Merge pull request #28 from ISISComputingGroup/20_user_facing_dae

20 user facing dae

doc/devices/dae.md

@@ -1,9 +1,252 @@
-# DAE
+# DAE (Data Acquisition Electronics)
 
-## DaeBase (base class)
+The `SimpleDae` class is designed to be a configurable DAE object, which will cover the
+majority of DAE use-cases within bluesky.
+
+This class uses several objects to configure its behaviour:
+- The `Controller` is responsible for beginning and ending acquisitions.
+- The `Waiter` is responsible for waiting for an acquisition to be "complete".
+- The `Reducer` is responsible for publishing data from an acquisition that has 
+  just been completed.
+
+This means that `SimpleDae` is generic enough to cope with most typical DAE use-casess, for
+example running using either one DAE run per scan point, or one DAE period per scan point.
+
+For complex use-cases, particularly those where the DAE may need to start and stop multiple 
+acquisitions per scan point (e.g. polarization measurements), `SimpleDae` is unlikely to be 
+suitable; instead the `Dae` class should be subclassed directly to allow for finer control.
+
+## Example configurations
+
+### Run-per-point
+
+```python
+from ibex_bluesky_core.devices import get_pv_prefix
+from ibex_bluesky_core.devices.simpledae import SimpleDae
+from ibex_bluesky_core.devices.simpledae.controllers import RunPerPointController
+from ibex_bluesky_core.devices.simpledae.waiters import GoodFramesWaiter
+from ibex_bluesky_core.devices.simpledae.reducers import GoodFramesNormalizer
+
+
+prefix = get_pv_prefix()
+# One DAE run for each scan point, save the runs after each point.
+controller = RunPerPointController(save_run=True)
+# Wait for 500 good frames on each run
+waiter = GoodFramesWaiter(500)
+# Sum spectra 1..99 inclusive, then normalize by total good frames
+reducer = GoodFramesNormalizer(
+    prefix=prefix,
+    detector_spectra=[i for i in range(1, 100)],
+)
+
+dae = SimpleDae(
+    prefix=prefix,
+    controller=controller,
+    waiter=waiter,
+    reducer=reducer,
+)
+
+# Can give signals user-friendly names if desired
+controller.run_number.set_name("run number")
+reducer.intensity.set_name("normalized counts")
+```
+
+### Period-per-point
+
+```python
+from ibex_bluesky_core.devices import get_pv_prefix
+from ibex_bluesky_core.devices.simpledae import SimpleDae
+from ibex_bluesky_core.devices.simpledae.controllers import PeriodPerPointController
+from ibex_bluesky_core.devices.simpledae.waiters import PeriodGoodFramesWaiter
+from ibex_bluesky_core.devices.simpledae.reducers import PeriodGoodFramesNormalizer
+
+
+prefix = get_pv_prefix()
+# One DAE period for each scan point, save the runs after the scan.
+controller = PeriodPerPointController(save_run=True)
+# Wait for 500 period good frames on each point
+waiter = PeriodGoodFramesWaiter(500)
+# Sum spectra 1..99 inclusive, then normalize by period good frames
+reducer = PeriodGoodFramesNormalizer(
+    prefix=prefix,
+    detector_spectra=[i for i in range(1, 100)],
+)
+
+dae = SimpleDae(
+    prefix=prefix,
+    controller=controller,
+    waiter=waiter,
+    reducer=reducer,
+)
+```
+
+```{note}
+You will also need to set up the DAE in advance with enough periods. This can be done from a
+plan using `yield from bps.mv(dae.number_of_periods, num_points)` before starting the scan.
+```
+
+## Mapping to bluesky device model
+
+### Start of scan (`stage`)
+
+`SimpleDae` will call `controller.setup()` to allow any pre-scan setup to be done.
+
+For example, this is where the period-per-point controller object will begin a DAE run.
+
+### Each scan point (`trigger`)
+
+`SimpleDae` will call:
+- `controller.start_counting()` to begin counting for a single scan point.
+- `waiter.wait()` to wait for that acquisition to complete
+- `controller.stop_counting()` to finish counting for a single scan point.
+- `reducer.reduce_data()` to do any necessary post-processing on 
+  the raw DAE data (e.g. normalization)
+
+### Each scan point (`read`)
+
+Any signals marked as "interesting" by the controller, reducer or waiter will be published
+in the top-level documents published when `read()`ing the `SimpleDae` object.
+
+These may correspond to EPICS signals directly from the DAE (e.g. good frames), or may be 
+soft signals derived at runtime (e.g. normalized intensity).
+
+This means that the `SimpleDae` object is suitable for use as a detector in most bluesky
