regenerate models

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_0/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -164,7 +164,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_0/core_nwb_file.py

@@ -394,7 +394,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: NDArray[Any, float] = Field(
+    x: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -403,7 +403,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: NDArray[Any, float] = Field(
+    y: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -412,7 +412,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: NDArray[Any, float] = Field(
+    z: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -421,7 +421,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: NDArray[Any, float] = Field(
+    imp: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Impedance of the channel.""",
         json_schema_extra={
@@ -430,7 +430,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -439,7 +439,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: NDArray[Any, float] = Field(
+    filtering: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Description of hardware filtering.""",
         json_schema_extra={
@@ -451,7 +451,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -460,7 +460,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -469,7 +469,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -478,7 +478,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -487,7 +487,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference used for this electrode.""",
         json_schema_extra={
@@ -501,7 +501,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_0/core_nwb_icephys.py

@@ -864,7 +864,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -893,7 +893,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_0/core_nwb_misc.py

@@ -401,7 +401,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -410,7 +410,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -424,12 +424,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -439,7 +439,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -489,19 +489,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -530,16 +532,20 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
@@ -547,7 +553,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_1/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -164,7 +164,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_1/core_nwb_file.py

@@ -394,7 +394,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: NDArray[Any, float] = Field(
+    x: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -403,7 +403,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: NDArray[Any, float] = Field(
+    y: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -412,7 +412,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: NDArray[Any, float] = Field(
+    z: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -421,7 +421,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: NDArray[Any, float] = Field(
+    imp: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Impedance of the channel.""",
         json_schema_extra={
@@ -430,7 +430,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -439,7 +439,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: NDArray[Any, float] = Field(
+    filtering: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Description of hardware filtering.""",
         json_schema_extra={
@@ -451,7 +451,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -460,7 +460,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -469,7 +469,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -478,7 +478,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -487,7 +487,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference used for this electrode.""",
         json_schema_extra={
@@ -501,7 +501,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_1/core_nwb_icephys.py

@@ -864,7 +864,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -893,7 +893,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_1/core_nwb_misc.py

@@ -401,7 +401,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -410,7 +410,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -424,12 +424,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -439,7 +439,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -489,19 +489,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -530,16 +532,20 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
@@ -547,7 +553,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_2/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -164,7 +164,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_2/core_nwb_file.py

@@ -394,7 +394,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: NDArray[Any, float] = Field(
+    x: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -403,7 +403,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: NDArray[Any, float] = Field(
+    y: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -412,7 +412,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: NDArray[Any, float] = Field(
+    z: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -421,7 +421,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: NDArray[Any, float] = Field(
+    imp: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Impedance of the channel.""",
         json_schema_extra={
@@ -430,7 +430,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -439,7 +439,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: NDArray[Any, float] = Field(
+    filtering: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Description of hardware filtering.""",
         json_schema_extra={
@@ -451,7 +451,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -460,7 +460,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -469,7 +469,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -478,7 +478,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -487,7 +487,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference used for this electrode.""",
         json_schema_extra={
@@ -501,7 +501,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_2/core_nwb_icephys.py

@@ -864,7 +864,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -893,7 +893,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_2/core_nwb_misc.py

@@ -401,7 +401,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -410,7 +410,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -424,12 +424,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -439,7 +439,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -489,19 +489,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -530,16 +532,20 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
@@ -547,7 +553,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_4/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -164,7 +164,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_4/core_nwb_file.py

@@ -370,7 +370,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: NDArray[Any, float] = Field(
+    x: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -379,7 +379,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: NDArray[Any, float] = Field(
+    y: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -388,7 +388,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: NDArray[Any, float] = Field(
+    z: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -397,7 +397,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: NDArray[Any, float] = Field(
+    imp: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Impedance of the channel.""",
         json_schema_extra={
@@ -406,7 +406,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -415,7 +415,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: NDArray[Any, float] = Field(
+    filtering: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Description of hardware filtering.""",
         json_schema_extra={
@@ -427,7 +427,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -436,7 +436,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -445,7 +445,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -454,7 +454,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -463,7 +463,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference used for this electrode.""",
         json_schema_extra={
@@ -477,7 +477,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_4/core_nwb_icephys.py

@@ -864,7 +864,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -893,7 +893,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_4/core_nwb_misc.py

@@ -401,7 +401,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -410,7 +410,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -424,12 +424,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -439,7 +439,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -489,19 +489,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -530,16 +532,20 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
@@ -547,7 +553,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_4/core_nwb_ophys.py

