def add_operators(self, beastxml):
xml.operator(beastxml.run,
id="PopulationSizeScaler.t:beastlingTree",
spec="ScaleOperator",
parameter="@popSize.t:beastlingTree",
scaleFactor="0.5",
weight="3.0")
def add_operators(self, beastxml):
if beastxml.config.languages.sample_branch_lengths:
updown = xml.operator(
beastxml.run,
attrib={
"id": "UpDown",
"spec": "UpDownOperator",
"scaleFactor": "0.5",
"weight": "3.0"})
xml.tree(updown, idref="Tree.t:beastlingTree", name="up")
xml.parameter(updown, idref="birthRate.t:beastlingTree", name="down")
### Include clock rates in up/down only if calibrations are given
if beastxml.config.calibrations:
for clock in beastxml.config.clocks:
if clock.estimate_rate:
xml.parameter(updown, idref=clock.mean_rate_id, name="down")
# Birth rate scaler
# Birth rate is *always* scaled.
xml.operator(
beastxml.run,
attrib={"id": "YuleBirthRateScaler.t:beastlingTree",
"spec": "ScaleOperator",
"parameter": "@birthRate.t:beastlingTree",
"scaleFactor": "0.5",
"weight": "3.0"})
def add_frequency_operators(self, run):
for name in self.parameter_identifiers():
xml.operator(run,
id="frequency_sampler.s:%s" % name,
spec="DeltaExchangeOperator",
parameter="@freqs_param.s:%s" % name,
delta="0.01",
weight="1.0")
def add_frequency_operators(self, run):
for fname in self.parameter_identifiers():
xml.operator(
run,
id="%s:pdcovarion_frequency_sampler.s" % fname,
spec="DeltaExchangeOperator",
parameter="@%s:visiblefrequencies.s" % fname,
delta="0.01",
weight="1.0")
def add_operators(self, run):
if self.estimate_rate:
# Scale mean clock rate
xml.operator(run,
id="clockScaler.c:%s" % self.name,
spec="ScaleOperator",
parameter="@clockRate.c:%s" % self.name,
scaleFactor="0.5",
weight="3.0")
def add_frequency_operators(self, run):
for f in self.features:
fname = "%s:%s" % (self.name, f)
xml.operator(run,
id="estimatedFrequencyOperator:%s" % fname,
spec="DeltaExchangeOperator",
parameter="@feature_freqs_param.s:%s" % fname,
delta="0.01",
weight="0.1")
def add_operators(self, run):
BaseModel.add_operators(self, run)
if self.gamma_categories > 0:
xml.operator(run,
id="gammaShapeScaler.s:%s" % self.name,
spec="ScaleOperator",
parameter="@gammaShape.s:%s" % self.name,
scaleFactor="0.5",
weight="0.1")
def add_operators(self, run):
RelaxedClock.add_operators(self, run)
# Sample lognormal stddev
if self.estimate_variance:
xml.operator(run,
id="ucldSdevScaler.c:%s" % self.name,
spec="ScaleOperator",
parameter="@ucldSdev.c:%s" % self.name,
scaleFactor="0.5",
weight="3.0")
def _add_operators(self, run, name):
xml.operator(run,
id="covarion_alpha_scaler.s:%s" % name,
spec="ScaleOperator",
parameter="@covarion_alpha.s:%s" % name,
scaleFactor="0.5",
weight="1.0")
xml.operator(run,
id="%s:covarion_s_scaler.s" % name,
spec="ScaleOperator",
parameter="@covarion_s.s:%s" % name,
scaleFactor="0.5",
weight="1.0")
def add_operators(self, run):
BaseModel.add_operators(self, run)
for n, f in enumerate(self.features):
fname = "%s:%s" % (self.name, f)
xml.operator(
run,
id="onGeorateScaler.s:%s" % fname,
spec="ScaleOperator",
parameter="@relativeGeoRates.s:%s" % fname,
indicator="@rateIndicator.s:%s" % fname,
scaleAllIndependently="true",
scaleFactor="0.5",
weight="10.0")
if self.rate_variation:
xml.operator(
run,
id="BSSVSoperator.c:%s" % fname,
spec="BitFlipBSSVSOperator",
indicator="@rateIndicator.s:%s" % fname,
mu="@featureClockRate:%s" % fname,
weight="30.0")
bssvs_bitflip = True
elif not self.global_config.arbitrary_tree:
