Scan Definition (p.scans.scan_00)#

ScanModel#

ScanModel(Param)#: default = Param({})

ScanModel.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

ScanModel.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

ScanModel.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

ScanModel.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

ScanModel.data.name(str)#

Name of the PtyScan subclass to use

default = None

ScanModel.illumination(Param, str)#

Container for probe initialization model

default = Param({})

ScanModel.sample(Param, str)#

Container for sample initialization model

default = Param({})

ScanModel.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

BlockScanModel#

BlockScanModel(Param)#: default = Param({})

BlockScanModel.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

BlockScanModel.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

BlockScanModel.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

BlockScanModel.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

BlockScanModel.data.name(str)#

Name of the PtyScan subclass to use

default = None

BlockScanModel.illumination(Param, str)#

Container for probe initialization model

default = Param({})

BlockScanModel.sample(Param, str)#

Container for sample initialization model

default = Param({})

BlockScanModel.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

Vanilla#

Vanilla(Param)#: default = Param({})

Vanilla.name(str)#: default = 'Vanilla'

Vanilla.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

Vanilla.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

Vanilla.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

Vanilla.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

Vanilla.data.name(str)#

Name of the PtyScan subclass to use

default = None

Vanilla.illumination(Param, str)#

Container for probe initialization model

default = Param({})

Vanilla.illumination.size(float)#

Initial probe size

The probe is initialized as a flat circle.

default = None

Vanilla.sample(Param, str)#

Container for sample initialization model

default = Param({})

Vanilla.sample.fill(float, complex)#

Initial sample value

The sample is initialized with this value everywhere.

default = 1

Vanilla.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

BlockVanilla#

BlockVanilla(Param)#: default = Param({})

BlockVanilla.name(str)#: default = 'Vanilla'

BlockVanilla.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

BlockVanilla.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

BlockVanilla.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

BlockVanilla.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

BlockVanilla.data.name(str)#

Name of the PtyScan subclass to use

default = None

BlockVanilla.illumination(Param, str)#

Container for probe initialization model

default = Param({})

BlockVanilla.illumination.size(float)#

Initial probe size

The probe is initialized as a flat circle.

default = None

BlockVanilla.sample(Param, str)#

Container for sample initialization model

default = Param({})

BlockVanilla.sample.fill(float, complex)#

Initial sample value

The sample is initialized with this value everywhere.

default = 1

BlockVanilla.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

Full#

Full(Param)#: default = Param({})

Full.name(str)#: default = 'Full'

Full.coherence(Param)#

Coherence parameters

default = Param({}) (>0.0)

Full.coherence.num_probe_modes(int)#

Number of probe modes

default = 1 (>0)

Full.coherence.num_object_modes(int)#

Number of object modes

default = 1 (>0)

Full.coherence.energies(list)#

default = [1.0]

Full.coherence.spectrum(list)#

Amplitude of relative energy bins if the probe modes have a different energy

default = [1.0] (>0.0)

Full.coherence.object_dispersion(str)#

Energy dispersive response of the object

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

Full.coherence.probe_dispersion(str)#

Energy dispersive response of the probe

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

Full.resolution(NoneType, float)#

Will force the reconstruction to adapt to the given resolution, this might lead to cropping/padding in diffraction space which could reduce performance.

Half-period resolution given in [m]

default = None (>0.0)

Full.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

Full.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

Full.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

Full.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

Full.data.name(str)#

Name of the PtyScan subclass to use

default = None

Full.illumination(Param, str)#

Illumination parameters

default = Param({})

Full.illumination.aperture(Param)#

Beam aperture parameters

default = Param({})

Full.illumination.aperture.rotate(float)#

Rotate aperture by this value

default = 0.0

Full.illumination.aperture.central_stop(float)#

size of central stop as a fraction of aperture.size

If not None: places a central beam stop in aperture. The value given here is the fraction of the beam stop compared to size

default = None (>0.0, <1.0)

Full.illumination.aperture.diffuser(tuple)#

Noise in the transparen part of the aperture

Can be either: - None : no noise - 2-tuple : noise in phase (amplitude (rms), minimum feature size) - 4-tuple : noise in phase & modulus (rms, mfs, rms_mod, mfs_mod)

default = None

Full.illumination.aperture.edge(float)#

Edge width of aperture (in pixels!)

