change to strings

src/spikeinterface/core/basesorting.py

@@ -135,7 +135,7 @@ def get_total_duration(self) -> float:
 
     def get_unit_spike_train(
         self,
-        unit_id,
+        unit_id: str | int,
         segment_index: Union[int, None] = None,
         start_frame: Union[int, None] = None,
         end_frame: Union[int, None] = None,

src/spikeinterface/core/generate.py

@@ -2,7 +2,7 @@
 import math
 import warnings
 import numpy as np
-from typing import Literal
+from typing import Literal, Optional
 from math import ceil
 
 from .basesorting import SpikeVectorSortingSegment
@@ -1138,6 +1138,7 @@ def __init__(
                 firing_rates=firing_rates,
                 refractory_period_seconds=self.refractory_period_seconds,
                 seed=segment_seed,
+                unit_ids=unit_ids,
                 t_start=None,
             )
             self.add_sorting_segment(segment)
@@ -1161,6 +1162,7 @@ def __init__(
         firing_rates: float | np.ndarray,
         refractory_period_seconds: float | np.ndarray,
         seed: int,
+        unit_ids: list[str],
         t_start: Optional[float] = None,
     ):
         self.num_units = num_units
@@ -1177,7 +1179,8 @@ def __init__(
             self.refractory_period_seconds = np.full(num_units, self.refractory_period_seconds, dtype="float64")
 
         self.segment_seed = seed
-        self.units_seed = {unit_id: self.segment_seed + hash(unit_id) for unit_id in range(num_units)}
+        self.units_seed = {unit_id: abs(self.segment_seed + hash(unit_id)) for unit_id in unit_ids}
+
         self.num_samples = math.ceil(sampling_frequency * duration)
         super().__init__(t_start)
 

src/spikeinterface/core/tests/test_basesnippets.py

@@ -41,8 +41,8 @@ def test_BaseSnippets(create_cache_folder):
     assert snippets.get_num_segments() == len(duration)
     assert snippets.get_num_channels() == num_channels
 
-    assert np.all(snippets.ids_to_indices([0, 1, 2]) == [0, 1, 2])
-    assert np.all(snippets.ids_to_indices([0, 1, 2], prefer_slice=True) == slice(0, 3, None))
+    assert np.all(snippets.ids_to_indices(["0", "1", "2"]) == [0, 1, 2])
+    assert np.all(snippets.ids_to_indices(["0", "1", "2"], prefer_slice=True) == slice(0, 3, None))
 
     # annotations / properties
     snippets.annotate(gre="ta")
@@ -60,7 +60,7 @@ def test_BaseSnippets(create_cache_folder):
     )
 
     # missing property
-    snippets.set_property("string_property", ["ciao", "bello"], ids=[0, 1])
+    snippets.set_property("string_property", ["ciao", "bello"], ids=["0", "1"])
     values = snippets.get_property("string_property")
     assert values[2] == ""
 
@@ -70,14 +70,14 @@ def test_BaseSnippets(create_cache_folder):
         snippets.set_property,
         key="string_property_nan",
         values=["hola", "chabon"],
-        ids=[0, 1],
+        ids=["0", "1"],
         missing_value=np.nan,
     )
 
     # int properties without missing values raise an error
     assert_raises(Exception, snippets.set_property, key="int_property", values=[5, 6], ids=[1, 2])
 
-    snippets.set_property("int_property", [5, 6], ids=[1, 2], missing_value=200)
+    snippets.set_property("int_property", [5, 6], ids=["1", "2"], missing_value=200)
     values = snippets.get_property("int_property")
     assert values.dtype.kind == "i"
 

src/spikeinterface/core/tests/test_channelsaggregationrecording.py

@@ -38,10 +38,12 @@ def test_channelsaggregationrecording():
 
         assert np.allclose(traces1_1, recording_agg.get_traces(channel_ids=[str(channel_ids[1])], segment_index=seg))
         assert np.allclose(
-            traces2_0, recording_agg.get_traces(channel_ids=[str(num_channels + channel_ids[0])], segment_index=seg)
+            traces2_0,
+            recording_agg.get_traces(channel_ids=[str(num_channels + int(channel_ids[0]))], segment_index=seg),
         )
         assert np.allclose(
-            traces3_2, recording_agg.get_traces(channel_ids=[str(2 * num_channels + channel_ids[2])], segment_index=seg)
+            traces3_2,
+            recording_agg.get_traces(channel_ids=[str(2 * num_channels + int(channel_ids[2]))], segment_index=seg),
         )
         # all traces
         traces1 = recording1.get_traces(segment_index=seg)

src/spikeinterface/core/tests/test_sortinganalyzer.py

@@ -76,8 +76,8 @@ def test_SortingAnalyzer_binary_folder(tmp_path, dataset):
 
     # test select_units see https://github.com/SpikeInterface/spikeinterface/issues/3041
     # this bug requires that we have an info.json file so we calculate templates above
-    select_units_sorting_analyer = sorting_analyzer.select_units(unit_ids=[1])
-    assert len(select_units_sorting_analyer.unit_ids) == 1
+    select_units_sorting_analyer = sorting_analyzer.select_units(unit_ids=["1"])
+    assert len(select_units_sorting_analyer.unit_ids) == "1"
 
     folder = tmp_path / "test_SortingAnalyzer_binary_folder"
     if folder.exists():
@@ -121,11 +121,11 @@ def test_SortingAnalyzer_zarr(tmp_path, dataset):
 
