Move structured dtypes to base

src/spikeinterface/benchmark/benchmark_matching.py

@@ -12,7 +12,7 @@
 
 import numpy as np
 from .benchmark_base import Benchmark, BenchmarkStudy, MixinStudyUnitCount
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 
 
 class MatchingBenchmark(Benchmark):

src/spikeinterface/benchmark/benchmark_peak_detection.py

@@ -13,7 +13,7 @@
 import numpy as np
 from spikeinterface.core.job_tools import fix_job_kwargs, split_job_kwargs
 from .benchmark_base import Benchmark, BenchmarkStudy
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 from spikeinterface.core.sortinganalyzer import create_sorting_analyzer
 from .benchmark_plot_tools import fit_sigmoid, sigmoid
 

src/spikeinterface/core/base.py

@@ -27,6 +27,31 @@
 from .job_tools import _shared_job_kwargs_doc
 
 
+# base dtypes used throughout spikeinterface
+base_peak_dtype = [
+    ("sample_index", "int64"),
+    ("channel_index", "int64"),
+    ("amplitude", "float64"),
+    ("segment_index", "int64"),
+]
+
+spike_peak_dtype = base_peak_dtype + [
+    ("unit_index", "int64"),
+]
+
+minimum_spike_dtype = [("sample_index", "int64"), ("unit_index", "int64"), ("segment_index", "int64")]
+
+base_period_dtype = [
+    ("start_sample_index", "int64"),
+    ("end_sample_index", "int64"),
+    ("segment_index", "int64"),
+]
+
+unit_period_dtype = base_period_dtype + [
+    ("unit_index", "int64"),
+]
+
+
 class BaseExtractor:
     """
     Base class for Recording/Sorting

src/spikeinterface/core/basesorting.py

@@ -5,13 +5,10 @@
 
 import numpy as np
 
-from .base import BaseExtractor, BaseSegment
+from .base import BaseExtractor, BaseSegment, minimum_spike_dtype
 from .waveform_tools import has_exceeding_spikes
 
 
-minimum_spike_dtype = [("sample_index", "int64"), ("unit_index", "int64"), ("segment_index", "int64")]
-
-
 class BaseSorting(BaseExtractor):
     """
     Abstract class representing several segment several units and relative spiketrains.

src/spikeinterface/core/generate.py

@@ -5,9 +5,9 @@
 from typing import Literal, Optional
 from math import ceil
 
+from .base import minimum_spike_dtype
 from .basesorting import SpikeVectorSortingSegment
 from .numpyextractors import NumpySorting
-from .basesorting import minimum_spike_dtype
 
 from probeinterface import Probe, generate_linear_probe, generate_multi_columns_probe
 

src/spikeinterface/core/node_pipeline.py

@@ -10,24 +10,12 @@
 
 import numpy as np
 
+from spikeinterface.core.base import base_peak_dtype, spike_peak_dtype
 from spikeinterface.core import BaseRecording, get_chunk_with_margin
 from spikeinterface.core.job_tools import ChunkRecordingExecutor, fix_job_kwargs, _shared_job_kwargs_doc
 from spikeinterface.core import get_channel_distances
 
 
-base_peak_dtype = [
-    ("sample_index", "int64"),
-    ("channel_index", "int64"),
-    ("amplitude", "float64"),
-    ("segment_index", "int64"),
-]
-
-
-spike_peak_dtype = base_peak_dtype + [
-    ("unit_index", "int64"),
-]
-
-
 class PipelineNode:
 
     # If False (general case) then compute(traces_chunk, *node_input_args)

src/spikeinterface/core/numpyextractors.py

@@ -12,7 +12,7 @@
     BaseSnippets,
     BaseSnippetsSegment,
 )
-from .basesorting import minimum_spike_dtype
+from .base import minimum_spike_dtype
 from .core_tools import make_shared_array
 from .recording_tools import write_memory_recording
 from multiprocessing.shared_memory import SharedMemory

src/spikeinterface/core/tests/test_node_pipeline.py

@@ -4,8 +4,10 @@
 import shutil
 
 from spikeinterface import create_sorting_analyzer, get_template_extremum_channel, generate_ground_truth_recording
+from spikeinterface.core.base import spike_peak_dtype
 from spikeinterface.core.job_tools import divide_recording_into_chunks
 
+
 # from spikeinterface.sortingcomponents.peak_detection import detect_peaks
 from spikeinterface.core.node_pipeline import (
     run_node_pipeline,
@@ -14,7 +16,6 @@
     PipelineNode,
     ExtractDenseWaveforms,
     sorting_to_peaks,
-    spike_peak_dtype,
 )
 
 

src/spikeinterface/core/tests/test_numpy_extractors.py

@@ -13,7 +13,7 @@
     generate_recording,
 )
 
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 from spikeinterface.core.testing import check_sortings_equal
 
