Merge pull request #3032 from h-mayorquin/support_numpy2.0

Numpy 2.0 cap Fix most egregorious deprecated behavior and cap version

pyproject.toml

@@ -20,7 +20,7 @@ classifiers = [
 
 
 dependencies = [
-    "numpy",
+    "numpy>=1.26, <2.0",  # 1.20 np.ptp, 1.26 for avoiding pickling errors when numpy >2.0
     "threadpoolctl>=3.0.0",
     "tqdm",
     "zarr>=2.16,<2.18",

src/spikeinterface/core/core_tools.py

@@ -83,7 +83,12 @@ def default(self, obj):
         if isinstance(obj, np.generic):
             return obj.item()
 
-        if np.issctype(obj):  # Cast numpy datatypes to their names
+        # Standard numpy dtypes like np.dtype('int32") are transformed this way
+        if isinstance(obj, np.dtype):
+            return np.dtype(obj).name
+
+        # This will transform to a string canonical representation of the dtype (e.g. np.int32 -> 'int32')
+        if isinstance(obj, type) and issubclass(obj, np.generic):
             return np.dtype(obj).name
 
         if isinstance(obj, np.ndarray):

src/spikeinterface/core/tests/test_jsonification.py

@@ -122,7 +122,6 @@ def test_numpy_dtype_alises_encoding():
     # People tend to use this a dtype instead of the proper classes
     json.dumps(np.int32, cls=SIJsonEncoder)
     json.dumps(np.float32, cls=SIJsonEncoder)
-    json.dumps(np.bool_, cls=SIJsonEncoder)  # Note that np.bool was deperecated in numpy 1.20.0
 
 
 def test_recording_encoding(numpy_generated_recording):

src/spikeinterface/generation/tests/test_template_database.py

@@ -36,7 +36,7 @@ def test_fetch_templates_database_info():
 def test_query_templates_from_database():
     templates_info = fetch_templates_database_info()
 
-    templates_info = templates_info.iloc[::15]
+    templates_info = templates_info.iloc[[1, 3, 5]]
     num_selected = len(templates_info)
 
     templates = query_templates_from_database(templates_info)

src/spikeinterface/preprocessing/tests/test_highpass_spatial_filter.py

@@ -8,14 +8,7 @@
 import spikeinterface.extractors as se
 from spikeinterface.core import generate_recording
 import spikeinterface.widgets as sw
-
-try:
-    import spikeglx
-    import neurodsp.voltage as voltage
-
-    HAVE_IBL_NPIX = True
-except ImportError:
-    HAVE_IBL_NPIX = False
+import importlib.util
 
 ON_GITHUB = bool(os.getenv("GITHUB_ACTIONS"))
 
@@ -31,7 +24,10 @@
 # ----------------------------------------------------------------------------------------------------------------------
 
 
-@pytest.mark.skipif(not HAVE_IBL_NPIX or ON_GITHUB, reason="Only local. Requires ibl-neuropixel install")
+@pytest.mark.skipif(
+    importlib.util.find_spec("neurodsp") is not None or importlib.util.find_spec("spikeglx") or ON_GITHUB,
+    reason="Only local. Requires ibl-neuropixel install",
+)
 @pytest.mark.parametrize("lagc", [False, 1, 300])
 def test_highpass_spatial_filter_real_data(lagc):
     """
@@ -56,6 +52,9 @@ def test_highpass_spatial_filter_real_data(lagc):
     use DEBUG = true to visualise.
 
     """
+    import spikeglx
+    import neurodsp.voltage as voltage
+
     options = dict(lagc=lagc, ntr_pad=25, ntr_tap=50, butter_kwargs=None)
     print(options)
 
@@ -146,6 +145,8 @@ def get_ibl_si_data():
     """
     Set fixture to session to ensure origional data is not changed.
     """
+    import spikeglx
+
     local_path = si.download_dataset(remote_path="spikeglx/Noise4Sam_g0")
     ibl_recording = spikeglx.Reader(
         local_path / "Noise4Sam_g0_imec0" / "Noise4Sam_g0_t0.imec0.ap.bin", ignore_warnings=True

src/spikeinterface/preprocessing/tests/test_interpolate_bad_channels.py

@@ -6,17 +6,10 @@
 import spikeinterface.preprocessing as spre
 import spikeinterface.extractors as se
 from spikeinterface.core.generate import generate_recording
+import importlib.util
 
