_submit_Interpolate0001_t_10M_wandt.sub

+universe   = vanilla
+getenv     = true
+# run script -- make sure that condor has execute permission for this file (chmod a+x script.py)
+executable = NR_Interpolate-0001_t_10M_wandt.py 
+# file to dump stdout (this directory should exist)
+output     = NR_Interpolate-0001_t_10M_wandt.out
+# file to dump stderr
+error     = NR_Interpolate-0001_t_10M_wandt.err
+# condor logs
+log     = NR_Interpolate-0001_t_10M_wandt.log
+initialdir = .
+notify_user = rl746@cornell.edu
+notification = Complete
+arguments  = "-processid $(Process)" 
+request_memory = 64GB
+request_cpus = 1
+on_exit_remove = (ExitBySignal == False) || ((ExitBySignal == True) && (ExitSignal != 11))
+accounting_group = aei.dev.test_dynesty
+queue 1
+