def access(self, **kw):
"""
Access numpy indexes informing pattern and observation index through keywords dict:
- pidx|fidx;
- oidx;
respectively.
You can use the char ':' to expand the full dimension. This is the same as
using slice(None).
"""
if set(("pidx","fidx")) <= set(kw.keys()):
raise KeyError('Cannot use both pidx and fidx keywords')
pidx = kw.pop('pidx', slice(None))
if pidx is None: pidx = kw.pop('fidx', None)
oidx = kw.pop('oidx', slice(None))
checkForUnusedVars(kw)
if type(pidx) is str and pidx == ':': pidx = slice(None)
if type(oidx) is str and oidx == ':': oidx = slice(None)
if type(pidx) == tuple:
pidx = slice(*pidx)
if type(oidx) == tuple:
oidx = slice(*oidx)
if self.__useFortran:
return pidx, oidx
else:
return oidx, pidx
def __init__(self, transientAttrs = set(), toPublicAttrs = set(), **kw):
"Initialize streamer and declare transient variables."
Logger.__init__(self, kw)
self.transientAttrs = set(transientAttrs) | {'_readVersion',}
self.toPublicAttrs = set(toPublicAttrs)
from RingerCore.util import checkForUnusedVars
checkForUnusedVars( kw, self._logger.warning )
def __init__(self, **kw): Logger.__init__(self, kw) self.__useFortran = kw.pop( 'useFortran', False ) self.order = 'F' if self.__useFortran else 'C' self.pdim = 0 if self.__useFortran else 1 self.odim = 1 if self.__useFortran else 0 self.fp_dtype = np.dtype( kw.pop( 'fp_dtype', np.float64 ) ) self.int_dtype = np.dtype( kw.pop( 'int_dtype', np.int64 ) ) self.scounter_dtype = np.dtype( kw.pop( 'scounter_dtype', np.uint8 ) ) self.flag_dtype = np.dtype( kw.pop( 'flag_dtype', np.int8 ) ) checkForUnusedVars(kw)
def __init__(self, *args, **kw):
"""
Set values using min:incr:max and matlabFlag as explained in class
documentation.
"""
from RingerCore.util import checkForUnusedVars
Logger.__init__(self, kw)
self._matlabFlag = kw.pop('matlabFlag', False )
checkForUnusedVars( kw, self._logger.warning )
del kw
if len(args) > 3:
raise ValueError("Input more than 3 values, format should be [min=0:[incr=1:]]max")
if len(args) == 0:
raise ValueError("No input. Format should be [min=0,[incr=1,]]max")
if isinstance(args[0], LoopingBounds ):
self._vec = args[0]._vec
oldFlag = self._matlabFlag
self._matlabFlag = args[0]._matlabFlag
if oldFlag != self._matlabFlag:
if self._matlabFlag:
self.turnMatlabFlagOn()
else:
self.turnMatlabFlagOff()
return
elif isinstance(args[0], list ):
self._vec = args[0]
else:
self._vec = list(args)
if len(self._vec) == 1:
self._vec.append( self._vec[0] + 1 )
if not self._matlabFlag:
self._vec[1] -= 1
self._vec[0] = 1 if self._matlabFlag else 0
elif len(self._vec) == 2:
if self._matlabFlag:
self._vec[1] += 1
else:
tmp = self._vec[1]
if self._matlabFlag:
if tmp > 0:
self._vec[1] = self._vec[2] + 1
else:
self._vec[1] = self._vec[2] - 1
else:
self._vec[1] = self._vec[2]
self._vec[2] = tmp
if len(self._vec) == 3 and self._vec[2] == 0:
raise ValueError("Attempted to create looping bounds without increment.")
def __init__(self, ignoreAttrs = set(), toProtectedAttrs = set(), ignoreRawChildren = False, **kw ):
"""
-> ignoreAttrs: not consider this attributes on the dictionary values.
-> toProtectedAttrs: change public attributes to protected or private
attributes. That is, suppose the dictionary value is 'val' and the class
value should be _val or __val, then add toProtectedAttrs = ['_val'] or
'__val'.
-> ignoreRawChildren: Do not attempt to conver raw children to higher level object.
"""
Logger.__init__(self, kw)
ignoreAttrs = list(set(ignoreAttrs) | RawDictCnv.baseAttrs)
import re
self.ignoreAttrs = [re.compile(ignoreAttr) for ignoreAttr in ignoreAttrs]
self.toProtectedAttrs = set(toProtectedAttrs)
self.ignoreRawChildren = ignoreRawChildren
from RingerCore.util import checkForUnusedVars
checkForUnusedVars( kw, self._logger.warning )
def shape(self, **kw):
"""
Return shape using total number of observations and patterns.
Retuned shape will always be a matrix.
"""
if set(("npat","nfeat")) <= set(kw.keys()):
raise KeyError('Cannot use both pidx and fidx keywords')
npat = kw.pop('npat', None)
if npat is None: npat = kw.pop('nfeat', None)
nobs = kw.pop('nobs', None)
checkForUnusedVars(kw)
if npat is None:
npat = 1
if nobs is None:
nobs = 1
if self.__useFortran:
return (npat, nobs)
else:
return (nobs, npat)
def __init__(self, tes, **kw):
Logger.__init__( self, **kw )
import logging
self.baseDir = kw.pop('baseDir','')
self.bucketName = kw.pop('bucketName','')
self.pidName = kw.pop('pidName','tight')
self._level = kw.pop('level',logging.INFO)
self.appName = kw.pop('appName','TrigAnalysisTool')
checkForUnusedVars(kw)
del kw
self._logger.info('Start wrapper between python and c++ core.')
self._trigAnalysisTool = ROOT.TrigAnalysisTool(self.appName,
self.bucketName,
self.baseDir,
self.pidName,
self._level)
for te in tes:
self._trigAnalysisTool.push_back( te() )
self._logger.info('TrigAnalysisTool has been created.' )