@@ -369,7 +369,7 @@ class PlaneSegmentation(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_5/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -164,7 +164,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_5/core_nwb_file.py

@@ -370,7 +370,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: NDArray[Any, float] = Field(
+    x: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -379,7 +379,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: NDArray[Any, float] = Field(
+    y: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -388,7 +388,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: NDArray[Any, float] = Field(
+    z: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -397,7 +397,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: NDArray[Any, float] = Field(
+    imp: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Impedance of the channel.""",
         json_schema_extra={
@@ -406,7 +406,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -415,7 +415,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: NDArray[Any, float] = Field(
+    filtering: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Description of hardware filtering.""",
         json_schema_extra={
@@ -427,7 +427,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -436,7 +436,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -445,7 +445,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -454,7 +454,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -463,7 +463,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference used for this electrode.""",
         json_schema_extra={
@@ -477,7 +477,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_5/core_nwb_icephys.py

@@ -864,7 +864,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -893,7 +893,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_5/core_nwb_misc.py

@@ -401,7 +401,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -410,7 +410,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -424,12 +424,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -439,7 +439,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -489,19 +489,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -530,16 +532,20 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
     colnames: List[str] = Field(
@@ -547,7 +553,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_2_5/core_nwb_ophys.py

@@ -371,7 +371,7 @@ class PlaneSegmentation(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_3_0/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -164,7 +164,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_3_0/core_nwb_file.py

@@ -370,7 +370,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: NDArray[Any, float] = Field(
+    x: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -379,7 +379,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: NDArray[Any, float] = Field(
+    y: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -388,7 +388,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: NDArray[Any, float] = Field(
+    z: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -397,7 +397,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: NDArray[Any, float] = Field(
+    imp: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Impedance of the channel, in ohms.""",
         json_schema_extra={
@@ -406,7 +406,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -415,7 +415,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: NDArray[Any, float] = Field(
+    filtering: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Description of hardware filtering, including the filter name and frequency cutoffs.""",
         json_schema_extra={
@@ -427,7 +427,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -436,7 +436,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -445,7 +445,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -454,7 +454,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -463,7 +463,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference used for this electrode.""",
         json_schema_extra={
@@ -477,7 +477,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_3_0/core_nwb_icephys.py

@@ -866,7 +866,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -895,7 +895,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_3_0/core_nwb_misc.py

@@ -413,7 +413,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -422,7 +422,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -436,12 +436,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -451,7 +451,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -498,19 +498,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -539,26 +541,32 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
-    waveforms: Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]] = Field(
-        None,
-        description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
-            }
-        },
+    waveforms: VectorData[Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]]] = (
+        Field(
+            None,
+            description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
+                }
+            },
+        )
     )
     waveforms_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -589,7 +597,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_3_0/core_nwb_ophys.py

@@ -380,7 +380,7 @@ class PlaneSegmentation(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_4_0/core_nwb_base.py

@@ -5,7 +5,20 @@ from enum import Enum
 import re
 import sys
 import numpy as np
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, overload, Iterable, Tuple
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from pydantic import BaseModel, ConfigDict, Field, RootModel, field_validator, model_validator
 from ...hdmf_common.v1_5_0.hdmf_common_base import Data, Container
 from numpydantic import NDArray, Shape
@@ -58,8 +71,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -67,7 +82,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -125,6 +140,9 @@ class TimeSeriesReferenceVectorDataMixin(VectorDataMixin):
 
     @model_validator(mode="after")
     def ensure_equal_length(self) -> "TimeSeriesReferenceVectorDataMixin":
+        """
+        Each of the three indexing columns must be the same length to work!
+        """
         assert len(self.idx_start) == len(self.timeseries) == len(self.count), (
             f"Columns have differing lengths: idx: {len(self.idx_start)}, count: {len(self.count)},"
             f" timeseries: {len(self.timeseries)}"

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_4_0/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -164,7 +164,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_4_0/core_nwb_file.py

@@ -378,7 +378,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: NDArray[Any, float] = Field(
+    x: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -387,7 +387,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: NDArray[Any, float] = Field(
+    y: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -396,7 +396,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: NDArray[Any, float] = Field(
+    z: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -405,7 +405,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: NDArray[Any, float] = Field(
+    imp: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Impedance of the channel, in ohms.""",
         json_schema_extra={
@@ -414,7 +414,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -423,7 +423,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: NDArray[Any, str] = Field(
+    filtering: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Description of hardware filtering, including the filter name and frequency cutoffs.""",
         json_schema_extra={
@@ -435,7 +435,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -444,7 +444,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -453,7 +453,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -462,7 +462,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -471,7 +471,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference used for this electrode.""",
         json_schema_extra={
@@ -485,7 +485,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_4_0/core_nwb_icephys.py

