First version with ML prediction code

[ric-app/qp.git] / qp / database.py

diff --git a/qp/database.py b/qp/database.py
new file mode 100644 (file)
index 0000000..42083ee
--- /dev/null
+++ b/qp/database.py
@@ -0,0 +1,78 @@
+# ==================================================================================
+#       Copyright (c) 2020 AT&T Intellectual Property.
+#       Copyright (c) 2020 HCL Technologies Limited.
+#
+#   Licensed under the Apache License, Version 2.0 (the "License");
+#   you may not use this file except in compliance with the License.
+#   You may obtain a copy of the License at
+#
+#          http://www.apache.org/licenses/LICENSE-2.0
+#
+#   Unless required by applicable law or agreed to in writing, software
+#   distributed under the License is distributed on an "AS IS" BASIS,
+#   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#   See the License for the specific language governing permissions and
+#   limitations under the License.
+# ==================================================================================
+from influxdb import DataFrameClient
+import pandas as pd
+import datetime
+
+
+class NoDataError(Exception):
+    pass
+
+
+class DATABASE(object):
+
+    def __init__(self, dbname, user='root', password='root', host='r4-influxdb.ricplt', port='8086'):
+        self.client = DataFrameClient(host, port, user, password, dbname)
+        self.data = None
+
+    def read_data(self, meas='ueMeasReport', limit=100000, cellid=False, ueid=False):
+        query = """select * from """ + meas
+
+        if cellid:
+            query += " where nrCellIdentity= '" + cellid + "'"
+
+        if ueid:
+            query += """ where "ue-id"  = \'{}\'""".format(ueid)
+        query += "  ORDER BY DESC LIMIT " + str(limit)
+        result = self.client.query(query)
+        try:
+            if len(result) != 0:
+                # print("Querying data : " + meas + " : size - " + str(len(result[meas])))
+                self.data = result[meas]
+                self.data['measTimeStampRf'] = self.data.index
+            else:
+                raise NoDataError
+
+        except NoDataError:
+            if cellid:
+                print('Data not found for ' + meas + ' CellID : '+cellid)
+            elif ueid:
+                print('Data not found for ' + meas + ' UEID : '+ueid)
+            else:
+                print('Data not found for ' + meas)
+            pass
+
+    def write_prediction(self, df, meas_name='QP'):
+        df.index = pd.date_range(start=datetime.datetime.now(), freq='10ms', periods=len(df))
+        self.client.write_points(df, meas_name)
+
+
+class DUMMY:
+
+    def __init__(self):
+        self.ue = pd.DataFrame([[1002, "c2/B13", 8, 69, 65, 113, 0.1, 0.1, "Waiting passenger 9", -882, -959, pd.to_datetime("2021-05-12T07:43:51.652")]], columns=["du-id", "nbCellIdentity", "prb_usage", "rsrp", "rsrq", "rssinr", "throughput", "targetTput", "ue-id", "x", "y", "measTimeStampRf"])
+        self.cell = pd.read_csv('qp/dummy.csv')
+        self.data = None
+
+    def read_data(self, meas='ueMeasReport', limit=100000, cellid=False, ueid=False):
+        if ueid:
+            self.data = self.ue.head(limit)
+        if cellid:
+            self.data = self.cell.head(limit)
+
+    def write_prediction(self, df, meas_name='QP'):
+        pass