default = 2.0

Full.illumination.aperture.form(NoneType, str)#

One of None, ‘rect’ or ‘circ’

One of: - None : no aperture, this may be useful for nearfield - 'rect' : rectangular aperture - 'circ' : circular aperture

default = 'circ'

Full.illumination.aperture.offset(float, tuple, list)#

Offset between center of aperture and optical axes

May also be a tuple (vertical,horizontal) for size in case of an asymmetric offset

default = 0.0

Full.illumination.aperture.size(float, tuple, list)#

Aperture width or diameter

May also be a tuple (vertical,horizontal) in case of an asymmetric aperture

default = None (>0.0)

Full.illumination.diversity(Param, NoneType)#

Probe mode(s) diversity parameters

Can be None i.e. no diversity

default = Param({})

Full.illumination.diversity.noise(tuple, list)#

Noise in each non-primary mode of the illumination.

Can be either: - None : no noise - 2-tuple : noise in phase (amplitude (rms), minimum feature size) - 4-tuple : noise in phase & modulus (rms, mfs, rms_mod, mfs_mod)

default = (0.5, 1.0)

Full.illumination.diversity.power(tuple, float, list)#

Power of modes relative to main mode (zero-layer)

default = 0.1 (>0.0, <1.0)

Full.illumination.diversity.shift(float)#

Lateral shift of modes relative to main mode

[not implemented]

default = None

Full.illumination.model(str, ndarray)#

Type of illumination model

One of: - None : model initialitziation defaults to flat array filled with the specified number of photons - 'recon' : load model from previous reconstruction, see recon Parameters - 'stxm' : Estimate model from autocorrelation of mean diffraction data - <resource> : one of ptypys internal image resource strings - <template> : one of the templates inillumination module

In script, you may pass a numpy.ndarray here directly as the model. It is considered as incoming wavefront and will be propagated according to propagation with an optional aperture applied before.

default = None

Full.illumination.photons(int, float, NoneType)#

Number of photons in the incident illumination

A value specified here will take precedence over calculated statistics from the loaded data.

default = None (>0)

Full.illumination.propagation(Param)#

Parameters for propagation after aperture plane

Propagation to focus takes precedence to parallel propagation if foccused is not None

default = Param({})

Full.illumination.propagation.antialiasing(float)#

Antialiasing factor

Antialiasing factor used when generating the probe. (numbers larger than 2 or 3 are memory hungry) [Untested]

default = 1

Full.illumination.propagation.focussed(NoneType, float)#

Propagation distance from aperture to focus

If None or 0 : No focus propagation

default = None

Full.illumination.propagation.parallel(NoneType, float)#

Parallel propagation distance

If None or 0 : No parallel propagation

default = None

Full.illumination.propagation.spot_size(NoneType, float)#

Focal spot diameter

If not None, this parameter is used to generate the appropriate aperture size instead of size

default = None (>0.0)

Full.illumination.recon(Param)#

Parameters to load from previous reconstruction

default = Param({})

Full.illumination.recon.label(NoneType, str)#

Scan label of diffraction that is to be used for probe estimate

If None, own scan label is used

default = None

Full.illumination.recon.rfile(str)#

Path to a .ptyr compatible file

default = '\\*.ptyr'

Full.sample(Param, str)#: default = Param({})

Full.sample.model(str, ndarray)#

Type of initial object model

One of: - None : model initialitziation defaults to flat array filled fill - 'recon' : load model from STXM analysis of diffraction data - 'stxm' : Estimate model from autocorrelation of mean diffraction data - <resource> : one of ptypys internal model resource strings - <template> : one of the templates in sample module In script, you may pass a numpy.array here directly as the model. This array will be processed according to process in order to simulate a sample from e.g. a thickness profile.

default = None

Full.sample.fill(float, complex)#

Default fill value

default = 1

Full.sample.recon(Param)#

Parameters to load from previous reconstruction

default = Param({})

Full.sample.recon.rfile(str)#

Path to a .ptyr compatible file

default = '\\*.ptyr'

Full.sample.stxm(Param)#

STXM analysis parameters

default = Param({})

Full.sample.stxm.label(str)#

Scan label of diffraction that is to be used for probe estimate

None, own scan label is used

default = None

Full.sample.process(Param, NoneType)#

Model processing parameters

Can be None, i.e. no processing

default = Param({})

Full.sample.process.offset(tuple, list)#

Offset between center of object array and scan pattern

default = (0, 0) (>0.0)

Full.sample.process.zoom(list, tuple, float)#

Zoom value for object simulation.

