def train(self):
dvc = DVC(bind=False,
organization='NMGRLData')
dvc.db.trait_set(name='pychronmeta1',
username=os.environ.get('ARGONSERVER_DB_USER'),
password=os.environ.get('ARGONSERVER_DB_PWD'),
kind='mysql',
host=os.environ.get('ARGONSERVER_HOST'))
dvc.connect()
isos = []
klasses = []
uuids = UUIDS
with dvc.session_ctx():
for uuid in uuids:
broke = False
dbai = dvc.get_analysis_uuid(uuid)
ai = dvc.make_analyses((dbai,))[0]
ai.load_raw_data()
for iso in ai.isotopes.values():
klass = self._get_klass(iso)
if klass is not None:
isos.append(iso)
klasses.append(klass)
else:
broke = True
break
if broke:
break
if isos:
clf = IsotopeClassifier()
clf.add_isotopes(isos, klasses)
clf.dump()
class IsotopeHealth(Loggable):
def __init__(self, *args, **kw):
super(IsotopeHealth, self).__init__(*args, **kw)
self._clf = IsotopeClassifier()
def check(self, iso, tol=0.5):
k, p = self._clf.predict(make_sample(iso))
self.debug('check {} {} {}'.format(iso.name, k, p))
if k is not None:
if not k and p > tol:
self.info('Isotope {} classified bad: {}<{}'.format(iso.name, p, tol))
return True
def train(self):
dvc = DVC(bind=False, organization='NMGRLData')
dvc.db.trait_set(name='pychronmeta1',
username=os.environ.get('ARGONSERVER_DB_USER'),
password=os.environ.get('ARGONSERVER_DB_PWD'),
kind='mysql',
host=os.environ.get('ARGONSERVER_HOST'))
dvc.connect()
isos = []
klasses = []
uuids = UUIDS
with dvc.session_ctx():
for uuid in uuids:
broke = False
dbai = dvc.get_analysis_uuid(uuid)
ai = dvc.make_analyses((dbai, ))[0]
ai.load_raw_data()
for iso in ai.isotopes.values():
klass = self._get_klass(iso)
if klass is not None:
isos.append(iso)
klasses.append(klass)
else:
broke = True
break
if broke:
break
if isos:
clf = IsotopeClassifier()
clf.add_isotopes(isos, klasses)
clf.dump()
def __init__(self, *args, **kw):
super(IsotopeHealth, self).__init__(*args, **kw)
self._clf = IsotopeClassifier()
