From 70a08dc3af6d498fd5d163b7ef0aba10e976f0e4 Mon Sep 17 00:00:00 2001 From: sgkit benchmark bot Date: Thu, 10 Oct 2024 13:49:13 +0000 Subject: [PATCH] Update benchmarks --- .../python-3.8/summary.json | 2 +- ...inkSpeedSuite.track_write_plink_speed.json | 2 +- ...ats.TimeSuite.time_count_call_alleles.json | 2 +- ...s.TimeSuite.time_count_cohort_alleles.json | 2 +- .../python-3.9/summary.json | 2 +- ...inkSpeedSuite.track_write_plink_speed.json | 2 +- ...ats.TimeSuite.time_count_call_alleles.json | 2 +- ...s.TimeSuite.time_count_cohort_alleles.json | 2 +- index.json | 2 +- info.json | 2 +- regressions.json | 2 +- regressions.xml | 5 +--- results/benchmarks.json | 27 ------------------- .../github-actions/f64dddb3-conda-py3.9.json | 1 + 14 files changed, 13 insertions(+), 42 deletions(-) create mode 100644 results/github-actions/f64dddb3-conda-py3.9.json diff --git a/graphs/branch-HEAD/machine-github-actions/python-3.8/summary.json 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away first run due to numba jit compilation\n for _ in range(2):\n duration = _time_func(write_plink, self.ds, path=self.output_plink)\n return _to_mb_per_s(get_dir_size(self.dir), duration)\n\n def setup(self) -> None:\n self.ds = simulate_genotype_call_dataset(\n n_variant=1000000, n_sample=1000, seed=0\n )\n \n self.dir = Path(tempfile.mkdtemp())\n self.output_plink = self.dir / \"plink_out\"", "name": "benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed", "param_names": [], "params": [], "type": "track", "unit": "unit", "version": "bd0a5d65a483fcc3805fe0397ded0bd7a60b220a9121a1e2fa2fccd2b4dcf304"}, "benchmarks_stats.TimeSuite.time_count_call_alleles": {"code": "class TimeSuite:\n def time_count_call_alleles(self) -> None:\n count_call_alleles(self.count_call_alleles_ds)\n\n def setup(self) -> None:\n self.count_call_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n self.count_cohort_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n sample_cohort = np.repeat(\n [0, 1], self.count_cohort_alleles_ds.dims[\"samples\"] // 2\n )\n self.count_cohort_alleles_ds[\"sample_cohort\"] = xr.DataArray(\n sample_cohort, dims=\"samples\"\n )", "min_run_count": 2, "name": "benchmarks_stats.TimeSuite.time_count_call_alleles", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "99097810ae6b766dfae46c4f296762848ccf073c2fd2f01204786c3957ae8c42", "warmup_time": -1}, "benchmarks_stats.TimeSuite.time_count_cohort_alleles": {"code": "class TimeSuite:\n def time_count_cohort_alleles(self) -> None:\n count_cohort_alleles(self.count_cohort_alleles_ds)\n\n def setup(self) -> None:\n self.count_call_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n self.count_cohort_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n sample_cohort = np.repeat(\n [0, 1], self.count_cohort_alleles_ds.dims[\"samples\"] // 2\n )\n self.count_cohort_alleles_ds[\"sample_cohort\"] = xr.DataArray(\n sample_cohort, dims=\"samples\"\n )", "min_run_count": 2, "name": "benchmarks_stats.TimeSuite.time_count_cohort_alleles", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "fb11db6a5b627835f0a682aa2ce1c793f9156522529ddfde2938933cc2278ff3", "warmup_time": -1}, "benchmarks_vcf.VcfCompressionSuite.track_zarr_compression_size": {"code": "class VcfCompressionSuite:\n def track_zarr_compression_size(self) -> None:\n encoding = {\n \"variant_AF\": {\n \"filters\": [\n FixedScaleOffset(offset=0, scale=10000, dtype=\"f4\", astype=\"u2\")\n ],\n },\n \"call_DS\": {\n \"filters\": [\n FixedScaleOffset(offset=0, scale=100, dtype=\"f4\", astype=\"u1\")\n ],\n },\n \"variant_DR2\": {\n \"filters\": [\n FixedScaleOffset(offset=0, scale=100, dtype=\"f4\", astype=\"u1\")\n ],\n },\n }\n \n