If None, leave the array untouched. Otherwise the modeled or loaded image will be resized using zoom().

default = None (>0.0)

Full.sample.process.formula(str)#

Chemical formula

A Formula compatible with a cxro database query,e.g. 'Au' or 'NaCl' or 'H2O'

default = None

Full.sample.process.density(float)#

Density in [g/ccm]

Only used if formula is not None

default = 1

Full.sample.process.thickness(float)#

Maximum thickness of sample

If None, the absolute values of loaded source array will be used

default = 1e-06

Full.sample.process.ref_index(list, tuple)#

Assigned refractive index, tuple of format (real, complex)

If None, treat source array as projection of refractive index a+bj for (a, b). If a refractive index is provided the array’s absolute value will be used to scale the refractive index.

default = (0.5, 0.0) (>0.0)

Full.sample.process.smoothing(int)#

Smoothing scale

Smooth the projection with gaussian kernel of width given by smoothing_mfs

default = 2 (>0)

Full.sample.diversity(Param)#

Probe mode(s) diversity parameters

Can be None i.e. no diversity

default = Param({})

Full.sample.diversity.noise(tuple)#

Noise in the generated modes of the illumination

Can be either: - None : no noise - 2-tuple : noise in phase (amplitude (rms), minimum feature size) - 4-tuple : noise in phase & modulus (rms, mfs, rms_mod, mfs_mod)

default = None

Full.sample.diversity.power(tuple, float)#

Power of modes relative to main mode (zero-layer)

default = 0.1

Full.sample.diversity.shift(float)#

Lateral shift of modes relative to main mode

[not implemented]

default = None

Full.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

BlockFull#

BlockFull(Param)#: default = Param({})

BlockFull.name(str)#: default = 'Full'

BlockFull.coherence(Param)#

Coherence parameters

default = Param({}) (>0.0)

BlockFull.coherence.num_probe_modes(int)#

Number of probe modes

default = 1 (>0)

BlockFull.coherence.num_object_modes(int)#

Number of object modes

default = 1 (>0)

BlockFull.coherence.energies(list)#

default = [1.0]

BlockFull.coherence.spectrum(list)#

Amplitude of relative energy bins if the probe modes have a different energy

default = [1.0] (>0.0)

BlockFull.coherence.object_dispersion(str)#

Energy dispersive response of the object

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

BlockFull.coherence.probe_dispersion(str)#

Energy dispersive response of the probe

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

BlockFull.resolution(NoneType, float)#

Will force the reconstruction to adapt to the given resolution, this might lead to cropping/padding in diffraction space which could reduce performance.

Half-period resolution given in [m]

default = None (>0.0)

BlockFull.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

BlockFull.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

BlockFull.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

BlockFull.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

BlockFull.data.name(str)#

Name of the PtyScan subclass to use

default = None

BlockFull.illumination(Param, str)#

Illumination parameters

default = Param({})

BlockFull.illumination.aperture(Param)#

Beam aperture parameters

default = Param({})

BlockFull.illumination.aperture.rotate(float)#

Rotate aperture by this value

default = 0.0

BlockFull.illumination.aperture.central_stop(float)#

size of central stop as a fraction of aperture.size

If not None: places a central beam stop in aperture. The value given here is the fraction of the beam stop compared to size

default = None (>0.0, <1.0)

BlockFull.illumination.aperture.diffuser(tuple)#

Noise in the transparen part of the aperture

Can be either: - None : no noise - 2-tuple : noise in phase (amplitude (rms), minimum feature size) - 4-tuple : noise in phase & modulus (rms, mfs, rms_mod, mfs_mod)

default = None

BlockFull.illumination.aperture.edge(float)#

Edge width of aperture (in pixels!)