     # test select_units see https://github.com/SpikeInterface/spikeinterface/issues/3041
     # this bug requires that we have an info.json file so we calculate templates above
-    select_units_sorting_analyer = sorting_analyzer.select_units(unit_ids=[1])
-    assert len(select_units_sorting_analyer.unit_ids) == 1
-    remove_units_sorting_analyer = sorting_analyzer.remove_units(remove_unit_ids=[1])
+    select_units_sorting_analyer = sorting_analyzer.select_units(unit_ids=["1"])
+    assert len(select_units_sorting_analyer.unit_ids) == "1"
+    remove_units_sorting_analyer = sorting_analyzer.remove_units(remove_unit_ids=["1"])
     assert len(remove_units_sorting_analyer.unit_ids) == len(sorting_analyzer.unit_ids) - 1
-    assert 1 not in remove_units_sorting_analyer.unit_ids
+    assert "1" not in remove_units_sorting_analyer.unit_ids
 
     # test no compression
     sorting_analyzer_no_compression = create_sorting_analyzer(
@@ -358,7 +358,7 @@ def _check_sorting_analyzers(sorting_analyzer, original_sorting, cache_folder):
                 shutil.rmtree(folder)
         else:
             folder = None
-        sorting_analyzer4 = sorting_analyzer.merge_units(merge_unit_groups=[[0, 1]], format=format, folder=folder)
+        sorting_analyzer4 = sorting_analyzer.merge_units(merge_unit_groups=[["0", "1"]], format=format, folder=folder)
 
         if format != "memory":
             if format == "zarr":

src/spikeinterface/core/tests/test_unitsselectionsorting.py

@@ -10,39 +10,43 @@
 def test_basic_functions():
     sorting = generate_sorting(num_units=3, durations=[0.100, 0.100], sampling_frequency=30000.0)
 
-    sorting2 = UnitsSelectionSorting(sorting, unit_ids=[0, 2])
-    assert np.array_equal(sorting2.unit_ids, [0, 2])
+    sorting2 = UnitsSelectionSorting(sorting, unit_ids=["0", "2"])
+    assert np.array_equal(sorting2.unit_ids, ["0", "2"])
     assert sorting2.get_parent() == sorting
 
-    sorting3 = UnitsSelectionSorting(sorting, unit_ids=[0, 2], renamed_unit_ids=["a", "b"])
+    sorting3 = UnitsSelectionSorting(sorting, unit_ids=["0", "2"], renamed_unit_ids=["a", "b"])
     assert np.array_equal(sorting3.unit_ids, ["a", "b"])
 
     assert np.array_equal(
-        sorting.get_unit_spike_train(0, segment_index=0), sorting2.get_unit_spike_train(0, segment_index=0)
+        sorting.get_unit_spike_train(unit_id="0", segment_index=0),
+        sorting2.get_unit_spike_train(unit_id="0", segment_index=0),
     )
     assert np.array_equal(
-        sorting.get_unit_spike_train(0, segment_index=0), sorting3.get_unit_spike_train("a", segment_index=0)
+        sorting.get_unit_spike_train(unit_id="0", segment_index=0),
+        sorting3.get_unit_spike_train(unit_id="a", segment_index=0),
     )
 
     assert np.array_equal(
-        sorting.get_unit_spike_train(2, segment_index=0), sorting2.get_unit_spike_train(2, segment_index=0)
+        sorting.get_unit_spike_train(unit_id="2", segment_index=0),
+        sorting2.get_unit_spike_train(unit_id="2", segment_index=0),
     )
     assert np.array_equal(
-        sorting.get_unit_spike_train(2, segment_index=0), sorting3.get_unit_spike_train("b", segment_index=0)
+        sorting.get_unit_spike_train(unit_id="2", segment_index=0),
+        sorting3.get_unit_spike_train(unit_id="b", segment_index=0),
     )
 
 
 def test_failure_with_non_unique_unit_ids():
     seed = 10
     sorting = generate_sorting(num_units=3, durations=[0.100], sampling_frequency=30000.0, seed=seed)
     with pytest.raises(AssertionError):
-        sorting2 = UnitsSelectionSorting(sorting, unit_ids=[0, 2], renamed_unit_ids=["a", "a"])
+        sorting2 = UnitsSelectionSorting(sorting, unit_ids=["0", "2"], renamed_unit_ids=["a", "a"])
 
 
 def test_custom_cache_spike_vector():
     sorting = generate_sorting(num_units=3, durations=[0.100, 0.100], sampling_frequency=30000.0)
 
-    sub_sorting = UnitsSelectionSorting(sorting, unit_ids=[2, 0], renamed_unit_ids=["b", "a"])
+    sub_sorting = UnitsSelectionSorting(sorting, unit_ids=["2", "0"], renamed_unit_ids=["b", "a"])
     cached_spike_vector = sub_sorting.to_spike_vector(use_cache=True)
     computed_spike_vector = sub_sorting.to_spike_vector(use_cache=False)
     assert np.all(cached_spike_vector == computed_spike_vector)