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.cache | ||
compile_commands.json | ||
.asv |
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{ | ||
// The version of the config file format. Do not change, unless | ||
// you know what you are doing. | ||
"version": 1, | ||
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// The name of the project being benchmarked | ||
"project": "reticula", | ||
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// The project's homepage | ||
"project_url": "https://reticula.network/", | ||
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// The URL or local path of the source code repository for the | ||
// project being benchmarked | ||
"repo": ".", | ||
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// The Python project's subdirectory in your repo. If missing or | ||
// the empty string, the project is assumed to be located at the root | ||
// of the repository. | ||
// "repo_subdir": "", | ||
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// Customizable commands for building the project. | ||
// See asv.conf.json documentation. | ||
// To build the package using pyproject.toml (PEP518), uncomment the following lines | ||
"build_command": [ | ||
"python -m pip wheel -v -w {build_cache_dir} {build_dir}" | ||
], | ||
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// Customizable commands for installing and uninstalling the project. | ||
// See asv.conf.json documentation. | ||
// "install_command": ["in-dir={env_dir} python -mpip install {wheel_file}"], | ||
// "uninstall_command": ["return-code=any python -mpip uninstall -y {project}"], | ||
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"branches": ["main"], // for git | ||
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// The DVCS being used. If not set, it will be automatically | ||
// determined from "repo" by looking at the protocol in the URL | ||
// (if remote), or by looking for special directories, such as | ||
// ".git" (if local). | ||
// "dvcs": "git", | ||
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// The tool to use to create environments. May be "conda", | ||
// "virtualenv", "mamba" (above 3.8) | ||
// or other value depending on the plugins in use. | ||
// If missing or the empty string, the tool will be automatically | ||
// determined by looking for tools on the PATH environment | ||
// variable. | ||
"environment_type": "virtualenv", | ||
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// timeout in seconds for installing any dependencies in environment | ||
// defaults to 10 min | ||
//"install_timeout": 600, | ||
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// the base URL to show a commit for the project. | ||
"show_commit_url": "http://github.com/reticula-network/reticula-python/commit/", | ||
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// The Pythons you'd like to test against. If not provided, defaults | ||
// to the current version of Python used to run `asv`. | ||
// "pythons": ["3.8", "3.12"], | ||
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// The list of conda channel names to be searched for benchmark | ||
// dependency packages in the specified order | ||
// "conda_channels": ["conda-forge", "defaults"], | ||
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// A conda environment file that is used for environment creation. | ||
// "conda_environment_file": "environment.yml", | ||
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// The matrix of dependencies to test. Each key of the "req" | ||
// requirements dictionary is the name of a package (in PyPI) and | ||
// the values are version numbers. An empty list or empty string | ||
// indicates to just test against the default (latest) | ||
// version. null indicates that the package is to not be | ||
// installed. If the package to be tested is only available from | ||
// PyPi, and the 'environment_type' is conda, then you can preface | ||
// the package name by 'pip+', and the package will be installed | ||
// via pip (with all the conda available packages installed first, | ||
// followed by the pip installed packages). | ||
// | ||
// The ``@env`` and ``@env_nobuild`` keys contain the matrix of | ||
// environment variables to pass to build and benchmark commands. | ||
// An environment will be created for every combination of the | ||
// cartesian product of the "@env" variables in this matrix. | ||
// Variables in "@env_nobuild" will be passed to every environment | ||
// during the benchmark phase, but will not trigger creation of | ||
// new environments. A value of ``null`` means that the variable | ||
// will not be set for the current combination. | ||
// | ||
// "matrix": { | ||
// "req": { | ||
// "numpy": ["1.6", "1.7"], | ||
// "six": ["", null], // test with and without six installed | ||
// "pip+emcee": [""] // emcee is only available for install with pip. | ||