# Don't scale the clock of a tree with arbitrary branch
# lengths, as birthRate is also scaled and one or the other
# will run away to infinity.
xml.operator(
run,
id="BSSVSoperator.c:%s" % fname,
spec="BitFlipBSSVSOperator",
indicator="@rateIndicator.s:%s" % fname,
mu=self.clock.mean_rate_idref,
weight="30.0")
bssvs_bitflip = True
else:
bssvs_bitflip = False
xml.operator(
run,
id="indicatorFlip.s:%s" % fname,
spec="BitFlipOperator",
parameter="@rateIndicator.s:%s" % fname,
weight="30.0" if bssvs_bitflip else "60.0")
sampoffop = xml.operator(
run,
id="offGeorateSampler:%s" % fname,
spec="SampleOffValues",
all="false",
values="@relativeGeoRates.s:%s" % fname,
indicators="@rateIndicator.s:%s" % fname,
weight="30.0")
xml.dist(sampoffop, idref="Gamma:%s.%d.0" % (fname, n))
def add_operators(self, run):
"""
Add <operators> for individual feature substitution rates if rate
variation is configured.
"""
if self.scale_precision:
xml.operator(run,
id="sphericalPrecisionScaler",
spec="ScaleOperator",
parameter="@sphericalPrecision",
weight="5",
scaleFactor="0.7")
if self.sampling_points:
xml.operator(run,
id="location.sampler",
spec="sphericalGeo.LocationOperatorF",
location="@location.geo",
likelihood="@sphericalGeographyLikelihood",
weight="10")
def add_operators(self, run):
RelaxedClock.add_operators(self, run)
updown = xml.operator(run,
id="relaxedClockGammaUpDown:%s" % self.name,
spec="UpDownOperator",
scaleFactor="0.5",
weight="3.0")
xml.parameter(updown,
idref="clockRateGammaShape:%s" % self.name,
name="up")
xml.parameter(updown,
idref="clockRateGammaScale:%s" % self.name,
name="down")
def add_operators(self, run):
BaseClock.add_operators(self, run)
# Operate on indicators
xml.operator(run,
id="IndicatorsBitFlip.c:%s" % self.name,
spec="BitFlipOperator",
parameter="@Indicators.c:%s" % self.name,
weight="15.0")
# Operate on branch rates
xml.operator(run,
id="ClockRateScaler.c:%s" % self.name,
spec="ScaleOperator",
parameter="@clockrates.c:%s" % self.name,
scaleFactor="0.5",
weight="15.0")
# Up/down for Gamma params
if self.estimate_variance:
updown = xml.operator(run,
id="randomClockGammaUpDown:%s" % self.name,
spec="UpDownOperator",
scaleFactor="0.5",
weight="1.0")
xml.parameter(updown, idref=self.shape_id, name="up")
xml.parameter(updown, idref=self.scale_id, name="down")
def add_operators(self):
"""
Add all <operator> elements.
"""
self.add_tree_operators()
for clock in self.config.clocks:
clock.add_operators(self.run)
for model in self.config.all_models:
model.add_operators(self.run)
# Add one DeltaExchangeOperator for feature rates per clock
for clock in self.config.clocks:
clock_models = [
m for m in self.config.models
if m.rate_variation and m.clock == clock
]
if not clock_models:
continue
# Add one big DeltaExchangeOperator which operates on all
# feature clock rates from all models
delta = xml.operator(self.run,
id="featureClockRateDeltaExchanger:%s" %
clock.name,
spec="DeltaExchangeOperator",
weight="3.0")
for model in clock_models:
xml.parameter(xml.plate(delta,
var="rate",
range=model.all_rates),
idref="featureClockRate:%s:$(rate)" % model.name)
# Add weight vector if there has been any binarisation
if any([
w != 1 for w in itertools.chain(
*[m.weights for m in clock_models])
]):
xml.weightvector(
delta,
text=" ".join(
itertools.chain(
*[map(str, m.weights) for m in clock_models])),
id="featureClockRateWeightParameter:%s" % clock.name,
spec="parameter.IntegerParameter",
dimension=str(sum([len(m.weights) for m in clock_models])),
estimate="false")
def add_operators(self, run):
"""
Add <operators> for individual feature substitution rates if rate
variation is configured.
