Commit faf06cd1 authored by Paul Graydon's avatar Paul Graydon

wendelin_telecom_base: Refactor KPI processing pipeline

parent cf866716
from xlte.amari import kpi as amari_kpi
from xlte import kpi
from zLOG import LOG, WARNING
import io
def load_measurements(alogm):
......@@ -9,13 +10,13 @@ def load_measurements(alogm):
while measurement is not None:
try:
mlog.append(measurement)
except AssertionError:
except Exception as e:
# Invalid measurement: simply skip it
pass
LOG('WendelinTelecomCalcOrsKpi.loadMeasurements', WARNING, "Skipped data during KPI calculation: %s" % e)
measurement = alogm.read()
except amari_kpi.LogError:
except amari_kpi.LogError as e:
# Invalid measurement: simply skip it
pass
LOG('WendelinTelecomCalcOrsKpi.loadMeasurements', WARNING, "Skipped data during KPI calculation: %s" % e)
finally:
alogm.close()
return mlog
......@@ -33,32 +34,49 @@ def calc_periods(mlog, tperiod):
# No data to read: exit
return
def getOrsKpiValues(data):
def calcEnbKpi(data, t_period):
fxlog = io.StringIO(data)
alogm = amari_kpi.LogMeasure(fxlog, open('/dev/null', 'r'))
mlog = load_measurements(alogm)
# E-RAB Accessibility KPI
vt = []
v_initial_epsb_estab_sr = []
v_added_epsb_estab_sr = []
tperiod = 60 # seconds
for calc in calc_periods(mlog, tperiod):
for calc in calc_periods(mlog, t_period):
try:
erab_accessibility = calc.erab_accessibility()
except AssertionError as e:
LOG('WendelinTelecomCalcOrsKpi.calcEnbKpi', WARNING, "Skipped data during KPI calculation: %s" % e)
continue
vt.append(calc.tau_lo)
erab_accessibility = calc.erab_accessibility()
v_initial_epsb_estab_sr.append((erab_accessibility[0]['lo'], erab_accessibility[0]['hi']))
v_added_epsb_estab_sr.append((erab_accessibility[1]['lo'], erab_accessibility[1]['hi']))
# E-UTRAN IP Throughput KPI
evt = []
v_ip_throughput_qci = []
tperiod = 3 # seconds
for calc in calc_periods(mlog, tperiod):
evt.append(calc.tau_lo)
eutran_ip_throughput = calc.eutran_ip_throughput()
for calc in calc_periods(mlog, t_period):
try:
eutran_ip_throughput = calc.eutran_ip_throughput()
except AssertionError as e:
LOG('WendelinTelecomCalcOrsKpi.calcEnbKpi', WARNING, "Skipped data during KPI calculation: %s" % e)
continue
period_qci_data = []
for qci, qci_measurement in enumerate(eutran_ip_throughput):
period_qci_data.append((qci, qci_measurement['dl']['lo'], qci_measurement['dl']['hi'], qci_measurement['ul']['lo'], qci_measurement['ul']['hi']))
for qci_measurement in eutran_ip_throughput:
period_qci_data.append((
qci_measurement['dl']['lo'],
qci_measurement['dl']['hi'],
qci_measurement['ul']['lo'],
qci_measurement['ul']['hi']
))
evt.append(calc.tau_lo)
v_ip_throughput_qci.append(period_qci_data)
return vt, v_initial_epsb_estab_sr, v_added_epsb_estab_sr, evt, v_ip_throughput_qci
kpi_data_dict = dict(
e_rab_accessibility=(vt, v_initial_epsb_estab_sr, v_added_epsb_estab_sr),
e_utran_ip_throughput=(evt, v_ip_throughput_qci)
)
return kpi_data_dict
\ No newline at end of file
<?xml version="1.0"?>
<ZopeData>
<record id="1" aka="AAAAAAAAAAE=">
<pickle>
<global name="Extension Component" module="erp5.portal_type"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>default_reference</string> </key>
<value> <string>WendelinTelecomCalcEnbKpi</string> </value>
</item>
<item>
<key> <string>default_source_reference</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>description</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>id</string> </key>
<value> <string>extension.erp5.WendelinTelecomCalcEnbKpi</string> </value>
</item>
<item>
<key> <string>sid</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>text_content_error_message</string> </key>
<value>
<tuple/>
</value>
</item>
<item>
<key> <string>text_content_warning_message</string> </key>
<value>
<tuple/>
</value>
</item>
<item>
<key> <string>version</string> </key>
<value> <string>erp5</string> </value>
</item>
<item>
<key> <string>workflow_history</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAI=</string> </persistent>
</value>
</item>
</dictionary>
</pickle>
</record>
<record id="2" aka="AAAAAAAAAAI=">
<pickle>
<global name="PersistentMapping" module="Persistence.mapping"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>data</string> </key>
<value>
<dictionary>
<item>
<key> <string>component_validation_workflow</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAM=</string> </persistent>
</value>
</item>
</dictionary>
</value>
</item>
</dictionary>
</pickle>
</record>
<record id="3" aka="AAAAAAAAAAM=">
<pickle>
<global name="WorkflowHistoryList" module="Products.ERP5Type.Workflow"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>_log</string> </key>
<value>
<list>
<dictionary>
<item>
<key> <string>action</string> </key>
<value> <string>validate</string> </value>
</item>
<item>
<key> <string>validation_state</string> </key>
<value> <string>validated</string> </value>
</item>
</dictionary>
</list>
</value>
</item>
</dictionary>
</pickle>
</record>
</ZopeData>
import json
import numpy as np
import pandas as pd
QCI_COUNT = 256
# The maximum number of points to show on a KPI graph
RESAMPLE_SIZE = 1000
# Values with which to replace NaNs for each data field
NA_VALUES_REPLACEMENTS = {
'vInitialEPSBEstabSR_lo': 0.,
'vInitialEPSBEstabSR_hi': 100.,
'vAddedEPSBEstabSR_lo': 0.,
'vAddedEPSBEstabSR_hi': 100.,
'dl_lo': 0.,
'dl_hi': 0.,
'ul_lo': 0.,
'ul_hi': 0.
}
def resample_data_array(
np_data_array, time_field,
time_start, time_end, resample_size
):
'''
Resample the provided numpy data array to the provided new size
by averaging values in regular time intervals, if it is long enough to be downsized.
Return a dictionary with the data arrays keyed to their respective data fields.
