def parseForBatch(self, vals=None):
if self.importanceParameter:
self.parser.add_argument('--noimportance', action='store_true',
help='original chains only, no importance sampled')
self.parser.add_argument('--importance', nargs='*', default=None,
help='data names for importance sampling runs to include')
self.parser.add_argument('--importancetag', nargs='*', default=None,
help='importance tags for importance sampling runs to include')
self.parser.add_argument('--name', default=None, nargs='+',
help='specific chain full name only (base_paramx_data1_data2)')
self.parser.add_argument('--param', default=None, nargs='+',
help='runs including specific parameter only (paramx)')
self.parser.add_argument('--paramtag', default=None, nargs='+',
help='runs with specific parameter tag only (base_paramx)')
self.parser.add_argument('--data', nargs='+', default=None, help='runs including specific data only (data1)')
self.parser.add_argument('--datatag', nargs='+', default=None,
help='runs with specific data tag only (data1_data2)')
self.parser.add_argument('--musthave_data', nargs='+', default=None,
help='include only runs that include specific data (data1)')
self.parser.add_argument('--skip_data', nargs='+', default=None,
help='skip runs containing specific data (data1)')
self.parser.add_argument('--skip_param', nargs='+', default=None,
help='skip runs containing specific parameter (paramx)')
self.parser.add_argument('--group', default=None, nargs='+', help='include only runs with given group names')
self.parser.add_argument('--skip_group', default=None, nargs='+', help='exclude runs with given group names')
if self.notExist:
self.parser.add_argument('--notexist', action='store_true',
help='only include chains that don\'t already exist on disk')
if self.notall:
self.parser.add_argument('--notall', type=int, default=None,
help='only include chains where all N chains don\'t already exist on disk')
if self.doplots:
self.parser.add_argument('--paramNameFile', default='clik_latex.paramnames',
help=".paramnames file for custom labels for parameters")
self.parser.add_argument('--param_list', default=None,
help=".paramnames file listing specific parameters to include (only)")
self.parser.add_argument('--size_inch', type=float, default=None, help='output subplot size in inches')
self.parser.add_argument('--nx', default=None, help='number of plots per row')
self.parser.add_argument('--outputs', nargs='+', default=['pdf'], help='output file type (default: pdf)')
args = self.parser.parse_args(vals)
self.args = args
if args.batchPath:
self.batch = batchjob.readobject(args.batchPath)
if self.batch is None:
raise Exception('batchPath %s does not exist or is not initialized with makeGrid.py' % args.batchPath)
if self.doplots:
import getdist.plots as plots
from getdist import paramnames
if args.paramList is not None: args.paramList = paramnames.ParamNames(args.paramList)
g = plots.GetDistPlotter(chain_dir=self.batch.batchPath)
if args.size_inch is not None: g.settings.set_with_subplot_size(args.size_inch)
return self.batch, self.args, g
else:
return self.batch, self.args
else:
return None, self.args
def load_supported_grid(chain_dir):
if is_grid_object(chain_dir):
return chain_dir
try:
# If cosmomc is installed, e.g. to allow use of old Planck grids
# The 2018 final Planck grid should be OK with getdist default chain grid below
from paramgrid import gridconfig, batchjob
if gridconfig.pathIsGrid(chain_dir):
return batchjob.readobject(chain_dir)
except ImportError:
pass
return None
from __future__ import absolute_import
from __future__ import print_function
import os
import sys
from paramgrid import batchjob
if len(sys.argv) < 3:
print('Usage: python/addGridBatch.py directory_with_outputs directory_with_output_to_add [and_another..]')
