def create(self,score):
"""
Create an McmData ORM object (hpf.hddb.db.McmData, hpf table mcm) from a Mammoth score.
Entities:
experiment_key - structure ID of "experiment" source entry in McmDB obj that cluster center was compared against
experiment - McmDB Struct object with ID = experiment_key. All from mcmdb data.mammothDb file entries.
- Struct(id, sequence_key, length, percent_alpha/beta, sccs, astral_ac)
Parameters:
score - hpf.mcm.mammoth.MammothScore object
Returns an McmData ORM object corresponding to the given mammoth score
"""
#?#TODO: Include values here to FULLY populate McmData ORM object. That way, return McmData
#?#TODO: objects can be added without modification to the DB
##NOTE: Leave outfile_mcm_result_key NULL (was used to reprsent MCM xml log files)
# sequence_key
# outfile_key
# convergence_key
# structure_key
# astral_structure_key
from hpf.hddb.db import McmData
experiment_key = int(score.experiment.split(".")[0])
experiment = self.mcmdb[experiment_key]
prob,ratio,aratio,bratio,ssclass = self.probability(score=score,
pred_percent_alpha=self.percent_alpha,
pred_percent_beta=self.percent_beta,
convergence=self.convergence_radius1,
experiment=experiment)
if self.debug: print "MCM probability: {0} {1} {2} {3} {4} {5}".format(experiment.id,
score.prediction, score.zscore, prob, ratio, ssclass)
data= McmData(ratio = ratio,
aratio = aratio,
bratio = bratio,
percent_alpha = self.percent_alpha,
percent_beta = self.percent_beta,
astral_percent_alpha = experiment.percent_alpha,
astral_percent_beta = experiment.percent_beta,
sequence_length = int(score.num_p),
astral_sequence_length = int(score.num_e),
probability = prob,
sccs = experiment.sccs,
scop = self.mcmdb.scop,
)
# "class" is a reserved word in python
data.__dict__["class"] = ssclass
# MammothScore object is saved in McmData object to make DB storage easier
data.mammoth = score
return data
def create(self,score):
"""
Create an McmData ORM object (hpf.hddb.db.McmData, hpf table mcm) from a Mammoth score.
Patrick:
Conspicuously missing from here is an 'outfile_key'. This is tricky. McmData objects
store EVERYTHING compiled from Rosetta clustering runs, mammoth, and the mcm database.
Entities:
experiment_key - structure ID of "experiment" source entry in McmDB obj that cluster center was compared against
experiment - McmDB Struct object with ID = experiment_key. All from mcmdb data.mammothDb file entries.
- Struct(id, sequence_key, length, percent_alpha/beta, sccs, astral_ac)
prediction - hpf.mcm.cluster.ClusterCenter object from convergence task (TODO: CHANGE)
Parameters:
score - hpf.mcm.mammoth.MammothScore object
Returns an McmData ORM object corresponding to the given mammoth score
"""
from hpf.hddb.db import McmData
experiment_key = int(score.experiment.split(".")[0])
experiment = self.mcmdb[experiment_key]
prediction = self.convergence[score.prediction]
prob,ratio,aratio,bratio,ssclass = self.probability(score,prediction,experiment)
e = experiment
p = prediction
s = score
print "probability: ", e.id, p.index, s.zscore, prob, ratio, ssclass
data= McmData(ratio = ratio,
aratio = aratio,
bratio = bratio,
percent_alpha = p.percent_alpha,
percent_beta = p.percent_beta,
astral_percent_alpha = e.percent_alpha,
astral_percent_beta = e.percent_beta,
sequence_length = s.num_p,
astral_sequence_length = int(s.num_e),
probability = prob,
sccs = e.sccs,
scop = self.mcmdb.scop,
)
# "class" is a reserved word in python
data.__dict__["class"] = ssclass
data.mammoth = score
return data