'''
data_frame = pd.DataFrame.from_records(np_data_array)
data_frame[time_field] = pd.to_datetime(data_frame[time_field], unit='s')
data_frame = data_frame.sort_values(by=time_field)
# Resample data
if len(np_data_array) > resample_size:
resample_period = '%ss' % int((time_end - time_start) / resample_size)
data_frame = data_frame.resample(resample_period, on=time_field).mean()
data_frame = data_frame.fillna(value=NA_VALUES_REPLACEMENTS)
data_frame = data_frame.reset_index()
data_frame[time_field] = data_frame[time_field].map(pd.Timestamp.timestamp)
return data_frame.to_dict(orient='list')
def getOrsEnbKpi(
self, data_array_url, kpi_type,
time_start=None, time_end=None, REQUEST=None, RESPONSE=None
):
'''
Return the requested KPI data in the response as a JSON object
with the data arrays keyed to their respective data fields.
Several optimizations are made:
- If required, the data will be resampled to at most RESAMPLE_SIZE data points.
- For the E-UTRAN IP Throughput KPI, optimize the data format by removing data
for "silent" QCIs, which have only zero values.
'''
portal = self.getPortalObject()
try:
data_array = portal.restrictedTraverse(data_array_url)
data_array = np.array(data_array.getArray())
except KeyError:
# Data Array does not exist
RESPONSE.setStatus(404)
return
# Data Array is empty
if data_array.shape in [(), (0,)]:
RESPONSE.write(json.dumps(dict()))
return
RESPONSE.setHeader("Content-Type", "application/json")
time_field = data_array.dtype.names[0]
if time_start is None or time_start == 'NaN':
time_start = data_array[time_field][0]
else:
time_start = float(time_start)
if time_end is None or time_end == 'NaN':
time_end = data_array[time_field][-1]
else:
time_end = float(time_end)
time_mask = (data_array[time_field] >= time_start) \
& (data_array[time_field] <= time_end)
if isinstance(time_mask, np.ndarray):
data_array = data_array[time_mask]
if kpi_type == 'e_rab_accessibility':
resampled_data_dict = resample_data_array(
data_array,
time_field,
time_start,
time_end,
RESAMPLE_SIZE
)
response_dict = dict(
vt=resampled_data_dict['vt'],
v_initial_epsb_estab_sr_lo=resampled_data_dict['vInitialEPSBEstabSR_lo'],
v_initial_epsb_estab_sr_hi=resampled_data_dict['vInitialEPSBEstabSR_hi'],
v_added_epsb_estab_sr_lo=resampled_data_dict['vAddedEPSBEstabSR_lo'],
v_added_epsb_estab_sr_hi=resampled_data_dict['vAddedEPSBEstabSR_hi']
)
RESPONSE.write(json.dumps(response_dict))
elif kpi_type == 'e_utran_ip_throughput':
evt = []
active_qci = []
dl_lo = []
dl_hi = []
ul_lo = []
ul_hi = []
for qci in range(QCI_COUNT):
qci_data_array = data_array[qci::QCI_COUNT]
qci_dl_hi = qci_data_array['dl_hi']
qci_ul_hi = qci_data_array['ul_hi']
# QCI is silent: skip it
if (qci_dl_hi == 0.).all() and (qci_ul_hi == 0.).all():
continue
resampled_qci_data_dict = resample_data_array(
qci_data_array,
time_field,
time_start,
time_end,
RESAMPLE_SIZE
)
evt = resampled_qci_data_dict['evt']
qci_dl_lo = resampled_qci_data_dict['dl_lo']
qci_dl_hi = resampled_qci_data_dict['dl_hi']
qci_ul_lo = resampled_qci_data_dict['ul_lo']
qci_ul_hi = resampled_qci_data_dict['ul_hi']
active_qci.append(qci)
dl_lo.append(qci_dl_lo)
dl_hi.append(qci_dl_hi)
ul_lo.append(qci_ul_lo)
ul_hi.append(qci_ul_hi)
response_dict = dict(
evt=evt,
active_qci=active_qci,
dl_lo=dl_lo,
dl_hi=dl_hi,
ul_lo=ul_lo,
ul_hi=ul_hi
)
RESPONSE.write(json.dumps(response_dict))
......@@ -8,7 +8,13 @@
<dictionary>
<item>
<key> <string>default_reference</string> </key>
<value> <string>OrsKpiUtils</string> </value>
<value> <string>WendelinTelecomGetOrsKpi</string> </value>
</item>
<item>
<key> <string>default_source_reference</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>description</string> </key>
......@@ -18,7 +24,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>extension.erp5.OrsKpiUtils</string> </value>
<value> <string>extension.erp5.WendelinTelecomGetOrsKpi</string> </value>
</item>
<item>
<key> <string>sid</string> </key>
......
......@@ -62,7 +62,7 @@
</item>
<item>
<key> <string>default_reference</string> </key>
<value> <string>calculate_ors_kpi</string> </value>
<value> <string>calculate_ors_enb_kpi</string> </value>
</item>
<item>
<key> <string>description</string> </key>
......@@ -72,7 +72,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>calculate_ors_kpi</string> </value>
<value> <string>calculate_ors_enb_kpi</string> </value>
</item>
<item>
<key> <string>language</string> </key>
......@@ -82,11 +82,11 @@
</item>
<item>
<key> <string>script_id</string> </key>
<value> <string>DataAnalysisLine_calculateOrsKpi</string> </value>
<value> <string>DataAnalysisLine_calculateOrsEnbKpi</string> </value>
</item>
<item>
<key> <string>title</string> </key>
<value> <string>Calculate ORS KPI</string> </value>
<value> <string>Calculate ORS eNB KPI</string> </value>
</item>
<item>
<key> <string>version</string> </key>
......@@ -160,7 +160,7 @@
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1018.50460.57093.18414</string> </value>
<value> <string>1021.29636.31750.64409</string> </value>
</item>
<item>
<key> <string>state</string> </key>
......@@ -180,7 +180,7 @@
</tuple>
<state>
<tuple>
<float>1724228941.27</float>
<float>1734605116.76</float>
<string>UTC</string>
</tuple>
</state>
......
......@@ -89,7 +89,7 @@
</item>
<item>
<key> <string>default_reference</string> </key>
<value> <string>ors_kpi</string> </value>
<value> <string>ors_enb_kpi</string> </value>
</item>
<item>
<key> <string>description</string> </key>
......@@ -99,7 +99,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>ors_kpi</string> </value>
<value> <string>ors_enb_kpi</string> </value>
</item>
<item>
<key> <string>individual_variation_base_category_list</string> </key>
......@@ -109,9 +109,15 @@
</tuple>
</value>
</item>
<item>
<key> <string>language</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>title</string> </key>
<value> <string>ORS KPI</string> </value>
<value> <string>ORS eNB KPI</string> </value>
</item>
<item>
<key> <string>workflow_history</string> </key>
......@@ -203,7 +209,7 @@
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1007.25758.5119.31470</string> </value>
<value> <string>1021.29669.43776.60125</string> </value>
</item>
<item>
<key> <string>state</string> </key>
......@@ -223,7 +229,7 @@
</tuple>
<state>
<tuple>
<float>1681374109.0</float>
<float>1734605141.66</float>
<string>UTC</string>
</tuple>
</state>
......