sys.exit()
batch = batchjob.readobject()
for subBatch in sys.argv[2:]:
batchPath2 = os.path.abspath(subBatch) + os.sep
batch2 = batchjob.readobject(batchPath2)
batch.subBatches.append(batch2)
for jobItem in list(batch.items()):
for x in [imp for imp in jobItem.importanceJobsRecursive()]:
if batch.hasName(x.name.replace('_post', '')):
print('replacing importance sampling run (not deleting files): ' + x.name)
jobItem.removeImportance(x)
batch.save()
def parseForBatch(self, vals=None):
if self.importanceParameter:
self.parser.add_argument('--noimportance', action='store_true',
help='original chains only, no importance sampled')
self.parser.add_argument('--importance', nargs='*', default=None,
help='data names for importance sampling runs to include')
self.parser.add_argument('--importancetag', nargs='*', default=None,
help='importance tags for importance sampling runs to include')
self.parser.add_argument('--name', default=None, nargs='+',
help='specific chain full name only (base_paramx_data1_data2)')
self.parser.add_argument('--param', default=None, nargs='+',
help='runs including specific parameter only (paramx)')
self.parser.add_argument('--paramtag', default=None, nargs='+',
help='runs with specific parameter tag only (base_paramx)')
self.parser.add_argument('--data', nargs='+', default=None, help='runs including specific data only (data1)')
self.parser.add_argument('--datatag', nargs='+', default=None,
help='runs with specific data tag only (data1_data2)')
self.parser.add_argument('--musthave_data', nargs='+', default=None,
help='include only runs that include specific data (data1)')
self.parser.add_argument('--skip_data', nargs='+', default=None,
help='skip runs containing specific data (data1)')
self.parser.add_argument('--skip_param', nargs='+', default=None,
help='skip runs containing specific parameter (paramx)')
self.parser.add_argument('--group', default=None, nargs='+', help='include only runs with given group names')
self.parser.add_argument('--skip_group', default=None, nargs='+', help='exclude runs with given group names')
if self.notExist:
self.parser.add_argument('--notexist', action='store_true',
help='only include chains that don\'t already exist on disk')
if self.notall:
self.parser.add_argument('--notall', type=int, default=None,
help='only include chains where all N chains don\'t already exist on disk')
if self.doplots:
self.parser.add_argument('--plot_data', nargs='*', default=None,
help='directory/ies containing getdist output plot_data')
self.parser.add_argument('--paramNameFile', default='clik_latex.paramnames',
help=".paramnames file for custom labels for parameters")
self.parser.add_argument('--paramList', default=None,
help=".paramnames file listing specific parameters to include (only)")
self.parser.add_argument('--size_inch', type=float, default=None, help='output subplot size in inches')
self.parser.add_argument('--nx', default=None, help='number of plots per row')
self.parser.add_argument('--outputs', nargs='+', default=['pdf'], help='output file type (default: pdf)')
args = self.parser.parse_args(vals)
self.args = args
if args.batchPath:
self.batch = batchjob.readobject(args.batchPath)
if self.batch is None: raise Exception('batchPath does not exist or it not initialized with makeGrid.py')
if self.doplots:
import getdist.plots as plots
from getdist import paramnames
if args.paramList is not None: args.paramList = paramnames.ParamNames(args.paramList)
if args.plot_data is not None:
g = plots.GetDistPlotter(plot_data=args.plot_data)
else:
g = plots.GetDistPlotter(chain_dir=self.batch.batchPath)
if args.size_inch is not None: g.settings.setWithSubplotSize(args.size_inch)
return self.batch, self.args, g
else:
return self.batch, self.args
else:
return None, self.args
def getBatch(self):
if not hasattr(self, 'batch'):
self.batch = batchjob.readobject(rootdir)
return self.batch
from __future__ import absolute_import
from __future__ import print_function
import os
import sys
from paramgrid import batchjob
if len(sys.argv) < 3:
print(
'Usage: python/addGridBatch.py directory_with_outputs directory_with_output_to_add [and_another..]'
)
sys.exit()
batch = batchjob.readobject()
for subBatch in sys.argv[2:]:
batchPath2 = os.path.abspath(subBatch) + os.sep
batch2 = batchjob.readobject(batchPath2)
batch.subBatches.append(batch2)
for jobItem in list(batch.items()):
for x in [imp for imp in jobItem.importanceJobs()]:
if batch.hasName(x.name.replace('_post', '')):
print('replacing importance sampling run (not deleting files): ' +
x.name)
jobItem.importanceItems.remove(x)
batch.save()
def getBatch(self):
if not hasattr(self, 'batch'): self.batch = batchjob.readobject(rootdir)
return self.batch
