Dervice PandA describe from datasets PV

src/ophyd_async/panda/_common_blocks.py

@@ -3,7 +3,7 @@
 from enum import Enum
 
 from ophyd_async.core import Device, DeviceVector, SignalR, SignalRW
-from ophyd_async.panda._table import SeqTable
+from ophyd_async.panda._table import DatasetTable, SeqTable
 
 
 class DataBlock(Device):
@@ -14,6 +14,7 @@ class DataBlock(Device):
     num_captured: SignalR[int]
     capture: SignalRW[bool]
     flush_period: SignalRW[float]
+    datasets: SignalR[DatasetTable]
 
 
 class PulseBlock(Device):

src/ophyd_async/panda/_hdf_panda.py

@@ -28,9 +28,7 @@ def __init__(
         create_children_from_annotations(self)
         controller = PandaPcapController(pcap=self.pcap)
         writer = PandaHDFWriter(
-            prefix=prefix,
             directory_provider=directory_provider,
-            name_provider=lambda: name,
             panda_device=self,
         )
         super().__init__(

src/ophyd_async/panda/_table.py

@@ -6,6 +6,16 @@
 import numpy.typing as npt
 
 
+class PandaHdf5DatasetType(str, Enum):
+    FLOAT_64 = "float64"
+    UINT_32 = "uint32"
+
+
+class DatasetTable(TypedDict):
+    name: npt.NDArray[np.str_]
+    hdf5_type: Sequence[PandaHdf5DatasetType]
+
+
 class SeqTrigger(str, Enum):
     IMMEDIATE = "Immediate"
     BITA_0 = "BITA=0"

src/ophyd_async/panda/writers/_hdf_writer.py

@@ -1,107 +1,32 @@
 import asyncio
-from dataclasses import dataclass
-from enum import Enum
 from pathlib import Path
-from typing import Any, AsyncGenerator, AsyncIterator, Dict, List, Optional
+from typing import AsyncGenerator, AsyncIterator, Dict, List, Optional
 
 from bluesky.protocols import DataKey, StreamAsset
 from p4p.client.thread import Context
 
 from ophyd_async.core import (
     DEFAULT_TIMEOUT,
     DetectorWriter,
-    Device,
     DirectoryProvider,
-    NameProvider,
-    SignalR,
     wait_for_value,
 )
 from ophyd_async.core.signal import observe_value
-from ophyd_async.panda import CommonPandaBlocks
 
+from .._common_blocks import CommonPandaBlocks
 from ._panda_hdf_file import _HDFDataset, _HDFFile
 
 
-class Capture(str, Enum):
-    # Capture signals for the HDF Panda
-    No = "No"
-    Value = "Value"
-    Diff = "Diff"
-    Sum = "Sum"
-    Mean = "Mean"
-    Min = "Min"
-    Max = "Max"
-    MinMax = "Min Max"
-    MinMaxMean = "Min Max Mean"
-
-
-def get_capture_signals(
-    block: Device, path_prefix: Optional[str] = ""
-) -> Dict[str, SignalR]:
-    """Get dict mapping a capture signal's name to the signal itself"""
-    if not path_prefix:
-        path_prefix = ""
-    signals: Dict[str, SignalR[Any]] = {}
-    for attr_name, attr in block.children():
-        # Capture signals end in _capture, but num_capture is a red herring
-        if attr_name == "num_capture":
-            continue
-        dot_path = f"{path_prefix}{attr_name}"
-        if isinstance(attr, SignalR) and attr_name.endswith("_capture"):
-            signals[dot_path] = attr
-        attr_signals = get_capture_signals(attr, path_prefix=dot_path + ".")
-        signals.update(attr_signals)
-    return signals
-
-
-@dataclass
-class CaptureSignalWrapper:
-    signal: SignalR
-    capture_type: Capture
-
-
-# This should return a dictionary which contains a dict, containing the Capture
-# signal object, and the value of that signal
-async def get_signals_marked_for_capture(
-    capture_signals: Dict[str, SignalR],
-) -> Dict[str, CaptureSignalWrapper]:
-    # Read signals to see if they should be captured
-    do_read = [signal.get_value() for signal in capture_signals.values()]
-
-    signal_values = await asyncio.gather(*do_read)
-
-    assert len(signal_values) == len(
-        capture_signals
-    ), "Length of read signals are different to length of signals"
-
-    signals_to_capture: Dict[str, CaptureSignalWrapper] = {}
-    for signal_path, signal_object, signal_value in zip(
-        capture_signals.keys(), capture_signals.values(), signal_values
-    ):
-        signal_path = signal_path.replace("_capture", "")
-        if (signal_value in iter(Capture)) and (signal_value != Capture.No):
-            signals_to_capture[signal_path] = CaptureSignalWrapper(
-                signal_object,
-                signal_value,
-            )
-
-    return signals_to_capture
-
-
 class PandaHDFWriter(DetectorWriter):
     _ctxt: Optional[Context] = None
 