default = 2.0

BlockFull.illumination.aperture.form(NoneType, str)#

One of None, ‘rect’ or ‘circ’

One of: - None : no aperture, this may be useful for nearfield - 'rect' : rectangular aperture - 'circ' : circular aperture

default = 'circ'

BlockFull.illumination.aperture.offset(float, tuple, list)#

Offset between center of aperture and optical axes

May also be a tuple (vertical,horizontal) for size in case of an asymmetric offset

default = 0.0

BlockFull.illumination.aperture.size(float, tuple, list)#

Aperture width or diameter

May also be a tuple (vertical,horizontal) in case of an asymmetric aperture

default = None (>0.0)

BlockFull.illumination.diversity(Param, NoneType)#

Probe mode(s) diversity parameters

Can be None i.e. no diversity

default = Param({})

BlockFull.illumination.diversity.noise(tuple, list)#

Noise in each non-primary mode of the illumination.

Can be either: - None : no noise - 2-tuple : noise in phase (amplitude (rms), minimum feature size) - 4-tuple : noise in phase & modulus (rms, mfs, rms_mod, mfs_mod)

default = (0.5, 1.0)

BlockFull.illumination.diversity.power(tuple, float, list)#

Power of modes relative to main mode (zero-layer)

default = 0.1 (>0.0, <1.0)

BlockFull.illumination.diversity.shift(float)#

Lateral shift of modes relative to main mode

[not implemented]

default = None

BlockFull.illumination.model(str, ndarray)#

Type of illumination model

In script, you may pass a numpy.ndarray here directly as the model. It is considered as incoming wavefront and will be propagated according to propagation with an optional aperture applied before.

default = None

BlockFull.illumination.photons(int, float, NoneType)#

Number of photons in the incident illumination

A value specified here will take precedence over calculated statistics from the loaded data.

default = None (>0)

BlockFull.illumination.propagation(Param)#

Parameters for propagation after aperture plane

Propagation to focus takes precedence to parallel propagation if foccused is not None

default = Param({})

BlockFull.illumination.propagation.antialiasing(float)#

Antialiasing factor

Antialiasing factor used when generating the probe. (numbers larger than 2 or 3 are memory hungry) [Untested]

default = 1

BlockFull.illumination.propagation.focussed(NoneType, float)#

Propagation distance from aperture to focus

If None or 0 : No focus propagation

default = None

BlockFull.illumination.propagation.parallel(NoneType, float)#

Parallel propagation distance

If None or 0 : No parallel propagation

default = None

BlockFull.illumination.propagation.spot_size(NoneType, float)#

Focal spot diameter

If not None, this parameter is used to generate the appropriate aperture size instead of size

default = None (>0.0)

BlockFull.illumination.recon(Param)#

Parameters to load from previous reconstruction

default = Param({})

BlockFull.illumination.recon.label(NoneType, str)#

Scan label of diffraction that is to be used for probe estimate

If None, own scan label is used

default = None

BlockFull.illumination.recon.rfile(str)#

Path to a .ptyr compatible file

default = '\\*.ptyr'

BlockFull.sample(Param, str)#: default = Param({})

BlockFull.sample.model(str, ndarray)#

Type of initial object model

default = None

BlockFull.sample.fill(float, complex)#

Default fill value

default = 1

BlockFull.sample.recon(Param)#

Parameters to load from previous reconstruction

default = Param({})

BlockFull.sample.recon.rfile(str)#

Path to a .ptyr compatible file

default = '\\*.ptyr'

BlockFull.sample.stxm(Param)#

STXM analysis parameters

default = Param({})

BlockFull.sample.stxm.label(str)#

Scan label of diffraction that is to be used for probe estimate

None, own scan label is used

default = None

BlockFull.sample.process(Param, NoneType)#

Model processing parameters

Can be None, i.e. no processing

default = Param({})

BlockFull.sample.process.offset(tuple, list)#

Offset between center of object array and scan pattern

default = (0, 0) (>0.0)

BlockFull.sample.process.zoom(list, tuple, float)#

Zoom value for object simulation.

