def test_components_array_dup(agipd_file_tid_high):
f = H5File(agipd_file_tid_high, inc_suspect_trains=False)
agipd = AGIPD1M(f, modules=[0])
arr = agipd.get_array('image.data', pulses=np.s_[:1])
assert arr.shape == (1, 485, 1, 2, 512, 128)
assert arr.dims == ('module', 'train', 'pulse', 'data_gain', 'slow_scan', 'fast_scan')
assert list(arr.coords['train'].values[9:11]) == [10009, 10011]
def test_write_virtual_cxi(mock_spb_proc_run, tmpdir):
run = RunDirectory(mock_spb_proc_run)
det = AGIPD1M(run)
test_file = osp.join(str(tmpdir), 'test.cxi')
det.write_virtual_cxi(test_file)
assert_isfile(test_file)
with h5py.File(test_file, 'r') as f:
det_grp = f['entry_1/instrument_1/detector_1']
ds = det_grp['data']
assert isinstance(ds, h5py.Dataset)
assert ds.is_virtual
assert ds.shape[1:] == (16, 512, 128)
assert 'axes' in ds.attrs
assert len(ds.virtual_sources()) == 16
# Check position of each source file in the modules dimension
for src in ds.virtual_sources():
start, _, block, count = src.vspace.get_regular_hyperslab()
assert block[1] == 1
assert count[1] == 1
expected_file = 'CORR-R0238-AGIPD{:0>2}-S00000.h5'.format(start[1])
assert osp.basename(src.file_name) == expected_file
# Check presence of other datasets
assert 'gain' in det_grp
assert 'mask' in det_grp
assert 'experiment_identifier' in det_grp
def test_write_virtual_cxi_dup(agipd_file_tid_high, tmp_path, caplog):
f = H5File(agipd_file_tid_high, inc_suspect_trains=False)
agipd = AGIPD1M(f, modules=[0])
cxi_path = tmp_path / 'exc_suspect.cxi'
agipd.write_virtual_cxi(str(cxi_path))
assert_isfile(cxi_path)
with h5py.File(cxi_path, 'r') as f:
assert f['entry_1/data_1/data'].shape == (485 * 64, 16, 2, 512, 128)
def test_get_dask_array_reduced_data(mock_reduced_spb_proc_run):
run = RunDirectory(mock_reduced_spb_proc_run)
det = AGIPD1M(run)
arr = det.get_dask_array('image.data')
assert arr.shape[2:] == (512, 128)
assert arr.dims == ('module', 'train_pulse', 'dim_0', 'dim_1')
np.testing.assert_array_equal(arr.coords['module'], np.arange(16))
assert np.isin(arr.coords['trainId'], np.arange(10000, 10480)).all()
assert np.isin(arr.coords['pulseId'], np.arange(0, 20)).all()
def test_write_virtual_cxi_reduced_data(mock_reduced_spb_proc_run, tmpdir):
run = RunDirectory(mock_reduced_spb_proc_run)
det = AGIPD1M(run)
test_file = osp.join(str(tmpdir), 'test.cxi')
det.write_virtual_cxi(test_file)
assert_isfile(test_file)
with h5py.File(test_file, 'r') as f:
det_grp = f['entry_1/instrument_1/detector_1']
ds = det_grp['data']
assert ds.shape[1:] == (16, 512, 128)
def test_write_selected_frames_proc(mock_spb_proc_run, tmp_path):
run = RunDirectory(mock_spb_proc_run)
det = AGIPD1M(run)
trains = np.repeat(np.arange(10000, 10010), 3)
pulses = np.tile([0, 1, 5], 10)
test_file = str(tmp_path / 'sel_frames.h5')
det.write_frames(test_file, trains, pulses)
assert_isfile(test_file)
with H5File(test_file) as f:
np.testing.assert_array_equal(
f.get_array('SPB_DET_AGIPD1M-1/DET/0CH0:xtdf', 'image.pulseId'),
pulses)
assert f.instrument_sources == {
f'SPB_DET_AGIPD1M-1/DET/{i}CH0:xtdf'
for i in range(16)
}
def test_get_array_pulse_id_reduced_data(mock_reduced_spb_proc_run):
run = RunDirectory(mock_reduced_spb_proc_run)
det = AGIPD1M(run.select_trains(by_index[:3]))
arr = det.get_array('image.data', pulses=by_id[0])
assert arr.shape == (16, 3, 1, 512, 128)
assert (arr.coords['pulse'] == 0).all()
arr = det.get_array('image.data', pulses=by_id[:5])
assert (arr.coords['pulse'] < 5).all()
# Empty selection
arr = det.get_array('image.data', pulses=by_id[:0])
assert arr.shape == (16, 0, 0, 512, 128)
arr = det.get_array('image.data', pulses=by_id[5:])
assert (arr.coords['pulse'] >= 5).all()
arr = det.get_array('image.data', pulses=by_id[[1, 7, 15, 23]])
assert np.isin(arr.coords['pulse'], [1, 7, 15, 23]).all()
def test_write_selected_frames_proc(mock_spb_proc_run, tmp_path):
run = RunDirectory(mock_spb_proc_run)
det = AGIPD1M(run)
trains = np.repeat(np.arange(10000, 10006), 2)
pulses = np.tile([0, 7], 6)
test_file = tmp_path / 'sel_frames.h5'
det.write_frames(test_file, trains, pulses)
assert_isfile(test_file)
with H5File(test_file) as f:
np.testing.assert_array_equal(
f.get_array('SPB_DET_AGIPD1M-1/DET/0CH0:xtdf', 'image.pulseId'),
pulses
)
assert f.instrument_sources == {
f'SPB_DET_AGIPD1M-1/DET/{i}CH0:xtdf' for i in range(16)
}
# pytest leaves temp files for inspection, but these files are big enough
# to be inconvenient, so delete them if the assertions have passed.
test_file.unlink()
def test_components_array(agipd_file_flag0):
f = H5File(agipd_file_flag0, inc_suspect_trains=False)
agipd = AGIPD1M(f, modules=[0])
arr = agipd.get_array('image.data', pulses=np.s_[:1])
assert arr.shape == (1, 485, 1, 2, 512, 128)
assert arr.dims == ('module', 'train', 'pulse', 'data_gain', 'slow_scan', 'fast_scan')
