update contamination analysis step size

This commit updates the step size used for the MCMC in the contamination
analysis to 0.5 times the error returned by scanning near the minimum. I ran
some tests and this seemed to be pretty efficient compared to either the full
error or 0.1 times the error. I also reduced the number of workers to 10.

1 files changed, 2 insertions, 2 deletions

diff --git a/utils/dc b/utils/dc
index 8227e99..b36579e 100755
--- a/utils/dc
+++ b/utils/dc
@@ -453,7 +453,7 @@ if __name__ == '__main__':
     #samples = metropolis_hastings(nll,xopt,stepsizes,100000)
     #print("nll(xopt) = %.2g" % nll(xopt))
 
-    pos = np.empty((100, len(x0)),dtype=np.double)
+    pos = np.empty((10, len(x0)),dtype=np.double)
     for i in range(pos.shape[0]):
         pos[i] = xopt + np.random.randn(len(x0))*stepsizes
         pos[i,:6] = np.clip(pos[i,:6],EPSILON,1e9)
@@ -465,7 +465,7 @@ if __name__ == '__main__':
 
     nwalkers, ndim = pos.shape
 
-    proposal = get_proposal_func(stepsizes,low,high)
+    proposal = get_proposal_func(stepsizes*0.5,low,high)
     sampler = emcee.EnsembleSampler(nwalkers, ndim, lambda x, grad, fill_value: -nll(x,grad,fill_value), moves=emcee.moves.MHMove(proposal),args=[None,np.inf])
     with np.errstate(invalid='ignore'):
         sampler.run_mcmc(pos, args.steps)