def test_write_virtual(mock_fxe_raw_run):
with TemporaryDirectory() as td:
new_file = osp.join(td, 'test.h5')
with RunDirectory(mock_fxe_raw_run) as run:
run.write_virtual(new_file)
assert_isfile(new_file)
with h5py.File(new_file) as f:
ds = f['CONTROL/SPB_XTD9_XGM/DOOCS/MAIN/beamPosition/ixPos/value']
assert ds.is_virtual
with H5File(new_file) as f:
np.testing.assert_array_equal(
f.train_ids, np.arange(10000, 10480, dtype=np.uint64))
assert 'SPB_XTD9_XGM/DOOCS/MAIN' in f.control_sources
assert 'SPB_XTD9_XGM/DOOCS/MAIN:output' in f.instrument_sources
s = f.get_series('SPB_XTD9_XGM/DOOCS/MAIN',
'beamPosition.ixPos.value')
# This should have concatenated the two sequence files (400 + 80)
assert len(s) == 480
a = f.get_array('SPB_XTD9_XGM/DOOCS/MAIN:output',
'data.intensityTD')
assert a.shape == (480, 1000)
def test_iterate_trains(mock_agipd_data):
with H5File(mock_agipd_data) as f:
for train_id, data in islice(f.trains(), 10):
assert train_id in range(10000, 10250)
assert 'SPB_DET_AGIPD1M-1/DET/7CH0:xtdf' in data.keys()
assert len(data) == 1
assert 'image.data' in data['SPB_DET_AGIPD1M-1/DET/7CH0:xtdf']
def test_iterate_trains_fxe(mock_fxe_control_data):
with H5File(mock_fxe_control_data) as f:
for train_id, data in islice(f.trains(), 10):
assert train_id in range(10000, 10400)
assert 'SA1_XTD2_XGM/DOOCS/MAIN' in data.keys()
assert 'beamPosition.ixPos.value' in data[
'SA1_XTD2_XGM/DOOCS/MAIN']
def test_iterate_file_select_trains(mock_fxe_control_data):
with H5File(mock_fxe_control_data) as f:
tids = [tid for (tid, _) in f.trains(train_range=by_id[:10003])]
assert tids == [10000, 10001, 10002]
tids = [tid for (tid, _) in f.trains(train_range=by_index[-2:])]
assert tids == [10398, 10399]
def test_filter_device():
dev_filter_1 = {
'SPB_XTD9_XGM/XGM/DOOCS':
{'pulseEnergy.pulseEnergy.value', 'current.right.output.value'}
}
dev_filter_2 = {''}
dev_filter_3 = {
'SPB_XTD9_XGM/XGM/DOOCS': {},
'SA1_XTD2_XGM/XGM/DOOCS': {'pulseEnergy.pulseEnergy.value'}
}
with H5File(RUNPATH_SLOW + '/RAW-R0115-DA01-S00000.h5') as f:
_, data = f.train_from_index(500, devices=dev_filter_1)
assert len(data) == 1
assert 'SPB_XTD9_XGM/XGM/DOOCS' in data
xgm = data['SPB_XTD9_XGM/XGM/DOOCS']
assert len(xgm) == 3 # metadata, pulseEnergy, current
assert 'pulseEnergy.pulseEnergy.value' in xgm
# assert xgm['pulseEnergy.pulseEnergy.value'] == approx(0.06392462, rel=1e-7)
# assert xgm['current.right.output.value'] == approx(-7.968561e-15, rel=1e-6)
_, data = f.train_from_index(0, devices=dev_filter_2)
assert len(data) == 0
_, data = f.train_from_index(0, devices=dev_filter_3)
assert len(data) == 2
assert len(data['SPB_XTD9_XGM/XGM/DOOCS']) == 77
assert len(data['SA1_XTD2_XGM/XGM/DOOCS']) == 2
def test_iterate_trains():
with H5File(FILEPATH) as f:
for train_id, data in f.trains():
print(train_id)
assert train_id in range(1455918683, 1455918703)
assert 'FXE_DET_LPD1M-1/DET/0CH0:xtdf' in data.keys()
assert len(data) == 1
assert len(data['FXE_DET_LPD1M-1/DET/0CH0:xtdf']) == 21
def test_get_train_per_index():
with H5File(FILEPATH) as f:
train, data = f.train_from_index(0)
assert data is not None
assert train == 1455918683
with pytest.raises(ValueError) as info:
data, _, _ = f.train_from_index(20) # index out of range
print(info)
def test_file_get_array(mock_fxe_control_data):
with H5File(mock_fxe_control_data) as f:
arr = f.get_array('FXE_XAD_GEC/CAM/CAMERA:daqOutput',
'data.image.pixels')
assert isinstance(arr, DataArray)
assert arr.dims == ('trainId', 'dim_0', 'dim_1')
assert arr.shape == (400, 255, 1024)
assert arr.coords['trainId'][0] == 10000
def test_lsxfel_file(mock_lpd_data, capsys):
with H5File(mock_lpd_data) as f:
img_ds, index = lsxfel.find_image(f)