     def __init__(
         self,
-        prefix: str,
         directory_provider: DirectoryProvider,
-        name_provider: NameProvider,
         panda_device: CommonPandaBlocks,
     ) -> None:
         self.panda_device = panda_device
-        self._prefix = prefix
         self._directory_provider = directory_provider
-        self._name_provider = name_provider
         self._datasets: List[_HDFDataset] = []
         self._file: Optional[_HDFFile] = None
         self._multiplier = 1
@@ -110,14 +35,9 @@ def __init__(
     async def open(self, multiplier: int = 1) -> Dict[str, DataKey]:
         """Retrieve and get descriptor of all PandA signals marked for capture"""
 
-        # Get capture PVs by looking at panda. Gives mapping of dotted attribute path
-        # to Signal object
-        self.capture_signals = get_capture_signals(self.panda_device)
-
         # Ensure flushes are immediate
         await self.panda_device.data.flush_period.set(0)
 
-        to_capture = await get_signals_marked_for_capture(self.capture_signals)
         self._file = None
         info = self._directory_provider()
         # Set the initial values
@@ -133,36 +53,21 @@ async def open(self, multiplier: int = 1) -> Dict[str, DataKey]:
 
         # Wait for it to start, stashing the status that tells us when it finishes
         await self.panda_device.data.capture.set(True)
-        name = self._name_provider()
         if multiplier > 1:
             raise ValueError(
                 "All PandA datasets should be scalar, multiplier should be 1"
             )
-        self._datasets = []
-        for attribute_path, capture_signal in to_capture.items():
-            split_path = attribute_path.split(".")
-            signal_name = split_path[-1]
-            # Get block names from numbered blocks, eg INENC[1]
-            block_name = (
-                f"{split_path[-3]}{split_path[-2]}"
-                if split_path[-2].isnumeric()
-                else split_path[-2]
-            )
 
-            for suffix in capture_signal.capture_type.split(" "):
-                self._datasets.append(
-                    _HDFDataset(
-                        name,
-                        block_name,
-                        f"{name}-{block_name}-{signal_name}-{suffix}",
-                        f"{block_name}-{signal_name}".upper() + f"-{suffix}",
-                        [1],
-                        multiplier=1,
-                    )
-                )
+        return await self._describe()
 
+    async def _describe(self) -> Dict[str, DataKey]:
+        """
+        Return a describe based on the datasets PV
+        """
+
+        await self._update_datasets()
         describe = {
-            ds.name: DataKey(
+            ds.data_key: DataKey(
                 source=self.panda_device.data.hdf_directory.source,
                 shape=ds.shape,
                 dtype="array" if ds.shape != [1] else "number",
@@ -172,6 +77,18 @@ async def open(self, multiplier: int = 1) -> Dict[str, DataKey]:
         }
         return describe
 
+    async def _update_datasets(self) -> None:
+        """
+        Load data from the datasets PV on the panda, update internal
+        representation of datasets that the panda will write.
+        """
+
+        capture_table = await self.panda_device.data.datasets.get_value()
+        self._datasets = [
+            _HDFDataset(dataset_name, dataset_name, [1], multiplier=1)
+            for dataset_name in capture_table["name"]
+        ]
+
     # Next few functions are exactly the same as AD writer. Could move as default
     # StandardDetector behavior
     async def wait_for_index(

src/ophyd_async/panda/writers/_panda_hdf_file.py

@@ -9,10 +9,8 @@
 
 @dataclass
 class _HDFDataset:
-    device_name: str
-    block: str
-    name: str
-    path: str
+    data_key: str
+    internal_path: str
     shape: List[int]
     multiplier: int
 