If None, leave the array untouched. Otherwise the modeled or loaded image will be resized using zoom().

default = None (>0.0)

BlockFull.sample.process.formula(str)#

Chemical formula

A Formula compatible with a cxro database query,e.g. 'Au' or 'NaCl' or 'H2O'

default = None

BlockFull.sample.process.density(float)#

Density in [g/ccm]

Only used if formula is not None

default = 1

BlockFull.sample.process.thickness(float)#

Maximum thickness of sample

If None, the absolute values of loaded source array will be used

default = 1e-06

BlockFull.sample.process.ref_index(list, tuple)#

Assigned refractive index, tuple of format (real, complex)

If None, treat source array as projection of refractive index a+bj for (a, b). If a refractive index is provided the array’s absolute value will be used to scale the refractive index.

default = (0.5, 0.0) (>0.0)

BlockFull.sample.process.smoothing(int)#

Smoothing scale

Smooth the projection with gaussian kernel of width given by smoothing_mfs

default = 2 (>0)

BlockFull.sample.diversity(Param)#

Probe mode(s) diversity parameters

Can be None i.e. no diversity

default = Param({})

BlockFull.sample.diversity.noise(tuple)#

Noise in the generated modes of the illumination

Can be either: - None : no noise - 2-tuple : noise in phase (amplitude (rms), minimum feature size) - 4-tuple : noise in phase & modulus (rms, mfs, rms_mod, mfs_mod)

default = None

BlockFull.sample.diversity.power(tuple, float)#

Power of modes relative to main mode (zero-layer)

default = 0.1

BlockFull.sample.diversity.shift(float)#

Lateral shift of modes relative to main mode

[not implemented]

default = None

BlockFull.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

OPRModel#

OPRModel(Param)#: default = Param({})

OPRModel.name(str)#: default = 'Full'

OPRModel.coherence(Param)#

Coherence parameters

default = Param({}) (>0.0)

OPRModel.coherence.num_probe_modes(int)#

Number of probe modes

default = 1 (>0)

OPRModel.coherence.num_object_modes(int)#

Number of object modes

default = 1 (>0)

OPRModel.coherence.energies(list)#

default = [1.0]

OPRModel.coherence.spectrum(list)#

Amplitude of relative energy bins if the probe modes have a different energy

default = [1.0] (>0.0)

OPRModel.coherence.object_dispersion(str)#

Energy dispersive response of the object

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

OPRModel.coherence.probe_dispersion(str)#

Energy dispersive response of the probe

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

OPRModel.resolution(NoneType, float)#

Will force the reconstruction to adapt to the given resolution, this might lead to cropping/padding in diffraction space which could reduce performance.

Half-period resolution given in [m]

default = None (>0.0)

OPRModel.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

OPRModel.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

OPRModel.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

OPRModel.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

OPRModel.data.name(str)#

Name of the PtyScan subclass to use

default = None

OPRModel.illumination(Param, str)#

Container for probe initialization model

default = Param({})

OPRModel.sample(Param, str)#

Container for sample initialization model

default = Param({})

OPRModel.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

BlockOPRModel#

BlockOPRModel(Param)#: default = Param({})

BlockOPRModel.name(str)#: default = 'Full'

BlockOPRModel.coherence(Param)#

Coherence parameters

default = Param({}) (>0.0)

BlockOPRModel.coherence.num_probe_modes(int)#

Number of probe modes

default = 1 (>0)

BlockOPRModel.coherence.num_object_modes(int)#

Number of object modes

default = 1 (>0)

BlockOPRModel.coherence.energies(list)#

default = [1.0]

BlockOPRModel.coherence.spectrum(list)#

Amplitude of relative energy bins if the probe modes have a different energy

default = [1.0] (>0.0)

BlockOPRModel.coherence.object_dispersion(str)#

Energy dispersive response of the object

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

BlockOPRModel.coherence.probe_dispersion(str)#

Energy dispersive response of the probe

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

BlockOPRModel.resolution(NoneType, float)#

Will force the reconstruction to adapt to the given resolution, this might lead to cropping/padding in diffraction space which could reduce performance.