<?xml version="1.0"?>
<ZopeData>
<record id="1" aka="AAAAAAAAAAE=">
<pickle>
<global name="Product Individual Variation" module="erp5.portal_type"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>id</string> </key>
<value> <string>2</string> </value>
</item>
<item>
<key> <string>title</string> </key>
<value> <string>e_utran</string> </value>
</item>
<item>
<key> <string>variation_base_category_list</string> </key>
<value>
<tuple>
<string>variation</string>
</tuple>
</value>
</item>
<item>
<key> <string>workflow_history</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAI=</string> </persistent>
</value>
</item>
</dictionary>
</pickle>
</record>
<record id="2" aka="AAAAAAAAAAI=">
<pickle>
<global name="PersistentMapping" module="Persistence.mapping"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>data</string> </key>
<value>
<dictionary>
<item>
<key> <string>edit_workflow</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAM=</string> </persistent>
</value>
</item>
</dictionary>
</value>
</item>
</dictionary>
</pickle>
</record>
<record id="3" aka="AAAAAAAAAAM=">
<pickle>
<global name="WorkflowHistoryList" module="Products.ERP5Type.Workflow"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>_log</string> </key>
<value>
<list>
<dictionary>
<item>
<key> <string>action</string> </key>
<value> <string>edit</string> </value>
</item>
<item>
<key> <string>actor</string> </key>
<value> <unicode>zope</unicode> </value>
</item>
<item>
<key> <string>comment</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>error_message</string> </key>
<value> <string></string> </value>
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1020.53498.7256.14643</string> </value>
</item>
<item>
<key> <string>state</string> </key>
<value> <string>current</string> </value>
</item>
<item>
<key> <string>time</string> </key>
<value>
<object>
<klass>
<global name="_reconstructor" module="copy_reg"/>
</klass>
<tuple>
<global name="DateTime" module="DateTime.DateTime"/>
<global name="object" module="__builtin__"/>
<none/>
</tuple>
<state>
<tuple>
<float>1734603116.58</float>
<string>UTC</string>
</tuple>
</state>
</object>
</value>
</item>
</dictionary>
</list>
</value>
</item>
</dictionary>
</pickle>
</record>
</ZopeData>
<?xml version="1.0"?>
<ZopeData>
<record id="1" aka="AAAAAAAAAAE=">
<pickle>
<global name="Product Individual Variation" module="erp5.portal_type"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>id</string> </key>
<value> <string>2</string> </value>
</item>
<item>
<key> <string>title</string> </key>
<value> <string>e_utran</string> </value>
</item>
<item>
<key> <string>variation_base_category_list</string> </key>
<value>
<tuple>
<string>variation</string>
</tuple>
</value>
</item>
</dictionary>
</pickle>
</record>
</ZopeData>
......@@ -22,7 +22,7 @@
<key> <string>categories</string> </key>
<value>
<tuple>
<string>resource/data_operation_module/calculate_ors_kpi</string>
<string>resource/data_operation_module/calculate_ors_enb_kpi</string>
<string>trade_phase/data/convert</string>
</tuple>
</value>
......
......@@ -31,8 +31,8 @@
<value>
<tuple>
<string>quantity_unit/unit/piece</string>
<string>resource/data_product_module/ors_kpi</string>
<string>variation/data_product_module/ors_kpi/1</string>
<string>resource/data_product_module/ors_enb_kpi</string>
<string>variation/data_product_module/ors_enb_kpi/1</string>
<string>trade_phase/data/subsample</string>
<string>use/big_data/ingestion/stream</string>
</tuple>
......
......@@ -31,10 +31,10 @@
<value>
<tuple>
<string>quantity_unit/unit/piece</string>
<string>resource/data_product_module/ors_kpi</string>
<string>resource/data_product_module/ors_enb_kpi</string>
<string>trade_phase/data/subsample</string>
<string>use/big_data/ingestion/stream</string>
<string>variation/data_product_module/ors_kpi/2</string>
<string>variation/data_product_module/ors_enb_kpi/2</string>
</tuple>
</value>
</item>
......
import json
import numpy as np
HISTORY_LINE_COUNT = 64
T_PERIOD = 30 # seconds
QCI_COUNT = 256
in_data_stream = in_stream['Data Stream']
progress_indicator = in_stream['Progress Indicator']
offset_index = progress_indicator.getIntOffsetIndex()
start = 0
end = in_data_stream.getSize()
# No new data to process
if offset_index >= end:
return
previous_log_data = ''.join(in_data_stream.readChunkList(start, offset_index))
new_log_data = ''.join(in_data_stream.readChunkList(offset_index, end))
previous_log_data_line_list = previous_log_data.splitlines()
new_log_data_line_list = new_log_data.splitlines()
log_data_line_list = previous_log_data_line_list + new_log_data_line_list
# Sort data lines by UTC timestamp
def get_log_line_timestamp(log_line):
try:
log_line_json = json.loads(log_line)
except ValueError:
# Invalid JSON
return 0.0
if 'meta' in log_line_json:
if 'srv_utc' in log_line_json['meta']:
return float(log_line_json['meta']['srv_utc'])
else:
return float(log_line_json['meta']['time'])
else:
return float(log_line_json.get('utc', 0.0))
log_data_line_list.sort(key=get_log_line_timestamp)
# Find the index of the earliest timestamp in the new data
new_log_data_line_first_index = min([
log_data_line_list.index(new_log_line) for new_log_line in new_log_data_line_list
])
# Use partial history of previous logs starting from the earliest timestamp of the new data
# This also gives some tolerance to log errors
history_start_index = max(0, new_log_data_line_first_index - HISTORY_LINE_COUNT)
log_data = '\n'.join(log_data_line_list[history_start_index:])
log_data = log_data.decode('utf8')
e_rab_data_array = None
e_utran_data_array = None
for array in out_array:
if array['variation'] == 'e_rab':
e_rab_data_array = array['Data Array']
if array['variation'] == 'e_utran':
