initial commit

doc/example-apps/data-aggregation.py

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+import time
+from collections import deque
+from math import sqrt
+
+from openmtc_app.onem2m import XAE
+from openmtc_onem2m.model import Container
+
+
+class DataAggregation(XAE):
+    remove_registration = True
+    remote_cse = '/mn-cse-1/onem2m'
+    period = 10
+
+    def _on_register(self):
+        # init variables
+        self.sensor_register = {}
+        self.dev_cnt_list = []
+        # start endless loop
+        self.periodic_discover(self.remote_cse,
+                               {'labels': ["openmtc:sensor_data"]},
+                               self.period, self.handle_discovery_sensor)
+
+    @staticmethod
+    def _time():
+        return format(round(time.time(), 3), '.3f')
+
+    def handle_discovery_sensor(self, discovery):
+        for uri in discovery:
+            self.sensor_register[uri] = {
+                'values': deque([], 10)
+            }
+            content = self.get_content(uri)
+            if content:
+                self.handle_sensor(uri, content)
+            self.add_container_subscription(uri, self.handle_sensor)
+
+    def create_sensor_structure(self, sensor_entry, content):
+        # dev_cnt
+        cnt_name = '_'.join(content[0]['bn'].split(':')[2:])
+        cnt_name += '_' + content[0]['n']
+        dev_cnt = Container(resourceName=cnt_name)
+        if dev_cnt not in self.dev_cnt_list:
+            sensor_entry['dev_cnt'] = dev_cnt = self.create_container(None, dev_cnt)
+            # mean cnt
+            mean_cnt = Container(resourceName='mean', labels=["openmtc:mean_data"])
+            sensor_entry['mean_cnt'] = self.create_container(dev_cnt, mean_cnt)
+            # Standard_deviation cnt
+            deviation_cnt = Container(resourceName='Standard_deviation', labels=["openmtc:Standard_deviation_data"])
+            sensor_entry['deviation_cnt'] = self.create_container(dev_cnt, deviation_cnt)
+            self.dev_cnt_list.append(dev_cnt)
+        else:
+            return dev_cnt,"already exists "
+
+    def handle_sensor(self, container, content):
+        sensor_entry = self.sensor_register[container]
+        values = sensor_entry['values']
+        try :
+            values.append(content[0]['v'])
+        except KeyError:
+            return
+        # check if container exists
+        try:
+            sensor_entry['dev_cnt']
+        except KeyError:
+            self.create_sensor_structure(sensor_entry, content)
+
+        # mean value
+        mean = sum(values) / len(values)
+        data = [{
+            'bn': content[0]['bn'],
+            'n': content[0]['n'] + '_mean',
+            'v': mean,
+            't': self._time()
+        }]
+
+        # Standard_deviation value
+        num_item = len(values)
+        standard_mean = sum(values) / num_item
+        differences = [((x - standard_mean) ** 2) ** 2 for x in values]
+        ssd = sum(differences)
+        variance = ssd / num_item
+        sd = sqrt(variance)
+        print sd
+        deviation_data = [{
+            'bn': content[0]['bn'],
+            'n': content[0]['n'] + '_Standard_deviation',
+            'v': sd,
+            't': self._time()
+        }]
+        try:
+            data[0]['u'] = content[0]['u']
+        except KeyError:
+            pass
+        self.push_content(sensor_entry['mean_cnt'], data)
+        self.push_content(sensor_entry['deviation_cnt'], deviation_data)
+
+
+if __name__ == "__main__":
+    from openmtc_app.flask_runner import SimpleFlaskRunner as Runner
+
+    ep = "http://localhost:8000"
+    Runner(DataAggregation(), port=6050, host='auto').run(ep)