@@ -873,7 +873,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -902,7 +902,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -939,7 +939,7 @@ class IntracellularElectrodesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -985,7 +985,7 @@ class IntracellularStimuliTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1031,7 +1031,7 @@ class IntracellularResponsesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1097,7 +1097,7 @@ class IntracellularRecordingsTable(AlignedDynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1146,7 +1146,7 @@ class SimultaneousRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1220,7 +1220,7 @@ class SequentialRecordingsTable(DynamicTable):
             }
         },
     )
-    stimulus_type: NDArray[Any, str] = Field(
+    stimulus_type: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""The type of stimulus used for the sequential recording.""",
         json_schema_extra={
@@ -1234,7 +1234,7 @@ class SequentialRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1313,7 +1313,7 @@ class RepetitionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1394,7 +1394,7 @@ class ExperimentalConditionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_4_0/core_nwb_misc.py

@@ -413,7 +413,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -422,7 +422,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -436,12 +436,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -451,7 +451,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -498,19 +498,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -539,26 +541,32 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
-    waveforms: Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]] = Field(
-        None,
-        description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
-            }
-        },
+    waveforms: VectorData[Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]]] = (
+        Field(
+            None,
+            description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
+                }
+            },
+        )
     )
     waveforms_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -589,7 +597,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_4_0/core_nwb_ophys.py

@@ -380,7 +380,7 @@ class PlaneSegmentation(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_5_0/core_nwb_base.py

@@ -16,12 +16,13 @@ from typing import (
     Dict,
     Optional,
     Union,
-    overload,
+    Generic,
     Iterable,
     Tuple,
+    TypeVar,
+    overload,
     Annotated,
     Type,
-    TypeVar,
 )
 from pydantic import (
     BaseModel,
@@ -81,8 +82,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -90,7 +93,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -148,6 +151,9 @@ class TimeSeriesReferenceVectorDataMixin(VectorDataMixin):
 
     @model_validator(mode="after")
     def ensure_equal_length(self) -> "TimeSeriesReferenceVectorDataMixin":
+        """
+        Each of the three indexing columns must be the same length to work!
+        """
         assert len(self.idx_start) == len(self.timeseries) == len(self.count), (
             f"Columns have differing lengths: idx: {len(self.idx_start)}, count: {len(self.count)},"
             f" timeseries: {len(self.timeseries)}"

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_5_0/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -173,7 +173,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_5_0/core_nwb_file.py

@@ -381,7 +381,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: Optional[NDArray[Any, float]] = Field(
+    x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -390,7 +390,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: Optional[NDArray[Any, float]] = Field(
+    y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -399,7 +399,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: Optional[NDArray[Any, float]] = Field(
+    z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -408,7 +408,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: Optional[NDArray[Any, float]] = Field(
+    imp: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""Impedance of the channel, in ohms.""",
         json_schema_extra={
@@ -417,7 +417,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -426,7 +426,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: Optional[NDArray[Any, str]] = Field(
+    filtering: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of hardware filtering, including the filter name and frequency cutoffs.""",
         json_schema_extra={
@@ -438,7 +438,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -447,7 +447,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -456,7 +456,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -465,7 +465,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -474,7 +474,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference electrode and/or reference scheme used for this electrode, e.g., \"stainless steel skull screw\" or \"online common average referencing\".""",
         json_schema_extra={
@@ -488,7 +488,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_5_0/core_nwb_icephys.py

@@ -874,7 +874,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -903,7 +903,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -940,7 +940,7 @@ class IntracellularElectrodesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -986,7 +986,7 @@ class IntracellularStimuliTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1032,7 +1032,7 @@ class IntracellularResponsesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1098,7 +1098,7 @@ class IntracellularRecordingsTable(AlignedDynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1147,7 +1147,7 @@ class SimultaneousRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1221,7 +1221,7 @@ class SequentialRecordingsTable(DynamicTable):
             }
         },
     )
-    stimulus_type: NDArray[Any, str] = Field(
+    stimulus_type: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""The type of stimulus used for the sequential recording.""",
         json_schema_extra={
@@ -1235,7 +1235,7 @@ class SequentialRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1314,7 +1314,7 @@ class RepetitionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1395,7 +1395,7 @@ class ExperimentalConditionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_5_0/core_nwb_misc.py