kwargs = zarr_array_sizes(self.input_vcf)\n \n vcf_to_zarr(\n self.input_vcf,\n self.output_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n chunk_length=500_000,\n encoding=encoding,\n **kwargs,\n )\n \n original_size = du(self.input_vcf)\n zarr_size = du(self.output_zarr)\n \n return float(zarr_size) / original_size\n\n def setup(self) -> None:\n asv_env_dir = os.environ[\"ASV_ENV_DIR\"]\n self.input_vcf = Path(\n asv_env_dir,\n \"project/sgkit/tests/io/vcf/data/1kg_target_chr20_38_imputed_chr20_500000.vcf.bgz\",\n )\n \n tmp_path = Path(tempfile.mkdtemp())\n self.output_zarr = tmp_path.joinpath(\"1000G.out.zarr\")", "name": "benchmarks_vcf.VcfCompressionSuite.track_zarr_compression_size", "param_names": [], "params": [], "type": "track", "unit": "unit", "version": "dc81912750ea5a54712af421cbe8af7a6b531ef662ebf983c7e142966344b137"}, "benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed": {"code": "class VcfSpeedSuite:\n def track_vcf_to_zarr_speed(self) -> None:\n duration = _time_func(\n vcf_to_zarr,\n self.input_vcf,\n self.output_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n field_defs=self.field_defs,\n chunk_length=1_000,\n target_part_size=None,\n )\n return _to_mb_per_s(os.path.getsize(self.input_vcf), duration)\n\n def setup(self) -> None:\n asv_env_dir = os.environ[\"ASV_ENV_DIR\"]\n path = Path(\n asv_env_dir,\n \"project/sgkit/tests/io/vcf/data/1000G.phase3.broad.withGenotypes.chr20.10100000.vcf.gz\",\n )\n tmp_path = Path(tempfile.mkdtemp())\n self.input_vcf = tmp_path.joinpath(\"1000G.in.vcf\").as_posix()\n self.input_zarr = tmp_path.joinpath(\"1000G.in.zarr\").as_posix()\n self.output_zarr = tmp_path.joinpath(\"1000G.out.zarr\").as_posix()\n self.output_vcf = tmp_path.joinpath(\"1000G.out.vcf\").as_posix()\n \n # decompress file into temp dir so we can measure speed of vcf_to_zarr for uncompressed text\n _gunzip(path, self.input_vcf)\n \n # create a zarr input file so we can measure zarr_to_vcf speed\n self.field_defs = {\n \"FORMAT/AD\": {\"Number\": \"R\"},\n }\n vcf_to_zarr(\n self.input_vcf,\n self.input_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n field_defs=self.field_defs,\n chunk_length=1_000,\n target_part_size=None,\n )", "name": "benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed", "param_names": [], "params": [], "type": "track", "unit": "unit", "version": "ddb5fdcd4aebc966f439fca8b63f35169eb26ec25b7916bac38bb34462de8d8c"}, "benchmarks_vcf.VcfSpeedSuite.track_zarr_to_vcf_speed": {"code": "class VcfSpeedSuite:\n def track_zarr_to_vcf_speed(self) -> None:\n # throw away first run due to numba jit compilation\n for _ in range(2):\n duration = _time_func(zarr_to_vcf, self.input_zarr, self.output_vcf)\n return _to_mb_per_s(os.path.getsize(self.output_vcf), duration)\n\n def setup(self) -> None:\n asv_env_dir = os.environ[\"ASV_ENV_DIR\"]\n path = Path(\n asv_env_dir,\n \"project/sgkit/tests/io/vcf/data/1000G.phase3.broad.withGenotypes.chr20.10100000.vcf.gz\",\n )\n tmp_path = Path(tempfile.mkdtemp())\n self.input_vcf = tmp_path.joinpath(\"1000G.in.vcf\").as_posix()\n self.input_zarr = tmp_path.joinpath(\"1000G.in.zarr\").as_posix()\n self.output_zarr = tmp_path.joinpath(\"1000G.out.zarr\").as_posix()\n self.output_vcf = tmp_path.joinpath(\"1000G.out.vcf\").as_posix()\n \n # decompress file into temp dir so we can measure speed of vcf_to_zarr for uncompressed text\n _gunzip(path, self.input_vcf)\n \n # create a zarr input file so we can measure zarr_to_vcf speed\n self.field_defs = {\n \"FORMAT/AD\": {\"Number\": \"R\"},\n }\n vcf_to_zarr(\n self.input_vcf,\n self.input_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n field_defs=self.field_defs,\n