assert img_ds.ndim == 4
assert index['first'].shape == (480, )
lsxfel.summarise_file(mock_lpd_data)
out, err = capsys.readouterr()
assert "480 trains, 128 frames/train" in out
def test_read_metadata():
with H5File(FILEPATH) as f:
_, data1 = f.train_from_index(0)
sleep(2)
_, data2 = f.train_from_index(0)
assert 'metadata' in data1['FXE_DET_LPD1M-1/DET/0CH0:xtdf']
assert data1['FXE_DET_LPD1M-1/DET/0CH0:xtdf']['metadata']['timestamp']['tid'] == 1455918683
assert data1['FXE_DET_LPD1M-1/DET/0CH0:xtdf']['metadata']['timestamp']['sec'] != data2['FXE_DET_LPD1M-1/DET/0CH0:xtdf']['metadata']['timestamp']['sec']
assert data1['FXE_DET_LPD1M-1/DET/0CH0:xtdf']['metadata']['source'] == 'FXE_DET_LPD1M-1/DET/0CH0:xtdf'
def test_get_train_per_id():
with H5File(FILEPATH) as f:
train, data = f.train_from_id(1455918700)
print(data)
assert data is not None
assert train == 1455918700
with pytest.raises(KeyError) as info:
data = f.train_from_id(1234) # train id not in file
print(info)
def test_get_train_bad_device_name(mock_spb_control_data_badname):
# Check that we can handle devices which don't have the standard Karabo
# name structure A/B/C.
with H5File(mock_spb_control_data_badname) as f:
train_id, data = f.train_from_id(10004)
assert train_id == 10004
assert 'SPB_IRU_SIDEMIC_CAM:daqOutput' in data
assert 'data.image.dims' in data['SPB_IRU_SIDEMIC_CAM:daqOutput']
dims = data['SPB_IRU_SIDEMIC_CAM:daqOutput']['data.image.dims']
assert list(dims) == [1000, 1000]
def test_file_get_array_missing_trains(mock_sa3_control_data):
with H5File(mock_sa3_control_data) as f:
sel = f.select_trains(by_index[:6])
arr = sel.get_array('SA3_XTD10_IMGFEL/CAM/BEAMVIEW2:daqOutput',
'data.image.dims')
assert isinstance(arr, DataArray)
assert arr.dims == ('trainId', 'dim_0')
assert arr.shape == (3, 2)
np.testing.assert_array_less(arr.coords['trainId'], 10006)
np.testing.assert_array_less(10000, arr.coords['trainId'])
def test_file_get_array_control_roi(mock_sa3_control_data):
with H5File(mock_sa3_control_data) as f:
sel = f.select_trains(by_index[:6])
arr = sel.get_array(
'SA3_XTD10_VAC/DCTRL/D6_APERT_IN_OK',
'interlock.a1.AActCommand.value',
roi=by_index[:25],
)
assert isinstance(arr, DataArray)
assert arr.shape == (6, 25)
assert arr.coords['trainId'][0] == 10000
def test_iterate_trains_require_all(mock_sa3_control_data):
with H5File(mock_sa3_control_data) as f:
trains_iter = f.trains(devices=[('*/CAM/BEAMVIEW:daqOutput',
'data.image.dims')],
require_all=True)
tids = [t for (t, _) in trains_iter]
assert tids == []
trains_iter = f.trains(devices=[('*/CAM/BEAMVIEW:daqOutput',
'data.image.dims')],
require_all=False)
tids = [t for (t, _) in trains_iter]
assert tids != []
def test_file_get_series_instrument(mock_agipd_data):
with H5File(mock_agipd_data) as f:
s = f.get_series('SPB_DET_AGIPD1M-1/DET/7CH0:xtdf', 'header.linkId')
assert isinstance(s, pd.Series)
assert len(s) == 250
assert s.index[0] == 10000
# Multiple readings per train
s2 = f.get_series('SPB_DET_AGIPD1M-1/DET/7CH0:xtdf', 'image.status')
assert isinstance(s2, pd.Series)
assert isinstance(s2.index, pd.MultiIndex)
assert len(s2) == 16000
assert len(s2.loc[10000:10004]) == 5 * 64
def test_get_file_info():
with H5File(FILEPATH) as f:
trains = f.train_ids
train_count = len(trains)
devices = f.devices
sources = f.sources
print('train ids:', trains)
print('count: ', train_count)
print('devices: ', devices)
print('data_sources: ', sources)
assert 1455918683 in trains
assert 1234 not in trains
assert train_count == 20
assert 'FXE_DET_LPD1M-1/DET/0CH0:xtdf/detector' in devices
assert 'INSTRUMENT/FXE_DET_LPD1M-1/DET/0CH0:xtdf/detector' in sources
def test_iterate_trains_select_keys(mock_fxe_control_data):