@@ -29,12 +27,10 @@ def __init__(
             compose_stream_resource(
                 spec="AD_HDF5_SWMR_SLICE",
                 root=str(directory_info.root),
-                data_key=ds.name,
+                data_key=ds.data_key,
                 resource_path=(f"{str(directory_info.root)}/{full_file_name}"),
                 resource_kwargs={
-                    "name": ds.name,
-                    "block": ds.block,
-                    "path": ds.path,
+                    "internal_path": ds.internal_path,
                     "multiplier": ds.multiplier,
                     "timestamps": "/entry/instrument/NDAttributes/NDArrayTimeStamp",
                 },

tests/panda/test_hdf_panda.py

@@ -1,5 +1,6 @@
 from typing import Dict
 
+import numpy as np
 import pytest
 from bluesky import plan_stubs as bps
 from bluesky.run_engine import RunEngine
@@ -9,9 +10,8 @@
 from ophyd_async.core.flyer import HardwareTriggeredFlyable
 from ophyd_async.core.mock_signal_utils import callback_on_mock_put
 from ophyd_async.core.signal import SignalR, assert_emitted
-from ophyd_async.epics.signal.signal import epics_signal_r
 from ophyd_async.panda import HDFPanda, StaticSeqTableTriggerLogic
-from ophyd_async.panda.writers._hdf_writer import Capture
+from ophyd_async.panda._table import DatasetTable, PandaHdf5DatasetType
 from ophyd_async.plan_stubs import (
     prepare_static_seq_table_flyer_and_detectors_with_same_trigger,
 )
@@ -26,25 +26,28 @@ class CaptureBlock(Device):
     mock_hdf_panda = HDFPanda(
         "HDFPANDA:", directory_provider=directory_provider, name="panda"
     )
-    block_a = CaptureBlock(name="block_a")
-    block_b = CaptureBlock(name="block_b")
-    block_a.test_capture = epics_signal_r(
-        Capture, "pva://test_capture_a", name="test_capture_a"
-    )
-    block_b.test_capture = epics_signal_r(
-        Capture, "pva://test_capture_b", name="test_capture_b"
-    )
-
-    setattr(mock_hdf_panda, "block_a", block_a)
-    setattr(mock_hdf_panda, "block_b", block_b)
     await mock_hdf_panda.connect(mock=True)
 
     def link_function(value, **kwargs):
         set_mock_value(mock_hdf_panda.pcap.active, value)
 
     callback_on_mock_put(mock_hdf_panda.pcap.arm, link_function)
-    set_mock_value(block_a.test_capture, Capture.Min)
-    set_mock_value(block_b.test_capture, Capture.Diff)
+
+    set_mock_value(
+        mock_hdf_panda.data.datasets,
+        DatasetTable(
+            name=np.array(
+                [
+                    "x",
+                    "y",
+                ]
+            ),
+            hdf5_type=[
+                PandaHdf5DatasetType.UINT_32,
+                PandaHdf5DatasetType.FLOAT_64,
+            ],
+        ),
+    )
 
     yield mock_hdf_panda
 
@@ -127,28 +130,23 @@ def flying_plan():
 
     # test descriptor
     data_key_names: Dict[str, str] = docs["descriptor"][0]["object_keys"]["panda"]
-    assert data_key_names == [
-        "panda-block_a-test-Min",
-        "panda-block_b-test-Diff",
-    ]
+    assert data_key_names == ["x", "y"]
     for data_key_name in data_key_names:
         assert (
             docs["descriptor"][0]["data_keys"][data_key_name]["source"]
             == "mock+soft://panda-data-hdf_directory"
         )
 
     # test stream resources
-    for block_letter, stream_resource, data_key_name in zip(
-        ("a", "b"), docs["stream_resource"], data_key_names
+    for dataset_name, stream_resource, data_key_name in zip(
+        ("x", "y"), docs["stream_resource"], data_key_names
     ):
         assert stream_resource["data_key"] == data_key_name
         assert stream_resource["spec"] == "AD_HDF5_SWMR_SLICE"
         assert stream_resource["run_start"] == docs["start"][0]["uid"]
         assert stream_resource["resource_kwargs"] == {
-            "block": f"block_{block_letter}",
+            "internal_path": dataset_name,
             "multiplier": 1,
-            "name": data_key_name,
-            "path": f"BLOCK_{block_letter.upper()}-TEST-{data_key_name.split('-')[-1]}",
             "timestamps": "/entry/instrument/NDAttributes/NDArrayTimeStamp",
         }