#y = np.mean(np.log10(np.array(wp_vals)),axis = 0 )
#y = np.log10(np.loadtxt('/nfs/slac/g/ki/ki18/des/swmclau2/AB_tests/sham_vpeak_wp.npy'))
# TODO need a way to get a measurement cov for the shams
cov = np.cov(np.log10(np.array(wp_vals).T)) #/np.sqrt(50)
#obs_nd = np.mean(np.array(nds))
#obs_nd = np.loadtxt('/nfs/slac/g/ki/ki18/des/swmclau2/AB_tests/sham_vpeak_nd.npy')
obs_nd_err = np.std(np.array(nds))
param_names = [k for k in em_params.iterkeys() if k not in fixed_params]
nwalkers = 100
nsteps = 1000
nburn = 0
chain = run_mcmc(emu, cat, param_names, y, cov, rpoints,obs_nd, obs_nd_err,'calc_analytic_nd', fixed_params = fixed_params,\
nwalkers = nwalkers, nsteps = nsteps, nburn = nburn)#\
#resume_from_previous = '/u/ki/swmclau2/des/PearceMCMC/100_walkers_1000_steps_chain_vpeak_sham_free_split_2.npy')#, ncores = 1)
#from sys import exit
#exit(1)
savedir = '/u/ki/swmclau2/des/PearceMCMC/'
np.savetxt(
path.join(
savedir,
'%d_walkers_%d_steps_chain_vpeak_sham_free_split_fixed_sat.npy' %
(nwalkers, nsteps)), chain)
#np.savetxt(path.join(savedir, '%d_walkers_%d_steps_truth_ld_errors_2.npy'%(nwalkers, nsteps)),\
# np.array([em_params[p] for p in param_names]))
#np.savetxt(path.join(savedir, '%d_walkers_%d_steps_fixed_old_errors_2.npy'%(nwalkers, nsteps)),\
# np.array([fixed_params[p] for p in param_names if p in fixed_params]))
#y = np.mean(np.log10(np.array(wp_vals)),axis = 0 )
#y = np.log10(np.loadtxt('/nfs/slac/g/ki/ki18/des/swmclau2/AB_tests/sham_vpeak_wp.npy'))
# TODO need a way to get a measurement cov for the shams
cov = np.cov(np.log10(np.array(wp_vals).T)) #/np.sqrt(50)
#obs_nd = np.mean(np.array(nds))
#obs_nd = np.loadtxt('/nfs/slac/g/ki/ki18/des/swmclau2/AB_tests/sham_vpeak_nd.npy')
obs_nd_err = np.std(np.array(nds))
param_names = [k for k in em_params.iterkeys() if k not in fixed_params]
nwalkers = 100
nsteps = 1000
nburn = 0
chain = run_mcmc(emu, cat, param_names, y, cov, rpoints,obs_nd, obs_nd_err,'calc_analytic_nd', fixed_params = fixed_params,\
nwalkers = nwalkers, nsteps = nsteps, nburn = nburn,\
resume_from_previous = '/u/ki/swmclau2/des/PearceMCMC/100_walkers_1000_steps_chain_vpeak_sham_free_split_2.npy')#, ncores = 1)
#from sys import exit
#exit(1)
savedir = '/u/ki/swmclau2/des/PearceMCMC/'
np.savetxt(
path.join(
savedir, '%d_walkers_%d_steps_chain_vpeak_sham_free_split_3.npy' %
(nwalkers, nsteps)), chain)
#np.savetxt(path.join(savedir, '%d_walkers_%d_steps_truth_ld_errors_2.npy'%(nwalkers, nsteps)),\
# np.array([em_params[p] for p in param_names]))
#np.savetxt(path.join(savedir, '%d_walkers_%d_steps_fixed_old_errors_2.npy'%(nwalkers, nsteps)),\
# np.array([fixed_params[p] for p in param_names if p in fixed_params]))