-try:
-    import spikeglx
-    import neurodsp.voltage as voltage
-
-    HAVE_IBL_NPIX = True
-except ImportError:
-    HAVE_IBL_NPIX = False
 
 ON_GITHUB = bool(os.getenv("GITHUB_ACTIONS"))
-
 DEBUG = False
 if DEBUG:
     import matplotlib.pyplot as plt
@@ -30,7 +23,10 @@
 # -------------------------------------------------------------------------------
 
 
-@pytest.mark.skipif(not HAVE_IBL_NPIX or ON_GITHUB, reason="Only local. Requires ibl-neuropixel install")
+@pytest.mark.skipif(
+    importlib.util.find_spec("neurodsp") is not None or importlib.util.find_spec("spikeglx") or ON_GITHUB,
+    reason="Only local. Requires ibl-neuropixel install",
+)
 def test_compare_real_data_with_ibl():
     """
     Test SI implementation of bad channel interpolation against native IBL.
@@ -43,6 +39,9 @@ def test_compare_real_data_with_ibl():
     si_scaled_recordin.get_traces(0) is also close to 1e-2.
     """
     # Download and load data
+    import spikeglx
+    import neurodsp.voltage as voltage
+
     local_path = si.download_dataset(remote_path="spikeglx/Noise4Sam_g0")
     si_recording = se.read_spikeglx(local_path, stream_id="imec0.ap")
     ibl_recording = spikeglx.Reader(
@@ -80,7 +79,10 @@ def test_compare_real_data_with_ibl():
     assert np.mean(is_close) > 0.999
 
 
-@pytest.mark.skipif(not HAVE_IBL_NPIX, reason="Requires ibl-neuropixel install")
+@pytest.mark.skipif(
+    importlib.util.find_spec("neurodsp") is not None or importlib.util.find_spec("spikeglx") is not None,
+    reason="Requires ibl-neuropixel install",
+)
 @pytest.mark.parametrize("num_channels", [32, 64])
 @pytest.mark.parametrize("sigma_um", [1.25, 40])
 @pytest.mark.parametrize("p", [0, -0.5, 1, 5])
@@ -90,6 +92,8 @@ def test_compare_input_argument_ranges_against_ibl(shanks, p, sigma_um, num_chan
     Perform an extended test across a range of function inputs to check
     IBL and SI interpolation results match.
     """
+    import neurodsp.voltage as voltage
+
     recording = generate_recording(num_channels=num_channels, durations=[1])
 
     # distribute default probe locations across 4 shanks if set

src/spikeinterface/sortingcomponents/peak_localization.py

@@ -204,7 +204,7 @@ def compute(self, traces, peaks, waveforms):
             wf = waveforms[idx][:, :, chan_inds]
 
             if self.feature == "ptp":
-                wf_data = wf.ptp(axis=1)
+                wf_data = np.ptp(wf, axis=1)
             elif self.feature == "mean":
                 wf_data = wf.mean(axis=1)
             elif self.feature == "energy":
@@ -293,7 +293,7 @@ def compute(self, traces, peaks, waveforms):
 
             wf = waveforms[i, :][:, chan_inds]
             if self.feature == "ptp":
-                wf_data = wf.ptp(axis=0)
+                wf_data = np.ptp(wf, axis=0)
             elif self.feature == "energy":
                 wf_data = np.linalg.norm(wf, axis=0)
             elif self.feature == "peak_voltage":

src/spikeinterface/sortingcomponents/tests/test_waveforms/test_waveform_thresholder.py

@@ -37,7 +37,7 @@ def test_waveform_thresholder_ptp(
         recording, peaks, nodes=pipeline_nodes, job_kwargs=chunk_executor_kwargs
     )
 
-    data = tresholded_waveforms.ptp(axis=1) / noise_levels
+    data = np.ptp(tresholded_waveforms, axis=1) / noise_levels
     assert np.all(data[data != 0] > 3)
 
 

src/spikeinterface/sortingcomponents/waveforms/waveform_thresholder.py

@@ -78,7 +78,7 @@ def __init__(
 
     def compute(self, traces, peaks, waveforms):
         if self.feature == "ptp":
-            wf_data = waveforms.ptp(axis=1) / self.noise_levels
+            wf_data = np.ptp(waveforms, axis=1) / self.noise_levels
         elif self.feature == "mean":
             wf_data = waveforms.mean(axis=1) / self.noise_levels
         elif self.feature == "energy":