def __init__( self, modelClass ):
Adaptor.__init__( self )
SqlAlchemyAdaptor._adaptors[modelClass] = self
table = modelClass.__table__
self.setTypeName( modelClass.__name__)
primary=[]
for c in table.columns:
if c.primary_key:
primary.append(c.name)
try:
self.addAttribute(c.name, c.type.python_type, editable=not c.primary_key)
# For Geometry type, which doesn't implement python_type yet.
except NotImplementedError:
pass
if len(primary) == 1:
self.setIdAttribute( primary[0] )
for relname in dir(modelClass):
if relname.startswith("_"):
continue
rel= type(modelClass).__getattribute__(modelClass,relname)
if 'property' not in dir(rel):
continue
prop = rel.property
if not isinstance(prop,RelationshipProperty):
continue
adaptor = SqlAlchemyAdaptor.getAdaptor(prop.mapper.class_)
islist = prop.uselist
self.addAttribute( relname, adaptor, editable=True, islist=islist )
kernel_type = config.get('kernel_type', '')
cost = config.get('cost', 1)
degree = config.get('degree', 3)
coef0 = config.get('coef0', 0)
sparse_matrix = config.get('sparse_matrix', False)
threshold = config.get('threshold', 50)
y_train, x_train = svm_read_problem(train_data_path)
y_test, x_test = svm_read_problem(test_data_path)
data_size_train = len(y_train)
data_size_test = len(y_test)
features_num = extract_features_from_data(x_train, x_test)
gamma = config.get('gamma', 1 / features_num)
adaptor_train = Adaptor(y=y_train,
x=x_train,
data_size=data_size_train,
features_num=features_num)
adaptor_test = Adaptor(y=y_test,
x=x_test,
data_size=data_size_test,
features_num=features_num)
npx_train = adaptor_train.adapt_x()
npy_train = adaptor_train.adapt_y()
npx_test = adaptor_test.adapt_x()
npy_test = adaptor_test.adapt_y()
lower_boundary = np.zeros((npy_train.shape[0], npy_train.shape[1]))
upper_boundary = np.ones((npy_train.shape[0], npy_train.shape[1])) * cost
q = np.ones((npy_train.shape[0], npy_train.shape[1]))
check_generation_memory(data_size_train, features_num, sparse_matrix)
def test_add_listener(self):
adaptor = Adaptor(1)
room = Room()
adaptor.add_listener(room)
self.assertEqual(len(adaptor.get_listeners()),1)
def test_start_reading(self):
adaptor = Adaptor(1)
adaptor.start_reading()
def test_add_listener(self):
adaptor = Adaptor(1)
room = Room()
adaptor.add_listener(room)
self.assertEqual(len(adaptor.get_listeners()), 1)
def test_start_reading(self):
adaptor = Adaptor(1)
adaptor.start_reading()
