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()