e_utran_data_array = array['Data Array']
# Calculate the KPI data
kpi_data_dict = context.Base_calcEnbKpi(log_data, T_PERIOD)
vt, v_initial_epsb_estab_sr, v_added_epsb_estab_sr = kpi_data_dict['e_rab_accessibility']
evt, v_ip_throughput_qci = kpi_data_dict['e_utran_ip_throughput']
e_rab_dtype = np.dtype([
('vt', 'float'),
('vInitialEPSBEstabSR_lo', 'float64'),
('vInitialEPSBEstabSR_hi', 'float64'),
('vAddedEPSBEstabSR_lo', 'float64'),
('vAddedEPSBEstabSR_hi', 'float64'),
])
e_utran_dtype = np.dtype([
('evt', 'float'),
('dl_lo', 'float64'),
('dl_hi', 'float64'),
('ul_lo', 'float64'),
('ul_hi', 'float64'),
])
e_rab_array = e_rab_data_array.getArray()
if not e_rab_array:
e_rab_array = e_rab_data_array.initArray(shape=(0,), dtype=e_rab_dtype)
e_rab_array_data = []
e_utran_array = e_utran_data_array.getArray()
if not e_utran_array:
e_utran_array = e_utran_data_array.initArray(shape=(0,), dtype=e_utran_dtype)
e_utran_array_data = []
# Don't duplicate KPI data:
# search and start inserting new timestamps from the first one
vt_column = e_rab_array[:]['vt']
first_new_row_vt = 0
while (first_new_row_vt < len(vt) and vt[first_new_row_vt] in vt_column):
first_new_row_vt += 1
for i in range(first_new_row_vt, len(vt)):
if vt[i] not in vt_column:
e_rab_array_data.append((
vt[i],
v_initial_epsb_estab_sr[i][0],
v_initial_epsb_estab_sr[i][1],
v_added_epsb_estab_sr[i][0],
v_added_epsb_estab_sr[i][1]
))
evt_column = e_utran_array[::QCI_COUNT]['evt']
first_new_row_evt = 0
while (first_new_row_evt < len(evt) and evt[first_new_row_evt] in evt_column):
first_new_row_evt += 1
for i in range(first_new_row_evt, len(evt)):
if evt[i] not in evt_column:
for qci_data in v_ip_throughput_qci[i]:
e_utran_array_data.append((evt[i], qci_data[0], qci_data[1], qci_data[2], qci_data[3]))
if e_rab_array_data:
e_rab_array_data = np.ndarray((len(e_rab_array_data),), e_rab_dtype, np.array(e_rab_array_data))
e_rab_array.append(e_rab_array_data)
if e_utran_array_data:
e_utran_array_data = np.ndarray((len(e_utran_array_data),), e_utran_dtype, np.array(e_utran_array_data))
e_utran_array.append(e_utran_array_data)
progress_indicator.setIntOffsetIndex(end)
return
......@@ -77,7 +77,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>DataAnalysisLine_calculateOrsKpi</string> </value>
<value> <string>DataAnalysisLine_calculateOrsEnbKpi</string> </value>
</item>
<item>
<key> <string>reference</string> </key>
......@@ -85,7 +85,7 @@
</item>
<item>
<key> <string>title</string> </key>
<value> <string>DataAnalysisLine_calculateOrsKpi</string> </value>
<value> <string>DataAnalysisLine_calculateOrsEnbKpi</string> </value>
</item>
</dictionary>
</pickle>
......
import numpy as np
progress_indicator = in_stream["Progress Indicator"]
in_data_stream = in_stream["Data Stream"]
start = progress_indicator.getIntOffsetIndex()
total_size = in_data_stream.getSize()
if start >= total_size:
return
chunk_size = 512 * 512
end = min(start + chunk_size, total_size)
log_data = ''.join(in_data_stream.readChunkList(start, end))
# Some lines may contain several contiguous JSON objects
# Normalize to one JSON object per line
newlines_offset = log_data.count('}{')
log_data = log_data.replace('}{', '}\n{')
# Last chunk may contain an incomplete JSON object: leave it for next iteration
log_data_lines = log_data.splitlines()
if len(log_data_lines) < 2:
return
log_data = '\n'.join(log_data_lines[:-1])
end = start + len(log_data) - newlines_offset + 1
log_data = log_data.decode('utf8')
e_rab_data_array = None
e_utran_data_array = None
for array in out_array:
if array['variation'] == 'e_rab':
e_rab_data_array = array['Data Array']
if array['variation'] == 'e_utran':
e_utran_data_array = array['Data Array']
vt, v_initial_epsb_estab_sr, v_added_epsb_estab_sr, evt, v_ip_throughput_qci = context.Base_getOrsKpiValues(log_data)
e_rab_dtype = np.dtype([
('vt', 'float'),
('vInitialEPSBEstabSR_lo', 'float64'),
('vInitialEPSBEstabSR_hi', 'float64'),
('vAddedEPSBEstabSR_lo', 'float64'),
('vAddedEPSBEstabSR_hi', 'float64'),
])
e_utran_dtype = np.dtype([
('evt', 'float'),
('qci', 'float'),
('dl_lo', 'float64'),
('dl_hi', 'float64'),
('ul_lo', 'float64'),
('ul_hi', 'float64'),
])
e_rab_array = e_rab_data_array.getArray()
if not e_rab_array:
e_rab_array = e_rab_data_array.initArray(shape=(0,), dtype=e_rab_dtype)
e_rab_array_data = []
for i in range(len(vt)):
e_rab_array_data.append((vt[i], v_initial_epsb_estab_sr[i][0], v_initial_epsb_estab_sr[i][1], v_added_epsb_estab_sr[i][0], v_added_epsb_estab_sr[i][1]))
if e_rab_array_data:
e_rab_array_data = np.ndarray((len(e_rab_array_data), ), e_rab_dtype, np.array(e_rab_array_data))
e_rab_array.append(e_rab_array_data)
e_utran_array = e_utran_data_array.getArray()
if not e_utran_array:
e_utran_array = e_utran_data_array.initArray(shape=(0,), dtype=e_utran_dtype)
e_utran_array_data = []
seen_qci_list = []
i = e_utran_array.shape[0] - 1
qci_idx = 1
while (i >= 0) and (e_utran_array[i][qci_idx] not in seen_qci_list):
seen_qci_list.append(e_utran_array[i][qci_idx])
i -= 1
for i in range(len(evt)):
for qci_data in v_ip_throughput_qci[i]:
qci = qci_data[0]
qci_data_hi = [qci_data[2], qci_data[4]]
if qci in seen_qci_list or any([data != 0 for data in qci_data_hi]):
e_utran_array_data.append((evt[i], qci, qci_data[1], qci_data[2], qci_data[3], qci_data[4]))
if e_utran_array_data:
e_utran_array_data = np.ndarray((len(e_utran_array_data), ), e_utran_dtype, np.array(e_utran_array_data))
e_utran_array.append(e_utran_array_data)
progress_indicator.setIntOffsetIndex(end)
return
......@@ -5,4 +5,7 @@ It will first unpack the MsgPack, then remove the first item of the tuple (times
get the actual data stored under the 'log' key and append the corresponding string to "Data Stream".
