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"aa75da38392d38d48c16e798d32c8fc13c405fba9bfd70f066899abe430b212e", 1728329151007], "mpas_ocean.RemapDownsample.time_inverse_distance_weighted_remapping": [null, [], "35146054f62256ab927954781012aad8a15b03eef90a4aece78bf2b7002c4853", 1722467263333], "mpas_ocean.RemapDownsample.time_nearest_neighbor_remapping": [null, [], "3454ce734208221027c7080a56f1e679ae092a93516752a89474d75d7a705472", 1722467263333], "mpas_ocean.RemapUpsample.time_inverse_distance_weighted_remapping": [null, [], "0836cc8c471952d8a557cf8d6c1d3c0677d0193d4ad961126f0bd34dab5dd9b9", 1722467263333], "mpas_ocean.RemapUpsample.time_nearest_neighbor_remapping": [null, [], "db94cc8878dce6417e0aa06f72be38042115986e62fe929389fb2b48d8c93582", 1722467263333], "mpas_ocean.HoleEdgeIndices.time_construct_hole_edge_indices": [null, [["'480km'", "'120km'"]], "a430053e96f9871237f9ff8ea704a577a4f63617ab7c6bed07eb840194d992b3", 1728329151007], "face_bounds.Bounds.time_bounds": [null, [], "f0dc6389b413dd90cc4bc89d04e22d4bded407582cf58cebc40a895c3e608dea", 1726609693598], "mpas_ocean.CheckNorm.time_check_norm": [null, [["'480km'", "'120km'"]], "80690bc549b4d4d30b9190960e39e99a70d987dd80b2fe9655f568b292f50f7c", 1726680422727]}, "durations": {"": 2.874875783920288}, "version": 2} \ No newline at end of file diff --git a/results/benchmarks.json b/results/benchmarks.json index 64d81259..8383cc59 100644 --- a/results/benchmarks.json +++ b/results/benchmarks.json @@ -79,7 +79,7 @@ "warmup_time": -1 }, "mpas_ocean.ConnectivityConstruction.time_face_face_connectivity": { - "code": "class ConnectivityConstruction:\n def time_face_face_connectivity(self, resolution):\n ux.grid.connectivity._populate_face_face_connectivity(self.uxds.uxgrid)\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class ConnectivityConstruction:\n def time_face_face_connectivity(self, resolution):\n ux.grid.connectivity._populate_face_face_connectivity(self.uxds.uxgrid)\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.ConnectivityConstruction.time_face_face_connectivity", "number": 0, @@ -97,11 +97,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "0e86f4796f5762f3d54fbc03de55c71678cd10713a9d855732c8d7f6271fb5d9", + "version": "d17d64682605c89f3a4a41dacad12310025c7e894bde080abaa54192989d3bfe", "warmup_time": -1 }, "mpas_ocean.ConnectivityConstruction.time_n_nodes_per_face": { - "code": "class ConnectivityConstruction:\n def time_n_nodes_per_face(self, resolution):\n self.uxds.uxgrid.n_nodes_per_face\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class ConnectivityConstruction:\n def time_n_nodes_per_face(self, resolution):\n self.uxds.uxgrid.n_nodes_per_face\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.ConnectivityConstruction.time_n_nodes_per_face", "number": 0, @@ -119,11 +119,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "048a954b109fd388237d52a513b83fdb053c87fe5b04e39e2b0ed22db26ac7cc", + "version": "eb11f7750b605d9f6ea6467f4d970fc820bcab30a71e4ebb06b2bae37172a76f", "warmup_time": -1 }, "mpas_ocean.ConstructTreeStructures.time_ball_tree": { - "code": "class ConstructTreeStructures:\n def time_ball_tree(self, resolution):\n self.uxds.uxgrid.get_ball_tree()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class ConstructTreeStructures:\n def time_ball_tree(self, resolution):\n self.uxds.uxgrid.get_ball_tree()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.ConstructTreeStructures.time_ball_tree", "number": 0, @@ -141,11 +141,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "e6c12f881e09c7410a76b884d48cbd5cfed69c7b1ac45f0a912c25e683644eec", + "version": "e7a6195397c4d1d166a7853510f074734c6066eeb2f5d8adb15911a8b29fc6eb", "warmup_time": -1 }, "mpas_ocean.ConstructTreeStructures.time_kd_tree": { - "code": "class ConstructTreeStructures:\n def time_kd_tree(self, resolution):\n self.uxds.uxgrid.get_kd_tree()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class ConstructTreeStructures:\n def time_kd_tree(self, resolution):\n self.uxds.uxgrid.get_kd_tree()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.ConstructTreeStructures.time_kd_tree", "number": 0, @@ -163,11 +163,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "5cb806e87ae96ad594fa332873c00f308209beb043243fad87db127a6f58d0d2", + "version": "aa75da38392d38d48c16e798d32c8fc13c405fba9bfd70f066899abe430b212e", "warmup_time": -1 }, "mpas_ocean.GeoDataFrame.time_to_geodataframe": { - "code": "class GeoDataFrame:\n def time_to_geodataframe(self, resolution, exclude_antimeridian):\n self.uxds[data_var].to_geodataframe(exclude_antimeridian=exclude_antimeridian)\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class GeoDataFrame:\n def time_to_geodataframe(self, resolution, exclude_antimeridian):\n