Merge pull request #418 from European-XFEL/rm-lpd-mini

Remove LPD Mini component class (pending redesign)

docs/agipd_lpd_data.rst

@@ -27,10 +27,6 @@ DSSC and JUNGFRAU, pulling together the separate modules into a single array.
 
  The methods of this class are identical to those of :class:`LPD1M`, below.
 
-.. autoclass:: LPDMini
-
- The methods of this class are identical to those of :class:`LPD1M:, below.
-
 .. autoclass:: LPD1M
 
  .. automethod:: get_array

docs/lpd_data.ipynb

@@ -292,14 +292,6 @@
  "source": [
  "LPD data may also be recorded in *parallel gain* mode, resulting in high-, medium- and low-gain frames for each pulse. To read this kind of data with the correct labels, use `LPD1M(run, parallel_gain=True)`. This will retrieve data with an extra gain dimension, labelled with 0, 1 and 2 for high-, medium- and low-gain respectively."
  ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "The LPD Mini consists of a single module. \n",
- "Its data can be accessed similarly using the `LPDMini` class."
- ]
  }
  ],
  "metadata": {

extra_data/components.py

@@ -19,7 +19,6 @@
  'AGIPD500K',
  'DSSC1M',
  'LPD1M',
- 'LPDMini',
  'JUNGFRAU',
  'identify_multimod_detectors',
 ]
@@ -1430,8 +1429,30 @@ class DSSC1M(XtdfDetectorBase):
  module_shape = (128, 512)
 
 
-class LPDBase:
- """Base LPD class supporting parallel gain mode."""
+@multimod_detectors
+class LPD1M(XtdfDetectorBase):
+ """An interface to LPD-1M data.
+
+ Parameters
+ ----------
+ data: DataCollection
+ A data collection, e.g. from :func:`.RunDirectory`.
+ modules: set of ints, optional
+ Detector module numbers to use. By default, all available modules
+ are used.
+ detector_name: str, optional
+ Name of a detector, e.g. 'FXE_DET_LPD1M-1'. This is only needed
+ if the dataset includes more than one LPD detector.
+ min_modules: int
+ Include trains where at least n modules have data. Default is 1.
+ parallel_gain: bool
+ Set to True to read this data as parallel gain data, where high, medium
+ and low gain data are stored sequentially within each train. This will
+ repeat the pulse & cell IDs from the first 1/3 of each train, and add gain
+ stage labels from 0 (high-gain) to 2 (low-gain).
+ """
+ _source_re = re.compile(r'(?P<detname>.+_LPD1M.*)/DET/(?P<modno>\d+)CH')
+ module_shape = (256, 256)
 
  def __init__(self, data: DataCollection, detector_name=None, modules=None,
  *, min_modules=1, parallel_gain=False):
@@ -1515,56 +1536,6 @@ def _make_image_index(self, tids, inner_ids, inner_name='pulse'):
  )
 
 
-@multimod_detectors
-class LPD1M(LPDBase, XtdfDetectorBase):
- """An interface to LPD-1M data.
-
- Parameters
- ----------
- data: DataCollection
- A data collection, e.g. from :func:`.RunDirectory`.
- modules: set of ints, optional
- Detector module numbers to use. By default, all available modules
- are used.
- detector_name: str, optional
- Name of a detector, e.g. 'FXE_DET_LPD1M-1'. This is only needed
- if the dataset includes more than one LPD detector.
- min_modules: int
- Include trains where at least n modules have data. Default is 1.
- parallel_gain: bool
- Set to True to read this data as parallel gain data, where high, medium
- and low gain data are stored sequentially within each train. This will
- repeat the pulse & cell IDs from the first 1/3 of each train, and add gain
- stage labels from 0 (high-gain) to 2 (low-gain).
- """
- _source_re = re.compile(r'(?P<detname>.+_LPD1M.*)/DET/(?P<modno>\d+)CH')
- module_shape = (256, 256)
-
-
-@multimod_detectors
-class LPDMini(LPDBase, XtdfDetectorBase):
- """An interface to LPD-Mini data.
-
- Parameters
- ----------
- data: DataCollection
- A data collection, e.g. from :func:`.RunDirectory`.
- modules: set of ints, optional
- Detector module numbers to use. By default, all available modules
- are used.
- detector_name: str, optional
- Name of a detector, e.g. 'FXE_DET_LPD_MINI'. This is only needed
- if the dataset includes more than one LPD detector.
- parallel_gain: bool
- Set to True to read this data as parallel gain data, where high, medium
- and low gain data are stored sequentially within each train. This will
- repeat the pulse & cell IDs from the first 1/3 of each train, and add gain
- stage labels from 0 (high-gain) to 2 (low-gain).
- """
- _source_re = re.compile(r'(?P<detname>.+_LPD_MINI.*)/DET/(?P<modno>\d+)CH')
- module_shape = (256, 256)
-
-
 @multimod_detectors
 class JUNGFRAU(MultimodDetectorBase):
  """An interface to JUNGFRAU data.

extra_data/tests/make_examples.py

@@ -242,11 +242,6 @@ def make_fxe_run(dir_path, raw=True, format_version='0.5'):
  frames_per_train=128)
  ], ntrains=480, chunksize=32, format_version=format_version)
 
