"""Module which defines abstract classes to work with detectors"""
import asyncio
import time
from abc import ABC, abstractmethod
from collections.abc import AsyncGenerator, AsyncIterator, Callable, Iterator, Sequence
from enum import Enum
from functools import cached_property
from typing import (
Generic,
)
from bluesky.protocols import (
Collectable,
Flyable,
Preparable,
Reading,
Stageable,
StreamAsset,
Triggerable,
WritesStreamAssets,
)
from event_model import DataKey
from pydantic import BaseModel, Field, NonNegativeInt, computed_field
from ._device import Device
from ._protocol import AsyncConfigurable, AsyncReadable
from ._signal import SignalR
from ._status import AsyncStatus, WatchableAsyncStatus
from ._utils import DEFAULT_TIMEOUT, T, WatcherUpdate, merge_gathered_dicts
[docs]
class DetectorTrigger(str, Enum):
"""Type of mechanism for triggering a detector to take frames"""
#: Detector generates internal trigger for given rate
internal = "internal"
#: Expect a series of arbitrary length trigger signals
edge_trigger = "edge_trigger"
#: Expect a series of constant width external gate signals
constant_gate = "constant_gate"
#: Expect a series of variable width external gate signals
variable_gate = "variable_gate"
[docs]
class TriggerInfo(BaseModel):
"""Minimal set of information required to setup triggering on a detector"""
#: Number of triggers that will be sent, (0 means infinite) Can be:
# - A single integer or
# - A list of integers for multiple triggers
# Example for tomography: TriggerInfo(number=[2,3,100,3])
#: This would trigger:
#: - 2 times for dark field images
#: - 3 times for initial flat field images
#: - 100 times for projections
#: - 3 times for final flat field images
number_of_triggers: NonNegativeInt | list[NonNegativeInt]
#: Sort of triggers that will be sent
trigger: DetectorTrigger = Field(default=DetectorTrigger.internal)
#: What is the minimum deadtime between triggers
deadtime: float | None = Field(default=None, ge=0)
#: What is the maximum high time of the triggers
livetime: float | None = Field(default=None, ge=0)
#: What is the maximum timeout on waiting for a frame
frame_timeout: float | None = Field(default=None, gt=0)
#: How many triggers make up a single StreamDatum index, to allow multiple frames
#: from a faster detector to be zipped with a single frame from a slow detector
#: e.g. if num=10 and multiplier=5 then the detector will take 10 frames,
#: but publish 2 indices, and describe() will show a shape of (5, h, w)
multiplier: int = 1
@computed_field
@cached_property
def total_number_of_triggers(self) -> int:
return (
sum(self.number_of_triggers)
if isinstance(self.number_of_triggers, list)
else self.number_of_triggers
)
[docs]
class DetectorController(ABC):
"""
Classes implementing this interface should hold the logic for
arming and disarming a detector
"""
[docs]
@abstractmethod
def get_deadtime(self, exposure: float | None) -> float:
"""For a given exposure, how long should the time between exposures be"""
[docs]
@abstractmethod
async def prepare(self, trigger_info: TriggerInfo):
"""
Do all necessary steps to prepare the detector for triggers.
Args:
trigger_info: This is a Pydantic model which contains
number Expected number of frames.
trigger Type of trigger for which to prepare the detector. Defaults
to DetectorTrigger.internal.
livetime Livetime / Exposure time with which to set up the detector.
Defaults to None
if not applicable or the detector is expected to use its previously-set
exposure time.
deadtime Defaults to None. This is the minimum deadtime between
triggers.
multiplier The number of triggers grouped into a single StreamDatum
index.