+plans, and will make an appropriate set of data available in the emitted documents.
+
+### End of scan (`unstage`)
+
+`SimpleDae` will call `controller.teardown()` to allow any post-scan teardown to be done.
+
+For example, this is where the period-per-point controller object will end a DAE run.
+
+## Controllers
+
+The `Controller` class is responsible for starting and stopping acquisitions, in a generic
+way.
+
+### RunPerPointController
+
+This controller starts and stops a new DAE run for each scan point. It can be configured to 
+either end runs or abort them on completion.
+
+This controller causes the following signals to be published by `SimpleDae`:
+
+- `controller.run_number` - The run number into which data was collected. Only published 
+  if runs are being saved.
+
+### PeriodPerPointController
+
+This controller begins a single DAE run at the start of a scan, and then counts into a new
+DAE period for each individual scan point.
+
+The DAE must be configured with enough periods in advance. This is possible to do from a
+plan as follows:
+
+```python
+import bluesky.plan_stubs as bps
+import bluesky.plans as bp
+from ibex_bluesky_core.devices.simpledae import SimpleDae
+from ibex_bluesky_core.devices.block import BlockRw
+
+
+def plan():
+    dae: SimpleDae = ...
+    block: BlockRw = ...
+    num_points = 20
+    yield from bps.mv(dae.number_of_periods, num_points)
+    yield from bp.scan([dae], block, 0, 10, num=num_points)
+```
+
+The controller causes the following signals to be published by `SimpleDae`:
+
+- `simpledae.period_num` - the period number into which this scan point was counted.
+
+## Reducers
+
+A `Reducer` for a `SimpleDae` is responsible for publishing any data derived from the raw
+DAE signals. For example, normalizing intensities are implemented as a reducer.
+
+A reducer may produce any number of reduced signals.
+
+### GoodFramesNormalizer
+
+This normalizer sums a set of user-defined detector spectra, and then divides by the number
+of good frames.
+
+Published signals:
+- `simpledae.good_frames` - the number of good frames reported by the DAE
+- `reducer.det_counts` - summed detector counts for all of the user-provided spectra
+- `reducer.intensity` - normalized intensity (`det_counts / good_frames`)
+
+### PeriodGoodFramesNormalizer
+
+Equivalent to the `GoodFramesNormalizer` above, but uses good frames only from the current
+period. This should be used if a controller which counts into multiple periods is being used.
+
+Published signals:
+- `simpledae.period.good_frames` - the number of good frames reported by the DAE
+- `reducer.det_counts` - summed detector counts for all of the user-provided spectra
+- `reducer.intensity` - normalized intensity (`det_counts / good_frames`)
+
+### DetectorMonitorNormalizer
+
+This normalizer sums a set of user-defined detector spectra, and then divides by the sum
+of a set of user-defined monitor spectra.
+
+Published signals:
+- `reducer.det_counts` - summed detector counts for the user-provided detector spectra
+- `reducer.mon_counts` - summed monitor counts for the user-provided monitor spectra
+- `reducer.intensity` - normalized intensity (`det_counts / mon_counts`)
+
+## Waiters
+
+A `waiter` defines an arbitrary strategy for how long to count at each point.
+
+Some waiters may be very simple, such as waiting for a fixed amount of time or for a number
+of good frames or microamp-hours. However, it is also possible to define much more 
+sophisticated waiters, for example waiting until sufficient statistics have been collected.
+
+### GoodUahWaiter
+
+Waits for a user-specified number of microamp-hours.
+
+Published signals:
+- `simpledae.good_uah` - actual good uAh for this run.
+
+### GoodFramesWaiter
+
+Waits for a user-specified number of good frames (in total for the entire run)
+
+Published signals:
+- `simpledae.good_frames` - actual good frames for this run.
+
+### GoodFramesWaiter
+
+Waits for a user-specified number of good frames (in the current period)
+
+Published signals:
+- `simpledae.period.good_frames` - actual period good frames for this run.
+
+### MEventsWaiter
+
+Waits for a user-specified number of millions of events
+
+Published signals:
+- `simpledae.m_events` - actual period good frames for this run.
+
+### TimeWaiter
+
+Waits for a user-specified time duration, irrespective of DAE state.
+
+Does not publish any additional signals.
+
+---
+
+## `Dae` (base class, advanced)
 