@@ -413,7 +413,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -422,7 +422,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -436,12 +436,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -451,7 +451,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -498,19 +498,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -539,26 +541,32 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
-    waveforms: Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]] = Field(
-        None,
-        description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
-            }
-        },
+    waveforms: VectorData[Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]]] = (
+        Field(
+            None,
+            description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
+                }
+            },
+        )
     )
     waveforms_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -589,7 +597,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_5_0/core_nwb_ophys.py

@@ -380,7 +380,7 @@ class PlaneSegmentation(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_6_0_alpha/core_nwb_base.py

@@ -16,12 +16,13 @@ from typing import (
     Dict,
     Optional,
     Union,
-    overload,
+    Generic,
     Iterable,
     Tuple,
+    TypeVar,
+    overload,
     Annotated,
     Type,
-    TypeVar,
 )
 from pydantic import (
     BaseModel,
@@ -81,8 +82,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -90,7 +93,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -148,6 +151,9 @@ class TimeSeriesReferenceVectorDataMixin(VectorDataMixin):
 
     @model_validator(mode="after")
     def ensure_equal_length(self) -> "TimeSeriesReferenceVectorDataMixin":
+        """
+        Each of the three indexing columns must be the same length to work!
+        """
         assert len(self.idx_start) == len(self.timeseries) == len(self.count), (
             f"Columns have differing lengths: idx: {len(self.idx_start)}, count: {len(self.count)},"
             f" timeseries: {len(self.timeseries)}"

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_6_0_alpha/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -173,7 +173,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_6_0_alpha/core_nwb_file.py

@@ -381,7 +381,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: Optional[NDArray[Any, float]] = Field(
+    x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -390,7 +390,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: Optional[NDArray[Any, float]] = Field(
+    y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -399,7 +399,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: Optional[NDArray[Any, float]] = Field(
+    z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -408,7 +408,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: Optional[NDArray[Any, float]] = Field(
+    imp: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""Impedance of the channel, in ohms.""",
         json_schema_extra={
@@ -417,7 +417,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -426,7 +426,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: Optional[NDArray[Any, str]] = Field(
+    filtering: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of hardware filtering, including the filter name and frequency cutoffs.""",
         json_schema_extra={
@@ -438,7 +438,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -447,7 +447,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -456,7 +456,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -465,7 +465,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -474,7 +474,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference electrode and/or reference scheme used for this electrode, e.g., \"stainless steel skull screw\" or \"online common average referencing\".""",
         json_schema_extra={
@@ -488,7 +488,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_6_0_alpha/core_nwb_icephys.py

@@ -874,7 +874,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -903,7 +903,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -940,7 +940,7 @@ class IntracellularElectrodesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -986,7 +986,7 @@ class IntracellularStimuliTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1032,7 +1032,7 @@ class IntracellularResponsesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1098,7 +1098,7 @@ class IntracellularRecordingsTable(AlignedDynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1147,7 +1147,7 @@ class SimultaneousRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1221,7 +1221,7 @@ class SequentialRecordingsTable(DynamicTable):
             }
         },
     )
-    stimulus_type: NDArray[Any, str] = Field(
+    stimulus_type: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""The type of stimulus used for the sequential recording.""",
         json_schema_extra={
@@ -1235,7 +1235,7 @@ class SequentialRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1314,7 +1314,7 @@ class RepetitionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1395,7 +1395,7 @@ class ExperimentalConditionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_6_0_alpha/core_nwb_misc.py

@@ -413,7 +413,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -422,7 +422,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -436,12 +436,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -451,7 +451,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -498,19 +498,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -539,26 +541,32 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
-    waveforms: Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]] = Field(
-        None,
-        description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
-            }
-        },
+    waveforms: VectorData[Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]]] = (
+        Field(
+            None,
+            description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
+                }
+            },
+        )
     )
     waveforms_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -589,7 +597,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_6_0_alpha/core_nwb_ophys.py

@@ -479,7 +479,7 @@ class PlaneSegmentation(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_7_0/core_nwb_base.py

@@ -1,4 +1,9 @@
 from __future__ import annotations
+from datetime import datetime, date
+from decimal import Decimal
+from enum import Enum
+import re
+import sys
 import numpy as np
 from ...hdmf_common.v1_8_0.hdmf_common_base import Data, Container
 from numpydantic import NDArray, Shape
@@ -11,18 +16,20 @@ from typing import (
     Dict,
     Optional,
     Union,
-    overload,
+    Generic,
     Iterable,
     Tuple,
+    TypeVar,
+    overload,
     Annotated,
     Type,
-    TypeVar,
 )
 from pydantic import (
     BaseModel,
     ConfigDict,
     Field,
     RootModel,
+    field_validator,
     model_validator,
     ValidationInfo,
     BeforeValidator,
@@ -75,8 +82,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -84,7 +93,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -142,6 +151,9 @@ class TimeSeriesReferenceVectorDataMixin(VectorDataMixin):
 
