add validation

src/pynwb/ndx_binned_spikes/__init__.py

@@ -1,5 +1,9 @@
 import os
+import numpy as np
+
 from pynwb import load_namespaces, get_class
+from pynwb.core import NWBDataInterface
+from hdmf.utils import docval, popargs_to_dict, get_docval, popargs
 
 try:
     from importlib.resources import files
@@ -18,7 +22,89 @@
 # Load the namespace
 load_namespaces(str(__spec_path))
 
-BinnedAlignedSpikes = get_class("BinnedAlignedSpikes", "ndx-binned-spikes")
+# BinnedAlignedSpikes = get_class("BinnedAlignedSpikes", "ndx-binned-spikes")
+
+from pynwb import register_class, docval
+
+
+@register_class(neurodata_type="BinnedAlignedSpikes", namespace="ndx-binned-spikes")
+class BinnedAlignedSpikes(NWBDataInterface):
+    __nwbfields__ = (
+        "name",
+        "bin_width_in_milliseconds",
+        "milliseconds_from_event_to_first_bin",
+        "data",
+        "event_timestamps",
+        "units",
+    )
+
+    DEFAULT_NAME = "BinnedAlignedSpikes"
+
+    @docval(
+        {
+            "name": "name",
+            "type": str,
+            "doc": "The name of this container",
+            "default": DEFAULT_NAME,
+        },
+        {
+            "name": "bin_width_in_milliseconds",
+            "type": float,
+            "doc": "The length in milliseconds of the bins",
+        },
+        {
+            "name": "milliseconds_from_event_to_first_bin",
+            "type": float,
+            "doc": (
+                "The time in milliseconds from the event (e.g. a stimuli or the beginning of a trial),"
+                "to the first bin. Note that this is a negative number if the first bin is before the event."
+            ),
+            "default": 0.0,
+        },
+        {
+            "name": "data",
+            "type": "array_data",
+            "shape": [(None, None, None), (None, None)],
+            "doc": "The source of the data",
+        },
+        {
+            "name": "event_timestamps",
+            "type": "array_data",
+            "doc": "The timestamps at which the event occurred.",
+            "shape": (None,),
+        },
+        {
+            "name": "units",
+            "type": ("DynamicTableRegion"),
+            "doc": "A reference to the Units table region that contains the units of the data.",
+            "default": None,
+        },
+    )
+    def __init__(self, **kwargs):
+
+        keys_to_set = ("bin_width_in_milliseconds", "milliseconds_from_event_to_first_bin", "units")
+        args_to_set = popargs_to_dict(keys_to_set, kwargs)
+
+        keys_to_process = ("data", "event_timestamps")  # these are properties and cannot be set with setattr
+        args_to_process = popargs_to_dict(keys_to_process, kwargs)
+        super().__init__(**kwargs)
+
+        # Set the values
+        for key, val in args_to_set.items():
+            setattr(self, key, val)
+
+        # Post-process / post_init
+        data = args_to_process["data"]
+
+        data = data if data.ndim == 3 else data[np.newaxis, ...]
+
+        event_timestamps = args_to_process["event_timestamps"]
+
+        if data.shape[1] != event_timestamps.shape[0]:
+            raise ValueError("The number of event timestamps must match the number of event repetitions in the data.")
+
+        self.fields["data"] = data
+        self.fields["event_timestamps"] = event_timestamps
 
 
 # Remove these functions from the package

src/pynwb/tests/test_binned_aligned_spikes.py

@@ -24,9 +24,9 @@ def setUp(self):
         self.number_of_event_repetitions = 4
         self.bin_width_in_milliseconds = 20.0
         self.milliseconds_from_event_to_first_bin = -100.0
-        rng = np.random.default_rng(seed=0)
+        self.rng = np.random.default_rng(seed=0)
 
-        self.data = rng.integers(
+        self.data = self.rng.integers(
             low=0,
             high=100,
             size=(
@@ -99,6 +99,25 @@ def test_constructor_units_region(self):
         expected_names = [unit_name_a, unit_name_c]
         self.assertListEqual(unit_table_names, expected_names)
 
+    def test_accepting_input_with_no_number_of_units_dimension(self):
+
+        data = self.rng.integers(
+            low=0,
+            high=100,
+            size=(
+                self.number_of_event_repetitions,
+                self.number_of_bins,
+            ),
+        )
+        binned_aligned_spikes = BinnedAlignedSpikes(
+            bin_width_in_milliseconds=self.bin_width_in_milliseconds,
+            milliseconds_from_event_to_first_bin=self.milliseconds_from_event_to_first_bin,
+            data=data,
+            event_timestamps=self.event_timestamps,
+        )
+
+        self.assertEqual(binned_aligned_spikes.data.shape, (1, self.number_of_event_repetitions, self.number_of_bins))
+
 
 class TestBinnedAlignedSpikesSimpleRoundtrip(TestCase):
     """Simple roundtrip test for BinnedAlignedSpikes."""