 `Dae` is the principal class in ibex_bluesky_core which exposes configuration settings
-and controls from the ISIS data acquisition electronics (DAE).
+and controls from the ISIS data acquisition electronics (DAE). `SimpleDae` derives from
+DAE, so all of the signals available on `Dae` are also available on `SimpleDae`.
 
 ```{note}
  The `Dae` class is not intended to be used directly in scans - it is a low-level class
@@ -16,11 +259,11 @@ and controls from the ISIS data acquisition electronics (DAE).
    that it will usually be better to implement functionality at the device level rather 
    than the plan level.
  
- For other use-cases, a user-facing DAE class is likely to be more appropriate to use
- as a detector in a scan - this class cannot be used by itself.
+ For other use-cases, a user-facing DAE class such as `SimpleDae` is likely to be more 
+ appropriate to use as a detector in a scan - this class cannot be used by itself.
 ```
 
-## Top-level signals
+### Top-level signals
 
 Some DAE parameters, particularly metadata parameters, are exposed as simple signals, 
 for example `dae.title` or `dae.good_uah`.
@@ -36,13 +279,13 @@ def plan(dae: Dae):
     yield from bps.mv(dae.title, "new title")
 ```
 
-## Period-specific signals
+### Period-specific signals
 
 For signals which apply to the current period, see `dae.period`, which contains signals
 such as `dae.period.good_uah` (the number of good uamp-hours collected in the current period).
 
 
-## Controlling the DAE directly
+### Controlling the DAE directly
 
 It is possible to control the DAE directly using the signals provided by `dae.controls`.
 
@@ -51,7 +294,7 @@ used by plans directly.
 
 For example, beginning a run is possible via `dae.controls.begin_run.trigger()`.
 
-### Advanced options
+### Additional begin_run flags
 
 Options on `begin` (for example, beginning a run in paused mode) can be specified
 using the `dae.controls.begin_run_ex` signal.
@@ -60,7 +303,7 @@ Unlike the standard `begin_run` signal, this needs to be `set()` rather than sim
 `trigger()`ed, the value on set is a combination of flags from `BeginRunExBits`.
 
 
-## DAE Settings
+### DAE Settings
 
 Many signals on the DAE are only available as composite signals - this includes most DAE 
 configuration parameters which are available under the "experiment setup" tab in IBEX, for
@@ -95,7 +338,7 @@ def plan(dae: Dae):
 ```
 
 
-## DAE Spectra
+### DAE Spectra
 
 Raw spectra are provided by the `DaeSpectra` class. Not all spectra are automatically available
 on the base DAE object - user classes will define the specific set of spectra which they are

pyproject.toml

@@ -44,7 +44,8 @@ dependencies = [
   "bluesky",
   "ophyd-async[ca]",
   "matplotlib",
-  "numpy"
+  "numpy",
+  "scipp",
 ]
 
 [project.optional-dependencies]
@@ -83,6 +84,12 @@ omit = [
 
 [tool.coverage.report]
 fail_under = 100
+exclude_lines = [
+  "pragma: no cover",
+  "if TYPE_CHECKING:",
+  "if typing.TYPE_CHECKING:",
+  "@abstractmethod",
+]
 
 [tool.coverage.html]
 directory = "coverage_html_report"