Change-Id: Ie8c22c76557bf491abc53aedc1e7f605c37c88d3
Signed-off-by: Tibor Frank <tifrank@cisco.com>
"""The coverage data tables.
"""
"""The coverage data tables.
"""
import hdrh.histogram
import hdrh.codec
import pandas as pd
import hdrh.histogram
import hdrh.codec
import pandas as pd
phy = selected["phy"].split("-")
if len(phy) == 4:
topo, arch, nic, drv = phy
phy = selected["phy"].split("-")
if len(phy) == 4:
topo, arch, nic, drv = phy
- drv = "" if drv == "dpdk" else drv.replace("_", "-")
+ drv_str = "" if drv == "dpdk" else drv.replace("_", "-")
df = df[
(df.job.str.endswith(f"{topo}-{arch}")) &
(df.test_id.str.contains(
df = df[
(df.job.str.endswith(f"{topo}-{arch}")) &
(df.test_id.str.contains(
- f"^.*\.{selected['area']}\..*{nic}.*{drv}.*$",
+ f"^.*\.{selected['area']}\..*{nic}.*{drv_str}.*$",
if ttype == "device":
cov = cov.assign(Result="PASS")
if ttype == "device":
cov = cov.assign(Result="PASS")
+ elif ttype == "mrr":
+ cov["Throughput_Unit"] = df["result_receive_rate_rate_unit"]
+ cov["Throughput_AVG"] = df.apply(
+ lambda row: row["result_receive_rate_rate_avg"] / 1e9, axis=1
+ )
+ cov["Throughput_STDEV"] = df.apply(
+ lambda row: row["result_receive_rate_rate_stdev"] / 1e9, axis=1
+ )
+ else: # NDRPDR
cov["Throughput_Unit"] = df["result_pdr_lower_rate_unit"]
cov["Throughput_NDR"] = df.apply(
lambda row: row["result_ndr_lower_rate_value"] / 1e6, axis=1
cov["Throughput_Unit"] = df["result_pdr_lower_rate_unit"]
cov["Throughput_NDR"] = df.apply(
lambda row: row["result_ndr_lower_rate_value"] / 1e6, axis=1
df_suite.rename(
columns={
"Throughput_NDR": f"Throughput_NDR_M{unit}",
df_suite.rename(
columns={
"Throughput_NDR": f"Throughput_NDR_M{unit}",
- "Throughput_PDR": f"Throughput_PDR_M{unit}"
+ "Throughput_PDR": f"Throughput_PDR_M{unit}",
+ "Throughput_AVG": f"Throughput_G{unit}_AVG",
+ "Throughput_STDEV": f"Throughput_G{unit}_STDEV"
l_data.append((suite, df_suite, ))
l_data.append((suite, df_suite, ))
"""
accordion_items = list()
"""
accordion_items = list()
- sel_data = select_coverage_data(data, selected, show_latency=show_latency)
+ sel_data, ttype = \
+ select_coverage_data(data, selected, show_latency=show_latency)
for suite, cov_data in sel_data:
for suite, cov_data in sel_data:
- if len(cov_data.columns) == 3: # VPP Device
+ if ttype == "device": # VPP Device
+ elif ttype == "mrr": # MRR
+ cols = list()
+ for idx, col in enumerate(cov_data.columns):
+ if idx == 0:
+ cols.append({
+ "name": ["", "", col],
+ "id": col,
+ "deletable": False,
+ "selectable": False,
+ "type": "text"
+ })
+ else:
+ cols.append({
+ "name": col.split("_"),
+ "id": col,
+ "deletable": False,
+ "selectable": False,
+ "type": "numeric",
+ "format": Format(precision=2, scheme=Scheme.fixed)
+ })
+ style_cell={"textAlign": "right"}
+ style_cell_conditional=[
+ {
+ "if": {"column_id": "Test Name"},
+ "textAlign": "left"
+ }
+ ]
+ else: # Performance NDRPDR
cols = list()
for idx, col in enumerate(cov_data.columns):
if idx == 0:
cols = list()
for idx, col in enumerate(cov_data.columns):
if idx == 0:
- result_latency_forward_pdr_90_hdrh
- result_latency_forward_pdr_50_hdrh
- result_latency_forward_pdr_10_hdrh
- result_latency_forward_pdr_90_hdrh
- result_latency_forward_pdr_50_hdrh
- result_latency_forward_pdr_10_hdrh
+- data_type: coverage
+ partition: test_type
+ partition_name: mrr
+ release: rls2310
+ path: s3://fdio-docs-s3-cloudfront-index/csit/parquet/coverage_rls2310
+ schema: iterative_rls2310_mrr
+ columns:
+ - job
+ - build
+ - dut_type
+ - dut_version
+ - start_time
+ - passed
+ - test_id
+ - version
+ - result_receive_rate_rate_avg
+ - result_receive_rate_rate_stdev
+ - result_receive_rate_rate_unit
- data_type: coverage
partition: test_type
partition_name: device
- data_type: coverage
partition: test_type
partition_name: device
# Maximal value of TIME_PERIOD for data read from the parquets in days.
# Do not change without a good reason.
# Maximal value of TIME_PERIOD for data read from the parquets in days.
# Do not change without a good reason.
# It defines the time period for data read from the parquets in days from
# now back to the past.
# It defines the time period for data read from the parquets in days from
# now back to the past.
"dpdk": "DPDK",
"container_memif": "LXC/DRC Container Memif",
"crypto": "IPSec IPv4 Routing",
"dpdk": "DPDK",
"container_memif": "LXC/DRC Container Memif",
"crypto": "IPSec IPv4 Routing",
"ip4": "IPv4 Routing",
"ip4_tunnels": "IPv4 Tunnels",
"ip6": "IPv6 Routing",
"ip4": "IPv4 Routing",
"ip4_tunnels": "IPv4 Tunnels",
"ip6": "IPv6 Routing",