diff options
Diffstat (limited to 'csit.infra.dash/app/cdash/coverage/tables.py')
| -rw-r--r-- | csit.infra.dash/app/cdash/coverage/tables.py | 55 |
1 files changed, 47 insertions, 8 deletions
diff --git a/csit.infra.dash/app/cdash/coverage/tables.py b/csit.infra.dash/app/cdash/coverage/tables.py index f2fa90ffb2..372a8206bf 100644 --- a/csit.infra.dash/app/cdash/coverage/tables.py +++ b/csit.infra.dash/app/cdash/coverage/tables.py @@ -14,6 +14,7 @@ """The coverage data tables. """ + import hdrh.histogram import hdrh.codec import pandas as pd @@ -54,7 +55,7 @@ def select_coverage_data( 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("_", "-") else: return l_data @@ -67,7 +68,7 @@ def select_coverage_data( df = df[ (df.job.str.endswith(f"{topo}-{arch}")) & (df.test_id.str.contains( - f"^.*\.{selected['area']}\..*{nic}.*{drv}.*$", + f"^.*\.{selected['area']}\..*{nic}.*{drv_str}.*$", regex=True )) ] @@ -115,7 +116,15 @@ def select_coverage_data( if ttype == "device": cov = cov.assign(Result="PASS") - else: + 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 @@ -152,7 +161,9 @@ def select_coverage_data( 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" }, inplace=True ) @@ -160,7 +171,7 @@ def select_coverage_data( l_data.append((suite, df_suite, )) - return l_data + return l_data, ttype def coverage_tables( @@ -181,9 +192,10 @@ def coverage_tables( """ 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: - if len(cov_data.columns) == 3: # VPP Device + if ttype == "device": # VPP Device cols = [ { "name": col, @@ -200,7 +212,34 @@ def coverage_tables( "textAlign": "right" } ] - else: # Performance + 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: |