"""
if self.frequencies == "estimate":
self.add_frequency_operators(run)
if self.rate_variation:
# UpDownOperator to scale the Gamma distribution for this model's
# feature rates
updown = xml.operator(run,
id="featureClockRateGammaUpDown:%s" %
self.name,
spec="UpDownOperator",
scaleFactor="0.5",
weight="0.3")
xml.parameter(updown,
idref="featureClockRateGammaShape:%s" % self.name,
name="up")
xml.parameter(updown,
idref="featureClockRateGammaScale:%s" % self.name,
name="down")
def add_operators(self, run):
BaseClock.add_operators(self, run)
# Add category operators
xml.operator(run,
id="rateCategoriesRandomWalkOperator.c:%s" % self.name,
spec="IntRandomWalkOperator",
parameter="@rateCategories.c:%s" % self.name,
windowSize="1",
weight="10.0")
xml.operator(run,
id="rateCategoriesSwapOperator.c:%s" % self.name,
spec="SwapOperator",
intparameter="@rateCategories.c:%s" % self.name,
weight="10.0")
xml.operator(run,
id="rateCategoriesUniformOperator.c:%s" % self.name,
spec="UniformOperator",
parameter="@rateCategories.c:%s" % self.name,
weight="10.0")
def _add_operators(self, run, name):
xml.operator(
run,
id="%s:pdcovarion_origin_scaler.s" % name,
spec="ScaleOperator",
parameter="@%s:pdcovarion_origin.s" % name,
scaleFactor="0.75",
weight="0.1")
xml.operator(
run,
id="%s:pdcovarion_s_scaler.s" % name,
spec="ScaleOperator",
parameter="@%s:pdcovarion_s.s" % name,
scaleFactor="0.75",
weight="0.1")
xml.operator(
run,
id="%s:pdcovarion_death_scaler.s" % name,
spec="ScaleOperator",
parameter="@%s:pdcovarion_death.s" % name,
scaleFactor="0.75",
weight="0.1")
def add_operators(self, beastxml):
"""
Add all <operator>s which act on the tree topology and branch lengths.
"""
# Tree operators
# Operators which affect the tree must respect the sample_topology and
# sample_branch_length options.
if beastxml.config.languages.sample_topology:
## Tree topology operators
xml.operator(beastxml.run, attrib={"id":"SubtreeSlide.t:beastlingTree","spec":"SubtreeSlide","tree":"@Tree.t:beastlingTree","markclades":"true", "weight":"15.0"})
xml.operator(beastxml.run, attrib={"id":"narrow.t:beastlingTree","spec":"Exchange","tree":"@Tree.t:beastlingTree","markclades":"true", "weight":"15.0"})
xml.operator(beastxml.run, attrib={"id":"wide.t:beastlingTree","isNarrow":"false","spec":"Exchange","tree":"@Tree.t:beastlingTree","markclades":"true", "weight":"3.0"})
xml.operator(beastxml.run, attrib={"id":"WilsonBalding.t:beastlingTree","spec":"WilsonBalding","tree":"@Tree.t:beastlingTree","markclades":"true","weight":"3.0"})
if beastxml.config.languages.sample_branch_lengths:
## Branch length operators
xml.operator(beastxml.run, attrib={"id":"UniformOperator.t:beastlingTree","spec":"Uniform","tree":"@Tree.t:beastlingTree","weight":"30.0"})
xml.operator(beastxml.run, attrib={"id":"treeScaler.t:beastlingTree","scaleFactor":"0.5","spec":"ScaleOperator","tree":"@Tree.t:beastlingTree","weight":"3.0"})
xml.operator(beastxml.run, attrib={"id":"treeRootScaler.t:beastlingTree","scaleFactor":"0.5","spec":"ScaleOperator","tree":"@Tree.t:beastlingTree","rootOnly":"true","weight":"3.0"})
## Up/down operator which scales tree height
# Add a Tip Date scaling operator if required
if beastxml.config.tip_calibrations and beastxml.config.languages.sample_branch_lengths:
# Get a list of taxa with non-point tip cals
tip_taxa = [next(cal.langs.__iter__()) for cal in beastxml.config.tip_calibrations.values() if cal.dist != "point"]
for taxon in tip_taxa:
tiprandomwalker = xml.operator(
beastxml.run,
attrib={"id": "TipDatesandomWalker:%s" % taxon,
"spec": "TipDatesRandomWalker",
"windowSize": "1",
"tree": "@Tree.t:beastlingTree",
"weight": "3.0",
})
beastxml.add_taxon_set(tiprandomwalker, taxon, (taxon,))
def add_operators(self, beastxml):
"""
Add all <operator>s which act on the tree topology and branch lengths.
"""
"""
Add all <operator>s which act on the tree topology and branch lengths.
