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add PyACP benchmarks (pytest) benchmark result for 799a674
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Nov 28, 2024
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@@ -1,5 +1,5 @@ | ||
window.BENCHMARK_DATA = { | ||
"lastUpdate": 1732783376984, | ||
"lastUpdate": 1732806222324, | ||
"repoUrl": "https://github.com/ansys/pyacp", | ||
"entries": { | ||
"PyACP benchmarks": [ | ||
|
@@ -22130,6 +22130,128 @@ window.BENCHMARK_DATA = { | |
"extra": "mean: 38.35206433334153 msec\nrounds: 27" | ||
} | ||
] | ||
}, | ||
{ | ||
"commit": { | ||
"author": { | ||
"email": "[email protected]", | ||
"name": "René Roos", | ||
"username": "roosre" | ||
}, | ||
"committer": { | ||
"email": "[email protected]", | ||
"name": "GitHub", | ||
"username": "web-flow" | ||
}, | ||
"distinct": true, | ||
"id": "799a674d483becbb68ec0d0d11cbfa81f685f962", | ||
"message": "Add example for Imported Plies and the hdf5 composite cae interface (#714)\n\n* Add examples for Imported Plies HDF5 composite CAE\r\n\r\n* Add solid_mesh property to ImportedAnalysisPly and ImportedSolidModel\r\n---------\r\n\r\nCo-authored-by: Dominik Gresch <[email protected]>", | ||
"timestamp": "2024-11-28T14:56:43Z", | ||
"tree_id": "0ee0d9d36ad6c1e2a11866cdb5e990070d9183eb", | ||
"url": "https://github.com/ansys/pyacp/commit/799a674d483becbb68ec0d0d11cbfa81f685f962" | ||
}, | ||
"date": 1732806190675, | ||
"tool": "pytest", | ||
"benches": [ | ||
{ | ||
"name": "tests/benchmarks/test_class40.py::test_class40[delay=0ms, rate=1000000.0kbit]", | ||
"value": 7.784738618584961, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.003910272782434686", | ||
"extra": "mean: 128.45646449999512 msec\nrounds: 6" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_class40.py::test_class40[delay=1ms, rate=1000000.0kbit]", | ||
"value": 2.679425244172109, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.005627992883958249", | ||
"extra": "mean: 373.21436833330307 msec\nrounds: 3" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_class40.py::test_class40[delay=10ms, rate=1000000.0kbit]", | ||
"value": 0.38803405101704724, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0", | ||
"extra": "mean: 2.5770934209999723 sec\nrounds: 1" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_class40.py::test_class40[delay=100ms, rate=1000000.0kbit]", | ||
"value": 0.04098091941161853, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0", | ||
"extra": "mean: 24.40159992399998 sec\nrounds: 1" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_class40.py::test_class40[delay=0ms, rate=10000.0kbit]", | ||
"value": 2.1579985888962083, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.004808279717992765", | ||
"extra": "mean: 463.3923326666718 msec\nrounds: 3" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_class40.py::test_class40[delay=0ms, rate=1000.0kbit]", | ||
"value": 0.2861610074114202, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0", | ||
"extra": "mean: 3.494536202000006 sec\nrounds: 1" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_class40.py::test_class40[delay=0ms, rate=100.0kbit]", | ||
"value": 0.029657336761437142, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0", | ||
"extra": "mean: 33.718469330000005 sec\nrounds: 1" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_create.py::test_create_modeling_group[delay=0ms, rate=1000000.0kbit]", | ||
"value": 1424.4310729238669, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.00017870407476167901", | ||
"extra": "mean: 702.0346712511291 usec\nrounds: 1527" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_create.py::test_create_modeling_group[delay=1ms, rate=1000000.0kbit]", | ||
"value": 402.30119081562754, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.00006670639033955183", | ||
"extra": "mean: 2.4856998259751477 msec\nrounds: 385" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_create.py::test_create_modeling_group[delay=10ms, rate=1000000.0kbit]", | ||
"value": 48.09703813414252, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.0001619216391342317", | ||
"extra": "mean: 20.791301061221326 msec\nrounds: 49" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_create.py::test_create_modeling_group[delay=100ms, rate=1000000.0kbit]", | ||
"value": 4.9735084035745745, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.00004859971627634996", | ||
"extra": "mean: 201.06530819999762 msec\nrounds: 5" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_create.py::test_create_modeling_group[delay=0ms, rate=10000.0kbit]", | ||
"value": 1028.9957042397389, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.0001265026719317496", | ||
"extra": "mean: 971.8213554048198 usec\nrounds: 1027" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_create.py::test_create_modeling_group[delay=0ms, rate=1000.0kbit]", | ||
"value": 233.64303290102765, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.00007536084040728036", | ||
"extra": "mean: 4.280033466367495 msec\nrounds: 223" | ||
}, | ||
{ | ||
"name": "tests/benchmarks/test_create.py::test_create_modeling_group[delay=0ms, rate=100.0kbit]", | ||
"value": 25.941489631167432, | ||
"unit": "iter/sec", | ||
"range": "stddev: 0.00017898121078326987", | ||
"extra": "mean: 38.548287481477125 msec\nrounds: 27" | ||
} | ||
] | ||
} | ||
] | ||
} | ||
|