tomoscan.esrf.scan.mock.MockEDF#

class tomoscan.esrf.scan.mock.MockEDF(scan_path, n_radio, n_ini_radio=None, n_extra_radio=0, scan_range=360, n_recons=0, n_pag_recons=0, recons_vol=False, dim=200, scene='noise', dark_n=0, ref_n=0, flat_n=0, rotation_angle_endpoint=False, energy=None, pixel_size=None, distance=None, srcurrent_start=200.0, srcurrent_end=100.0)#

Bases: ScanMock

Mock a EDF acquisition

__init__(scan_path, n_radio, n_ini_radio=None, n_extra_radio=0, scan_range=360, n_recons=0, n_pag_recons=0, recons_vol=False, dim=200, scene='noise', dark_n=0, ref_n=0, flat_n=0, rotation_angle_endpoint=False, energy=None, pixel_size=None, distance=None, srcurrent_start=200.0, srcurrent_end=100.0)#
Parameters

  • scan_path –

  • n_radio –

  • n_ini_radio –

  • n_extra_radio –

  • scan_range –

  • n_recons –

  • n_pag_recons –

  • recons_vol –

  • dim –

  • ref_n – repalced by flat_n

  • flat_n –

  • dark_n –

  • scene – scene type. * ‘noise’: generate radios from numpy.random * increase value: first frame value will be0, then second 1… * arange: arange through frames * ‘perfect-sphere: generate a sphere which just fit in the detector dimensions

TODO: add some differente scene type.

Methods

__init__(scan_path, n_radio[, n_ini_radio, ...])

param scan_path

add_dark(index)

add_dark_series(scan_path, n_elmt, index, ...)

add_flat(index)

add_flat_series(scan_path, n_elmt, index, ...)

add_pag_reconstruction([index])

add_radio([index])

add_recons_vol()

add_reconstruction([index])

end_acquisition()

fastMockAcquisition(folder[, n_radio, ...])

Simple function creating an acquisition into the given directory This won't complete data, scan.info of scan.xml files but just create the structure that data watcher is able to detect in edf mode.

get_info_file()

mockReconstruction(folder[, nRecons, nPagRecons])

create reconstruction files into the given folder

mockScan(scanID[, nRadio, nRecons, ...])

Create some random radios and reconstruction in the folder

write_metadata(n_radio, scan_range, flat_n, ...)

Attributes

PIXEL_SIZE

distance

rtype

float

energy

rtype

float

pixel_size

rtype

float
static fastMockAcquisition(folder, n_radio=20, n_extra_radio=0, scan_range=360)#

Simple function creating an acquisition into the given directory This won’t complete data, scan.info of scan.xml files but just create the structure that data watcher is able to detect in edf mode.

static mockReconstruction(folder, nRecons=5, nPagRecons=0)#

create reconstruction files into the given folder

Parameters

  • folder – the path of the folder where to save the reconstruction

  • nRecons – the number of reconstruction to mock

  • nPagRecons – the number of paganin reconstruction to mock

  • volFile – true if we want to add a volFile with reconstruction

static mockScan(scanID, nRadio=5, nRecons=1, nPagRecons=0, dim=10, scan_range=360, n_extra_radio=0, start_dark=False, end_dark=False, start_flat=False, end_flat=False, start_dark_data=None, end_dark_data=None, start_flat_data=None, end_flat_data=None)#

Create some random radios and reconstruction in the folder

Parameters

  • scanID – the folder where to save the radios and scans

  • nRadio – The number of radios to create

  • nRecons – the number of reconstruction to mock

  • nRecons – the number of paganin reconstruction to mock

  • dim – dimension of the files (nb row/columns)

  • scan_range – scan range, usually 180 or 360

  • n_extra_radio – number of radio run after the full range is made usually used to observe any sample movement during acquisition

  • start_dark – do we want to create dark series at start

  • end_dark – do we want to create dark series at end

  • start_flat – do we want to create flat series at start

  • end_flat – do we want to create flat series at end

  • start_dark_data – if start_dark set to True Optional value for the dark series. Else will generate some random values

  • end_dark_data – if end_dark set to True Optional value for the dark series. Else will generate some random values

  • start_flat_data – if start_flat set to True Optional value for the flat series. Else will generate some random values

  • end_flat_data – if end_flat set to True Optional value for the flat series. Else will generate some random values