"""
# Tree operators
# Operators which affect the tree must respect the sample_topology and
# sample_branch_length options.
if beastxml.config.languages.sample_topology:
## Tree topology operators
xml.operator(beastxml.run,
attrib={
"id": "SubtreeSlide.t:beastlingTree",
"spec": "SubtreeSlide",
"tree": "@Tree.t:beastlingTree",
"markclades": "true",
"weight": "15.0"
})
xml.operator(beastxml.run,
attrib={
"id": "narrow.t:beastlingTree",
"spec": "Exchange",
"tree": "@Tree.t:beastlingTree",
"markclades": "true",
"weight": "15.0"
})
xml.operator(beastxml.run,
attrib={
"id": "wide.t:beastlingTree",
"isNarrow": "false",
"spec": "Exchange",
"tree": "@Tree.t:beastlingTree",
"markclades": "true",
"weight": "3.0"
})
xml.operator(beastxml.run,
attrib={
"id": "WilsonBalding.t:beastlingTree",
"spec": "WilsonBalding",
"tree": "@Tree.t:beastlingTree",
"markclades": "true",
"weight": "3.0"
})
if beastxml.config.languages.sample_branch_lengths:
## Branch length operators
xml.operator(beastxml.run,
attrib={
"id": "UniformOperator.t:beastlingTree",
"spec": "Uniform",
"tree": "@Tree.t:beastlingTree",
"weight": "30.0"
})
xml.operator(beastxml.run,
attrib={
"id": "treeScaler.t:beastlingTree",
"scaleFactor": "0.5",
"spec": "ScaleOperator",
"tree": "@Tree.t:beastlingTree",
"weight": "3.0"
})
xml.operator(beastxml.run,
attrib={
"id": "treeRootScaler.t:beastlingTree",
"scaleFactor": "0.5",
"spec": "ScaleOperator",
"tree": "@Tree.t:beastlingTree",
"rootOnly": "true",
"weight": "3.0"
})
## Up/down operator which scales tree height
if self.type in ["yule", "birthdeath"]:
updown = xml.operator(beastxml.run,
attrib={
"id": "UpDown",
"spec": "UpDownOperator",
"scaleFactor": "0.5",
"weight": "3.0"
})
xml.tree(updown, idref="Tree.t:beastlingTree", name="up")
xml.parameter(updown,
idref="birthRate.t:beastlingTree",
name="down")
### Include clock rates in up/down only if calibrations are given
if beastxml.config.calibrations:
for clock in beastxml.config.clocks:
if clock.estimate_rate:
xml.parameter(updown,
idref=clock.mean_rate_id,
name="down")
if self.type in ["yule", "birthdeath"]:
# Birth rate scaler
# Birth rate is *always* scaled.
xml.operator(beastxml.run,
attrib={
"id": "YuleBirthRateScaler.t:beastlingTree",
"spec": "ScaleOperator",
"parameter": "@birthRate.t:beastlingTree",
"scaleFactor": "0.5",
"weight": "3.0"
})
elif self.type == "coalescent":
xml.operator(beastxml.run,
attrib={
"id": "PopulationSizeScaler.t:beastlingTree",
"spec": "ScaleOperator",
"parameter": "@popSize.t:beastlingTree",
"scaleFactor": "0.5",
"weight": "3.0"
})
if self.type in ["birthdeath"]:
xml.operator(beastxml.run,
attrib={
"id": "SamplingScaler.t:beastlingTree",
"spec": "ScaleOperator",
"parameter": "@sampling.t:beastlingTree",
"scaleFactor": "0.8",
"weight": "1.0"
})
xml.operator(beastxml.run,
attrib={
"id": "DeathRateScaler.t:beastlingTree",
"spec": "ScaleOperator",
"parameter": "@deathRate.t:beastlingTree",
"scaleFactor": "0.5",
"weight": "3.0"
})
# Add a Tip Date scaling operator if required
if beastxml.config.tip_calibrations and beastxml.config.languages.sample_branch_lengths:
# Get a list of taxa with non-point tip cals
tip_taxa = [
next(cal.langs.__iter__())
for cal in beastxml.config.tip_calibrations.values()
if cal.dist != "point"
]
for taxon in tip_taxa:
tiprandomwalker = xml.operator(beastxml.run,
attrib={
"id":
"TipDatesandomWalker:%s" %
taxon,
"spec":
"TipDatesRandomWalker",
"windowSize":
"1",
"tree":
"@Tree.t:beastlingTree",
"weight":
"3.0",
})
beastxml.add_taxon_set(tiprandomwalker, taxon, (taxon, ))