"""
out_stream["Data Stream"].appendData('\n'.join([c[1]['log'] for c in context.unpack(data_chunk)]))
unpacked_data = '\n'.join([c[1]["log"] for c in context.unpack(data_chunk)])
if unpacked_data == '':
return
out_stream["Data Stream"].appendData(unpacked_data + '\n')
......@@ -10,10 +10,8 @@
<script src="renderjs.js" type="text/javascript"></script>
<!-- custom script -->
<script src="ndarray_bundle.js" type="text/javascript"></script>
<script src="wendelin.js" type="text/javascript"></script>
<script src="plotly_strict_v2.34.0.js" type="text/javascript"></script>
<script src="gadget_ors_e_rab_kpi.js" type="text/javascript"></script>
<script src="gadget_ors_e_rab_accessibility_kpi.js" type="text/javascript"></script>
<link href="gadget_ors_kpi.css" rel="stylesheet" type="text/css">
</head>
<body>
......
......@@ -73,7 +73,7 @@
</item>
<item>
<key> <string>default_reference</string> </key>
<value> <string>gadget_ors_e_rab_kpi.html</string> </value>
<value> <string>gadget_ors_e_rab_accessibility_kpi.html</string> </value>
</item>
<item>
<key> <string>description</string> </key>
......@@ -83,7 +83,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>ors_e_rab_kpi_html</string> </value>
<value> <string>ors_e_rab_accessibility_kpi_html</string> </value>
</item>
<item>
<key> <string>language</string> </key>
......@@ -101,7 +101,7 @@
</item>
<item>
<key> <string>title</string> </key>
<value> <string>Gadget ORS E RAB KPI HTML</string> </value>
<value> <string>Gadget ORS E RAB Accessibility KPI HTML</string> </value>
</item>
<item>
<key> <string>version</string> </key>
......@@ -132,18 +132,6 @@
<persistent> <string encoding="base64">AAAAAAAAAAM=</string> </persistent>
</value>
</item>
<item>
<key> <string>edit_workflow</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAQ=</string> </persistent>
</value>
</item>
<item>
<key> <string>processing_status_workflow</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAU=</string> </persistent>
</value>
</item>
</dictionary>
</value>
</item>
......@@ -167,7 +155,7 @@
</item>
<item>
<key> <string>actor</string> </key>
<value> <string>zope</string> </value>
<value> <unicode>zope</unicode> </value>
</item>
<item>
<key> <string>comment</string> </key>
......@@ -191,7 +179,7 @@
</tuple>
<state>
<tuple>
<float>1680075443.84</float>
<float>1734617150.07</float>
<string>UTC</string>
</tuple>
</state>
......@@ -209,132 +197,4 @@
</dictionary>
</pickle>
</record>
<record id="4" aka="AAAAAAAAAAQ=">
<pickle>
<global name="WorkflowHistoryList" module="Products.ERP5Type.Workflow"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>_log</string> </key>
<value>
<list>
<dictionary>
<item>
<key> <string>action</string> </key>
<value> <string>edit</string> </value>
</item>
<item>
<key> <string>actor</string> </key>
<value> <unicode>zope</unicode> </value>
</item>
<item>
<key> <string>comment</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>error_message</string> </key>
<value> <string></string> </value>
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1018.50745.28244.6348</string> </value>
</item>
<item>
<key> <string>state</string> </key>
<value> <string>current</string> </value>
</item>
<item>
<key> <string>time</string> </key>
<value>
<object>
<klass>
<global name="_reconstructor" module="copy_reg"/>
</klass>
<tuple>
<global name="DateTime" module="DateTime.DateTime"/>
<global name="object" module="__builtin__"/>
<none/>
</tuple>
<state>
<tuple>
<float>1724246207.17</float>
<string>UTC</string>
</tuple>
</state>
</object>
</value>
</item>
</dictionary>
</list>
</value>
</item>
</dictionary>
</pickle>
</record>
<record id="5" aka="AAAAAAAAAAU=">
<pickle>
<global name="WorkflowHistoryList" module="Products.ERP5Type.Workflow"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>_log</string> </key>
<value>
<list>
<dictionary>
<item>
<key> <string>action</string> </key>
<value> <string>detect_converted_file</string> </value>
</item>
<item>
<key> <string>actor</string> </key>
<value> <string>zope</string> </value>
</item>
<item>
<key> <string>comment</string> </key>
<value> <string></string> </value>
</item>
<item>
<key> <string>error_message</string> </key>
<value> <string></string> </value>
</item>
<item>
<key> <string>external_processing_state</string> </key>
<value> <string>converted</string> </value>
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>0.0.0.0</string> </value>
</item>
<item>
<key> <string>time</string> </key>
<value>
<object>
<klass>
<global name="_reconstructor" module="copy_reg"/>
</klass>
<tuple>
<global name="DateTime" module="DateTime.DateTime"/>
<global name="object" module="__builtin__"/>
<none/>
</tuple>
<state>
<tuple>
<float>1680075412.12</float>
<string>UTC</string>
</tuple>
</state>
</object>
</value>
</item>
</dictionary>
</list>
</value>
</item>
</dictionary>
</pickle>
</record>
</ZopeData>
/*global window, rJS, RSVP, console, Plotly */
/*jslint indent: 2, maxlen: 80, nomen: true */
(function (window, rJS, RSVP, Plotly, loopEventListener) {
'use strict';
var gadget_klass = rJS(window);
function getNoDataPlotLayout(title, annotation) {
return {
'title' : title,
'xaxis': {
'fixedrange': true
},
'yaxis': {
'fixedrange': true
},
'annotations': [
{
'text': annotation,
'xref': 'paper',
'yref': 'paper',
'showarrow': false,
'font': {
'size': 28
}
}
]
};
}
function getDataPlotLayout(title) {
return {
'title' : title,
'xaxis': {
title: {
text: 'Date'
},
'autorange': true,
'autosize': true
},
'yaxis': {
'fixedrange': true,
title: {
text: '%'
}
}
};
}
function plotFromResponse(response, element, data_type) {
var kpi_data_dict,
date = [],
epsb_estab_sr_lo = [],
epsb_estab_sr_hi = [],
success_rate_data = [],
data_name = '';
kpi_data_dict = response;
if (Object.keys(kpi_data_dict).length === 0 ||
kpi_data_dict.vt.length === 0) {
Plotly.react(
element,
[],
getNoDataPlotLayout(data_type, 'No data found')
);
return;
}
kpi_data_dict.vt.forEach(function (element) {
date.push(new Date(element * 1000));
});
if (data_type === 'Initial E-RAB establishment success rate') {
epsb_estab_sr_lo = kpi_data_dict.v_initial_epsb_estab_sr_lo;