// }, | ||
// "env": {"ENV_VAR_1": ["val1", "val2"]}, | ||
// "env_nobuild": {"ENV_VAR_2": ["val3", null]}, | ||
// }, | ||
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// Combinations of libraries/python versions can be excluded/included | ||
// from the set to test. Each entry is a dictionary containing additional | ||
// key-value pairs to include/exclude. | ||
// | ||
// An exclude entry excludes entries where all values match. The | ||
// values are regexps that should match the whole string. | ||
// | ||
// An include entry adds an environment. Only the packages listed | ||
// are installed. The 'python' key is required. The exclude rules | ||
// do not apply to includes. | ||
// | ||
// In addition to package names, the following keys are available: | ||
// | ||
// - python | ||
// Python version, as in the *pythons* variable above. | ||
// - environment_type | ||
// Environment type, as above. | ||
// - sys_platform | ||
// Platform, as in sys.platform. Possible values for the common | ||
// cases: 'linux2', 'win32', 'cygwin', 'darwin'. | ||
// - req | ||
// Required packages | ||
// - env | ||
// Environment variables | ||
// - env_nobuild | ||
// Non-build environment variables | ||
// | ||
// "exclude": [ | ||
// {"python": "3.2", "sys_platform": "win32"}, // skip py3.2 on windows | ||
// {"environment_type": "conda", "req": {"six": null}}, // don't run without six on conda | ||
// {"env": {"ENV_VAR_1": "val2"}}, // skip val2 for ENV_VAR_1 | ||
// ], | ||
// | ||
// "include": [ | ||
// // additional env for python3.12 | ||
// {"python": "3.12", "req": {"numpy": "1.26"}, "env_nobuild": {"FOO": "123"}}, | ||
// // additional env if run on windows+conda | ||
// {"platform": "win32", "environment_type": "conda", "python": "3.12", "req": {"libpython": ""}}, | ||
// ], | ||
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// The directory (relative to the current directory) that benchmarks are | ||
// stored in. If not provided, defaults to "benchmarks" | ||
// "benchmark_dir": "benchmarks", | ||
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// The directory (relative to the current directory) to cache the Python | ||
// environments in. If not provided, defaults to "env" | ||
"env_dir": ".asv/env", | ||
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// The directory (relative to the current directory) that raw benchmark | ||
// results are stored in. If not provided, defaults to "results". | ||
"results_dir": ".asv/results", | ||
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// The directory (relative to the current directory) that the html tree | ||
// should be written to. If not provided, defaults to "html". | ||
"html_dir": ".asv/html", | ||
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// The number of characters to retain in the commit hashes. | ||
// "hash_length": 8, | ||
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// `asv` will cache results of the recent builds in each | ||
// environment, making them faster to install next time. This is | ||
// the number of builds to keep, per environment. | ||
// "build_cache_size": 2, | ||
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// The commits after which the regression search in `asv publish` | ||
// should start looking for regressions. Dictionary whose keys are | ||
// regexps matching to benchmark names, and values corresponding to | ||
// the commit (exclusive) after which to start looking for | ||
// regressions. The default is to start from the first commit | ||
// with results. If the commit is `null`, regression detection is | ||
// skipped for the matching benchmark. | ||
// | ||
// "regressions_first_commits": { | ||
// "some_benchmark": "352cdf", // Consider regressions only after this commit | ||
// "another_benchmark": null, // Skip regression detection altogether | ||
// }, | ||
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// The thresholds for relative change in results, after which `asv | ||
// publish` starts reporting regressions. Dictionary of the same | ||
// form as in ``regressions_first_commits``, with values | ||
// indicating the thresholds. If multiple entries match, the | ||
// maximum is taken. If no entry matches, the default is 5%. | ||
// | ||
// "regressions_thresholds": { | ||
// "some_benchmark": 0.01, // Threshold of 1% | ||
// "another_benchmark": 0.5, // Threshold of 50% | ||
// }, | ||
} |
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class ModuleImport: | ||
""" | ||
Benchmark total import time. | ||
""" | ||
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def timeraw_import_reticula(self): | ||
return """ | ||
import reticula | ||
""" |
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import reticula as ret | ||
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import random | ||
import json | ||
import pathlib | ||
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class Construction: | ||
