diff --git a/lalburst/python/lalburst/ligolw_burca2.py b/lalburst/python/lalburst/ligolw_burca2.py
index db576a70a7be295cba6a50befbe2e092e151d09a..0d7fda2aa0eedc60b7b62af83fb20b6645071e62 100644
--- a/lalburst/python/lalburst/ligolw_burca2.py
+++ b/lalburst/python/lalburst/ligolw_burca2.py
@@ -51,7 +51,7 @@ from git_version import version as __version__
#
-def assign_likelihood_ratios(connection, coinc_def_id, offset_vectors, vetoseglists, events_func, veto_func, ln_likelihood_ratio_func, likelihood_params_func, verbose = False, params_func_extra_args = ()):
+def assign_likelihood_ratios(connection, coinc_def_id, offset_vectors, vetoseglists, events_func, veto_func, ln_likelihood_ratio_func, verbose = False):
"""
Assigns likelihood ratio values to coincidences.
"""
@@ -77,8 +77,7 @@ def assign_likelihood_ratios(connection, coinc_def_id, offset_vectors, vetosegli
def ln_likelihood_ratio(coinc_event_id, time_slide_id):
try:
- params = likelihood_params_func([event for event in events_func(cursor, coinc_event_id) if veto_func(event, vetoseglists)], offset_vectors[time_slide_id], *params_func_extra_args)
- return ln_likelihood_ratio_func(params) if params is not None else None
+ return ln_likelihood_ratio_func([event for event in events_func(cursor, coinc_event_id) if veto_func(event, vetoseglists)], offset_vectors[time_slide_id])
except:
traceback.print_exc()
raise
@@ -109,7 +108,7 @@ WHERE
cursor.close()
-def assign_likelihood_ratios_xml(xmldoc, coinc_def_id, offset_vectors, vetoseglists, events_func, veto_func, ln_likelihood_ratio_func, likelihood_params_func, verbose = False, params_func_extra_args = ()):
+def assign_likelihood_ratios_xml(xmldoc, coinc_def_id, offset_vectors, vetoseglists, events_func, veto_func, ln_likelihood_ratio_func, verbose = False):
"""
Assigns likelihood ratio values to coincidences (XML version).
"""
@@ -129,8 +128,7 @@ def assign_likelihood_ratios_xml(xmldoc, coinc_def_id, offset_vectors, vetosegli
progressbar.increment()
if coinc_event.coinc_def_id != coinc_def_id:
continue
- params = likelihood_params_func([event for event in events_func(None, coinc_event.coinc_event_id) if veto_func(event, vetoseglists)], offset_vectors[coinc_event.time_slide_id], *params_func_extra_args)
- coinc_event.likelihood = ln_likelihood_ratio_func(params) if params is not None else None
+ coinc_event.likelihood = ln_likelihood_ratio_func([event for event in events_func(None, coinc_event.coinc_event_id) if veto_func(event, vetoseglists)], offset_vectors[coinc_event.time_slide_id])
del progressbar
@@ -166,11 +164,9 @@ def sngl_burst_veto_func(event, vetoseglists):
return event.ifo not in vetoseglists or event.peak not in vetoseglists[event.ifo]
-def ligolw_burca2(database, ln_likelihood_ratio, params_func, verbose = False, params_func_extra_args = ()):
+def ligolw_burca2(database, ln_likelihood_ratio_func, verbose = False):
"""
Assigns likelihood ratio values to excess power coincidences.
- database is lalburst.SnglBurstUtils.CoincDatabase instance, and
- ln_likelihood_ratio is a LnLikelihoodRatio class instance.
"""
#
# Run core function
@@ -183,10 +179,8 @@ def ligolw_burca2(database, ln_likelihood_ratio, params_func, verbose = False, p
vetoseglists = database.vetoseglists,
events_func = lambda cursor, coinc_event_id: sngl_burst_events_func(cursor, coinc_event_id, database.sngl_burst_table.row_from_cols),
veto_func = sngl_burst_veto_func,
- ln_likelihood_ratio_func = ln_likelihood_ratio,
- likelihood_params_func = params_func,
- verbose = verbose,
- params_func_extra_args = params_func_extra_args
+ ln_likelihood_ratio_func = ln_likelihood_ratio_func,
+ verbose = verbose
)
#
diff --git a/lalburst/python/lalburst/snglcoinc.py b/lalburst/python/lalburst/snglcoinc.py
index c8ebfd9351ba05a5ca67fba1a038f6d2fc5f63b6..287f8931d2d86cc45b5666c91af1c5d6ed1660b0 100644
--- a/lalburst/python/lalburst/snglcoinc.py
+++ b/lalburst/python/lalburst/snglcoinc.py
@@ -1535,12 +1535,12 @@ class LnLRDensity(object):
histogram of the candidates observed in a search.
Typically, the ranking statistic implementation will provide a
- function to transform a candidate to a "params" object for use with
- the .__call__() implementation, and so in this way a LnLRDensity
- object is generally only meaningful in the context of the ranking
+ function to transform a candidate to the arguments to use with the
+ .__call__() implementation, and so in this way a LnLRDensity object
+ is generally only meaningful in the context of the ranking
statistic class for which it has been constructed.