self.uxds[data_var].to_geodataframe(exclude_antimeridian=exclude_antimeridian)\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.GeoDataFrame.time_to_geodataframe", "number": 0, @@ -190,11 +190,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "5ae84430963547882e3ca35285f39b2c73c17832f240321838d046fe481aff0a", + "version": "fdda72e8afd45608569fb3343f6f067cf3716dba26532eb142be9223fc5d0b98", "warmup_time": -1 }, "mpas_ocean.Gradient.peakmem_gradient": { - "code": "class Gradient:\n def peakmem_gradient(self, resolution):\n grad = self.uxds[data_var].gradient()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class Gradient:\n def peakmem_gradient(self, resolution):\n grad = self.uxds[data_var].gradient()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "name": "mpas_ocean.Gradient.peakmem_gradient", "param_names": [ "resolution" @@ -207,10 +207,10 @@ ], "type": "peakmemory", "unit": "bytes", - "version": "ec24e9b4704c46d7ab04c978ae9b9d24c2e8ef6e77498414f29ec74ca6e8a34d" + "version": "2c5704784f88210b00288651dbcee688318ff4ebf5674568a090a297c508c8ff" }, "mpas_ocean.Gradient.time_gradient": { - "code": "class Gradient:\n def time_gradient(self, resolution):\n self.uxds[data_var].gradient()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class Gradient:\n def time_gradient(self, resolution):\n self.uxds[data_var].gradient()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.Gradient.time_gradient", "number": 0, @@ -228,11 +228,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "a6a46ac79f2cff8797ec9dc46acbbdf483ada08ae6701d6631d0382b0051c35d", + "version": "19b8246a1b7f7cd52ec73d727dca3bb45b1952d4ef7644d2f13f7929bb16c0ad", "warmup_time": -1 }, "mpas_ocean.HoleEdgeIndices.time_construct_hole_edge_indices": { - "code": "class HoleEdgeIndices:\n def time_construct_hole_edge_indices(self, resolution):\n ux.grid.geometry._construct_hole_edge_indices(self.uxds.uxgrid.edge_face_connectivity)\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class HoleEdgeIndices:\n def time_construct_hole_edge_indices(self, resolution):\n ux.grid.geometry._construct_hole_edge_indices(self.uxds.uxgrid.edge_face_connectivity)\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.HoleEdgeIndices.time_construct_hole_edge_indices", "number": 0, @@ -250,11 +250,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "40d01110d8192eb24b3d3c7ce52f74afbaa2f8efd645eb650339db1cbfe9e4f9", + "version": "a430053e96f9871237f9ff8ea704a577a4f63617ab7c6bed07eb840194d992b3", "warmup_time": -1 }, "mpas_ocean.Integrate.peakmem_integrate": { - "code": "class Integrate:\n def peakmem_integrate(self, resolution):\n integral = self.uxds[data_var].integrate()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class Integrate:\n def peakmem_integrate(self, resolution):\n integral = self.uxds[data_var].integrate()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "name": "mpas_ocean.Integrate.peakmem_integrate", "param_names": [ "resolution" @@ -267,10 +267,10 @@ ], "type": "peakmemory", "unit": "bytes", - "version": "c0f563e9fa258207351e560866f616dcbd6c00d73cba40377a8cdfcde2ecfd24" + "version": "9627f636ac2c145feb90416484eb94c9b0fe421250ff0f8f4f89e526da8d2c9a" }, "mpas_ocean.Integrate.time_integrate": { - "code": "class Integrate:\n def time_integrate(self, resolution):\n self.uxds[data_var].integrate()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class Integrate:\n def time_integrate(self, resolution):\n self.uxds[data_var].integrate()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.Integrate.time_integrate", "number": 0, @@ -288,11 +288,11 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "602926f39f66a5fee325785baf58dba3ae5cad8c95697670b119457ddcdb2461", + "version": "180accc984e741ea109341e013c286885335fc9eb4fc4bbe072ef49006c717f9", "warmup_time": -1 }, "mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection": { - "code": "class MatplotlibConversion:\n def time_dataarray_to_polycollection(self, resolution, periodic_elements):\n self.uxds[data_var].to_polycollection()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n \n \n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", + "code": "class MatplotlibConversion:\n def time_dataarray_to_polycollection(self, resolution, periodic_elements):\n self.uxds[data_var].to_polycollection()\n\nclass DatasetBenchmark:\n def setup(self, resolution, *args, **kwargs):\n self.uxds = ux.open_dataset(file_path_dict[resolution][0], file_path_dict[resolution][1])", "min_run_count": 2, "name": "mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection", "number": 0, @@ -316,7 +316,7 @@ "sample_time": 0.01, "type": "time", "unit": "seconds", - "version": "f8d69840e549a19644389544b092a40b8b32f29d28a21fc1c35c2fe6578a5977", + "version": "743db07382b77e8f1686d62df074bdbc72cb59afc76016db59c510653208b8a1", "warmup_time": -1 }, "mpas_ocean.RemapDownsample.time_inverse_distance_weighted_remapping": {