sel = {
'SA1_XTD2_XGM/DOOCS/MAIN': {
'beamPosition.ixPos.value',
'beamPosition.ixPos.timestamp',
}
}
with H5File(mock_fxe_control_data) as f:
for train_id, data in islice(f.trains(devices=sel), 10):
assert train_id in range(10000, 10400)
assert 'SA1_XTD2_XGM/DOOCS/MAIN' in data.keys()
assert 'beamPosition.ixPos.value' in data[
'SA1_XTD2_XGM/DOOCS/MAIN']
assert 'beamPosition.ixPos.timestamp' in data[
'SA1_XTD2_XGM/DOOCS/MAIN']
assert 'beamPosition.iyPos.value' not in data[
'SA1_XTD2_XGM/DOOCS/MAIN']
assert 'SA3_XTD10_VAC/TSENS/S30160K' not in data
def test_write_selected(mock_fxe_raw_run):
with TemporaryDirectory() as td:
new_file = osp.join(td, 'test.h5')
with RunDirectory(mock_fxe_raw_run) as run:
run.select('SPB_XTD9_XGM/*').write(new_file)
assert_isfile(new_file)
with H5File(new_file) as f:
assert f.control_sources == {'SPB_XTD9_XGM/DOOCS/MAIN'}
assert f.instrument_sources == {'SPB_XTD9_XGM/DOOCS/MAIN:output'}
s = f.get_series('SPB_XTD9_XGM/DOOCS/MAIN',
'beamPosition.ixPos.value')
# This should have concatenated the two sequence files (400 + 80)
assert len(s) == 480
a = f.get_array('SPB_XTD9_XGM/DOOCS/MAIN:output',
'data.intensityTD')
assert a.shape == (480, 1000)
def test_file_get_series_instrument(mock_agipd_data):
with H5File(mock_agipd_data) as f:
s = f.get_series('SPB_DET_AGIPD1M-1/DET/7CH0:xtdf', 'header.linkId')
assert isinstance(s, pd.Series)
assert len(s) == 250
assert s.index[0] == 10000
# Multiple readings per train
s2 = f.get_series('SPB_DET_AGIPD1M-1/DET/7CH0:xtdf', 'image.status')
assert isinstance(s2, pd.Series)
assert isinstance(s2.index, pd.MultiIndex)
assert len(s2) == 16000
assert len(s2.loc[10000:10004]) == 5 * 64
sel = f.select_trains(by_index[5:10])
s3 = sel.get_series('SPB_DET_AGIPD1M-1/DET/7CH0:xtdf', 'image.status')
assert isinstance(s3, pd.Series)
assert isinstance(s3.index, pd.MultiIndex)
assert len(s3) == 5 * 64
np.testing.assert_array_equal(s3.index.get_level_values(0),
np.arange(10005, 10010).repeat(64))
def test_detector_info_oldfmt(mock_agipd_data):
with H5File(mock_agipd_data) as f:
di = f.detector_info('SPB_DET_AGIPD1M-1/DET/7CH0:xtdf')
assert di['dims'] == (512, 128)
assert di['frames_per_train'] == 64
assert di['total_frames'] == 16000
def test_detector_info(mock_lpd_data):
with H5File(mock_lpd_data) as f:
di = f.detector_info()
assert di['dims'] == (256, 256)
assert di['frames_per_train'] == 128
assert di['total_frames'] == 128 * 480
def test_detector_info_oldfmt(mock_agipd_data):
with H5File(mock_agipd_data) as f:
di = f.detector_info()
assert di['dims'] == (512, 128)
assert di['frames_per_train'] == 64
assert di['total_frames'] == 16000
def test_file_get_series_control(mock_fxe_control_data):
with H5File(mock_fxe_control_data) as f:
s = f.get_series('SA1_XTD2_XGM/DOOCS/MAIN', "beamPosition.iyPos.value")
assert isinstance(s, pd.Series)
assert len(s) == 400
assert s.index[0] == 10000
def test_train_info(mock_lpd_data, capsys):
with H5File(mock_lpd_data) as f:
f.train_info(10004)
out, err = capsys.readouterr()
assert "Devices" in out
assert "FXE_DET_LPD1M-1/DET/0CH0:xtdf" in out
def test_open_file_format_1_0(mock_sa3_control_data_fmt_1_0):
f = H5File(mock_sa3_control_data_fmt_1_0)
file_access = f.files[0]
assert file_access.format_version == '1.0'
assert 'SA3_XTD10_VAC/TSENS/S30180K' in f.control_sources
def test_detector_info(mock_lpd_data):
with H5File(mock_lpd_data) as f:
di = f.detector_info('FXE_DET_LPD1M-1/DET/0CH0:xtdf')
assert di['dims'] == (256, 256)
assert di['frames_per_train'] == 128
assert di['total_frames'] == 128 * 480
def test_H5File():
f = H5File(FILEPATH)
assert f.file.filename == FILEPATH
assert len(f.train_ids) == 20
f.close()