Half-period resolution given in [m]

default = None (>0.0)

BlockOPRModel.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

BlockOPRModel.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

BlockOPRModel.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

BlockOPRModel.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

BlockOPRModel.data.name(str)#

Name of the PtyScan subclass to use

default = None

BlockOPRModel.illumination(Param, str)#

Container for probe initialization model

default = Param({})

BlockOPRModel.sample(Param, str)#

Container for sample initialization model

default = Param({})

BlockOPRModel.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

GradFull#

GradFull(Param)#: default = Param({})

GradFull.name(str)#: default = 'Full'

GradFull.coherence(Param)#

Coherence parameters

default = Param({}) (>0.0)

GradFull.coherence.num_probe_modes(int)#

Number of probe modes

default = 1 (>0)

GradFull.coherence.num_object_modes(int)#

Number of object modes

default = 1 (>0)

GradFull.coherence.energies(list)#

default = [1.0]

GradFull.coherence.spectrum(list)#

Amplitude of relative energy bins if the probe modes have a different energy

default = [1.0] (>0.0)

GradFull.coherence.object_dispersion(str)#

Energy dispersive response of the object

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

GradFull.coherence.probe_dispersion(str)#

Energy dispersive response of the probe

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

GradFull.resolution(NoneType, float)#

Will force the reconstruction to adapt to the given resolution, this might lead to cropping/padding in diffraction space which could reduce performance.

Half-period resolution given in [m]

default = None (>0.0)

GradFull.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

GradFull.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

GradFull.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

GradFull.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

GradFull.data.name(str)#

Name of the PtyScan subclass to use

default = None

GradFull.illumination(Param, str)#

Container for probe initialization model

default = Param({})

GradFull.sample(Param, str)#

Container for sample initialization model

default = Param({})

GradFull.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

BlockGradFull#

BlockGradFull(Param)#: default = Param({})

BlockGradFull.name(str)#: default = 'Full'

BlockGradFull.coherence(Param)#

Coherence parameters

default = Param({}) (>0.0)

BlockGradFull.coherence.num_probe_modes(int)#

Number of probe modes

default = 1 (>0)

BlockGradFull.coherence.num_object_modes(int)#

Number of object modes

default = 1 (>0)

BlockGradFull.coherence.energies(list)#

default = [1.0]

BlockGradFull.coherence.spectrum(list)#

Amplitude of relative energy bins if the probe modes have a different energy

default = [1.0] (>0.0)

BlockGradFull.coherence.object_dispersion(str)#

Energy dispersive response of the object

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

BlockGradFull.coherence.probe_dispersion(str)#

Energy dispersive response of the probe

One of: - None or 'achromatic': no dispersion - 'linear': linear response model - 'irregular': no assumption [not implemented]

default = None

BlockGradFull.resolution(NoneType, float)#

Will force the reconstruction to adapt to the given resolution, this might lead to cropping/padding in diffraction space which could reduce performance.

Half-period resolution given in [m]

default = None (>0.0)

BlockGradFull.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

BlockGradFull.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

BlockGradFull.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

BlockGradFull.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

BlockGradFull.data.name(str)#

Name of the PtyScan subclass to use

default = None

BlockGradFull.illumination(Param, str)#

Container for probe initialization model

default = Param({})

BlockGradFull.sample(Param, str)#

Container for sample initialization model

default = Param({})

BlockGradFull.resample(int, NoneType)#

Resampling fraction of the image frames w.r.t. diffraction frames

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1

Bragg3dModel#

Bragg3dModel(Param)#: default = Param({})

Bragg3dModel.illumination(Param, str)#

Container for probe initialization model

default = Param({})

Bragg3dModel.illumination.aperture(Param)#

Beam aperture parameters

default = Param({})

Bragg3dModel.illumination.aperture.rotate(float)#

Rotate aperture by this value

default = 0.0

Bragg3dModel.illumination.aperture.central_stop(float)#

size of central stop as a fraction of aperture.size

If not None: places a central beam stop in aperture. The value given here is the fraction of the beam stop compared to size

default = None (>0.0, <1.0)

