diff --git a/data.js b/data.js index f38e481d..31191654 100644 --- a/data.js +++ b/data.js @@ -1,5 +1,5 @@ window.BENCHMARK_DATA = { - "lastUpdate": 1691440379662, + "lastUpdate": 1692913145539, "repoUrl": "https://github.com/ComPWA/tensorwaves", "entries": { "TensorWaves benchmark results": [ @@ -14470,6 +14470,142 @@ window.BENCHMARK_DATA = { "extra": "mean: 782.7159961999996 msec\nrounds: 5" } ] + }, + { + "commit": { + "author": { + "email": "29308176+redeboer@users.noreply.github.com", + "name": "Remco de Boer", + "username": "redeboer" + }, + "committer": { + "email": "noreply@github.com", + "name": "GitHub", + "username": "web-flow" + }, + "distinct": true, + "id": "713ee4706d220aae1926358c699960d3f1155393", + "message": "DOC: add `CITATION.cff` (#494)\n\n* MAINT: update pip constraints and pre-commit\r\n\r\n---------\r\n\r\nCo-authored-by: GitHub \r\nCo-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>", + "timestamp": "2023-08-24T23:34:46+02:00", + "tree_id": "53af84d009aec9063ecbfcdbcf1e546900769dba", + "url": "https://github.com/ComPWA/tensorwaves/commit/713ee4706d220aae1926358c699960d3f1155393" + }, + "date": 1692913144187, + "tool": "pytest", + "benches": [ + { + "name": "benchmarks/ampform.py::TestJPsiToGammaPiPi::test_data[10000-jax]", + "value": 0.24959983218904094, + "unit": "iter/sec", + "range": "stddev: 0", + "extra": "mean: 4.006412949999998 sec\nrounds: 1" + }, + { + "name": "benchmarks/ampform.py::TestJPsiToGammaPiPi::test_data[10000-numpy]", + "value": 0.21135751503689257, + "unit": "iter/sec", + "range": "stddev: 0", + "extra": "mean: 4.73131982000001 sec\nrounds: 1" + }, + { + "name": "benchmarks/ampform.py::TestJPsiToGammaPiPi::test_data[10000-tf]", + "value": 0.21000245185212618, + "unit": "iter/sec", + "range": "stddev: 0", + "extra": "mean: 4.761849165000001 sec\nrounds: 1" + }, + { + "name": "benchmarks/ampform.py::TestJPsiToGammaPiPi::test_fit[10000-jax]", + "value": 0.42378336184033394, + "unit": "iter/sec", + "range": "stddev: 0", + "extra": "mean: 2.359696226999972 sec\nrounds: 1" + }, + { + "name": "benchmarks/expression.py::test_data[3000-jax]", + "value": 16.953623044462237, + "unit": "iter/sec", + "range": "stddev: 0.0008862769761021869", + "extra": "mean: 58.98444228572381 msec\nrounds: 7" + }, + { + "name": "benchmarks/expression.py::test_data[3000-numpy]", + "value": 92.81156145094401, + "unit": "iter/sec", + "range": "stddev: 0.024084186023176923", + "extra": "mean: 10.774519729727364 msec\nrounds: 111" + }, + { + "name": "benchmarks/expression.py::test_data[3000-numba]", + "value": 2.8767153345800454, + "unit": "iter/sec", + "range": "stddev: 0.13627043966099855", + "extra": "mean: 347.6186843999926 msec\nrounds: 5" + }, + { + "name": "benchmarks/expression.py::test_data[3000-tf]", + "value": 61.61703164230807, + "unit": "iter/sec", + "range": "stddev: 0.0003248264634993141", + "extra": "mean: 16.229279037735573 msec\nrounds: 53" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-Minuit2-jax]", + "value": 5.848575798978509, + "unit": "iter/sec", + "range": "stddev: 0.0009428402866469838", + "extra": "mean: 170.98179699999037 msec\nrounds: 5" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-Minuit2-numpy]", + "value": 11.621560726214309, + "unit": "iter/sec", + "range": "stddev: 0.0008280923295628769", + "extra": "mean: 86.04696249999695 msec\nrounds: 12" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-Minuit2-numba]", + "value": 11.787878162546095, + "unit": "iter/sec", + "range": "stddev: 0.0013624288130991498", + "extra": "mean: 84.83290938460186 msec\nrounds: 13" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-Minuit2-tf]", + "value": 0.7812387346595209, + "unit": "iter/sec", + "range": "stddev: 0.006792205948986749", + "extra": "mean: 1.28001845739999 sec\nrounds: 5" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-ScipyMinimizer-jax]", + "value": 5.582618701569379, + "unit": "iter/sec", + "range": "stddev: 0.00022273950941768686", + "extra": "mean: 179.12740479998774 msec\nrounds: 5" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-ScipyMinimizer-numpy]", + "value": 11.76694126664417, + "unit": "iter/sec", + "range": "stddev: 0.0010683697287373701", + "extra": "mean: 84.98385241666047 msec\nrounds: 12" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-ScipyMinimizer-numba]", + "value": 11.720960248028737, + "unit": "iter/sec", + "range": "stddev: 0.0018686744763574653", + "extra": "mean: 85.31724183333722 msec\nrounds: 12" + }, + { + "name": "benchmarks/expression.py::test_fit[1000-ScipyMinimizer-tf]", + "value": 0.8986269653580083, + "unit": "iter/sec", + "range": "stddev: 0.005795386871764559", + "extra": "mean: 1.1128088056000025 sec\nrounds: 5" + } + ] } ] }