adds the select_random_timeseries function

src/tape/ensemble.py

@@ -1847,6 +1847,36 @@ def _sync_tables(self):
         self.object.set_dirty(False)
         return self
 
+    def select_random_timeseries(self, seed=None):
+        """Selects a random lightcurve from the Ensemble
+
+        Parameters
+        ----------
+        seed: int, or None
+            Sets a seed to return the same object id on successive runs. `None`
+            by default, in which case a seed is not set for the operation.
+
+        Returns
+        -------
+        ts: `TimeSeries`
+            Timeseries for a single object
+
+        """
+
+        if seed is not None:
+            np.random.seed(seed)
+
+        # Avoid a choice from full index space, select a random partition to grab from
+        if self.object.npartitions > 1:
+            partition_num = np.random.randint(0, self.object.npartitions - 1)
+            partition_ids = self.object.get_partition(partition_num).index.values
+            lcid = np.random.choice(partition_ids)
+        else:
+            partition_num = 0
+            lcid = np.random.choice(self.object.index.values)
+        print(f"Selected Object {lcid} from Partition {partition_num}")
+        return self.to_timeseries(lcid)
+
     def to_timeseries(
         self,
         target,

tests/tape_tests/test_ensemble.py

@@ -17,6 +17,7 @@
     TapeSeries,
     TapeObjectFrame,
     TapeSourceFrame,
+    TimeSeries,
 )
 from tape.analysis.stetsonj import calc_stetson_J
 from tape.analysis.structure_function.base_argument_container import StructureFunctionArgumentContainer
@@ -1829,6 +1830,26 @@ def test_batch_with_custom_frame_meta(parquet_ensemble, custom_meta):
     assert isinstance(parquet_ensemble.select_frame("sf2_result"), EnsembleFrame)
 
 
+@pytest.mark.parametrize("repartition", [False, True])
+@pytest.mark.parametrize("seed", [None, 42])
+def test_select_random_timeseries(parquet_ensemble, repartition, seed):
+    """Test the behavior of ensemble.select_random_timeseries"""
+
+    ens = parquet_ensemble
+
+    if repartition:
+        ens.object = ens.object.repartition(3)
+
+    ts = ens.select_random_timeseries(seed=seed)
+
+    assert isinstance(ts, TimeSeries)
+
+    if seed == 42 and not repartition:
+        assert ts.meta["id"] == 88480000587403327
+    elif seed == 42 and repartition:
+        assert ts.meta["id"] == 88480000310609896
+
+
 def test_to_timeseries(parquet_ensemble):
     """
     Test that ensemble.to_timeseries() runs and assigns the correct metadata