chunk_length=1_000,\n target_part_size=None,\n )", "name": "benchmarks_vcf.VcfSpeedSuite.track_zarr_to_vcf_speed", "param_names": [], "params": [], "type": "track", "unit": "unit", "version": "b3e02860bad64aa5888fc20c1e3b54934ee5d2285b65e07dcf4bd09d2ab69be1"}}, "machines": {"github-actions": {"machine": "github-actions", "version": 1}}, "tags": {"0.1.0a1": 402, "0.2.0a1": 540, "0.3.0a1": 665, "0.3.0a2": 667, "0.3.0": 715, "0.4.0": 831, "0.5.0": 888, "0.6.0": 1098, "0.7.0": 1199, "0.8.0": 1288, "0.9.0": 1306}, "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": "sgkit", "project_url": "https://sgkit-dev.github.io/sgkit/", "show_commit_url": "http://github.com/sgkit-dev/sgkit/commit/", "hash_length": 8, "revision_to_hash": {"402": "712f2cf1e5bba0812bf5990eafc61a3d570e940f", "540": "da81a168f1feafb3504a7616669d49645d002b71", "665": "119c0b93c4ec4fa6ad3c7d7a3b4c943761fca6f9", "667": "6790d9526178fa22494d1a0cb78d5d709ff5849b", "715": "5d58d09f22f023c866e6b252662f84f83302eb61", "831": "4169d9a37eb7974ee2ff38e08f60002ee6f95f52", "877": "93af9a26f372c9136694b85727b7f540129f193d", "880": "ce34ca1151e8613ae8f6a53f0718105aa1c486b3", "882": 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1682326302000, "1187": 1682417416000, "1199": 1683019549000, "1228": 1693910600000, "1230": 1683109649000, "1234": 1690235412000, "1240": 1693876628000, "1242": 1696851117000, "1244": 1699873995000, "1246": 1701052143000, "1248": 1701174764000, "1250": 1701053335000, "1254": 1701719376000, "1257": 1702913345000, "1262": 1707145493000, "1264": 1707650022000, "1266": 1709566110000, "1274": 1708086077000, "1277": 1710290256000, "1279": 1711633264000, "1281": 1711635864000, "1282": 1711636162000, "1286": 1711736100000, "1288": 1714564441000, "1306": 1719478532000, "1317": 1725267052000, "1319": 1725283215000, "1322": 1725867857000, "1330": 1725880469000, "1332": 1725400826000, "1334": 1726061093000, "1336": 1725356904000, "1339": 1726580751000, "1343": 1726488282000, "1345": 1724597944000, "1355": 1728402227000}, "params": {"machine": ["github-actions"], "python": ["3.8", "3.9"], "branch": ["HEAD"]}, "graph_param_list": [{"machine": "github-actions", "python": "3.9", "branch": "HEAD"}, {"machine": "github-actions", "python": "3.8", "branch": "HEAD"}], "benchmarks": {"benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed": {"code": "class PlinkSpeedSuite:\n def track_write_plink_speed(self) -> None:\n # throw away first run due to numba jit compilation\n for _ in range(2):\n duration = _time_func(write_plink, self.ds, path=self.output_plink)\n return _to_mb_per_s(get_dir_size(self.dir), duration)\n\n def setup(self) -> None:\n self.ds = simulate_genotype_call_dataset(\n n_variant=1000000, n_sample=1000, seed=0\n )\n \n self.dir = Path(tempfile.mkdtemp())\n self.output_plink = self.dir / \"plink_out\"", "name": "benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed", "param_names": [], "params": [], "type": "track", "unit": "unit", "version": "bd0a5d65a483fcc3805fe0397ded0bd7a60b220a9121a1e2fa2fccd2b4dcf304"}, "benchmarks_stats.TimeSuite.time_count_call_alleles": {"code": "class TimeSuite:\n def time_count_call_alleles(self) -> None:\n count_call_alleles(self.count_call_alleles_ds)\n\n def setup(self) -> None:\n self.count_call_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n self.count_cohort_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n sample_cohort = np.repeat(\n [0, 1], self.count_cohort_alleles_ds.dims[\"samples\"] // 2\n )\n self.count_cohort_alleles_ds[\"sample_cohort\"] = xr.DataArray(\n sample_cohort, dims=\"samples\"\n )", "min_run_count": 