"""
[docs]
@abstractmethod
async def arm(self) -> None:
"""
Arm the detector
"""
[docs]
@abstractmethod
async def wait_for_idle(self):
"""
This will wait on the internal _arm_status and wait for it to get disarmed/idle
"""
[docs]
@abstractmethod
async def disarm(self):
"""Disarm the detector, return detector to an idle state"""
[docs]
class DetectorWriter(ABC):
"""Logic for making a detector write data to somewhere persistent
(e.g. an HDF5 file)"""
[docs]
@abstractmethod
async def open(self, multiplier: int = 1) -> dict[str, DataKey]:
"""Open writer and wait for it to be ready for data.
Args:
multiplier: Each StreamDatum index corresponds to this many
written exposures
Returns:
Output for ``describe()``
"""
[docs]
@abstractmethod
def observe_indices_written(
self, timeout=DEFAULT_TIMEOUT
) -> AsyncGenerator[int, None]:
"""Yield the index of each frame (or equivalent data point) as it is written"""
[docs]
@abstractmethod
async def get_indices_written(self) -> int:
"""Get the number of indices written"""
[docs]
@abstractmethod
def collect_stream_docs(self, indices_written: int) -> AsyncIterator[StreamAsset]:
"""Create Stream docs up to given number written"""
[docs]
@abstractmethod
async def close(self) -> None:
"""Close writer, blocks until I/O is complete"""
[docs]
class StandardDetector(
Device,
Stageable,
AsyncConfigurable,
AsyncReadable,
Triggerable,
Preparable,
Flyable,
Collectable,
WritesStreamAssets,
Generic[T],
):
"""
Useful detector base class for step and fly scanning detectors.
Aggregates controller and writer logic together.
"""
def __init__(
self,
controller: DetectorController,
writer: DetectorWriter,
config_sigs: Sequence[SignalR] = (),
name: str = "",
) -> None:
"""
Constructor
Args:
controller: Logic for arming and disarming the detector
writer: Logic for making the detector write persistent data
config_sigs: Signals to read when describe and read
configuration are called. Defaults to ().
name: Device name. Defaults to "".
"""
self._controller = controller
self._writer = writer
self._describe: dict[str, DataKey] = {}
self._config_sigs = list(config_sigs)
# For prepare
self._arm_status: AsyncStatus | None = None
self._trigger_info: TriggerInfo | None = None
# For kickoff
self._watchers: list[Callable] = []
self._fly_status: WatchableAsyncStatus | None = None
self._fly_start: float | None = None
self._frames_to_complete: int = 0
# Represents the total number of frames that will have been completed at the
# end of the next `complete`.
self._completable_frames: int = 0
self._number_of_triggers_iter: Iterator[int] | None = None
self._initial_frame: int = 0
super().__init__(name)
@property
def controller(self) -> DetectorController:
return self._controller
@property
def writer(self) -> DetectorWriter:
return self._writer
@AsyncStatus.wrap
async def stage(self) -> None:
# Disarm the detector, stop file writing.
await self._check_config_sigs()
await asyncio.gather(self.writer.close(), self.controller.disarm())
self._trigger_info = None
async def _check_config_sigs(self):
"""Checks configuration signals are named and connected."""
for signal in self._config_sigs:
if signal.name == "":
raise Exception(
"config signal must be named before it is passed to the detector"
)
try:
await signal.get_value()
except NotImplementedError as e:
raise Exception(
f"config signal {signal.name} must be connected before it is "
+ "passed to the detector"
) from e
@AsyncStatus.wrap
async def unstage(self) -> None:
# Stop data writing.
await asyncio.gather(self.writer.close(), self.controller.disarm())
async def read_configuration(self) -> dict[str, Reading]:
return await merge_gathered_dicts(sig.read() for sig in self._config_sigs)
async def describe_configuration(self) -> dict[str, DataKey]:
return await merge_gathered_dicts(sig.describe() for sig in self._config_sigs)
async def read(self) -> dict[str, Reading]:
# All data is in StreamResources, not Events, so nothing to output here
return {}
async def describe(self) -> dict[str, DataKey]:
return self._describe
@AsyncStatus.wrap
async def trigger(self) -> None:
if self._trigger_info is None:
await self.prepare(
TriggerInfo(
number_of_triggers=1,
trigger=DetectorTrigger.internal,
deadtime=None,
livetime=None,
frame_timeout=None,
)
)
