def optimizeTree(tree):
if "comments" in optimize:
commentoptimizer.patch(tree)
# "variants" prunes parts of the tree, so all subsequent optimizations benefit
if "variants" in optimize:
variantoptimizer.search(tree, variantSet, self.id)
# 'statics' has to come before 'privates', as it needs the original key names in tree
# if features should be removed recursively, this has to be controlled on the calling
# level.
if "statics" in optimize:
if not featureMap:
console.warn(
"Empty feature map passed to static methods optimization; skipping"
)
elif self.type == 'static' and self.id in featureMap:
featureoptimizer.patch(tree, self, featureMap)
if "basecalls" in optimize:
basecalloptimizer.patch(tree)
if "privates" in optimize:
privatesMap = load_privates()
privateoptimizer.patch(tree, id, privatesMap)
write_privates(privatesMap)
if "strings" in optimize:
tree = self._stringOptimizer(tree)
if "variables" in optimize:
variableoptimizer.search(tree)
return tree
def optimizeTree(tree):
if "comments" in optimize:
commentoptimizer.patch(tree)
# "variants" prunes parts of the tree, so all subsequent optimizations benefit
if "variants" in optimize:
variantoptimizer.search(tree, variantSet, self.id)
# 'statics' has to come before 'privates', as it needs the original key names in tree
# if features should be removed recursively, this has to be controlled on the calling
# level.
if "statics" in optimize:
if not featureMap:
console.warn(
"Empty feature map passed to static methods optimization; skipping"
)
elif self.type == 'static' and self.id in featureMap:
optimzed_features = featureoptimizer.patch(
tree, self, featureMap)
if optimzed_features:
optimized_statics_overall = load_features()
copy = optimized_statics_overall.copy()
copy.update(optimzed_features)
write_features(copy)
if "basecalls" in optimize:
basecalloptimizer.patch(tree)
if "privates" in optimize:
privatesMap = load_privates()
privateoptimizer.patch(tree, id, privatesMap)
write_privates(privatesMap)
if "globals" in optimize:
tree = globalsoptimizer.process(
tree
) # need to re-assign as this optimizer might change the root node
if "strings" in optimize:
tree = stringoptimizer.process(tree, self.id)
if "variables" in optimize:
variableoptimizer.search(tree)
return tree
