Collect iteration runtimes (#60)

* Collect iteration runtimes

* Bump version

alns/ALNS.py

@@ -1,3 +1,4 @@
+import time
 from typing import Callable, Dict, List, Optional, Tuple
 
 import numpy.random as rnd
@@ -164,6 +165,7 @@ class of vehicle routing problems with backhauls. *European Journal of
 
         stats = Statistics()
         stats.collect_objective(initial_solution.objective())
+        stats.collect_runtime(time.perf_counter())
 
         for iteration in range(iterations):
             d_idx, r_idx = weight_scheme.select_operators(self._rnd_state)
@@ -181,6 +183,7 @@ class of vehicle routing problems with backhauls. *European Journal of
             stats.collect_objective(curr.objective())
             stats.collect_destroy_operator(d_name, s_idx)
             stats.collect_repair_operator(r_name, s_idx)
+            stats.collect_runtime(time.perf_counter())
 
         return Result(best, stats)
 

alns/Statistics.py

@@ -12,6 +12,7 @@ def __init__(self):
         optionally populated by the ALNS algorithm.
         """
         self._objectives = []
+        self._runtimes = []
 
         self._destroy_operator_counts = defaultdict(lambda: [0, 0, 0, 0])
         self._repair_operator_counts = defaultdict(lambda: [0, 0, 0, 0])
@@ -23,6 +24,13 @@ def objectives(self) -> np.ndarray:
         """
         return np.array(self._objectives)
 
+    @property
+    def runtimes(self) -> np.ndarray:
+        """
+        Returns an array of iteration run times (in seconds).
+        """
+        return np.diff(self._runtimes, prepend=self._runtimes[0])
+
     @property
     def destroy_operator_counts(self) -> DefaultDict[str, List[float]]:
         """
@@ -62,6 +70,17 @@ def collect_objective(self, objective: float):
         """
         self._objectives.append(objective)
 
+    def collect_runtime(self, time: float):
+        """
+        Collects the time one iteration took.
+
+        Parameters
+        ----------
+        time
+            Time in seconds.
+        """
+        self._runtimes.append(time)
+
     def collect_destroy_operator(self, operator_name: str, s_idx: int):
         """
         Collects a score (index) for a used destroy operator. This maintains

alns/tests/test_statistics.py

@@ -1,4 +1,4 @@
-from numpy.testing import assert_equal, assert_almost_equal
+from numpy.testing import assert_equal, assert_almost_equal, assert_allclose
 
 from alns.Statistics import Statistics
 
@@ -27,6 +27,20 @@ def test_collect_objectives():
         assert_almost_equal(statistics.objectives[-1], objective)
 
 
+def test_collect_runtimes():
+    """
+    Tests if a Statistics object properly collects runtime values.
+    """
+    statistics = Statistics()
+
+    for time in range(1, 100):
+        statistics.collect_runtime(time)
+
+    assert_equal(len(statistics.runtimes), time)
+    assert_almost_equal(statistics.runtimes[0], 0)
+    assert_allclose(statistics.runtimes[1:], 1)
+
+
 def test_collect_destroy_counts_example():
     """
     Tests if collecting for a destroy operator works as expected in a simple

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "alns"
-version = "2.0.2"
+version = "2.1.0"
 description = "A flexible implementation of the adaptive large neighbourhood search (ALNS) algorithm."
 authors = ["Niels Wouda <[email protected]>"]
 license = "MIT"