Bragg3dModel.illumination.aperture.diffuser(tuple)#

Noise in the transparen part of the aperture

Can be either: - None : no noise - 2-tuple : noise in phase (amplitude (rms), minimum feature size) - 4-tuple : noise in phase & modulus (rms, mfs, rms_mod, mfs_mod)

default = None

Bragg3dModel.illumination.aperture.edge(float)#

Edge width of aperture (in pixels!)

default = 2.0

Bragg3dModel.illumination.aperture.form(NoneType, str)#

One of None, ‘rect’ or ‘circ’

One of: - None : no aperture, this may be useful for nearfield - 'rect' : rectangular aperture - 'circ' : circular aperture

default = 'circ'

Bragg3dModel.illumination.aperture.offset(float, tuple, list)#

Offset between center of aperture and optical axes

May also be a tuple (vertical,horizontal) for size in case of an asymmetric offset

default = 0.0

Bragg3dModel.illumination.aperture.size(float, tuple, list)#

Aperture width or diameter

May also be a tuple (vertical,horizontal) in case of an asymmetric aperture

default = None (>0.0)

Bragg3dModel.illumination.model(str, ndarray)#

Type of illumination model

In script, you may pass a numpy.ndarray here directly as the model. It is considered as incoming wavefront and will be propagated according to propagation with an optional aperture applied before.

default = None

Bragg3dModel.illumination.photons(int, float, NoneType)#

Number of photons in the incident illumination

A value specified here will take precedence over calculated statistics from the loaded data.

default = None (>0)

Bragg3dModel.illumination.propagation(Param)#

Parameters for propagation after aperture plane

Propagation to focus takes precedence to parallel propagation if foccused is not None

default = Param({})

Bragg3dModel.illumination.propagation.antialiasing(float)#

Antialiasing factor

Antialiasing factor used when generating the probe. (numbers larger than 2 or 3 are memory hungry) [Untested]

default = 1

Bragg3dModel.illumination.propagation.focussed(NoneType, float)#

Propagation distance from aperture to focus

If None or 0 : No focus propagation

default = None

Bragg3dModel.illumination.propagation.parallel(NoneType, float)#

Parallel propagation distance

If None or 0 : No parallel propagation

default = None

Bragg3dModel.illumination.propagation.spot_size(NoneType, float)#

Focal spot diameter

If not None, this parameter is used to generate the appropriate aperture size instead of size

default = None (>0.0)

Bragg3dModel.illumination.recon(Param)#

Parameters to load from previous reconstruction

default = Param({})

Bragg3dModel.illumination.recon.label(NoneType, str)#

Scan label of diffraction that is to be used for probe estimate

If None, own scan label is used

default = None

Bragg3dModel.illumination.recon.rfile(str)#

Path to a .ptyr compatible file

default = '\\*.ptyr'

Bragg3dModel.illumination.size(float)#

Initial probe size

The probe is initialized as a flat circle.

default = None

Bragg3dModel.name(str)#: default = 'Bragg3dModel'

Bragg3dModel.tags(list)#

Comma seperated string tags describing the data input

[deprecated?]

default = ['dummy']

Bragg3dModel.propagation(str)#

Propagation type

Either “farfield” or “nearfield”

default = 'farfield'

Bragg3dModel.ffttype(str)#

FFT library

Choose from “numpy”, “scipy” or “fftw”

default = 'scipy'

Bragg3dModel.data(Param)#

Link to container for data preparation

default = scandata.PtyScan

Bragg3dModel.data.name(str)#

Name of the PtyScan subclass to use

default = None

Bragg3dModel.sample(Param, str)#

Container for sample initialization model

default = Param({})

Bragg3dModel.sample.fill(float, complex)#

Initial sample value

The sample is initialized with this value everywhere.

default = 1

Bragg3dModel.resample(int, NoneType)#

Diffraction resampling CURRENTLY NOT SUPPORTED FOR BRAGG CASE

A resampling of 2 means that the image frame is to be sampled (in the detector plane) twice as densely as the raw diffraction data.

default = 1