""" | ||
Benchmarking the construction and basic operation of static graphs. | ||
""" | ||
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def setup(self): | ||
self.n = 2**16 | ||
k = 32 | ||
self.g = ret.regular_ring_lattice[ret.int64](size=self.n, degree=k) | ||
self.verts = list(self.g.vertices()) | ||
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self.edges = list(self.g.edges()) | ||
self.tuples = [] | ||
for e in self.edges: | ||
verts = e.incident_verts() | ||
self.tuples.append((verts[0], verts[-1])) | ||
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rand = random.Random(42) | ||
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self.shuffled_edges = rand.sample(self.edges, k=len(self.edges)) | ||
self.shuffled_tuples = [] | ||
for e in self.shuffled_edges: | ||
verts = e.incident_verts() | ||
if rand.random() > 0.5: | ||
self.shuffled_tuples.append((verts[0], verts[-1])) | ||
else: | ||
self.shuffled_tuples.append((verts[-1], verts[0])) | ||
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def time_copy_construction(self): | ||
ret.undirected_network[ret.int64](self.g) | ||
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def time_tuple_construction(self): | ||
ret.undirected_network[ret.int64]( | ||
verts=self.verts, edges=self.tuples) | ||
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def time_shuffled_tuple_construction(self): | ||
ret.undirected_network[ret.int64]( | ||
verts=self.verts, edges=self.shuffled_tuples) | ||
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def time_edge_obj_construction(self): | ||
ret.undirected_network[ret.int64]( | ||
verts=self.verts, edges=self.edges) | ||
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def time_shuffled_edge_obj_construction(self): | ||
ret.undirected_network[ret.int64]( | ||
verts=self.verts, edges=self.shuffled_edges) | ||
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class Graphicallity: | ||
def setup(self): | ||
base_path = pathlib.Path(__file__).parent | ||
with open(base_path / "ba_sequence.json") as f: | ||
self.ba_sequence = json.load(f) | ||
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def time_is_graphic(self): | ||
ret.is_graphic(self.ba_sequence) | ||
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class Algorithms: | ||
def setup(self): | ||
self.n = 2**16 | ||
k = 32 | ||
self.g = ret.regular_ring_lattice[ret.int64](size=self.n, degree=k) | ||
self.g_isolated = ret.undirected_network[ret.int64]( | ||
edges=[], verts=range(self.n)) | ||
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def time_degree(self): | ||
ret.degree(self.g, 12) | ||
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def time_degree_sequence(self): | ||
ret.degree_sequence(self.g) | ||
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def time_density(self): | ||
ret.density(self.g) | ||
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def time_assortativity(self): | ||
ret.degree_assortativity(self.g) | ||
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def time_attribute_assortativity_lambda(self): | ||
ret.attribute_assortativity(self.g, lambda x: x) | ||
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def time_connected_component(self): | ||
ret.connected_component(self.g, 12) | ||
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def time_connected_component_isolated(self): | ||
ret.connected_component(self.g_isolated, 12) | ||
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def time_connected_components(self): | ||
ret.connected_components(self.g) | ||
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def time_connected_components_isolated(self): | ||
ret.connected_components(self.g_isolated) | ||
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def time_is_connected(self): | ||
ret.is_connected(self.g) | ||
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def time_is_connected_isolated(self): | ||
ret.is_connected(self.g_isolated) | ||
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def time_largest_connected_component(self): | ||
ret.largest_connected_component(self.g) | ||
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def time_largest_connected_component_isolated(self): | ||
ret.largest_connected_component(self.g_isolated) | ||
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def time_is_reachable(self): | ||
ret.is_reachable(self.g, 0, self.n//2) | ||
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def time_is_reachable_isolated(self): | ||
ret.is_reachable(self.g_isolated, 0, self.n//2) | ||
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def time_shortest_path_lengths_from(self): | ||
ret.shortest_path_lengths_from(self.g, 0) | ||
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def time_shortest_path_lengths_to(self): | ||
ret.shortest_path_lengths_to(self.g, 0) |
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