2, "name": "benchmarks_stats.TimeSuite.time_count_call_alleles", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "99097810ae6b766dfae46c4f296762848ccf073c2fd2f01204786c3957ae8c42", "warmup_time": -1}, "benchmarks_stats.TimeSuite.time_count_cohort_alleles": {"code": "class TimeSuite:\n def time_count_cohort_alleles(self) -> None:\n count_cohort_alleles(self.count_cohort_alleles_ds)\n\n def setup(self) -> None:\n self.count_call_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n self.count_cohort_alleles_ds = simulate_genotype_call_dataset(\n n_variant=100_000, n_sample=1000\n )\n sample_cohort = np.repeat(\n [0, 1], self.count_cohort_alleles_ds.dims[\"samples\"] // 2\n )\n self.count_cohort_alleles_ds[\"sample_cohort\"] = xr.DataArray(\n sample_cohort, dims=\"samples\"\n )", "min_run_count": 2, "name": "benchmarks_stats.TimeSuite.time_count_cohort_alleles", "number": 0, "param_names": [], "params": [], "repeat": 0, "rounds": 2, "sample_time": 0.01, "type": "time", "unit": "seconds", "version": "fb11db6a5b627835f0a682aa2ce1c793f9156522529ddfde2938933cc2278ff3", "warmup_time": -1}}, "machines": {"github-actions": {"machine": "github-actions", "version": 1}}, "tags": {"0.1.0a1": 402, "0.2.0a1": 540, "0.3.0a1": 665, "0.3.0a2": 667, "0.3.0": 715, "0.4.0": 831, "0.5.0": 888, "0.6.0": 1098, "0.7.0": 1199, "0.8.0": 1288, "0.9.0": 1306}, "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 163f2a9..cc79c3c 100644 --- a/info.json +++ b/info.json @@ -1,4 +1,4 @@ { "asv-version": "0.6.4", - "timestamp": 1727684054846 + "timestamp": 1728568153558 } \ No newline at end of file diff --git a/regressions.json b/regressions.json index a6a2570..11db7bc 100644 --- a/regressions.json +++ b/regressions.json @@ -1 +1 @@ -{"regressions": [["benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed", "graphs/branch-HEAD/machine-github-actions/python-3.8/benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed.json", {"python": "3.8"}, null, 41.11403111153426, 17.225664780926454, [[null, 1244, 17.225664780926454, 41.11403111153426]]], ["benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed", "graphs/branch-HEAD/machine-github-actions/python-3.8/benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed.json", {"python": "3.8"}, null, 10.097180963357445, 6.5875330848592455, [[null, 1244, 6.5875330848592455, 10.097180963357445]]]]} \ No newline at end of file +{"regressions": [["benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed", "graphs/branch-HEAD/machine-github-actions/python-3.8/benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed.json", {"python": "3.8"}, null, 41.11403111153426, 17.225664780926454, [[null, 1244, 17.225664780926454, 41.11403111153426]]]]} \ No newline at end of file diff --git a/regressions.xml b/regressions.xml index 30bff42..8185ea0 100644 --- a/regressions.xml +++ b/regressions.xml @@ -1,8 +1,5 @@ -tag:sgkit.asv,1970-01-01:/1fa4d8efe749b95747253e91769bc7150e7cefbb940f58885061fc1a00edcb69Airspeed Velocitysgkit performance regressions2023-11-13T14:15:23Ztag:sgkit.asv,2023-11-13:/e21516be2366c08733863a89715c11bb64b9e10deb46083dc20751cf50c4e2d453.28% benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed2023-11-13T14:15:23Z<a href="index.html#benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed?python=3.8&commits=788f6cc1e7c28b8a1c0066eb069f7296fdbd3de6">53.28% regression</a> on 2023-11-13 11:13:15 in commit <a href="http://github.com/sgkit-dev/sgkit/commit/788f6cc1e7c28b8a1c0066eb069f7296fdbd3de6">788f6cc1</a>.<br> - New value: 10.097180963357445, old value: 6.5875330848592455.