     @model_validator(mode="after")
     def ensure_equal_length(self) -> "TimeSeriesReferenceVectorDataMixin":
+        """
+        Each of the three indexing columns must be the same length to work!
+        """
         assert len(self.idx_start) == len(self.timeseries) == len(self.count), (
             f"Columns have differing lengths: idx: {len(self.idx_start)}, count: {len(self.count)},"
             f" timeseries: {len(self.timeseries)}"

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_7_0/core_nwb_epoch.py

@@ -105,7 +105,7 @@ class TimeIntervals(DynamicTable):
     )
 
     name: str = Field(...)
-    start_time: NDArray[Any, float] = Field(
+    start_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Start time of epoch, in seconds.""",
         json_schema_extra={
@@ -114,7 +114,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    stop_time: NDArray[Any, float] = Field(
+    stop_time: VectorData[NDArray[Any, float]] = Field(
         ...,
         description="""Stop time of epoch, in seconds.""",
         json_schema_extra={
@@ -123,7 +123,7 @@ class TimeIntervals(DynamicTable):
             }
         },
     )
-    tags: Optional[NDArray[Any, str]] = Field(
+    tags: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""User-defined tags that identify or categorize events.""",
         json_schema_extra={
@@ -173,7 +173,7 @@ class TimeIntervals(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_7_0/core_nwb_file.py

@@ -389,7 +389,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             "linkml_meta": {"equals_string": "electrodes", "ifabsent": "string(electrodes)"}
         },
     )
-    x: Optional[NDArray[Any, float]] = Field(
+    x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate of the channel location in the brain (+x is posterior).""",
         json_schema_extra={
@@ -398,7 +398,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    y: Optional[NDArray[Any, float]] = Field(
+    y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate of the channel location in the brain (+y is inferior).""",
         json_schema_extra={
@@ -407,7 +407,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    z: Optional[NDArray[Any, float]] = Field(
+    z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate of the channel location in the brain (+z is right).""",
         json_schema_extra={
@@ -416,7 +416,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    imp: Optional[NDArray[Any, float]] = Field(
+    imp: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""Impedance of the channel, in ohms.""",
         json_schema_extra={
@@ -425,7 +425,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    location: NDArray[Any, str] = Field(
+    location: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Location of the electrode (channel). Specify the area, layer, comments on estimation of area/layer, stereotaxic coordinates if in vivo, etc. Use standard atlas names for anatomical regions when possible.""",
         json_schema_extra={
@@ -434,7 +434,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    filtering: Optional[NDArray[Any, str]] = Field(
+    filtering: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of hardware filtering, including the filter name and frequency cutoffs.""",
         json_schema_extra={
@@ -446,7 +446,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
     group: List[ElectrodeGroup] = Field(
         ..., description="""Reference to the ElectrodeGroup this electrode is a part of."""
     )
-    group_name: NDArray[Any, str] = Field(
+    group_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the ElectrodeGroup this electrode is a part of.""",
         json_schema_extra={
@@ -455,7 +455,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_x: Optional[NDArray[Any, float]] = Field(
+    rel_x: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""x coordinate in electrode group""",
         json_schema_extra={
@@ -464,7 +464,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_y: Optional[NDArray[Any, float]] = Field(
+    rel_y: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""y coordinate in electrode group""",
         json_schema_extra={
@@ -473,7 +473,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    rel_z: Optional[NDArray[Any, float]] = Field(
+    rel_z: VectorData[Optional[NDArray[Any, float]]] = Field(
         None,
         description="""z coordinate in electrode group""",
         json_schema_extra={
@@ -482,7 +482,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
             }
         },
     )
-    reference: Optional[NDArray[Any, str]] = Field(
+    reference: VectorData[Optional[NDArray[Any, str]]] = Field(
         None,
         description="""Description of the reference electrode and/or reference scheme used for this electrode, e.g., \"stainless steel skull screw\" or \"online common average referencing\".""",
         json_schema_extra={
@@ -496,7 +496,7 @@ class ExtracellularEphysElectrodes(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_7_0/core_nwb_icephys.py

