### the DISPATCHER is responsible for job management
[dispatcher]
type = local # run locally
ncores = 1 # optionally, specify number of cores (autodetect by default)

# specificy destination file using scan numbers
destination= test_{first}.hdf5
overwrite = true

### choose an appropriate INPUT class and specify custom options
[input]
type = example:input # refers to class Input in BINoculars/backends/example.py

## approximate number of images per job, only useful when running on the oar cluster
target_weight = 4000

# technical details for this particular input class
wavelength = 0.5
centralpixel = 50,50
sdd=636 #sample detector distance
pixelsize=0.055, 0.055

### choose PROJECTION plus resolution
[projection]
type = example:qprojection # refers to qprojection in BINoculars/backends/example.py

## for L-scans (previous values)
resolution = 0.01 # or just give 1 number for all