<br> - Latest value: 10.097180963357445 (53.28% worse - than best value 6.5875330848592455).tag:sgkit.asv,2023-11-13:/2f87989baa01869669e0731e36fba51c43c2ac9921b36ed3eb00ec49ff3b103f138.68% benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed2023-11-13T14:14:46Z<a href="index.html#benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed?python=3.8&commits=788f6cc1e7c28b8a1c0066eb069f7296fdbd3de6">138.68% regression</a> on 2023-11-13 11:13:15 in commit <a href="http://github.com/sgkit-dev/sgkit/commit/788f6cc1e7c28b8a1c0066eb069f7296fdbd3de6">788f6cc1</a>.<br> +tag:sgkit.asv,1970-01-01:/1fa4d8efe749b95747253e91769bc7150e7cefbb940f58885061fc1a00edcb69Airspeed Velocitysgkit performance regressions2023-11-13T14:14:46Ztag:sgkit.asv,2023-11-13:/2f87989baa01869669e0731e36fba51c43c2ac9921b36ed3eb00ec49ff3b103f138.68% benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed2023-11-13T14:14:46Z<a href="index.html#benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed?python=3.8&commits=788f6cc1e7c28b8a1c0066eb069f7296fdbd3de6">138.68% regression</a> on 2023-11-13 11:13:15 in commit <a href="http://github.com/sgkit-dev/sgkit/commit/788f6cc1e7c28b8a1c0066eb069f7296fdbd3de6">788f6cc1</a>.<br> New value: 41.11403111153426, old value: 17.225664780926454.<br> Latest value: 41.11403111153426 (138.68% worse than best value 17.225664780926454). \ No newline at end of file diff --git a/results/benchmarks.json b/results/benchmarks.json index 133423d..24889bc 100644 --- a/results/benchmarks.json +++ b/results/benchmarks.json @@ -38,32 +38,5 @@ "version": "fb11db6a5b627835f0a682aa2ce1c793f9156522529ddfde2938933cc2278ff3", "warmup_time": -1 }, - "benchmarks_vcf.VcfCompressionSuite.track_zarr_compression_size": { - "code": "class VcfCompressionSuite:\n def track_zarr_compression_size(self) -> None:\n encoding = {\n \"variant_AF\": {\n \"filters\": [\n FixedScaleOffset(offset=0, scale=10000, dtype=\"f4\", astype=\"u2\")\n ],\n },\n \"call_DS\": {\n \"filters\": [\n FixedScaleOffset(offset=0, scale=100, dtype=\"f4\", astype=\"u1\")\n ],\n },\n \"variant_DR2\": {\n \"filters\": [\n FixedScaleOffset(offset=0, scale=100, dtype=\"f4\", astype=\"u1\")\n ],\n },\n }\n \n kwargs = zarr_array_sizes(self.input_vcf)\n \n vcf_to_zarr(\n self.input_vcf,\n self.output_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n chunk_length=500_000,\n encoding=encoding,\n **kwargs,\n )\n \n original_size = du(self.input_vcf)\n zarr_size = du(self.output_zarr)\n \n return float(zarr_size) / original_size\n\n def setup(self) -> None:\n asv_env_dir = os.environ[\"ASV_ENV_DIR\"]\n self.input_vcf = Path(\n asv_env_dir,\n \"project/sgkit/tests/io/vcf/data/1kg_target_chr20_38_imputed_chr20_500000.vcf.bgz\",\n )\n \n tmp_path = Path(tempfile.mkdtemp())\n self.output_zarr = tmp_path.joinpath(\"1000G.out.zarr\")", - "name": "benchmarks_vcf.VcfCompressionSuite.track_zarr_compression_size", - "param_names": [], - "params": [], - "type": "track", - "unit": "unit", - "version": "dc81912750ea5a54712af421cbe8af7a6b531ef662ebf983c7e142966344b137" - }, - "benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed": { - "code": "class VcfSpeedSuite:\n def track_vcf_to_zarr_speed(self) -> None:\n duration = _time_func(\n vcf_to_zarr,\n self.input_vcf,\n self.output_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n field_defs=self.field_defs,\n chunk_length=1_000,\n target_part_size=None,\n )\n return _to_mb_per_s(os.path.getsize(self.input_vcf), duration)\n\n def setup(self) -> None:\n asv_env_dir = os.environ[\"ASV_ENV_DIR\"]\n path = Path(\n asv_env_dir,\n \"project/sgkit/tests/io/vcf/data/1000G.phase3.broad.withGenotypes.chr20.10100000.vcf.gz\",\n )\n tmp_path = Path(tempfile.mkdtemp())\n self.input_vcf = tmp_path.joinpath(\"1000G.in.vcf\").as_posix()\n self.input_zarr = tmp_path.joinpath(\"1000G.in.zarr\").as_posix()\n self.output_zarr = tmp_path.joinpath(\"1000G.out.zarr\").as_posix()\n self.output_vcf = tmp_path.joinpath(\"1000G.out.vcf\").as_posix()\n \n # decompress file into temp dir so we can measure speed of vcf_to_zarr for uncompressed text\n _gunzip(path, self.input_vcf)\n \n # create a zarr input file so we can measure zarr_to_vcf speed\n self.field_defs = {\n \"FORMAT/AD\": {\"Number\": \"R\"},\n }\n vcf_to_zarr(\n self.input_vcf,\n self.input_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n field_defs=self.field_defs,\n chunk_length=1_000,\n target_part_size=None,\n )", - "name": "benchmarks_vcf.VcfSpeedSuite.track_vcf_to_zarr_speed", - "param_names": [], - "params": [], - "type": "track", - "unit": "unit", - "version": "ddb5fdcd4aebc966f439fca8b63f35169eb26ec25b7916bac38bb34462de8d8c" - }, - "benchmarks_vcf.VcfSpeedSuite.track_zarr_to_vcf_speed": { - "code": "class VcfSpeedSuite:\n def track_zarr_to_vcf_speed(self) -> None:\n # throw away first run due to numba jit compilation\n for _ in range(2):\n duration = _time_func(zarr_to_vcf, self.input_zarr, self.output_vcf)\n return _to_mb_per_s(os.path.getsize(self.output_vcf), duration)\n\n def setup(self) -> None:\n asv_env_dir = os.environ[\"ASV_ENV_DIR\"]\n path = Path(\n asv_env_dir,\n \"project/sgkit/tests/io/vcf/data/1000G.phase3.broad.withGenotypes.chr20.10100000.vcf.gz\",\n )\n tmp_path = Path(tempfile.mkdtemp())\n self.input_vcf = tmp_path.joinpath(\"1000G.in.vcf\").as_posix()\n self.input_zarr = tmp_path.joinpath(\"1000G.in.zarr\").as_posix()\n self.output_zarr = tmp_path.joinpath(\"1000G.out.zarr\").as_posix()\n self.output_vcf = tmp_path.joinpath(\"1000G.out.vcf\").as_posix()\n \n # decompress file into temp dir so we can measure speed of vcf_to_zarr for uncompressed text\n _gunzip(path, self.input_vcf)\n \n # create a zarr input file so we can measure zarr_to_vcf speed\n self.field_defs = {\n \"FORMAT/AD\": {\"Number\": \"R\"},\n }\n vcf_to_zarr(\n self.input_vcf,\n self.input_zarr,\n fields=[\"INFO/*\", \"FORMAT/*\"],\n field_defs=self.field_defs,\n chunk_length=1_000,\n target_part_size=None,\n )", - "name": "benchmarks_vcf.VcfSpeedSuite.track_zarr_to_vcf_speed", - "param_names": [], - "params": [], - "type": "track", - "unit": "unit", - "version": "b3e02860bad64aa5888fc20c1e3b54934ee5d2285b65e07dcf4bd09d2ab69be1" - }, "version": 2 } \ No newline at end of file diff --git a/results/github-actions/f64dddb3-conda-py3.9.json b/results/github-actions/f64dddb3-conda-py3.9.json new file mode 100644 index 0000000..c6ae08d --- /dev/null +++ b/results/github-actions/f64dddb3-conda-py3.9.json @@ -0,0 +1 @@ +{"commit_hash": "f64dddb33e389e9facddadc362910158bc8a6ca8", "env_name": "conda-py3.9", "date": 1728402227000, "params": {"machine": "github-actions", "python": "3.9"}, "python": "3.9", "requirements": {}, "env_vars": {}, "result_columns": ["result", "params", "version", "started_at", "duration", "stats_ci_99_a", "stats_ci_99_b", "stats_q_25", "stats_q_75", "stats_number", "stats_repeat", "samples", "profile"], "results": {"benchmarks_stats.TimeSuite.time_count_call_alleles": [[0.11926969099999951], [], "99097810ae6b766dfae46c4f296762848ccf073c2fd2f01204786c3957ae8c42", 1728568134060, 14.601, [0.11915], [0.12399], [0.11919], [0.11939], [1], [10]], "benchmarks_stats.TimeSuite.time_count_cohort_alleles": [[0.12119378650000101], [], "fb11db6a5b627835f0a682aa2ce1c793f9156522529ddfde2938933cc2278ff3", 1728568141356, 22.688, [0.12111], [0.12151], [0.12118], [0.12148], [1], [8]], "benchmarks_plink.PlinkSpeedSuite.track_write_plink_speed": [[43.62521133163991], [], "bd0a5d65a483fcc3805fe0397ded0bd7a60b220a9121a1e2fa2fccd2b4dcf304", 1728568117961, 16.099]}, "durations": {}, "version": 2} \ No newline at end of file