@@ -874,7 +874,7 @@ class SweepTable(DynamicTable):
     )
 
     name: str = Field(...)
-    sweep_number: NDArray[Any, int] = Field(
+    sweep_number: VectorData[NDArray[Any, int]] = Field(
         ...,
         description="""Sweep number of the PatchClampSeries in that row.""",
         json_schema_extra={
@@ -903,7 +903,7 @@ class SweepTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -940,7 +940,7 @@ class IntracellularElectrodesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -998,7 +998,7 @@ class IntracellularStimuliTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1044,7 +1044,7 @@ class IntracellularResponsesTable(DynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1110,7 +1110,7 @@ class IntracellularRecordingsTable(AlignedDynamicTable):
         ...,
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1159,7 +1159,7 @@ class SimultaneousRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1233,7 +1233,7 @@ class SequentialRecordingsTable(DynamicTable):
             }
         },
     )
-    stimulus_type: NDArray[Any, str] = Field(
+    stimulus_type: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""The type of stimulus used for the sequential recording.""",
         json_schema_extra={
@@ -1247,7 +1247,7 @@ class SequentialRecordingsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1326,7 +1326,7 @@ class RepetitionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -1407,7 +1407,7 @@ class ExperimentalConditionsTable(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_7_0/core_nwb_misc.py

@@ -413,7 +413,7 @@ class DecompositionSeriesBands(DynamicTable):
         "bands",
         json_schema_extra={"linkml_meta": {"equals_string": "bands", "ifabsent": "string(bands)"}},
     )
-    band_name: NDArray[Any, str] = Field(
+    band_name: VectorData[NDArray[Any, str]] = Field(
         ...,
         description="""Name of the band, e.g. theta.""",
         json_schema_extra={
@@ -422,7 +422,7 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_limits: NDArray[Shape["* num_bands, 2 low_high"], float] = Field(
+    band_limits: VectorData[NDArray[Shape["* num_bands, 2 low_high"], float]] = Field(
         ...,
         description="""Low and high limit of each band in Hz. If it is a Gaussian filter, use 2 SD on either side of the center.""",
         json_schema_extra={
@@ -436,12 +436,12 @@ class DecompositionSeriesBands(DynamicTable):
             }
         },
     )
-    band_mean: NDArray[Shape["* num_bands"], float] = Field(
+    band_mean: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The mean Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
     )
-    band_stdev: NDArray[Shape["* num_bands"], float] = Field(
+    band_stdev: VectorData[NDArray[Shape["* num_bands"], float]] = Field(
         ...,
         description="""The standard deviation of Gaussian filters, in Hz.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_bands"}]}}},
@@ -451,7 +451,7 @@ class DecompositionSeriesBands(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -498,19 +498,21 @@ class Units(DynamicTable):
             }
         },
     )
-    obs_intervals: Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]] = Field(
-        None,
-        description="""Observation intervals for each unit.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {
-                    "dimensions": [
-                        {"alias": "num_intervals"},
-                        {"alias": "start_end", "exact_cardinality": 2},
-                    ]
+    obs_intervals: VectorData[Optional[NDArray[Shape["* num_intervals, 2 start_end"], float]]] = (
+        Field(
+            None,
+            description="""Observation intervals for each unit.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {
+                        "dimensions": [
+                            {"alias": "num_intervals"},
+                            {"alias": "start_end", "exact_cardinality": 2},
+                        ]
+                    }
                 }
-            }
-        },
+            },
+        )
     )
     electrodes_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -539,26 +541,32 @@ class Units(DynamicTable):
     electrode_group: Optional[List[ElectrodeGroup]] = Field(
         None, description="""Electrode group that each spike unit came from."""
     )
-    waveform_mean: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_mean: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform mean for each spike unit.""")
-    waveform_sd: Optional[
-        Union[
-            NDArray[Shape["* num_units, * num_samples"], float],
-            NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+    waveform_sd: VectorData[
+        Optional[
+            Union[
+                NDArray[Shape["* num_units, * num_samples"], float],
+                NDArray[Shape["* num_units, * num_samples, * num_electrodes"], float],
+            ]
         ]
     ] = Field(None, description="""Spike waveform standard deviation for each spike unit.""")
-    waveforms: Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]] = Field(
-        None,
-        description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
-        json_schema_extra={
-            "linkml_meta": {
-                "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
-            }
-        },
+    waveforms: VectorData[Optional[NDArray[Shape["* num_waveforms, * num_samples"], float]]] = (
+        Field(
+            None,
+            description="""Individual waveforms for each spike on each electrode. This is a doubly indexed column. The 'waveforms_index' column indexes which waveforms in this column belong to the same spike event for a given unit, where each waveform was recorded from a different electrode. The 'waveforms_index_index' column indexes the 'waveforms_index' column to indicate which spike events belong to a given unit. For example, if the 'waveforms_index_index' column has values [2, 5, 6], then the first 2 elements of the 'waveforms_index' column correspond to the 2 spike events of the first unit, the next 3 elements of the 'waveforms_index' column correspond to the 3 spike events of the second unit, and the next 1 element of the 'waveforms_index' column corresponds to the 1 spike event of the third unit. If the 'waveforms_index' column has values [3, 6, 8, 10, 12, 13], then the first 3 elements of the 'waveforms' column contain the 3 spike waveforms that were recorded from 3 different electrodes for the first spike time of the first unit. See https://nwb-schema.readthedocs.io/en/stable/format_description.html#doubly-ragged-arrays for a graphical representation of this example. When there is only one electrode for each unit (i.e., each spike time is associated with a single waveform), then the 'waveforms_index' column will have values 1, 2, ..., N, where N is the number of spike events. The number of electrodes for each spike event should be the same within a given unit. The 'electrodes' column should be used to indicate which electrodes are associated with each unit, and the order of the waveforms within a given unit x spike event should be in the same order as the electrodes referenced in the 'electrodes' column of this table. The number of samples for each waveform must be the same.""",
+            json_schema_extra={
+                "linkml_meta": {
+                    "array": {"dimensions": [{"alias": "num_waveforms"}, {"alias": "num_samples"}]}
+                }
+            },
+        )
     )
     waveforms_index: Named[Optional[VectorIndex]] = Field(
         None,
@@ -589,7 +597,7 @@ class Units(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/core/v2_7_0/core_nwb_ophys.py

