Merge pull request #392 from dirac-institute/add_benchmarks

Add benchmarks

benchmarks/bench_filter_cluster.py

@@ -0,0 +1,123 @@
+import timeit
+import numpy as np
+
+from kbmod.filters.clustering_filters import *
+from kbmod.result_list import ResultList, ResultRow
+from kbmod.search import *
+
+
+def _make_data(objs, times):
+    """Create a ResultList for the given objects.
+
+    Parameters
+    ----------
+    obj : list of lists
+        A list where each element specifies a Trajectory
+        as [x, y, xv, yv].
+
+    Returns
+    -------
+    ResultList
+    """
+    num_times = len(times)
+    rs = ResultList(times, track_filtered=True)
+    for x in objs:
+        t = Trajectory()
+        t.x = x[0]
+        t.y = x[1]
+        t.vx = x[2]
+        t.vy = x[3]
+        t.lh = 100.0
+
+        row = ResultRow(t, num_times)
+        rs.append_result(row)
+    return rs
+
+
+def run_index_benchmark(filter, rs):
+    tmr = timeit.Timer(stmt="filter.keep_indices(rs)", globals=locals())
+    res_time = np.mean(tmr.repeat(repeat=10, number=20))
+    return res_time
+
+
+def run_all_benchmarks():
+    times = [(10.0 + 0.1 * float(i)) for i in range(20)]
+    rs1 = _make_data(
+        [
+            [10, 11, 1, 2],
+            [10, 11, 1000, -1000],
+            [10, 11, 0.0, 0.0],
+            [25, 24, 1.0, 1.0],
+            [25, 26, 10.0, 10.0],
+            [10, 12, 5, 5],
+        ],
+        times,
+    )
+
+    print("Method                    |    Time")
+    print("-" * 40)
+
+    f1 = DBSCANFilter("position", 0.025, 100, 100, [0, 50], [0, 1.5], times)
+
+    res_time = run_index_benchmark(f1, rs1)
+    print(f"position - 2 clusters     | {res_time:10.7f}")
+
+    f2 = DBSCANFilter("position", 0.025, 100, 100, [0, 50], [0, 1.5], times)
+
+    res_time = run_index_benchmark(f2, rs1)
+    print(f"position - 4 clusters     | {res_time:10.7f}")
+
+    f3 = DBSCANFilter("position", 0.025, 1000, 1000, [0, 50], [0, 1.5], times)
+
+    res_time = run_index_benchmark(f3, rs1)
+    print(f"position - 1 cluster      | {res_time:10.7f}")
+
+    rs2 = _make_data(
+        [
+            [10, 11, 1, 2],
+            [10, 11, 1000, -1000],
+            [10, 11, 1.0, 2.1],
+            [55, 54, 1.0, 1.0],
+            [55, 56, 10.0, 10.0],
+            [10, 12, 4.1, 8],
+        ],
+        times,
+    )
+
+    f4 = DBSCANFilter("all", 0.025, 100, 100, [0, 100], [0, 1.5], times)
+
+    res_time = run_index_benchmark(f4, rs2)
+    print(f"all - 5 clusters          | {res_time:10.7f}")
+
+    # Larger eps is 3 clusters.
+    f5 = DBSCANFilter("all", 0.25, 100, 100, [0, 100], [0, 1.5], times)
+
+    res_time = run_index_benchmark(f5, rs2)
+    print(f"all - 3 clusters          | {res_time:10.7f}")
+
+    # Larger scale is 3 clusters.
+    f6 = DBSCANFilter("all", 0.025, 100, 100, [0, 5000], [0, 1.5], times)
+
+    res_time = run_index_benchmark(f6, rs2)
+    print(f"all (larger) - 3 clusters | {res_time:10.7f}")
+
+    rs3 = _make_data(
+        [
+            [10, 11, 1, 2],
+            [10, 11, 2, 5],
+            [10, 11, 1.01, 1.99],
+            [21, 23, 1, 2],
+            [21, 23, -10, -10],
+            [5, 10, 6, 1],
+            [5, 10, 1, 2],
+        ],
+        times,
+    )
+
+    f7 = DBSCANFilter("mid_position", 0.1, 20, 20, [0, 100], [0, 1.5], times)
+    res_time = run_index_benchmark(f7, rs3)
+    print(f"mid_position              | {res_time:10.7f}")
+
+
+if __name__ == "__main__":
+    run_all_benchmarks()

benchmarks/bench_filter_stats.py

@@ -0,0 +1,33 @@
+import timeit
+import numpy as np
+
+from kbmod.filters.stats_filters import *
+from kbmod.result_list import ResultRow
+from kbmod.search import Trajectory
+
+
+def run_row_benchmark(create_filter=""):
+    row = ResultRow(Trajectory(), 1000)
+
+    filt = eval(create_filter)
+
+    # Do the timing runs.
+    full_cmd = "filt.keep_row(row)"
+    tmr = timeit.Timer(stmt="filt.keep_row(row)", globals=locals())
+    res_time = np.mean(tmr.repeat(repeat=10, number=20))
+    return res_time
+
+
+def run_all_benchmarks():
+    print("Method       |    Time")
+    print("-" * 40)
+
+    res_time = run_row_benchmark(f"LHFilter(1, 19)")
+    print(f"LHFilter     | {res_time:10.7f}")
+
+    res_time = run_row_benchmark(f"NumObsFilter(1)")
+    print(f"NumObsFilter | {res_time:10.7f}")
+
+
+if __name__ == "__main__":
+    run_all_benchmarks()