epsb_estab_sr_hi = kpi_data_dict.v_initial_epsb_estab_sr_hi;
data_name = 'InitialEPSBEstabSR';
} else if (data_type === 'Added E-RAB establishment success rate') {
epsb_estab_sr_lo = kpi_data_dict.v_added_epsb_estab_sr_lo;
epsb_estab_sr_hi = kpi_data_dict.v_added_epsb_estab_sr_hi;
data_name = 'AddedEPSBEstabSR';
}
success_rate_data = [
{
x: date,
mode: 'lines+markers',
y: epsb_estab_sr_lo,
type: 'scatter',
line: {shape: 'hv'},
hovertemplate: 'Date: %{x}<br>Rate: %{y}%',
name: data_name
},
{
x: date,
mode: 'lines+markers',
fill: 'tonexty',
y: epsb_estab_sr_hi,
type: 'scatter',
line: {
color: '#6cb9e5',
shape: 'hv'
},
hovertemplate: 'Date: %{x}<br>Rate: %{y}%',
name: data_name + ' uncertainty'
}
];
Plotly.react(
element,
success_rate_data,
getDataPlotLayout(data_type)
);
}
gadget_klass
.declareAcquiredMethod('getSetting', 'getSetting')
.declareAcquiredMethod('jio_get', 'jio_get')
.declareAcquiredMethod('jio_getAttachment', 'jio_getAttachment')
.declareService(function () {
var gadget = this;
return loopEventListener(window, 'resize', false, function () {
Plotly.Plots.resize(
gadget.element.querySelector('.graph-initial-success-rate')
);
Plotly.Plots.resize(
gadget.element.querySelector('.graph-added-success-rate')
);
});
})
.declareMethod('render', function (option_dict) {
var gadget = this,
kpi_url,
initial_success_rate_element =
gadget.element.querySelector('.graph-initial-success-rate'),
added_success_rate_element =
gadget.element.querySelector('.graph-added-success-rate');;
return new RSVP.Queue().push(function () {
return gadget.getSetting('hateoas_url');
})
.push(function (hateoas_url) {
kpi_url =
(new URI(hateoas_url)).absoluteTo(location.href).toString() +
'Base_getOrsEnbKpi?data_array_url=' +
option_dict.data_array_url +
'&kpi_type=' + option_dict.kpi_type;
return gadget.jio_getAttachment('erp5', kpi_url, {
format: 'json'
});
})
.push(function (response) {
plotFromResponse(
response,
initial_success_rate_element,
'Initial E-RAB establishment success rate'
);
plotFromResponse(
response,
added_success_rate_element,
'Added E-RAB establishment success rate'
);
gadget.element.querySelector('.ui-icon-spinner').hidden = true;
initial_success_rate_element.on(
'plotly_relayout',
function (eventdata) {
var x_start = new Date(eventdata['xaxis.range[0]']).getTime()
/ 1000,
x_end = new Date(eventdata['xaxis.range[1]']).getTime()
/ 1000,
update_kpi_url = kpi_url +
'&time_start=' + x_start +
'&time_end=' + x_end;
return new RSVP.Queue().push(function () {
return gadget.jio_getAttachment('erp5', update_kpi_url, {
format: 'json'
});
})
.push(function (response) {
plotFromResponse(
response,
initial_success_rate_element,
'Initial E-RAB establishment success rate'
);
});
}
);
added_success_rate_element.on(
'plotly_relayout',
function (eventdata) {
var x_start = new Date(eventdata['xaxis.range[0]']).getTime()
/ 1000,
x_end = new Date(eventdata['xaxis.range[1]']).getTime()
/ 1000,
update_kpi_url = kpi_url +
'&time_start=' + x_start +
'&time_end=' + x_end;
return new RSVP.Queue().push(function () {
return gadget.jio_getAttachment('erp5', update_kpi_url, {
format: 'json'
});
})
.push(function (response) {
plotFromResponse(
response,
added_success_rate_element,
'Added E-RAB establishment success rate'
);
});
}
);
}, function () {
// On request error, show empty plots
plotFromResponse(
{},
initial_success_rate_element,
'Initial E-RAB establishment success rate'
);
plotFromResponse(
{},
added_success_rate_element,
'Added E-RAB establishment success rate'
);
gadget.element.querySelector('.ui-icon-spinner').hidden = true;
});
});
}(window, rJS, RSVP, Plotly, loopEventListener));
......@@ -75,7 +75,7 @@
</item>
<item>
<key> <string>default_reference</string> </key>
<value> <string>gadget_ors_e_rab_kpi.js</string> </value>
<value> <string>gadget_ors_e_rab_accessibility_kpi.js</string> </value>
</item>
<item>
<key> <string>description</string> </key>
......@@ -85,7 +85,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>ors_e_rab_kpi_js</string> </value>
<value> <string>ors_e_rab_accessibility_kpi_js</string> </value>
</item>
<item>
<key> <string>language</string> </key>
......@@ -99,7 +99,7 @@
</item>
<item>
<key> <string>title</string> </key>
<value> <string>Gadget ORS E RAB KPI JS</string> </value>
<value> <string>Gadget ORS E RAB Accessibility KPI JS</string> </value>
</item>
<item>
<key> <string>version</string> </key>
......@@ -130,18 +130,6 @@
<persistent> <string encoding="base64">AAAAAAAAAAM=</string> </persistent>
</value>
</item>
<item>
<key> <string>edit_workflow</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAQ=</string> </persistent>
</value>
</item>
<item>
<key> <string>processing_status_workflow</string> </key>
<value>
<persistent> <string encoding="base64">AAAAAAAAAAU=</string> </persistent>
</value>
</item>
</dictionary>
</value>
</item>
......@@ -165,7 +153,7 @@
</item>
<item>
<key> <string>actor</string> </key>
<value> <string>zope</string> </value>
<value> <unicode>zope</unicode> </value>
</item>
<item>
<key> <string>comment</string> </key>
......@@ -189,7 +177,7 @@
</tuple>
<state>
<tuple>
<float>1680075654.87</float>
<float>1734617161.66</float>
<string>UTC</string>
</tuple>
</state>
......@@ -207,134 +195,4 @@
</dictionary>
</pickle>
</record>
<record id="4" aka="AAAAAAAAAAQ=">
<pickle>
<global name="WorkflowHistoryList" module="Products.ERP5Type.Workflow"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>_log</string> </key>
<value>
<list>
<dictionary>
<item>
<key> <string>action</string> </key>
<value> <string>edit</string> </value>
</item>
<item>
<key> <string>actor</string> </key>
<value> <unicode>zope</unicode> </value>
</item>
<item>
<key> <string>comment</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>error_message</string> </key>
<value> <string></string> </value>
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1019.54468.57368.35892</string> </value>
</item>
<item>
<key> <string>state</string> </key>
<value> <string>current</string> </value>
</item>
<item>
<key> <string>time</string> </key>
<value>