@@ -479,7 +479,7 @@ class PlaneSegmentation(DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_1_0/hdmf_common_table.py

@@ -5,7 +5,20 @@ from enum import Enum
 import re
 import sys
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from numpydantic import NDArray, Shape
 from pydantic import (
     BaseModel,
@@ -67,8 +80,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -76,7 +91,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -119,13 +134,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -406,20 +421,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -569,6 +592,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -698,7 +747,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_1_2/hdmf_common_table.py

@@ -5,7 +5,20 @@ from enum import Enum
 import re
 import sys
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from numpydantic import NDArray, Shape
 from pydantic import (
     BaseModel,
@@ -67,8 +80,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -76,7 +91,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -119,13 +134,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -406,20 +421,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -569,6 +592,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -698,7 +747,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_1_3/hdmf_common_table.py

@@ -5,7 +5,20 @@ from enum import Enum
 import re
 import sys
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from numpydantic import NDArray, Shape
 from pydantic import (
     BaseModel,
@@ -67,8 +80,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -76,7 +91,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -119,13 +134,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -406,20 +421,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -569,6 +592,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -717,7 +766,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_2_0/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_2_0.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from numpydantic import NDArray, Shape
 from pydantic import (
     BaseModel,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -711,7 +760,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_2_1/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_2_1.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from numpydantic import NDArray, Shape
 from pydantic import (
     BaseModel,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -711,7 +760,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_3_0/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_3_0.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from numpydantic import NDArray, Shape
 from pydantic import (
     BaseModel,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -711,7 +760,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_4_0/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_4_0.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from numpydantic import NDArray, Shape
 from pydantic import (
     BaseModel,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -685,7 +734,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_5_0/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_5_0.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from pydantic import (
     BaseModel,
     ConfigDict,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -685,7 +734,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -713,7 +762,7 @@ class AlignedDynamicTable(AlignedDynamicTableMixin, DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_5_1/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_5_1.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from pydantic import (
     BaseModel,
     ConfigDict,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -685,7 +734,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -713,7 +762,7 @@ class AlignedDynamicTable(AlignedDynamicTableMixin, DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_6_0/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_6_0.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from pydantic import (
     BaseModel,
     ConfigDict,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -685,7 +734,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -713,7 +762,7 @@ class AlignedDynamicTable(AlignedDynamicTableMixin, DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_7_0/hdmf_common_table.py

@@ -6,7 +6,20 @@ import re
 import sys
 from ...hdmf_common.v1_7_0.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Literal, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from pydantic import (
     BaseModel,
     ConfigDict,
@@ -68,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -77,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -120,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -407,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -570,6 +593,32 @@ class AlignedDynamicTableMixin(DynamicTableMixin):
         df.set_index((self.name, "id"), drop=True, inplace=True)
         return df
 