- path = osp.join(dir_path, f'{prefix}-R0450-LPDMINI00-S00000.h5')
- write_file(path, [
- LPDModule('FXE_DET_LPD_MINI/DET/0CH0', raw=raw, frames_per_train=128)
- ], ntrains=480, chunksize=32, format_version=format_version)
-
  if not raw:
  return
  write_file(osp.join(dir_path, 'RAW-R0450-DA01-S00000.h5'), [
@@ -273,10 +268,6 @@ def make_lpd_parallelgain_run(dir_path, raw=True, format_version='0.5'):
  frames_per_train=300)
  ], ntrains=100, chunksize=32, format_version=format_version)
 
- path = osp.join(dir_path, f'{prefix}-R0450-LPDMINI00-S00000.h5')
- write_file(path, [
- LPDModule('FXE_DET_LPD_MINI/DET/0CH0', raw=raw, frames_per_train=300)
- ], ntrains=100, chunksize=32, format_version=format_version)
 
 def make_lpd_run_mini_missed_train(dir_path):
  write_file(osp.join(dir_path, 'RAW-R0450-LPD00-S00000.h5'), [

extra_data/tests/test_components.py

@@ -7,7 +7,7 @@
 
 from extra_data.reader import RunDirectory, H5File, by_id, by_index
 from extra_data.components import (
- AGIPD1M, DSSC1M, LPD1M, LPDMini, JUNGFRAU, identify_multimod_detectors,
+ AGIPD1M, DSSC1M, LPD1M, JUNGFRAU, identify_multimod_detectors,
 )
 
 
@@ -179,17 +179,6 @@ def test_get_array_lpd_parallelgain(mock_lpd_parallelgain_run):
  np.testing.assert_array_equal(arr.coords['gain'], np.arange(3))
  np.testing.assert_array_equal(arr.coords['pulse'], np.arange(100))
 
- run = RunDirectory(mock_lpd_parallelgain_run)
- det = LPDMini(run.select_trains(by_index[:2]), parallel_gain=True)
- assert det.detector_name == 'FXE_DET_LPD_MINI'
-
- arr = det.get_array('image.data')
- assert arr.shape == (1, 2, 3, 100, 256, 256)
- assert arr.dims == ('module', 'train', 'gain', 'pulse', 'slow_scan', 'fast_scan')
- np.testing.assert_array_equal(arr.coords['gain'], np.arange(3))
- np.testing.assert_array_equal(arr.coords['pulse'], np.arange(100))
-
-
 
 def test_get_array_lpd_parallelgain_select_pulses(mock_lpd_parallelgain_run):
  run = RunDirectory(mock_lpd_parallelgain_run)
@@ -206,20 +195,6 @@ def test_get_array_lpd_parallelgain_select_pulses(mock_lpd_parallelgain_run):
  assert arr.shape == (16, 2, 3, 5, 256, 256)
  np.testing.assert_array_equal(arr.coords['pulse'], np.arange(5))
 
- run = RunDirectory(mock_lpd_parallelgain_run)
- det = LPDMini(run.select_trains(by_index[:2]), parallel_gain=True)
- assert det.detector_name == 'FXE_DET_LPD_MINI'
-
- arr = det.get_array('image.data', pulses=np.s_[:5])
- assert arr.shape == (1, 2, 3, 5, 256, 256)
- assert arr.dims == ('module', 'train', 'gain', 'pulse', 'slow_scan', 'fast_scan')
- np.testing.assert_array_equal(arr.coords['gain'], np.arange(3))
- np.testing.assert_array_equal(arr.coords['pulse'], np.arange(5))
-
- arr = det.get_array('image.data', pulses=by_id[:5])
- assert arr.shape == (1, 2, 3, 5, 256, 256)
- np.testing.assert_array_equal(arr.coords['pulse'], np.arange(5))
-
 
 def test_get_array_jungfrau(mock_jungfrau_run):
  run = RunDirectory(mock_jungfrau_run)
@@ -609,7 +584,7 @@ def test_write_selected_frames_proc(mock_spb_proc_run, tmp_path):
  test_file.unlink()
 
 def test_identify_multimod_detectors(mock_fxe_raw_run):
- run = RunDirectory(mock_fxe_raw_run, include='*LPD[!MINI]*')
+ run = RunDirectory(mock_fxe_raw_run)
  name, cls = identify_multimod_detectors(run, single=True)
  assert name == 'FXE_DET_LPD1M-1'
  assert cls is LPD1M

extra_data/tests/test_reader_mockdata.py

@@ -161,7 +161,7 @@ def test_iterate_trains_require_all(mock_sa3_control_data):
 
 def test_read_fxe_raw_run(mock_fxe_raw_run):
  run = RunDirectory(mock_fxe_raw_run)
- assert len(run.files) == 19 # 16 LPD 1M, 1 LPD Minimodules + 2 control data files
+ assert len(run.files) == 18 # 16 LPD 1M + 2 control data files
  assert run.train_ids == list(range(10000, 10480))
  run.info() # Smoke test
 

extra_data/tests/test_streamer.py

@@ -11,7 +11,7 @@
 
 
 def test_merge_detector(mock_fxe_raw_run, mock_fxe_control_data, mock_spb_proc_run):
- with RunDirectory(mock_fxe_raw_run, include="*LPD[!MINI]*") as run:
+ with RunDirectory(mock_fxe_raw_run) as run:
  for tid, data in _iter_trains(run, merge_detector=True):
  assert 'FXE_DET_LPD1M-1/DET/APPEND' in data
  assert 'FXE_DET_LPD1M-1/DET/0CH0:xtdf' not in data