def titer_model(self, **kwargs):
'''
estimate a titer tree and substitution model using titers in titer_fname.
'''
from base.titer_model import tree_model, substitution_model
## TREE MODEL
self.titer_tree = tree_model(self.tree.tree, titer_fname = self.titer_fname, **kwargs)
self.titer_tree.prepare(**kwargs) # make training set, find subtree with titer measurements, and make_treegraph
self.titer_tree.train(**kwargs) # pick longest branch on path between each (test, ref) pair, assign titer drops to this branch
# then calculate a cumulative antigenic evolution score for each node
# add tree attributes to the list of attributes that are saved in intermediate files
for n in self.tree.tree.find_clades():
n.attr['cTiter'] = n.cTiter
n.attr['dTiter'] = n.dTiter
# SUBSTITUTION MODEL
self.titer_subs = substitution_model(self.tree.tree, titer_fname = self.titer_fname,**kwargs)
self.titer_subs.prepare(**kwargs)
self.titer_subs.train(**kwargs)
if kwargs['training_fraction'] != 1.0:
self.titer_tree.validate() #(plot=True, fname='treeModel_%s.png'%lineage)
self.titer_subs.validate() #(plot=True, fname='subModel_%s.png'%lineage)
logfile = open('params_log.tsv', 'a')
logfile.write('\t'.join(['substitution_model', lineage, '%.3f'%kwargs['lam_pot'], '%.3f'%kwargs['lam_avi'], '%.3f'%kwargs['lam_drop'], '%.3f'%self.titer_subs.abs_error, '%.3f'%self.titer_subs.rms_error, '%.3f'%self.titer_subs.r2])+'\n')
logfile.write('\t'.join(['tree_model', lineage, '%.3f'%kwargs['lam_pot'], '%.3f'%kwargs['lam_avi'], '%.3f'%kwargs['lam_drop'], '%.3f'%self.titer_tree.abs_error, '%.3f'%self.titer_tree.rms_error, '%.3f'%self.titer_tree.r2])+'\n')
logfile.close()
def HI_model(self):
'''
estimate a tree and substitution model using titers titer_fname.
'''
from base.titer_model import tree_model, substitution_model
## define the filenames here
fname = str(self.config["titers"]["fname"].replace("<LINEAGE>",
self.info["lineage"]))
## define the kwargs explicitly
kwargs = {}
if "criterium" in self.config["titers"]:
kwargs["criterium"] = self.config["titers"]["criterium"]
## TREE MODEL
self.HI_tree = tree_model(self.tree.tree, titer_fname=fname, **kwargs)
self.HI_tree.prepare(**kwargs)
self.HI_tree.train(**kwargs)
# add tree attributes to the list of attributes that are saved in intermediate files
for n in self.tree.tree.find_clades():
n.attr['cTiter'] = n.cTiter
n.attr['dTiter'] = n.dTiter
# print("cumulative: {} delta: {}".format(n.cTiter, n.dTiter))
self.config["auspice"]["color_options"]["cTiter"] = {
"menuItem": "antigenic advance",
"type": "continuous",
"legendTitle": "Antigenic Advance",
"key": "cTiter"
}
def HI_model(self, titer_fname, **kwargs):
'''
estimate a tree and substitution model using titers titer_fname.
'''
from base.titer_model import tree_model, substitution_model
## TREE MODEL
self.HI_tree = tree_model(self.tree.tree, titer_fname = titer_fname, **kwargs)
self.HI_tree.prepare(**kwargs)
self.HI_tree.train(**kwargs)
# add tree attributes to the list of attributes that are saved in intermediate files
self.tree.dump_attr.extend(['cTiter', 'dTiter'])
# SUBSTITION MODEL
self.HI_subs = substitution_model(self.tree.tree, titer_fname = titer_fname,**kwargs)
self.HI_subs.prepare(**kwargs)
self.HI_subs.train(**kwargs)
def HI_model(self, **kwargs):
'''
estimate a tree and substitution model using titers titer_fname.
'''
from base.titer_model import tree_model, substitution_model
## TREE MODEL
self.HI_tree = tree_model(self.tree.tree, titer_fname = self.HI_titer_fname, **kwargs)
self.HI_tree.prepare(**kwargs)
self.HI_tree.train(**kwargs)
# add tree attributes to the list of attributes that are saved in intermediate files
for n in self.tree.tree.find_clades():
n.attr['cTiter'] = n.cTiter
n.attr['dTiter'] = n.dTiter
# SUBSTITUTION MODEL
self.HI_subs = substitution_model(self.tree.tree, titer_fname = self.HI_titer_fname,**kwargs)
self.HI_subs.prepare(**kwargs)
self.HI_subs.train(**kwargs)