Merge pull request #2712 from zm711/n_jobs_sorter

Remove separate default job_kwarg `n_jobs` for sorters

src/spikeinterface/core/globals.py

@@ -42,9 +42,9 @@ def set_global_tmp_folder(folder):
     temp_folder_set = True
 
 
-def is_set_global_tmp_folder():
+def is_set_global_tmp_folder() -> bool:
     """
-    Check is the global path temporary folder have been manually set.
+    Check if the global path temporary folder have been manually set.
     """
     global temp_folder_set
     return temp_folder_set
@@ -88,9 +88,9 @@ def set_global_dataset_folder(folder):
     dataset_folder_set = True
 
 
-def is_set_global_dataset_folder():
+def is_set_global_dataset_folder() -> bool:
     """
-    Check is the global path dataset folder have been manually set.
+    Check if the global path dataset folder has been manually set.
     """
     global dataset_folder_set
     return dataset_folder_set
@@ -138,7 +138,10 @@ def reset_global_job_kwargs():
     global_job_kwargs = dict(n_jobs=1, chunk_duration="1s", progress_bar=True)
 
 
-def is_set_global_job_kwargs_set():
+def is_set_global_job_kwargs_set() -> bool:
+    """
+    Check if the global job kwargs have been manually set.
+    """
     global global_job_kwargs_set
     return global_job_kwargs_set
 

src/spikeinterface/core/job_tools.py

@@ -28,8 +28,9 @@
                     Total memory usage (e.g. "500M", "2G")
                 - chunk_duration : str or float or None
                     Chunk duration in s if float or with units if str (e.g. "1s", "500ms")
-            * n_jobs: int
-                Number of jobs to use. With -1 the number of jobs is the same as number of cores
+            * n_jobs: int | float
+                Number of jobs to use. With -1 the number of jobs is the same as number of cores.
+                Using a float between 0 and 1 will use that fraction of the total cores.
             * progress_bar: bool
                 If True, a progress bar is printed
             * mp_context: "fork" | "spawn" | None, default: None
@@ -60,7 +61,7 @@
 
 
 def fix_job_kwargs(runtime_job_kwargs):
-    from .globals import get_global_job_kwargs
+    from .globals import get_global_job_kwargs, is_set_global_job_kwargs_set
 
     job_kwargs = get_global_job_kwargs()
 
@@ -99,6 +100,15 @@ def fix_job_kwargs(runtime_job_kwargs):
 
     job_kwargs["n_jobs"] = max(n_jobs, 1)
 
+    if "n_jobs" not in runtime_job_kwargs and job_kwargs["n_jobs"] == 1 and not is_set_global_job_kwargs_set():
+        warnings.warn(
+            "`n_jobs` is not set so parallel processing is disabled! "
+            "To speed up computations, it is recommended to set n_jobs either "
+            "globally (with the `spikeinterface.set_global_job_kwargs()` function) or "
+            "locally (with the `n_jobs` argument). Use `spikeinterface.set_global_job_kwargs?` "
+            "for more information about job_kwargs."
+        )
+
     return job_kwargs
 
 

src/spikeinterface/core/tests/test_globals.py

@@ -1,4 +1,5 @@
 import pytest
+import warnings
 from pathlib import Path
 
 from spikeinterface import (
@@ -39,11 +40,22 @@ def test_global_tmp_folder():
 def test_global_job_kwargs():
     job_kwargs = dict(n_jobs=4, chunk_duration="1s", progress_bar=True, mp_context=None, max_threads_per_process=1)
     global_job_kwargs = get_global_job_kwargs()
+
+    # test warning when not setting n_jobs and calling fix_job_kwargs
+    with pytest.warns(UserWarning):
+        job_kwargs_split = fix_job_kwargs({})
+
     assert global_job_kwargs == dict(
         n_jobs=1, chunk_duration="1s", progress_bar=True, mp_context=None, max_threads_per_process=1
     )
     set_global_job_kwargs(**job_kwargs)
     assert get_global_job_kwargs() == job_kwargs
+
+    # after setting global job kwargs, fix_job_kwargs should not raise a warning
+    with warnings.catch_warnings():
+        warnings.simplefilter("error")
+        job_kwargs_split = fix_job_kwargs({})
+
     # test updating only one field
     partial_job_kwargs = dict(n_jobs=2)
     set_global_job_kwargs(**partial_job_kwargs)

src/spikeinterface/sorters/basesorter.py

@@ -17,15 +17,14 @@
 
 from spikeinterface.core import load_extractor, BaseRecordingSnippets
 from spikeinterface.core.core_tools import check_json
+from spikeinterface.core.globals import get_global_job_kwargs
 from spikeinterface.core.job_tools import fix_job_kwargs, split_job_kwargs
 from .utils import SpikeSortingError, ShellScript
 
 
-default_job_kwargs = {"n_jobs": -1}
-
 default_job_kwargs_description = {
-    "n_jobs": "Number of jobs (when saving ti binary) - default -1 (all cores)",
-    "chunk_size": "Number of samples per chunk (when saving ti binary) - default global",
+    "n_jobs": "Number of jobs (when saving to binary) - default global",
+    "chunk_size": "Number of samples per chunk (when saving to binary) - default global",
     "chunk_memory": "Memory usage for each job (e.g. '100M', '1G') (when saving to binary) - default global",
     "total_memory": "Total memory usage (e.g. '500M', '2G') (when saving to binary) - default global",
     "chunk_duration": "Chunk duration in s if float or with units if str (e.g. '1s', '500ms') (when saving to binary)"
@@ -156,7 +155,7 @@ def initialize_folder(cls, recording, output_folder, verbose, remove_existing_fo
     def default_params(cls):
         p = copy.deepcopy(cls._default_params)
         if cls.requires_binary_data:
-            job_kwargs = fix_job_kwargs(default_job_kwargs)
+            job_kwargs = get_global_job_kwargs()
             p.update(job_kwargs)
         return p