In [4]:

    

import yaml
import copy
from os import path
import numpy as np


    

In [6]:

    

orig_cfg_fname = '/home/users/swmclau2//Git/pearce/bin/mcmc/nh_gg_sham_hsab_mcmc_config.yaml'
with open(orig_cfg_fname, 'r') as yamlfile:
    orig_cfg = yaml.load(yamlfile)


    

In [7]:

    

orig_cfg


    

    
Out[7]:





{'chain': {'fixed_params': {},
  'nburn': 0,
  'nsteps': 10000,
  'nwalkers': 500,
  'seed': 0},
 'data': {'cov': {'emu_cov_fname': '/home/users/swmclau2/Git/pearce/bin/covmat/xi_gg_nh_emu_cov.npy',
   'meas_cov_fname': '/home/users/swmclau2/Git/pearce/notebooks/meas_cov_testboxes_gg.npy'},
  'obs': {'mean': False,
   'obs': 'xi',
   'rbins': [0.07943282,
    0.11220185,
    0.15848932,
    0.22387211,
    0.31622777,
    0.44668359,
    0.63095734,
    0.89125094,
    1.25892541,
    1.77827941,
    2.51188643,
    3.54813389,
    5.01187234,
    7.07945784,
    10.0,
    14.12537545,
    19.95262315,
    28.18382931,
    39.81071706]},
  'sim': {'gal_type': 'SHAM',
   'halo_property': 'halo_vpeak',
   'min_ptcl': 100,
   'nd': '5e-4',
   'scale_factor': 1.001,
   'scatter': 0.2,
   'sim_hps': {'system': 'sherlock'},
   'simname': 'ds_14_b_sub'},
  'true_cov_fname': ['/home/users/swmclau2/Git/pearce/bin/shams/xigg_cov_mcmc.npy'],
  'true_data_fname': ['/home/users/swmclau2/Git/pearce/bin/shams/ds14b_sub_xi_gg.npy']},
 'emu': {'emu_hps': {},
  'emu_type': 'NashvilleHot',
  'fixed_params': {'z': 0.0},
  'training_file': '/home/users/swmclau2/scratch/xi_gg_abzheng07/PearceXiggHSABCosmo.hdf5'},
 'fname': '/scratch/users/swmclau2/PearceMCMC/pearce_mcmc_nh_gg_sham_hsab.hdf5'}

In [8]:

    

#this will enable easier string formatting
sbatch_template = """#!/bin/bash
#SBATCH --job-name={jobname}
#SBATCH --time=12:00:00
#SBATCH -p kipac
#SBATCH -o /home/users/swmclau2/Git/pearce/bin/mcmc/config/{jobname}.out
#SBATCH --ntasks=16
###SBATCH --exclusive

module load python/2.7.13
module load py-scipystack
module load hdf5/1.10.0p1
module load py-numpy

python /home/users/swmclau2/Git/pearce/pearce/inference/initialize_mcmc.py {jobname}.yaml
python /home/users/swmclau2/Git/pearce/pearce/inference/run_mcmc.py {jobname}.yaml
"""


    

In [9]:

    

#emu fnames
#emu_fnames = [#'/nfs/slac/g/ki/ki18/des/swmclau2/xi_gg_zheng07_v4/PearceXiggCosmo.hdf5',\
#              '/nfs/slac/g/ki/ki18/des/swmclau2/xi_gg_hsabzheng07_v2/PearceXiggCosmoCorrAB.hdf5']
emu_fnames = [['/scratch/users/swmclau2/wp_zheng07/PearceWpCosmo.hdf5', '/scratch/users/swmclau2/ds_zheng07/PearceDsCosmo.hdf5']]
#emu_cov_fnames = [#'/afs/slac.stanford.edu/u/ki/swmclau2/Git/pearce/bin/covmat/xi_gg_nh_emu_cov_v4.npy',
#                  '/afs/slac.stanford.edu/u/ki/swmclau2/Git/pearce/bin/covmat/xi_gg_nh_emu_hsab_cov_v4.npy']
emu_names = ['HOD']


    

In [10]:

    

np.save('dummy_emu_covmat.npy', np.zeros((18,18)))


    

In [11]:

    

meas_cov_fname = '/home/users/swmclau2/Git/pearce/bin/covmat/wp_ds_full_covmat.npy'

# TODO replace with actual ones onace test boxes are done 
emu_cov_fnames = [['/home/users/swmclau2/Git/pearce/notebooks/dummy_emu_covmat.npy' for i in xrange(2)]]


    

In [16]:

    

orig_cfg_fname = '/home/users/swmclau2/Git/pearce/bin/mcmc/nh_gg_mcmc_config.yaml'
with open(orig_cfg_fname, 'r') as yamlfile:
    orig_cfg = yaml.load(yamlfile)


    

In [19]:

    

tmp_cfg = copy.deepcopy(orig_cfg)
directory = "/home/users/swmclau2/Git/pearce/bin/mcmc/config/"
output_dir = "/home/users/swmclau2/scratch/PearceMCMC/"
jobname_template = "HOD_wp_ds_rmin_{rmin}_{emu_name}"

for rmin in [None, 0.5, 1.0, 2.0]:
    for emu_fname, emu_name, emu_cov in zip(emu_fnames, emu_names, emu_cov_fnames):
        
        tmp_cfg['chain']['nwalkers'] = 500
        if rmin is not None:
            tmp_cfg['emu']['fixed_params'] = {'z': 0.0, 'rmin':rmin}
            
        tmp_cfg['emu']['training_file'] = emu_fname
        tmp_cfg['emu']['emu_type'] = ['NashvilleHot' for i in xrange(len(emu_fname))]
        tmp_cfg['emu']['emu_cov_fname'] = emu_cov_fnames
        
        tmp_cfg['data']['cov']['meas_cov_fname'] = meas_cov_fname
        
        jobname = jobname_template.format(rmin=rmin, emu_name=emu_name)
        tmp_cfg['fname'] = path.join(output_dir, jobname+'.hdf5')
        
        tmp_cfg['sim']= {'gal_type': 'HOD',
       'hod_name': 'zheng07',
       'hod_params': {'alpha': 1.083,
        'logM0': 13.2,
        'logM1': 14.2,
        'sigma_logM': 0.2},
       'nd': '5e-4',
       'scale_factor': 1.0,
       'sim_hps': {'boxno': 1,
        'downsample_factor': '1e-2',
        'particles': True,
        'realization': 0,
        'system': 'sherlock'},
       'simname': 'testbox'}
        
        tmp_cfg['data']['sim']['sim_hps']['system'] = 'sherlock'
        
        
        tmp_cfg['chain']['nsteps'] = 20000

        with open(path.join(directory, jobname +'.yaml'), 'w') as f:
            yaml.dump(tmp_cfg, f)

        with open(path.join(directory, jobname + '.sbatch'), 'w') as f:
            f.write(sbatch_template.format(jobname=jobname))


    

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