+    @model_validator(mode="before")
+    @classmethod
+    def create_categories(cls, model: Dict[str, Any]) -> Dict:
+        """
+        Construct categories from arguments.
+
+        the model dict is ordered after python3.6, so we can use that minus
+        anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
+        """
+        if "categories" not in model:
+            categories = [
+                k for k in model if k not in cls.NON_CATEGORY_FIELDS and not k.endswith("_index")
+            ]
+            model["categories"] = categories
+        else:
+            # add any columns not explicitly given an order at the end
+            categories = [
+                k
+                for k in model
+                if k not in cls.NON_COLUMN_FIELDS
+                and not k.endswith("_index")
+                and k not in model["categories"]
+            ]
+            model["categories"].extend(categories)
+        return model
+
 
 linkml_meta = LinkMLMeta(
     {
@@ -685,7 +734,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -713,7 +762,7 @@ class AlignedDynamicTable(AlignedDynamicTableMixin, DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},

nwb_linkml/src/nwb_linkml/models/pydantic/hdmf_common/v1_8_0/hdmf_common_table.py

@@ -1,7 +1,25 @@
 from __future__ import annotations
-from ...hdmf_common.v1_8_0.hdmf_common_base import Data
+from datetime import datetime, date
+from decimal import Decimal
+from enum import Enum
+import re
+import sys
+from ...hdmf_common.v1_8_0.hdmf_common_base import Data, Container
 import pandas as pd
-from typing import Any, ClassVar, List, Dict, Optional, Union, Iterable, Tuple, overload
+from typing import (
+    Any,
+    ClassVar,
+    List,
+    Literal,
+    Dict,
+    Optional,
+    Union,
+    Generic,
+    Iterable,
+    Tuple,
+    TypeVar,
+    overload,
+)
 from pydantic import (
     BaseModel,
     ConfigDict,
@@ -63,8 +81,10 @@ class LinkMLMeta(RootModel):
 
 NUMPYDANTIC_VERSION = "1.2.1"
 
+T = TypeVar("T", bound=NDArray)
 
-class VectorDataMixin(BaseModel):
+
+class VectorDataMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorData indexing abilities
     """
@@ -72,7 +92,7 @@ class VectorDataMixin(BaseModel):
     _index: Optional["VectorIndex"] = None
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
         if value is not None and "value" not in kwargs:
@@ -115,13 +135,13 @@ class VectorDataMixin(BaseModel):
             return len(self.value)
 
 
-class VectorIndexMixin(BaseModel):
+class VectorIndexMixin(BaseModel, Generic[T]):
     """
     Mixin class to give VectorIndex indexing abilities
     """
 
     # redefined in `VectorData`, but included here for testing and type checking
-    value: Optional[NDArray] = None
+    value: Optional[T] = None
     target: Optional["VectorData"] = None
 
     def __init__(self, value: Optional[NDArray] = None, **kwargs):
@@ -402,20 +422,28 @@ class DynamicTableMixin(BaseModel):
         anything in :attr:`.NON_COLUMN_FIELDS` to determine order implied from passage order
         """
         if "colnames" not in model:
-            colnames = [
-                k for k in model if k not in cls.NON_COLUMN_FIELDS and not k.endswith("_index")
-            ]
-            model["colnames"] = colnames
-        else:
-            # add any columns not explicitly given an order at the end
             colnames = [
                 k
                 for k in model
                 if k not in cls.NON_COLUMN_FIELDS
                 and not k.endswith("_index")
-                and k not in model["colnames"]
+                and not isinstance(model[k], VectorIndexMixin)
             ]
-            model["colnames"].extend(colnames)
+            model["colnames"] = colnames
+        else:
+            # add any columns not explicitly given an order at the end
+            colnames = model["colnames"].copy()
+            colnames.extend(
+                [
+                    k
+                    for k in model
+                    if k not in cls.NON_COLUMN_FIELDS
+                    and not k.endswith("_index")
+                    and k not in model["colnames"]
+                    and not isinstance(model[k], VectorIndexMixin)
+                ]
+            )
+            model["colnames"] = colnames
         return model
 
     @model_validator(mode="after")
@@ -706,7 +734,7 @@ class DynamicTable(DynamicTableMixin):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},
@@ -734,7 +762,7 @@ class AlignedDynamicTable(AlignedDynamicTableMixin, DynamicTable):
         description="""The names of the columns in this table. This should be used to specify an order to the columns.""",
     )
     description: str = Field(..., description="""Description of what is in this dynamic table.""")
-    id: NDArray[Shape["* num_rows"], int] = Field(
+    id: VectorData[NDArray[Shape["* num_rows"], int]] = Field(
         ...,
         description="""Array of unique identifiers for the rows of this dynamic table.""",
         json_schema_extra={"linkml_meta": {"array": {"dimensions": [{"alias": "num_rows"}]}}},