"""
- def __call__(self, params):
+ def __call__(self, *args, **kwargs):
"""
Evaluate. Return the natural logarithm of the density
evaluated at the given parameters.
@@ -1553,10 +1553,10 @@ class LnLRDensity(object):
"""
raise NotImplementedError
- def increment(self, params, weight = 1.0):
+ def increment(self, *args, **kwargs):
"""
- Increment the counts defining this density by weight
- (default = 1) at the given parameters.
+ Increment the counts defining this density at the given
+ parameters.
"""
raise NotImplementedError
@@ -2120,7 +2120,7 @@ class LnLikelihoodRatioMixin(object):
warnings.warn("inf/inf encountered")
return lnP_signal - lnP_noise
- def ln_lr_samples(self, random_params_seq, sampler_coinc_params = None, **kwargs):
+ def ln_lr_samples(self, random_params_seq, sampler_coinc_params = None):
"""
Generator that yields an unending sequence of 3-element
tuples. Each tuple's elements are a value of the natural
@@ -2139,15 +2139,16 @@ class LnLikelihoodRatioMixin(object):
the two populations.
random_params_seq is a sequence (generator is OK) yielding
- 2-element tuples whose first element is a choice of
- parameter values and whose second element is the natural
+ 3-element tuples whose first two elements provide the *args
+ and **kwargs values passed to the numerator and denominator
+ density functions, and whose thrid element is the natural
logarithm of the probability density from which the
parameters have been drawn evaluated at the parameters.
- On each iteration, the sample of parameter values yielded
- by random_params_seq is passed to our own .__call__()
- method to evalute the log likelihood ratio at that choice
- of parameter values. If sampler_coinc_params is None the
+ On each iteration, the *args and **kwargs values yielded by
+ random_params_seq is passed to our own .__call__() method
+ to evalute the log likelihood ratio at that choice of
+ parameter values. If sampler_coinc_params is None the
parameters are also passed to the .__call__() mehods of the
.numerator and .denominator attributes of self to obtain
the signal and noise population densities at those
@@ -2166,7 +2167,7 @@ class LnLikelihoodRatioMixin(object):
else:
lnP_signal_func = sampler_coinc_params.numerator
lnP_noise_func = sampler_coinc_params.denominator
- for params, lnP_params in random_params_seq:
- lnP_signal = lnP_signal_func(params, **kwargs)
- lnP_noise = lnP_noise_func(params, **kwargs)
- yield self(params, **kwargs), lnP_signal - lnP_params, lnP_noise - lnP_params
+ for args, kwargs, lnP_params in random_params_seq:
+ lnP_signal = lnP_signal_func(*args, **kwargs)
+ lnP_noise = lnP_noise_func(*args, **kwargs)
+ yield self(*args, **kwargs), lnP_signal - lnP_params, lnP_noise - lnP_params
diff --git a/lalinspiral/python/lalinspiral/thinca.py b/lalinspiral/python/lalinspiral/thinca.py
index 95ede85be71a79e8e6b56fcd2917ec648ec4cb50..82d770fdac9eadcfefa5854cda026a4ffc481f59 100644
--- a/lalinspiral/python/lalinspiral/thinca.py
+++ b/lalinspiral/python/lalinspiral/thinca.py
@@ -109,17 +109,14 @@ InspiralCoincDef = lsctables.CoincDef(search = u"inspiral", search_coinc_type =
class InspiralCoincTables(snglcoinc.CoincTables):
- def __init__(self, xmldoc, likelihood_func = None, likelihood_params_func = None):
+ def __init__(self, xmldoc, likelihood_func = None):
snglcoinc.CoincTables.__init__(self, xmldoc)
#
# configure the likelihood ratio evaluator
#
- if likelihood_func is None and likelihood_params_func is not None or likelihood_func is not None and likelihood_params_func is None:
- raise ValueError("must provide both a likelihood function and a parameter function or neither")
self.likelihood_func = likelihood_func
- self.likelihood_params_func = likelihood_params_func
#
# find the coinc_inspiral table or create one if not found
@@ -177,7 +174,7 @@ class InspiralCoincTables(snglcoinc.CoincTables):
#
if self.likelihood_func is not None:
- coinc.likelihood = self.likelihood_func(self.likelihood_params_func(events, offsetvector))
+ coinc.likelihood = self.likelihood_func(events, offsetvector)
#
# done
@@ -343,7 +340,6 @@ def ligolw_thinca(
seglists = None,
veto_segments = None,
likelihood_func = None,
- likelihood_params_func = None,
min_instruments = 2,
min_log_L = None,
verbose = False
@@ -363,7 +359,7 @@ def ligolw_thinca(
if verbose:
print("indexing ...", file=sys.stderr)
- coinc_tables = InspiralCoincTables(xmldoc, likelihood_func = likelihood_func, likelihood_params_func = likelihood_params_func)
+ coinc_tables = InspiralCoincTables(xmldoc, likelihood_func = likelihood_func)
coinc_def_id = ligolw_coincs.get_coinc_def_id(xmldoc, coinc_definer_row.search, coinc_definer_row.search_coinc_type, create_new = True, description = coinc_definer_row.description)
instruments = set(coinc_tables.time_slide_table.getColumnByName("instrument"))