From b37e3379ed96fd0a4fa3f94ddea306b9b5837efc Mon Sep 17 00:00:00 2001 From: jeremykubica <104161096+jeremykubica@users.noreply.github.com> Date: Fri, 13 Sep 2024 21:18:16 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20lincc-fr?= =?UTF-8?q?ameworks/tdastro@c7ecfa54cb13160d8e63a32bf15c24c974afdc51=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../packaging/python-3.10/benchmarks.time_chained_evaluate.json | 2 +- .../packaging/python-3.10/benchmarks.time_x1_from_hostmass.json | 2 +- .../build/machine-gh-runner/packaging/python-3.10/summary.json | 2 +- graphs/summary/benchmarks.time_chained_evaluate.json | 2 +- graphs/summary/benchmarks.time_x1_from_hostmass.json | 2 +- index.json | 2 +- info.json | 2 +- regressions.xml | 2 +- 8 files changed, 8 insertions(+), 8 deletions(-) diff --git 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Use those to\n # generate a sample from the normal distribution. Then shift that sample by -5.0.\n loc_node = NumpyRandomFunc(\"uniform\", low=10.0, high=20.0)\n scale_node = NumpyRandomFunc(\"uniform\", low=0.5, high=1.0)\n norm_node = NumpyRandomFunc(\"normal\", loc=loc_node, scale=scale_node)\n val_node = FunctionNode(_add_func, a=norm_node, b=-5.0)\n\n # Generate 100,000 samples.\n _ = val_node.sample_parameters(num_samples=100_000)", "min_run_count": 2, "name": "benchmarks.time_chained_evaluate", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b4af9f0021b65861c69db8702dd0a230a74916ac2d379702d0c9d1f047d711f2", "warmup_time": -1}, "benchmarks.time_x1_from_hostmass": {"code": "def time_x1_from_hostmass():\n \"\"\"Time the generation of random numbers from the X1 function.\"\"\"\n x1_func = HostmassX1Func(11.0)\n _ = x1_func.sample_parameters(num_samples=10)", "min_run_count": 2, "name": "benchmarks.time_x1_from_hostmass", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "884f0102518d908729fb55e5e29a036490aedd2a1590976b46d3492ed5cf99a1", "warmup_time": -1}}, "machines": {"gh-runner": {"machine": "gh-runner", "version": 1}}, "tags": {}, "pages": [["", "Grid view", "Display as a agrid"], ["summarylist", "List view", "Display as a list"], ["regressions", "Show regressions", "Display information about recent regressions"]]} \ No newline at end of file +{"project": "tdastro", "project_url": "https://github.com/lincc-frameworks/tdastro", "show_commit_url": "https://github.com/lincc-frameworks/tdastro/commit/", "hash_length": 8, "revision_to_hash": {"0": "98eb15f5c411d9a136d18b0ae5ec9df14e2f6287", "1": "30225d1b54431d19dcfe9552898df5366d798b66", "2": "678d58e603bac97e57e5c20344d46af7acaa6c33", "3": "7519ef02db3e46d29645eb024787c4780fd90e49", "4": "7bef979448ce46b5f1dcbf448f0aea941b69aeb9", "12": "3c83d1c92e7876354587e153fd6c51690cb7670b", "15": 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def _add_func(a, b):\n return a + b\n\n # Generate a starting mean and scale from uniform distributions. Use those to\n # generate a sample from the normal distribution. Then shift that sample by -5.0.\n loc_node = NumpyRandomFunc(\"uniform\", low=10.0, high=20.0)\n scale_node = NumpyRandomFunc(\"uniform\", low=0.5, high=1.0)\n norm_node = NumpyRandomFunc(\"normal\", loc=loc_node, scale=scale_node)\n val_node = FunctionNode(_add_func, a=norm_node, b=-5.0)\n\n # Generate 100,000 samples.\n _ = val_node.sample_parameters(num_samples=100_000)", "min_run_count": 2, "name": "benchmarks.time_chained_evaluate", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "b4af9f0021b65861c69db8702dd0a230a74916ac2d379702d0c9d1f047d711f2", "warmup_time": -1}, "benchmarks.time_x1_from_hostmass": {"code": "def time_x1_from_hostmass():\n \"\"\"Time the generation of random numbers from the X1 function.\"\"\"\n x1_func = HostmassX1Func(11.0)\n _ = x1_func.sample_parameters(num_samples=10)", "min_run_count": 2, "name": "benchmarks.time_x1_from_hostmass", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "884f0102518d908729fb55e5e29a036490aedd2a1590976b46d3492ed5cf99a1", "warmup_time": -1}}, "machines": {"gh-runner": {"machine": "gh-runner", "version": 1}}, "tags": {}, "pages": [["", "Grid view", "Display as a agrid"], ["summarylist", "List view", "Display as a list"], ["regressions", "Show regressions", "Display information about recent regressions"]]} \ No newline at end of file diff --git a/info.json b/info.json index 04982b6f..f3496500 100644 --- a/info.json +++ b/info.json @@ -1,4 +1,4 @@ { "asv-version": "0.6.1", - "timestamp": 1726084941943 + "timestamp": 1726262296104 } \ No newline at end of file diff --git a/regressions.xml b/regressions.xml index f01bc809..6faac343 100644 --- a/regressions.xml +++ b/regressions.xml @@ -1,2 +1,2 @@ -tag:tdastro.asv,1970-01-01:/ebf359c79517f805bb81f390ee0edbc35610f7474e3a5cd79486c82d8dd189a2Airspeed Velocitytdastro performance regressions2024-09-11T20:02:21Z \ No newline at end of file +tag:tdastro.asv,1970-01-01:/ebf359c79517f805bb81f390ee0edbc35610f7474e3a5cd79486c82d8dd189a2Airspeed Velocitytdastro performance regressions2024-09-13T21:18:16Z \ No newline at end of file