 

src/spikeinterface/core/zarrextractors.py

@@ -7,8 +7,9 @@
 
 from probeinterface import ProbeGroup
 
+from .base import minimum_spike_dtype
 from .baserecording import BaseRecording, BaseRecordingSegment
-from .basesorting import BaseSorting, SpikeVectorSortingSegment, minimum_spike_dtype
+from .basesorting import BaseSorting, SpikeVectorSortingSegment
 from .core_tools import define_function_from_class, check_json
 from .job_tools import split_job_kwargs
 from .core_tools import is_path_remote

src/spikeinterface/metrics/quality/tests/test_metrics_functions.py

@@ -53,7 +53,7 @@
 )
 
 
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 
 
 job_kwargs = dict(n_jobs=2, progress_bar=True, chunk_duration="1s")

src/spikeinterface/preprocessing/silence_artifacts.py

@@ -2,15 +2,15 @@
 
 import numpy as np
 
+from spikeinterface.core.base import base_peak_dtype
 from spikeinterface.core.core_tools import define_function_handling_dict_from_class
+from spikeinterface.core.job_tools import split_job_kwargs, fix_job_kwargs
+from spikeinterface.core.recording_tools import get_noise_levels
+from spikeinterface.core.node_pipeline import PeakDetector
 from spikeinterface.preprocessing.silence_periods import SilencedPeriodsRecording
 from spikeinterface.preprocessing.rectify import RectifyRecording
 from spikeinterface.preprocessing.common_reference import CommonReferenceRecording
 from spikeinterface.preprocessing.filter_gaussian import GaussianFilterRecording
-from spikeinterface.core.job_tools import split_job_kwargs, fix_job_kwargs
-from spikeinterface.core.recording_tools import get_noise_levels
-from spikeinterface.core.node_pipeline import PeakDetector, base_peak_dtype
-import numpy as np
 
 
 class DetectThresholdCrossing(PeakDetector):

src/spikeinterface/sorters/internal/lupin.py

@@ -15,7 +15,7 @@
 from spikeinterface.core.job_tools import fix_job_kwargs
 
 from spikeinterface.preprocessing import bandpass_filter, common_reference, zscore, whiten
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 
 from spikeinterface.sortingcomponents.tools import cache_preprocessing, clean_cache_preprocessing
 

src/spikeinterface/sorters/internal/spyking_circus2.py

@@ -15,7 +15,7 @@
     get_shuffled_recording_slices,
     _set_optimal_chunk_size,
 )
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 from spikeinterface.core import compute_sparsity
 
 

src/spikeinterface/sorters/internal/tridesclous2.py

@@ -18,7 +18,7 @@
 from spikeinterface.core.job_tools import fix_job_kwargs
 
 from spikeinterface.preprocessing import bandpass_filter, common_reference, zscore, whiten
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 
 from spikeinterface.sortingcomponents.tools import cache_preprocessing, clean_cache_preprocessing
 

src/spikeinterface/sortingcomponents/clustering/random_projections.py

@@ -13,7 +13,7 @@
 else:
     HAVE_HDBSCAN = False
 
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 from spikeinterface.core.waveform_tools import estimate_templates
 from spikeinterface.sortingcomponents.clustering.merging_tools import merge_peak_labels_from_templates
 from spikeinterface.sortingcomponents.waveforms.savgol_denoiser import SavGolDenoiser

src/spikeinterface/sortingcomponents/clustering/tools.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 from spikeinterface.core import Templates, estimate_templates, fix_job_kwargs
-from spikeinterface.core.basesorting import minimum_spike_dtype
+from spikeinterface.core.base import minimum_spike_dtype
 
 # TODO find a way to attach a a sparse_mask to a given features (waveforms, pca, tsvd ....)
 

src/spikeinterface/sortingcomponents/peak_detection/iterative.py

@@ -5,13 +5,12 @@
 
 import numpy as np
 
-
+from spikeinterface.core.base import base_peak_dtype
 from spikeinterface.core.baserecording import BaseRecording
 from spikeinterface.core.node_pipeline import (
     PeakDetector,
     WaveformsNode,
     ExtractSparseWaveforms,
-    base_peak_dtype,
 )
 
 expanded_base_peak_dtype = np.dtype(base_peak_dtype + [("iteration", "int8")])

src/spikeinterface/sortingcomponents/peak_detection/matched_filtering.py

@@ -2,18 +2,14 @@
 
 from __future__ import annotations
 
+import importlib.util
 import numpy as np
 
-
-from spikeinterface.core.node_pipeline import (
-    PeakDetector,
-    base_peak_dtype,
-)
-
+from spikeinterface.core.base import base_peak_dtype
+from spikeinterface.core.node_pipeline import PeakDetector
 from spikeinterface.core.recording_tools import get_channel_distances, get_random_data_chunks
 from spikeinterface.postprocessing.localization_tools import get_convolution_weights
 
-import importlib.util
 
 numba_spec = importlib.util.find_spec("numba")
 if numba_spec is not None: