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import os
import os.path as osp
import h5py
import numpy as np
from .mockdata import write_file
from .mockdata.adc import ADC
from .mockdata.agipd import AGIPD1MFPGA, AGIPD1MPSC, AGIPD500KFPGA, AGIPDMDL
from .mockdata.base import write_base_index
from .mockdata.basler_camera import BaslerCamera as BaslerCam
from .mockdata.dctrl import DCtrl
from .mockdata.detectors import AGIPDModule, DSSCModule, LPDModule
from .mockdata.gauge import Gauge
from .mockdata.gec_camera import GECCamera
from .mockdata.imgfel import IMGFELCamera, IMGFELMotor
from .mockdata.jungfrau import (
JUNGFRAUControl, JUNGFRAUModule, JUNGFRAUMonitor, JUNGFRAUPower
)
from .mockdata.motor import Motor
from .mockdata.mpod import MPOD
from .mockdata.proc import ReconstructedDLD6
from .mockdata.tsens import TemperatureSensor
from .mockdata.uvlamp import UVLamp
from .mockdata.xgm import XGM
vlen_bytes = h5py.special_dtype(vlen=bytes)
def make_metadata(h5file, data_sources, chunksize=16):
N = len(data_sources)
if N % chunksize:
N += chunksize - (N % chunksize)
root = [ds.split('/', 1)[0] for ds in data_sources]
devices = [ds.split('/', 1)[1] for ds in data_sources]
sources_ds = h5file.create_dataset('METADATA/dataSourceId', (N,),
dtype=vlen_bytes, maxshape=(None,))
sources_ds[:len(data_sources)] = data_sources
root_ds = h5file.create_dataset('METADATA/root', (N,),
dtype=vlen_bytes, maxshape=(None,))
root_ds[:len(data_sources)] = root
devices_ds = h5file.create_dataset('METADATA/deviceId', (N,),
dtype=vlen_bytes, maxshape=(None,))
devices_ds[:len(data_sources)] = devices
def make_agipd_example_file(path, format_version='0.5'):
"""Make the structure of a data file from the AGIPD detector
Based on /gpfs/exfel/d/proc/XMPL/201750/p700000/r0803/CORR-R0803-AGIPD07-S00000.h5
This has the old index format (first/last/status), whereas the other examples
have the newer (first/count) format.
"""
f = h5py.File(path, 'w')
slow_channels = ['header', 'detector', 'trailer']
channels = slow_channels + ['image']
train_ids = np.arange(10000, 10250) # Real train IDs are ~10^9
# RUN - empty in the example I'm working from
f.create_group('RUN')
# METADATA - lists the data sources in this file
make_metadata(f, ['INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/'+ch
for ch in channels])
def make_train_ids(path):
d = f.create_dataset(path, (256,), 'u8', maxshape=(None,))
d[:250] = train_ids
# INDEX - matching up data to train IDs
write_base_index(f, 250, format_version=format_version)
for ch in channels:
grp_name = 'INDEX/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/%s/' % ch
first = f.create_dataset(grp_name + 'first', (256,), 'u8', maxshape=(None,))
last = f.create_dataset(grp_name + 'last', (256,), 'u8', maxshape=(None,))
status = f.create_dataset(grp_name + 'status', (256,), 'u4', maxshape=(None,))
if ch in slow_channels:
first[:250] = np.arange(250)
last[:250] = np.arange(250)
else:
first[:250] = np.arange(0, 16000, 64)
last[:250] = np.arange(63, 16000, 64)
status[:250] = 1
# INSTRUMENT - the data itself
# first, train IDs for each channel
for ch in slow_channels:
make_train_ids('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/%s/trainId' % ch)
fast_tids = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/trainId',
(16000, 1), 'u8')
fast_tids[:,0] = np.repeat(train_ids, 64)
# TODO: Not sure what this is, but it has quite a regular structure.
# 5408 = 13 x 13 x 32
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/detector/data',
(256, 5408), 'u1', maxshape=(None, 5408))
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/header/dataId',
(256,), 'u8', maxshape=(None,)) # Empty in example
linkId = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/header/linkId',
(256,), 'u8', maxshape=(None,))
linkId[:250] = 18446744069414584335 # Copied from example
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/header/magicNumberBegin',
(256, 8), 'i1', maxshape=(None, 8)) # TODO: fill in data
vmaj = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/header/majorTrainFormatVersion',
(256,), 'u4', maxshape=(None,))
vmaj[:250] = 1
vmin = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/header/minorTrainFormatVersion',
(256,), 'u4', maxshape=(None,))
vmin[:250] = 0
pc = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/header/pulseCount',
(256,), 'u8', maxshape=(None,))
pc[:250] = 64
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/header/reserved',
(256, 16), 'u1', maxshape=(None, 16)) # Empty in example
cellId = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/cellId',
(16000, 1), 'u2')
cellId[:, 0] = np.tile(np.arange(64), 250)
# The data itself
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/data',
(16000, 512, 128), 'f4')
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/gain',
(16000, 512, 128), 'u1')
length = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/length',
(16000, 1), 'u4', maxshape=(None, 1))
length[:] = 262144 # = 512*128*4(bytes) ?
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/mask',
(16000, 512, 128, 3), 'u1') # TODO: values 128 or 0
pulseId = f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/pulseId',
(16000, 1), 'u8')
# In the real data, these are unevenly spaced, but this is close enough
pulseId[:, 0] = np.tile(np.linspace(0, 125, 64, dtype='u8'), 250)
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/image/status',
(16000, 1), 'u2') # Empty in example
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/trailer/checksum',
(256, 16), 'i1', maxshape=(None, 16)) # Empty in example
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/trailer/magicNumberEnd',
(256, 8), 'i1', maxshape=(None, 8)) # TODO: fill in data
f.create_dataset('INSTRUMENT/SPB_DET_AGIPD1M-1/DET/7CH0:xtdf/trailer/status',
(256,), 'u8', maxshape=(None,)) # Empty in example
def make_fxe_da_file(path, format_version='0.5', firsttrain=10000):
"""Make the structure of a file with non-detector data from the FXE experiment
Based on .../FXE/201830/p900023/r0450/RAW-R0450-DA01-S00001.h5
"""
write_file(path, [
XGM('SA1_XTD2_XGM/DOOCS/MAIN'),
XGM('SPB_XTD9_XGM/DOOCS/MAIN'),
GECCamera('FXE_XAD_GEC/CAM/CAMERA'),
GECCamera('FXE_XAD_GEC/CAM/CAMERA_NODATA', nsamples=0)
], ntrains=400, chunksize=200, firsttrain=firsttrain, format_version=format_version)
def make_sa3_da_file(path, ntrains=500, format_version='0.5'):
"""Make the structure of a file with non-detector data from SASE3 tunnel
Based on .../SA3/201830/p900026/r0317/RAW-R0317-DA01-S00000.h5
"""
write_file(path, [
ADC('SA3_XTD10_MCP/ADC/1', nsamples=0, channels=(
'channel_3.output/data',
'channel_5.output/data',
'channel_9.output/data',
)),
UVLamp('SA3_XTD10_MCP/DCTRL/UVLAMP'),
Motor('SA3_XTD10_MCP/MOTOR/X2'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30100K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30160K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30180K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30190K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30200K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30250K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30260K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30280K'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30300K'),
Gauge('SA3_XTD10_VAC/GAUGE/G30470D_IN'),
Gauge('SA3_XTD10_VAC/GAUGE/G30480D_IN'),
Gauge('SA3_XTD10_VAC/GAUGE/G30490D_IN'),
Gauge('SA3_XTD10_VAC/GAUGE/G30500P'),
Gauge('SA3_XTD10_VAC/GAUGE/G30510C'),
DCtrl('SA3_XTD10_VAC/DCTRL/D6_APERT_IN_OK'),
DCtrl('SA3_XTD10_VAC/DCTRL/D12_APERT_IN_OK'),
XGM('SA3_XTD10_XGM/XGM/DOOCS'),
IMGFELCamera('SA3_XTD10_IMGFEL/CAM/BEAMVIEW', nsamples=0),
IMGFELCamera('SA3_XTD10_IMGFEL/CAM/BEAMVIEW2', nsamples=250),
IMGFELCamera('SA3_XTD10_IMGFEL/CAM/BEAMVIEW3', nsamples=200),
IMGFELMotor('SA3_XTD10_IMGFEL/MOTOR/FILTER'),
IMGFELMotor('SA3_XTD10_IMGFEL/MOTOR/SCREEN'),
MPOD('SA3_XTD10_MCP/MCPS/MPOD'),
], ntrains=ntrains, chunksize=50, format_version=format_version)
def make_da_file_with_empty_source(path, ntrains=500, format_version='0.5'):
write_file(path, [
ADC('SA3_XTD10_MCP/ADC/1', nsamples=0, channels=(
'channel_3.output/data',
'channel_5.output/data',
'channel_9.output/data',
)),
UVLamp('SA3_XTD10_MCP/DCTRL/UVLAMP'),
Motor('SA3_XTD10_MCP/MOTOR/X2'),
TemperatureSensor('SA3_XTD10_VAC/TSENS/S30100K'),
Gauge('SA3_XTD10_VAC/GAUGE/G30510C'),
Gauge('SA3_XTD10_VAC/GAUGE/G30520C', no_ctrl_data=True),
DCtrl('SA3_XTD10_VAC/DCTRL/D6_APERT_IN_OK'),
XGM('SA3_XTD10_XGM/XGM/DOOCS'),
IMGFELCamera('SA3_XTD10_IMGFEL/CAM/BEAMVIEW', nsamples=0),
IMGFELCamera('SA3_XTD10_IMGFEL/CAM/BEAMVIEW2', nsamples=250),
IMGFELMotor('SA3_XTD10_IMGFEL/MOTOR/FILTER'),
MPOD('SA3_XTD10_MCP/MCPS/MPOD'),
], ntrains=ntrains, chunksize=50, format_version=format_version)
def make_data_file_bad_device_name(path, format_version='0.5'):
"""Not all devices have the Karabo standard A/B/C naming convention"""
write_file(path, [
BaslerCam('SPB_IRU_SIDEMIC_CAM', sensor_size=(1000, 1000))
], ntrains=500, chunksize=50, format_version=format_version)
def make_agipd_file(path, format_version='0.5'):
write_file(path, [
AGIPDModule('SPB_DET_AGIPD1M-1/DET/0CH0', frames_per_train=64)
], ntrains=486, chunksize=32, format_version=format_version)
def make_lpd_file(path, format_version='0.5'):
write_file(path, [
LPDModule('FXE_DET_LPD1M-1/DET/0CH0', frames_per_train=128)
], ntrains=480, chunksize=32, format_version=format_version)
def make_fxe_run(dir_path, raw=True, format_version='0.5'):
prefix = 'RAW' if raw else 'CORR'
for modno in range(16):
path = osp.join(dir_path,
'{}-R0450-LPD{:0>2}-S00000.h5'.format(prefix, modno))
write_file(path, [
LPDModule('FXE_DET_LPD1M-1/DET/{}CH0'.format(modno), 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'), [
XGM('SA1_XTD2_XGM/DOOCS/MAIN'),
XGM('SPB_XTD9_XGM/DOOCS/MAIN'),
GECCamera('FXE_XAD_GEC/CAM/CAMERA'),
GECCamera('FXE_XAD_GEC/CAM/CAMERA_NODATA', nsamples=0),
], ntrains=400, chunksize=200, format_version=format_version)
write_file(osp.join(dir_path, '{}-R0450-DA01-S00001.h5'.format(prefix)), [
XGM('SA1_XTD2_XGM/DOOCS/MAIN'),
XGM('SPB_XTD9_XGM/DOOCS/MAIN'),
GECCamera('FXE_XAD_GEC/CAM/CAMERA'),
GECCamera('FXE_XAD_GEC/CAM/CAMERA_NODATA', nsamples=0),
], ntrains=80, firsttrain=10400, chunksize=200, format_version=format_version)
def make_lpd_parallelgain_run(dir_path, raw=True, format_version='0.5'):
prefix = 'RAW' if raw else 'CORR'
for modno in range(16):
path = osp.join(dir_path,
'{}-R0450-LPD{:0>2}-S00000.h5'.format(prefix,
modno))
write_file(path, [
LPDModule('FXE_DET_LPD1M-1/DET/{}CH0'.format(modno), 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'), [
LPDModule('FXE_DET_LPD1M-1/DET/0CH0', frames_per_train=10),
], ntrains=5, chunksize=5, format_version='1.0')
mod1_f = osp.join(dir_path, 'RAW-R0450-LPD01-S00000.h5')
write_file(mod1_f, [
LPDModule('FXE_DET_LPD1M-1/DET/1CH0', frames_per_train=10),
], ntrains=4, chunksize=5, format_version='1.0')
# Modify the file for module 1, as if it missed train 10002
# & fill some data to check in the test.
with h5py.File(mod1_f, 'r+') as f:
f['INDEX/trainId'][:4] = [10000, 10001, 10003, 10004]
mod1_dset = f['INSTRUMENT/FXE_DET_LPD1M-1/DET/1CH0:xtdf/image/data']
mod1_dset[8::10, 0, 0, 0] = np.arange(1, 5)
def make_spb_run(dir_path, raw=True, sensor_size=(1024, 768), format_version='0.5'):
prefix = 'RAW' if raw else 'CORR'
for modno in range(16):
path = osp.join(dir_path,
'{}-R0238-AGIPD{:0>2}-S00000.h5'.format(prefix, modno))
write_file(path, [
AGIPDModule('SPB_DET_AGIPD1M-1/DET/{}CH0'.format(modno), raw=raw,
frames_per_train=64)
], ntrains=64, chunksize=32, format_version=format_version)
if not raw:
return
write_file(osp.join(dir_path, '{}-R0238-DA01-S00000.h5'.format(prefix)),
[ XGM('SA1_XTD2_XGM/DOOCS/MAIN'),
XGM('SPB_XTD9_XGM/DOOCS/MAIN'),
BaslerCam('SPB_IRU_CAM/CAM/SIDEMIC', sensor_size=sensor_size)
], ntrains=32, chunksize=32, format_version=format_version)
write_file(osp.join(dir_path, '{}-R0238-DA01-S00001.h5'.format(prefix)),
[ XGM('SA1_XTD2_XGM/DOOCS/MAIN'),
XGM('SPB_XTD9_XGM/DOOCS/MAIN'),
BaslerCam('SPB_IRU_CAM/CAM/SIDEMIC', sensor_size=sensor_size)
], ntrains=32, firsttrain=10032, chunksize=32,
format_version=format_version)
def make_reduced_spb_run(dir_path, raw=True, rng=None, format_version='0.5'):
# Simulate reduced AGIPD data, with varying number of frames per train.
# Counts across modules should be consistent
prefix = 'RAW' if raw else 'CORR'
if rng is None:
rng = np.random.RandomState()
frame_counts = rng.randint(0, 20, size=64)
for modno in range(16):
path = osp.join(dir_path,
'{}-R0238-AGIPD{:0>2}-S00000.h5'.format(prefix, modno))
write_file(path, [
AGIPDModule('SPB_DET_AGIPD1M-1/DET/{}CH0'.format(modno), raw=raw,
frames_per_train=frame_counts)
], ntrains=64, chunksize=32, format_version=format_version)
if modno == 9 and not raw:
# For testing masked_data
with h5py.File(path, 'a') as f:
mask_ds = f['INSTRUMENT/SPB_DET_AGIPD1M-1/DET/9CH0:xtdf/image/mask']
mask_ds[0, 0, :32] = np.arange(32)
write_file(osp.join(dir_path, '{}-R0238-DA01-S00000.h5'.format(prefix)),
[ XGM('SA1_XTD2_XGM/DOOCS/MAIN'),
XGM('SPB_XTD9_XGM/DOOCS/MAIN'),
BaslerCam('SPB_IRU_CAM/CAM/SIDEMIC', sensor_size=(1024, 768))
], ntrains=32, chunksize=32, format_version=format_version)
write_file(osp.join(dir_path, '{}-R0238-DA01-S00001.h5'.format(prefix)),
[ XGM('SA1_XTD2_XGM/DOOCS/MAIN'),
XGM('SPB_XTD9_XGM/DOOCS/MAIN'),
BaslerCam('SPB_IRU_CAM/CAM/SIDEMIC', sensor_size=(1024, 768))
], ntrains=32, firsttrain=10032, chunksize=32,
format_version=format_version)
def make_modern_spb_proc_run(dir_path, format_version='1.2'):
for modno in range(16):
path = osp.join(dir_path, f'CORR-R0142-AGIPD{modno:0>2}-S00000.h5')
write_file(path, [
AGIPDModule(f'SPB_DET_AGIPD1M-1/CORR/{modno}CH0', channel_name='output',
raw=False, frames_per_train=32,
legacy_name=f'SPB_DET_AGIPD1M-1/DET/{modno}CH0')
], ntrains=64, chunksize=32, format_version=format_version)
def make_agipd1m_run(
dir_path,
rep_rate=True,
gain_setting=True,
integration_time=True,
bias_voltage=True
):
# Naming based on /gpfs/exfel/exp/SPB/202130/p900203/raw/r9015
for modno in range(16):
path = osp.join(dir_path, f'RAW-R9015-AGIPD{modno:02}-S00000.h5')
write_file(path, [
AGIPDModule(
f'SPB_DET_AGIPD1M-1/DET/{modno}CH0', frames_per_train=64)
], ntrains=100, chunksize=32, format_version='1.0')
write_file(osp.join(dir_path, 'RAW-R9015-AGIPD1MCTRL00-S00000.h5'), [
AGIPDMDL(
'SPB_IRU_AGIPD1M1/MDL/FPGA_COMP',
rep_rate=rep_rate,
gain_setting=gain_setting,
integration_time=integration_time,
),
AGIPD1MFPGA('SPB_IRU_AGIPD1M1/FPGA/MASTER_H1'),
AGIPD1MPSC('SPB_IRU_AGIPD1M/PSC/HV', bias_voltage=bias_voltage),
], ntrains=100, chunksize=1, format_version='1.0')
def make_agipd500k_run(dir_path):
# Naming based on /gpfs/exfel/exp/SPB/202130/p900203/raw/r9023
for modno in range(8):
path = osp.join(dir_path, f'RAW-R9023-AGIPD{modno:02}-S00000.h5')
write_file(path, [
AGIPDModule(
f'HED_DET_AGIPD500K2G/DET/{modno}CH0', frames_per_train=64)
], ntrains=100, chunksize=32, format_version='1.0')
write_file(osp.join(dir_path, 'RAW-R9023-AGIPD500K2G00-S00000.h5'), [
AGIPDMDL('HED_EXP_AGIPD500K2G/MDL/FPGA_COMP'),
AGIPD500KFPGA('HED_EXP_AGIPD500K2G/FPGA/M_0'),
], ntrains=100, chunksize=1, format_version='1.0')
def make_jungfrau_run(dir_path):
# Naming based on /gpfs/exfel/exp/SPB/202022/p002732/raw/r0012
for modno in range(1, 9):
path = osp.join(dir_path, f'RAW-R0012-JNGFR{modno:02}-S00000.h5')
write_file(path, [
JUNGFRAUModule(f'SPB_IRDA_JF4M/DET/JNGFR{modno:02}')
], ntrains=100, chunksize=1, format_version='1.0')
write_file(osp.join(dir_path, f'RAW-R0012-JNGFRCTRL00-S00000.h5'), [
JUNGFRAUControl('SPB_IRDA_JF4M/DET/CONTROL'),
JUNGFRAUMonitor('SPB_IRDA_JF4M/MDL/MONITOR'),
JUNGFRAUPower('SPB_IRDA_JF4M/MDL/POWER'),
], ntrains=100, chunksize=1, format_version='1.0')
def make_fxe_jungfrau_run(dir_path):
# Naming based on /gpfs/exfel/exp/FXE/202101/p002478/raw/
for modno in range(1, 3):
path = osp.join(dir_path, f'RAW-R0012-JNGFR{modno:02}-S00000.h5')
write_file(path, [
JUNGFRAUModule(f'FXE_XAD_JF1M/DET/JNGFR{modno:02}')
], ntrains=100, chunksize=1, format_version='1.0')
path = osp.join(dir_path, f'RAW-R0052-JNGFR03-S00000.h5')
write_file(path, [
JUNGFRAUModule(f'FXE_XAD_JF500K/DET/JNGFR03')
], ntrains=100, chunksize=1, format_version='1.0')
with h5py.File(path, 'a') as f:
# For testing masked_data
mask_ds = f['INSTRUMENT/FXE_XAD_JF500K/DET/JNGFR03:daqOutput/data/mask']
mask_ds[0, 0, 0, :32] = np.arange(32)
write_file(osp.join(dir_path, f'RAW-R0052-JNGFRCTRL00-S00000.h5'), [
JUNGFRAUControl('FXE_XAD_JF1M/DET/CONTROL'),
JUNGFRAUControl('FXE_XAD_JF500K/DET/CONTROL'),
], ntrains=100, chunksize=1, format_version='1.0')
def make_remi_run(dir_path):
write_file(osp.join(dir_path, f'CORR-R0210-REMI01-S00000.h5'), [
ReconstructedDLD6('SQS_REMI_DLD6/DET/TOP'),
], ntrains=100, chunksize=1, format_version='1.0')
def make_scs_run(dir_path):
# Multiple sequence files for detector modules
for modno in range(16):
mod = DSSCModule(f'SCS_DET_DSSC1M-1/DET/{modno}CH0', frames_per_train=64)
for seq in range(2):
path = osp.join(dir_path, f'RAW-R0163-DSSC{modno:0>2}-S{seq:0>5}.h5')
write_file(path, [mod], ntrains=64, firsttrain=(10000 + seq * 64),
chunksize=32, format_version='1.0')
if __name__ == '__main__':
make_agipd_example_file('agipd_example.h5')
make_fxe_da_file('fxe_control_example.h5')
make_sa3_da_file('sa3_control_example.h5')
make_agipd_file('agipd_example2.h5')
make_lpd_file('lpd_example.h5')
os.makedirs('fxe_example_run', exist_ok=True)
make_fxe_run('fxe_example_run')
os.makedirs('spb_example_run', exist_ok=True)
make_spb_run('spb_example_run')
print("Written examples.")
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