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# author : S. Mandalia
# s.p.mandalia@qmul.ac.uk
#
# date : March 17, 2018
"""
Misc functions for the BSM flavour ratio analysis
"""
from __future__ import absolute_import, division
import os
import errno
from collections import Sequence
import multiprocessing
import numpy as np
from utils.enums import Likelihood, ParamTag
class Param(object):
"""Parameter class to store parameters.
"""
def __init__(self, name, value, ranges, std=None, tex=None, tag=None):
self._ranges = None
self._tex = None
self._tag = None
self.name = name
self.value = value
self.ranges = ranges
self.std = std
self.tex = tex
self.tag = tag
@property
def ranges(self):
return tuple(self._ranges)
@ranges.setter
def ranges(self, values):
self._ranges = [val for val in values]
@property
def tex(self):
return r'{0}'.format(self._tex)
@tex.setter
def tex(self, t):
self._tex = t if t is not None else r'{\rm %s}' % self.name
@property
def tag(self):
return self._tag
@tex.setter
def tag(self, t):
if t is None: self._tag = ParamTag.NONE
else:
assert t in ParamTag
self._tag = t
class ParamSet(Sequence):
"""Container class for a set of parameters.
"""
def __init__(self, *args):
param_sequence = []
for arg in args:
try:
param_sequence.extend(arg)
except TypeError:
param_sequence.append(arg)
# Disallow duplicated params
all_names = [p.name for p in param_sequence]
unique_names = set(all_names)
if len(unique_names) != len(all_names):
duplicates = set([x for x in all_names if all_names.count(x) > 1])
raise ValueError('Duplicate definitions found for param(s): ' +
', '.join(str(e) for e in duplicates))
# Elements of list must be Param type
assert all([isinstance(x, Param) for x in param_sequence]), \
'All params must be of type "Param"'
self._params = param_sequence
def __len__(self):
return len(self._params)
def __getitem__(self, i):
if isinstance(i, int):
return self._params[i]
elif isinstance(i, basestring):
return self._by_name[i]
def __getattr__(self, attr):
try:
return super(ParamSet, self).__getattribute__(attr)
except AttributeError:
t, v, tb = sys.exc_info()
try:
return self[attr]
except KeyError:
raise t, v, tb
def __iter__(self):
return iter(self._params)
@property
def _by_name(self):
return {obj.name: obj for obj in self._params}
@property
def names(self):
return tuple([obj.name for obj in self._params])
@property
def labels(self):
return tuple([obj.tex for obj in self._params])
@property
def values(self):
return tuple([obj.value for obj in self._params])
@property
def ranges(self):
return tuple([obj.ranges for obj in self._params])
@property
def stds(self):
return tuple([obj.std for obj in self._params])
@property
def tags(self):
return tuple([obj.tag for obj in self._params])
@property
def params(self):
return self._params
def to_dict(self):
return {obj.name: obj.value for obj in self._params}
def from_tag(self, tag):
return tuple([obj for obj in self._params if obj.tag is tag])
def idx_from_tag(self, tag):
return tuple([idx for idx, obj in enumerate(self._params)
if obj.tag is tag])
def gen_outfile_name(args):
"""Generate a name for the output file based on the input args.
Parameters
----------
args : argparse
argparse object to print
"""
mr = args.measured_ratio
si = args.sigma_ratio
if args.fix_source_ratio:
sr = args.source_ratio
if args.fix_mixing:
outfile = args.outfile+'_{0:03d}_{1:03d}_{2:03d}_{3:04d}_sfr_{4:03d}_{5:03d}_{6:03d}_DIM{7}_fix_mixing'.format(
int(mr[0]*100), int(mr[1]*100), int(mr[2]*100), int(si*1000),
int(sr[0]*100), int(sr[1]*100), int(sr[2]*100), args.dimension
)
elif args.fix_scale:
outfile = args.outfile+'_{0:03d}_{1:03d}_{2:03d}_{3:04d}_sfr_{4:03d}_{5:03d}_{6:03d}_DIM{7}_fixed_scale_{8}'.format(
int(mr[0]*100), int(mr[1]*100), int(mr[2]*100), int(si*1000),
int(sr[0]*100), int(sr[1]*100), int(sr[2]*100), args.dimension,
args.scale
)
else:
outfile = args.outfile+'_{0:03d}_{1:03d}_{2:03d}_{3:04d}_sfr_{4:03d}_{5:03d}_{6:03d}_DIM{7}_single_scale'.format(
int(mr[0]*100), int(mr[1]*100), int(mr[2]*100), int(si*1000),
int(sr[0]*100), int(sr[1]*100), int(sr[2]*100), args.dimension
)
else:
if args.fix_mixing:
outfile = args.outfile+'_{0:03d}_{1:03d}_{2:03d}_{3:04d}_DIM{4}_fix_mixing'.format(
int(mr[0]*100), int(mr[1]*100), int(mr[2]*100),
int(si*1000), args.dimension
)
elif args.fix_scale:
outfile = args.outfile+'_{0:03d}_{1:03d}_{2:03d}_{3:04d}_DIM{4}_fixed_scale_{5}'.format(
int(mr[0]*100), int(mr[1]*100), int(mr[2]*100),
int(si*1000), args.dimension, args.scale
)
else:
outfile = args.outfile+'_{0:03d}_{1:03d}_{2:03d}_{3:04d}_DIM{4}'.format(
int(mr[0]*100), int(mr[1]*100), int(mr[2]*100),
int(si*1000), args.dimension
)
if args.likelihood is Likelihood.FLAT: outfile += '_flat'
return outfile
def parse_bool(s):
"""Parse a string to a boolean.
Parameters
----------
s : str
String to parse
Returns
----------
bool
Examples
----------
>>> from misc import parse_bool
>>> print parse_bool('true')
True
"""
if s.lower() == 'true':
return True
elif s.lower() == 'false':
return False
else:
raise ValueError
def print_args(args):
"""Print the input arguments.
Parameters
----------
args : argparse
argparse object to print
"""
arg_vars = vars(args)
for key in arg_vars.iterkeys():
print '== {0:<25} = {1}'.format(key, arg_vars[key])
def enum_keys(e):
return e.__members__.keys()
def enum_parse(s, c):
return c[s.upper()]
def make_dir(outfile):
try:
os.makedirs(outfile[:-len(os.path.basename(outfile))])
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(outfile[:-len(os.path.basename(outfile))]):
pass
else:
raise
def thread_type(t):
if t.lower() == 'max':
return multiprocessing.cpu_count()
else:
return int(t)
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