amari.kpi: Add DRB.UEActive measurement

amari/kpi.py

@@ -29,6 +29,8 @@ from xlte import kpi
 from xlte.amari import xlog
 from golang import func
 
+from math import floor
+
 
 # LogMeasure takes enb.xlog (TODO and enb.log) as input, and produces kpi.Measurements on output.
 #
@@ -205,10 +207,14 @@ def _read(logm):
 # _handle_stats handles next stats xlog entry upon _read request.
 @func(LogMeasure)
 def _handle_stats(logm, stats: xlog.Message, m_prev: kpi.Measurement):
-    # build Measurement from stats' counters.
+    # build Measurement from stats' values, by mapping Amarisoft non-counters
+    # (non-cumulative) and counters to their respective 3GPP value specified by
+    # kpi.Measurement.
+    #
+    # for non-counters, simply map the value to the corresponding 3GPP value.
     #
-    # we take δ(stats_prev, stat) and process it mapping Amarisoft counters to
-    # 3GPP ones specified by kpi.Measurement. This approach has following limitations:
+    # for cumulative counters, we take δ(stats_prev, stat) and process it
+    # before performing the mapping. This approach has following limitations:
     #
     # - for most of the counters there is no direct mapping in between
     #   Amarisoft and 3GPP. For example we currently use s1_erab_setup_request for
@@ -302,6 +308,17 @@ def _handle_stats(logm, stats: xlog.Message, m_prev: kpi.Measurement):
         if m[fini] > m[init]:
             m[fini] = m[init]
 
+    cells = set(stats['cells'].keys())  # NOTE cells are taken only from stats, not from stat_prev
+
+    # map non-counter values, which are independent between periods
+    # and do not need any special processing.
+    Σue_active_count_avg = 0
+    for cell in cells:
+      Σue_active_count_avg += _stats_cell_nc(stats, cell, 'ue_active_count_avg')
+    # flooring the sum of averages is more accurate to the 3GPP spec than summing the floors.
+    Σue_active_count_avg = int(floor(Σue_active_count_avg))
+    m['DRB.UEActive'] = Σue_active_count_avg
+
     # compute δ for counters.
     # any logic error in data will be reported via LogError.
     try:
@@ -315,7 +332,6 @@ def _handle_stats(logm, stats: xlog.Message, m_prev: kpi.Measurement):
         # same whether we do aggregation here or in kpi.Calc.erab_accessibility().
         #
         # TODO rework to emit per-cell measurements when/if we need per-cell KPIs
-        cells = set(stats['cells'].keys())  # NOTE cells are taken only from stats, not from stat_prev
         δΣcell_rrc_connection_request = 0   # (if a cell disappears its counters stop to be accounted)
         δΣcell_rrc_connection_setup_complete = 0
         for cell in cells:
@@ -368,12 +384,25 @@ def _stats_check(stats: xlog.Message):
         raise LogError(stats.timestamp, "stats: %s" % e)  from None
     return
 
+# _stats_nc returns specified global non-counter from stats result.
+#
+# stats is assumed to be already verified by _stats_check.
+def _stats_nc(stats: xlog.Message, non_counter: str):
+    return stats.get(non_counter, 0.0)
+
 # _stats_cc returns specified global cumulative counter from stats result.
 #
 # stats is assumed to be already verified by _stats_check.
 def _stats_cc(stats: xlog.Message, counter: str):
     return stats['counters']['messages'].get(counter, 0)
 
+# _stats_cell_nc is like _stats_nc but returns specified per-cell non-counter from stats result.
+def _stats_cell_nc(stats: xlog.Message, cell: str, non_counter: str):
+    _ = stats['cells'].get(cell)
+    if _ is None:
+        return 0.0  # cell is absent in this stats
+    return _.get(non_counter, 0.0)
+
 # _stats_cell_cc is like _stats_cc but returns specified per-cell cumulative counter from stats result.
 def _stats_cell_cc(stats: xlog.Message, cell: str, counter: str):
     _ = stats['cells'].get(cell)

kpi.py

@@ -179,6 +179,9 @@ class Measurement(np.void):
 
         ('DRB.PdcpSduBitrateUl.QCI',        np.float64),# bit/s     4.4.1.1                 NOTE not kbit/s
         ('DRB.PdcpSduBitrateDl.QCI',        np.float64),# bit/s     4.4.1.2                 NOTE not kbit/s
+
+        ('DRB.UEActive',                    np.int32),  # 1         4.4.2.4  36.314:4.1.3.3
+
         # XXX mean is not good for our model
         # TODO mean -> total + npkt?
         #('DRB.IPLatDl.QCI',                Ttime),     # s         4.4.5.1  32.450:6.3.2   NOTE not ms

kpi_test.py

@@ -53,6 +53,8 @@ def test_Measurement():
     assert m['S1SIG.ConnEstabAtt'] == 123
     m['RRC.ConnEstabAtt.sum'] = 17
     assert m['RRC.ConnEstabAtt.sum'] == 17
+    m['DRB.UEActive'] = 6
+    assert m['DRB.UEActive'] == 6
     m['DRB.IPVolDl.QCI'][:] = 0
     m['DRB.IPVolDl.5'] = 55
     m['DRB.IPVolDl.7'] = NA(m['DRB.IPVolDl.7'].dtype)
@@ -67,13 +69,14 @@ def test_Measurement():
         assert m['DRB.IPVolDl.QCI'][k] == 0
 
     # str/repr
-    assert repr(m) == "Measurement(RRC.ConnEstabAtt.sum=17, DRB.IPVolDl.QCI={5:55 7:ø 9:99}, S1SIG.ConnEstabAtt=123)"
+    assert repr(m) == "Measurement(RRC.ConnEstabAtt.sum=17, DRB.UEActive=6, DRB.IPVolDl.QCI={5:55 7:ø 9:99}, S1SIG.ConnEstabAtt=123)"
     s = str(m)
     assert s[0]  == '('
     assert s[-1] == ')'
     v = s[1:-1].split(', ')
     vok = ['ø'] * len(m._dtype0.names)
     vok[m.dtype.names.index("RRC.ConnEstabAtt.sum")]   = "17"
+    vok[m.dtype.names.index("DRB.UEActive")]           = "6"
     vok[m.dtype.names.index("S1SIG.ConnEstabAtt")]     = "123"
     vok[m.dtype.names.index("DRB.IPVolDl.QCI")]        = "{5:55 7:ø 9:99}"
     assert v == vok