def run(self, registry):
from liota.edge_component.sklearn_edge_component import SKLearnEdgeComponent
# initialize and run the physical model (simulated device)
sklearn_edge_component = SKLearnEdgeComponent(config['modelPath'],
None)
registry.register("sklearn_edge_component", sklearn_edge_component)
def test_SKLearnEdgeComponent_takes_valid_actionActuator(self):
edge_component = SKLearnEdgeComponent(ModelPath, action_actuator)
assert isinstance(edge_component, SKLearnEdgeComponent)
def test_SKLearnEdgeComponent_fails_without_valid_actionActuator(self):
#Fails if action_actuator not of function type
with self.assertRaises(Exception):
edge_component = SKLearnEdgeComponent(ModelPath, "asd")
assertNotIsInstance(edge_component, SKLearnEdgeComponent)
def test_SKLearnEdgeComponent_fails_without_valid_ModelPath(self):
with self.assertRaises(Exception):
edge_component = SKLearnEdgeComponent(ModelPath, "asd")
assert isinstance(edge_component, SKLearnEdgeComponent)
def test_Component_fails_without_valid_ModelPath(self):
with self.assertRaises(Exception):
edge_component = SKLearnEdgeComponent("/home/asd", "asd")
assertNotIsInstance(edge_component, SKLearnEdgeComponent)
def action_actuator(value):
print value
def read_csv_file():
global line
line += 1
if not line > len(rows):
return int(rows[line][0])
# ---------------------------------------------------------------------------
# In this example, we demonstrate how System health and some simulated data
# can be directed to data center component IoTCC using Liota.
# The program illustrates the ease of use Liota brings to IoT application developers.
if __name__ == '__main__':
read_file("/home/vl/Desktop/sample.csv")
sample = SKLearnEdgeComponent(
'/home/pi/Desktop/Borathon/liota/edge_intelligence_models/windmill/finalized_model.sav',
action_actuator)
sample_metric = Metric(name="File Metric",
unit=None,
interval=1,
aggregation_size=1,
sampling_function=read_csv_file)
reg_sample_metric = sample.register(sample_metric)
reg_sample_metric.start_collecting()
reg_vibration_metric.start_collecting()
rpm_metric = Metric(
name="RPM",
unit=None,
interval=0,
aggregation_size=1,
sampling_function=lambda: get_rpm(sensor_tag_collector)
)
reg_rpm_metric = iotcc.register(rpm_metric)
iotcc.create_relationship(reg_sensor_tag, reg_rpm_metric)
reg_rpm_metric.start_collecting()
pfa_rpm_metric = Metric(
name="RPM",
unit=None,
interval=0,
aggregation_size=1,
sampling_function=get_rpm_for_model
)
edge_component = SKLearnEdgeComponent('/home/pi/Desktop/Borathon/liota/edge_intelligence_models/windmill/finalized_model.sav',
actuator_udm=action_actuator)
pfa_reg_rpm_metric = edge_component.register(pfa_rpm_metric)
pfa_reg_rpm_metric.start_collecting()
except RegistrationFailure:
print "Registration to IOTCC failed"
sensor_tag_collector.stop()