<object>
<klass>
<global name="_reconstructor" module="copy_reg"/>
</klass>
<tuple>
<global name="DateTime" module="DateTime.DateTime"/>
<global name="object" module="__builtin__"/>
<none/>
</tuple>
<state>
<tuple>
<float>1728632990.63</float>
<string>UTC</string>
</tuple>
</state>
</object>
</value>
</item>
</dictionary>
</list>
</value>
</item>
</dictionary>
</pickle>
</record>
<record id="5" aka="AAAAAAAAAAU=">
<pickle>
<global name="WorkflowHistoryList" module="Products.ERP5Type.Workflow"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>_log</string> </key>
<value>
<list>
<dictionary>
<item>
<key> <string>action</string> </key>
<value>
<none/>
</value>
</item>
<item>
<key> <string>actor</string> </key>
<value> <string>zope</string> </value>
</item>
<item>
<key> <string>comment</string> </key>
<value> <string></string> </value>
</item>
<item>
<key> <string>error_message</string> </key>
<value> <string></string> </value>
</item>
<item>
<key> <string>external_processing_state</string> </key>
<value> <string>empty</string> </value>
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>0.0.0.0</string> </value>
</item>
<item>
<key> <string>time</string> </key>
<value>
<object>
<klass>
<global name="_reconstructor" module="copy_reg"/>
</klass>
<tuple>
<global name="DateTime" module="DateTime.DateTime"/>
<global name="object" module="__builtin__"/>
<none/>
</tuple>
<state>
<tuple>
<float>1680075617.54</float>
<string>UTC</string>
</tuple>
</state>
</object>
</value>
</item>
</dictionary>
</list>
</value>
</item>
</dictionary>
</pickle>
</record>
</ZopeData>
/*global window, rJS, RSVP, console, Plotly */
/*jslint nomen: true, indent: 2 */
(function (window, rJS, RSVP, Plotly, wendelin, loopEventListener) {
"use strict";
var gadget_klass = rJS(window);
gadget_klass
.declareAcquiredMethod("getSetting", "getSetting")
.declareAcquiredMethod("jio_get", "jio_get")
.declareAcquiredMethod("jio_getAttachment", "jio_getAttachment")
.declareService(function () {
var gadget = this;
return loopEventListener(window, 'resize', false, function () {
Plotly.Plots.resize(gadget.element.querySelector('.graph-initial-success-rate'));
Plotly.Plots.resize(gadget.element.querySelector('.graph-added-success-rate'));
});
})
.declareMethod('render', function (option_dict) {
var gadget = this,
i,
initial_success_data,
added_success_data,
label_list = ["vt", "vInitialEPSBEstabSR_lo", "vInitialEPSBEstabSR_hi", "vAddedEPSBEstabSR_lo", "vAddedEPSBEstabSR_hi"];
return new RSVP.Queue().push(function () {
return wendelin.getArrayRawSlice(gadget, option_dict.data_array_key);
})
.push(function (result) {
var graph_data = nj.unpack(result.pick(null, label_list)),
date = [],
vInitialEPSBEstabSR_lo = [],
vInitialEPSBEstabSR_hi = [],
vAddedEPSBEstabSR_lo = [],
vAddedEPSBEstabSR_hi = [];
graph_data.sort(function (a, b) {
return (a[0] - b[0]);
});
for (i = 0; i < graph_data.length; i += 1) {
date.push(new Date(graph_data[i][0] * 1000));
vInitialEPSBEstabSR_lo.push(graph_data[i][1]);
vInitialEPSBEstabSR_hi.push(graph_data[i][2]);
vAddedEPSBEstabSR_lo.push(graph_data[i][3]);
vAddedEPSBEstabSR_hi.push(graph_data[i][4]);
}
initial_success_data = [
{
x: date,
mode: 'lines+markers',
y: vInitialEPSBEstabSR_lo,
type: 'scatter',
line: {shape: 'hv'},
hovertemplate: 'Date: %{x}<br>Rate: %{y}%',
name: 'InitialEPSBEstabSR'
},
{
x: date,
mode: 'lines+markers',
fill: 'tonexty',
y: vInitialEPSBEstabSR_hi,
type: 'scatter',
line: {
color: "#6cb9e5",
shape: 'hv'
},
hovertemplate: 'Date: %{x}<br>Rate: %{y}%',
name: 'InitialEPSBEstabSR uncertainty'
}
];
added_success_data = [
{
x: date,
mode: 'lines+markers',
y: vAddedEPSBEstabSR_lo,
type: 'scatter',
line: {shape: 'hv'},
hovertemplate: 'Date: %{x}<br>Rate: %{y}%',
name: 'AddedEPSBEstabSR'
},
{
x: date,
mode: 'lines+markers',
fill: 'tonexty',
y: vAddedEPSBEstabSR_hi,
type: 'scatter',
line: {
color: "#6cb9e5",
shape: 'hv'
},
hovertemplate: 'Date: %{x}<br>Rate: %{y}%',
name: 'AddedEPSBEstabSR uncertainty'
}
];
Plotly.newPlot(
gadget.element.querySelector('.graph-initial-success-rate'),
initial_success_data,
{
'title' : 'Initial E-RAB establishment success rate',
'xaxis': {
'autorange': true,
'autosize': true
},
'yaxis': {
title: {
text: '%'
}
}
}
);
Plotly.newPlot(
gadget.element.querySelector('.graph-added-success-rate'),
added_success_data,
{
'title' : 'Added E-RAB establishment success rate',
'xaxis': {
'autorange': true,
'autosize': true
},
'yaxis': {
title: {
text: '%'
}
}
}
);
gadget.element.querySelector('.ui-icon-spinner').hidden = true;
});
});
}(window, rJS, RSVP, Plotly, wendelin, loopEventListener));
......@@ -10,15 +10,13 @@
<script src="renderjs.js" type="text/javascript"></script>
<!-- custom script -->
<script src="ndarray_bundle.js" type="text/javascript"></script>
<script src="wendelin.js" type="text/javascript"></script>
<script src="plotly_strict_v2.34.0.js" type="text/javascript"></script>
<script src="gadget_ors_e_utran_ip_throughput_kpi.js" type="text/javascript"></script>
<link href="gadget_ors_kpi.css" rel="stylesheet" type="text/css">
</head>
<body>
<div class="graph-download-link"></div>
<div class="graph-upload-link"></div>
<div class="graph-downlink"></div>
<div class="graph-uplink"></div>
<div class="ui-icon-spinner ui-btn-icon-notext first-loader"></div>
</body>
</html>
\ No newline at end of file
......@@ -240,7 +240,7 @@
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1018.60805.51967.7987</string> </value>
<value> <string>1020.64896.36157.8226</string> </value>
</item>
<item>
<key> <string>state</string> </key>
......@@ -260,7 +260,7 @@
</tuple>
<state>
<tuple>
<float>1724849643.71</float>
<float>1732873094.4</float>
<string>UTC</string>
</tuple>
</state>
......
......@@ -238,7 +238,7 @@
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1019.54468.57368.35892</string> </value>
<value> <string>1021.10867.58743.39594</string> </value>
</item>
<item>
<key> <string>state</string> </key>
......@@ -258,7 +258,7 @@
</tuple>
<state>
<tuple>
<float>1728633034.89</float>
<float>1733477211.82</float>
<string>UTC</string>
</tuple>
</state>
......
