Removed the subdir.

pyrate/scripts/benchmark_graph_neighbor_search.py

@@ -0,0 +1,100 @@
+#!/usr/bin/env python3
+
+"""Benchmark the neighbor search in graphs.
+
+Initially written as part of
+`Issue #90 <https://gitlab.sailingteam.hg.tu-darmstadt.de/informatik/pyrate/-/issues/90>`__ to determine
+whether a faster implementation is needed.
+That issue also contains a draft which *might* make it faster if that is required in the future.
+
+Examples:
+    These are the benchmark results when run on a `Lenovo ThinkPad T560 laptop <https://thinkwiki.de/T560>`__
+    with an `Intel(R) Core(TM) i5-6300U CPU @ 2.40GHz
+    <https://ark.intel.com/content/www/de/de/ark/products/88190/intel-core-i5-6300u-processor-3m-cache-up-to-3-00-ghz.html>`__
+    and 16GB RAM (at commit ``9a8177326dc0d82d0aea4559e6c85071ceebf56f``):
+
+    .. code-block:: bash
+
+       ./scripts/benchmark_graph_neighbor_search.py --iterations 100
+        frequency = 2 for distance 5000 km
+        generated graph in 0.018192768096923828 seconds
+        number of nodes = 42, number of edges = 120
+        non-empty entries in neighbor table = 240
+        computation time = 0.0003081770000221695 (avg. over 100 samples)
+
+        frequency = 8 for distance 1000 km
+        generated graph in 0.0327601432800293 seconds
+        number of nodes = 642, number of edges = 1920
+        non-empty entries in neighbor table = 3840
+        computation time = 0.0033796210000218707 (avg. over 100 samples)
+
+        frequency = 71 for distance 100 km
+        generated graph in 1.8711962699890137 seconds
+        number of nodes = 50412, number of edges = 151230
+        non-empty entries in neighbor table = 302460
+        computation time = 0.30925760600001695 (avg. over 100 samples)
+
+        frequency = 142 for distance 50 km
+        generated graph in 7.630561828613281 seconds
+        number of nodes = 201642, number of edges = 604920
+        non-empty entries in neighbor table = 1209840
+        computation time = 1.1302456550000102 (avg. over 100 samples)
+
+        frequency = 706 for distance 10 km
+        generated graph in 260.7689461708069 seconds
+        number of nodes = 4984362, number of edges = 14953080
+        non-empty entries in neighbor table = 29906160
+        computation time = 27.382845137000004 (avg. over 100 samples)
+
+
+"""
+
+# Standard library
+from argparse import ArgumentDefaultsHelpFormatter
+from argparse import ArgumentParser
+from time import time
+from timeit import timeit
+
+# Scientific
+import numpy
+
+# Graph
+from pyrate.plan.graph.generate import create_earth_graph
+from pyrate.plan.graph.generate import min_required_frequency
+from pyrate.plan.graph import NavigationGraph
+
+
+def _main() -> None:
+    """The main function."""
+    parser = ArgumentParser(
+        description="Benchmark the neighbor search in graphs.", formatter_class=ArgumentDefaultsHelpFormatter
+    )
+    parser.add_argument(
+        "--iterations", type=int, default=100, help="the number of timing samples to collect per graph size"
+    )
+    args = parser.parse_args()
+
+    for distance_km in [5000, 1000, 100, 50, 10]:
+        frequency = min_required_frequency(distance_km * 1000, in_meters=True)
+        print(f"frequency = {frequency} for distance {distance_km} km")
+
+        time_before_generation = time()
+        graph = create_earth_graph(frequency, print_status=False)
+        print(f"generated graph in {time() - time_before_generation} seconds")
+        print(f"number of nodes = {len(graph)}, number of edges = {graph.num_edges}")
+
+        def setup(local_graph: NavigationGraph = graph) -> None:
+            local_graph._neighbors = None  # pylint: disable=protected-access
+
+        def statement(local_graph: NavigationGraph = graph) -> None:
+            _ = local_graph.neighbors
+
+        avg_time = timeit(setup=setup, stmt=statement, number=args.iterations)
+        print(f"non-empty entries in neighbor table = {numpy.count_nonzero(graph.neighbors != -1)}")
+        print(f"computation time = {avg_time} (avg. over {args.iterations} samples)")
+
+        print()  # empty line between distances
+
+
+if __name__ == "__main__":
+    _main()