assert self._trigger_info
assert self._trigger_info.trigger is DetectorTrigger.internal
# Arm the detector and wait for it to finish.
indices_written = await self.writer.get_indices_written()
await self.controller.arm()
await self.controller.wait_for_idle()
end_observation = indices_written + 1
async for index in self.writer.observe_indices_written(
DEFAULT_TIMEOUT
+ (self._trigger_info.livetime or 0)
+ (self._trigger_info.deadtime or 0)
):
if index >= end_observation:
break
[docs]
@AsyncStatus.wrap
async def prepare(self, value: TriggerInfo) -> None:
"""
Arm detector.
Prepare the detector with trigger information. This is determined at and passed
in from the plan level.
This currently only prepares detectors for flyscans and stepscans just use the
trigger information determined in trigger.
To do: Unify prepare to be use for both fly and step scans.
Args:
value: TriggerInfo describing how to trigger the detector
"""
if value.trigger != DetectorTrigger.internal:
assert (
value.deadtime
), "Deadtime must be supplied when in externally triggered mode"
if value.deadtime:
required = self.controller.get_deadtime(value.livetime)
assert required <= value.deadtime, (
f"Detector {self.controller} needs at least {required}s deadtime, "
f"but trigger logic provides only {value.deadtime}s"
)
self._trigger_info = value
self._number_of_triggers_iter = iter(
self._trigger_info.number_of_triggers
if isinstance(self._trigger_info.number_of_triggers, list)
else [self._trigger_info.number_of_triggers]
)
self._initial_frame = await self.writer.get_indices_written()
self._describe, _ = await asyncio.gather(
self.writer.open(value.multiplier), self.controller.prepare(value)
)
if value.trigger != DetectorTrigger.internal:
await self.controller.arm()
self._fly_start = time.monotonic()
@AsyncStatus.wrap
async def kickoff(self):
if self._trigger_info is None or self._number_of_triggers_iter is None:
raise RuntimeError("Prepare must be called before kickoff!")
try:
self._frames_to_complete = next(self._number_of_triggers_iter)
self._completable_frames += self._frames_to_complete
except StopIteration as err:
raise RuntimeError(
f"Kickoff called more than the configured number of "
f"{self._trigger_info.total_number_of_triggers} iteration(s)!"
) from err
@WatchableAsyncStatus.wrap
async def complete(self):
assert self._trigger_info
indices_written = self.writer.observe_indices_written(
self._trigger_info.frame_timeout
or (
DEFAULT_TIMEOUT
+ (self._trigger_info.livetime or 0)
+ (self._trigger_info.deadtime or 0)
)
)
try:
async for index in indices_written:
yield WatcherUpdate(
name=self.name,
current=index,
initial=self._initial_frame,
target=self._frames_to_complete,
unit="",
precision=0,
time_elapsed=time.monotonic() - self._fly_start
if self._fly_start
else None,
)
if index >= self._frames_to_complete:
break
finally:
await indices_written.aclose()
if self._completable_frames >= self._trigger_info.total_number_of_triggers:
self._completable_frames = 0
self._frames_to_complete = 0
self._number_of_triggers_iter = None
await self.controller.wait_for_idle()
async def describe_collect(self) -> dict[str, DataKey]:
return self._describe
async def collect_asset_docs(
self, index: int | None = None
) -> AsyncIterator[StreamAsset]:
# Collect stream datum documents for all indices written.
# The index is optional, and provided for fly scans, however this needs to be
# retrieved for step scans.
if index is None:
index = await self.writer.get_indices_written()
async for doc in self.writer.collect_stream_docs(index):
yield doc
async def get_index(self) -> int:
return await self.writer.get_indices_written()