......@@ -238,7 +238,7 @@
</item>
<item>
<key> <string>serial</string> </key>
<value> <string>1018.50736.46413.16776</string> </value>
<value> <string>1020.52201.24472.32051</string> </value>
</item>
<item>
<key> <string>state</string> </key>
......@@ -258,7 +258,7 @@
</tuple>
<state>
<tuple>
<float>1724245506.16</float>
<float>1732111313.58</float>
<string>UTC</string>
</tuple>
</state>
......
......@@ -8,15 +8,15 @@
<dictionary>
<item>
<key> <string>_function</string> </key>
<value> <string>getOrsKpiValues</string> </value>
<value> <string>calcEnbKpi</string> </value>
</item>
<item>
<key> <string>_module</string> </key>
<value> <string>OrsKpiUtils</string> </value>
<value> <string>WendelinTelecomCalcEnbKpi</string> </value>
</item>
<item>
<key> <string>id</string> </key>
<value> <string>Base_getOrsKpiValues</string> </value>
<value> <string>Base_calcEnbKpi</string> </value>
</item>
<item>
<key> <string>title</string> </key>
......
......@@ -2,25 +2,25 @@
<ZopeData>
<record id="1" aka="AAAAAAAAAAE=">
<pickle>
<global name="Product Individual Variation" module="erp5.portal_type"/>
<global name="ExternalMethod" module="Products.ExternalMethod.ExternalMethod"/>
</pickle>
<pickle>
<dictionary>
<item>
<key> <string>id</string> </key>
<value> <string>1</string> </value>
<key> <string>_function</string> </key>
<value> <string>getOrsEnbKpi</string> </value>
</item>
<item>
<key> <string>title</string> </key>
<value> <string>e_rab</string> </value>
<key> <string>_module</string> </key>
<value> <string>WendelinTelecomGetOrsKpi</string> </value>
</item>
<item>
<key> <string>id</string> </key>
<value> <string>Base_getOrsEnbKpi</string> </value>
</item>
<item>
<key> <string>variation_base_category_list</string> </key>
<value>
<tuple>
<string>variation</string>
</tuple>
</value>
<key> <string>title</string> </key>
<value> <string></string> </value>
</item>
</dictionary>
</pickle>
......
......@@ -54,7 +54,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>DataAcquisitionUnit_getERabDataArrayKey</string> </value>
<value> <string>DataAcquisitionUnit_getERabDataArrayUrl</string> </value>
</item>
</dictionary>
</pickle>
......
......@@ -54,7 +54,7 @@
</item>
<item>
<key> <string>id</string> </key>
<value> <string>DataAcquisitionUnit_getEUtranDataArrayKey</string> </value>
<value> <string>DataAcquisitionUnit_getEUtranDataArrayUrl</string> </value>
</item>
</dictionary>
</pickle>
......
......@@ -211,7 +211,7 @@
</item>
<item>
<key> <string>gadget_url</string> </key>
<value> <string>gadget_ors_e_rab_kpi.html</string> </value>
<value> <string>gadget_ors_e_rab_accessibility_kpi.html</string> </value>
</item>
<item>
<key> <string>hidden</string> </key>
......@@ -253,7 +253,7 @@
<dictionary>
<item>
<key> <string>_text</string> </key>
<value> <string>python: [(\'data_array_key\', context.DataAcquisitionUnit_getERabDataArrayKey())]</string> </value>
<value> <string>python: [(\'data_array_url\', context.DataAcquisitionUnit_getERabDataArrayUrl()), (\'kpi_type\', \'e_rab_accessibility\')]</string> </value>
</item>
</dictionary>
</pickle>
......
......@@ -253,7 +253,7 @@
<dictionary>
<item>
<key> <string>_text</string> </key>
<value> <string>python: [(\'data_array_key\', context.DataAcquisitionUnit_getEUtranDataArrayKey())]</string> </value>
<value> <string>python: [(\'data_array_url\', context.DataAcquisitionUnit_getEUtranDataArrayUrl()), (\'kpi_type\', \'e_utran_ip_throughput\')]</string> </value>
</item>
</dictionary>
</pickle>
......
extension.erp5.OrsKpiUtils
\ No newline at end of file
extension.erp5.WendelinTelecomCalcEnbKpi
extension.erp5.WendelinTelecomGetOrsKpi
\ No newline at end of file
data_operation_module/calculate_ors_kpi
data_operation_module/calculate_ors_enb_kpi
data_operation_module/ingest_ors_enb_log_data
data_product_module/ors_enb_kpi
data_product_module/ors_enb_kpi/**
data_product_module/ors_enb_log_data
data_product_module/ors_kpi
data_product_module/ors_kpi/**
data_transformation_module/ors_enb_log_data_transformation
data_transformation_module/ors_enb_log_data_transformation/**
organisation_module/open_radio_station
organisation_module/rapid_space_data_center
portal_callables/DataAnalysisLine_calculateOrsKpi
portal_callables/DataAnalysisLine_calculateOrsEnbKpi
portal_callables/DataIngestionLine_writeOrsFluentdIngestionToDataStream
portal_callables/IngestionPolicy_parseOrsFluentdTag
portal_ingestion_policies/ors_enb_log_ingestion
web_page_module/ndarray_bundle.js
web_page_module/ors_e_rab_kpi_*
web_page_module/ors_e_rab_accessibility_kpi_*
web_page_module/ors_e_utran_ip_throughput_kpi_*
web_page_module/plotly_strict_v2.34.0.js
web_page_module/rjs_gadget_ors_kpi_css
\ No newline at end of file
data_operation_module/calculate_ors_kpi
data_operation_module/calculate_ors_enb_kpi
data_operation_module/ingest_ors_enb_log_data
data_product_module/ors_enb_kpi
data_product_module/ors_enb_kpi/**
data_product_module/ors_enb_log_data
data_product_module/ors_kpi
data_product_module/ors_kpi/**
data_transformation_module/ors_enb_log_data_transformation
data_transformation_module/ors_enb_log_data_transformation/**
organisation_module/open_radio_station
organisation_module/rapid_space_data_center
portal_callables/DataAnalysisLine_calculateOrsKpi
portal_callables/DataAnalysisLine_calculateOrsEnbKpi
portal_callables/DataIngestionLine_writeOrsFluentdIngestionToDataStream
portal_callables/IngestionPolicy_parseOrsFluentdTag
portal_ingestion_policies/ors_enb_log_ingestion
web_page_module/ndarray_bundle.js
web_page_module/ors_e_rab_kpi_*
web_page_module/ors_e_rab_accessibility_kpi_*
web_page_module/ors_e_utran_ip_throughput_kpi_*
web_page_module/plotly_strict_v2.34.0.js
web_page_module/rjs_gadget_ors_kpi_css
\ No newline at end of file
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