STParams#

class pyrost.simulation.STParams(defocus, det_dist, n_frames, step_size, step_rnd, detx_size, dety_size, pix_size, p0, th_s, wl, alpha, ap_x, ap_y, focus, ab_cnt, bar_atn, bar_rnd, bar_sigma, bar_size, bulk_atn, offset, num_threads=0, seed=0)#

Container with the simulation parameters for the wavefront propagation.

Parameters

barcode –
A dictionary of barcode sample parameters. The following elements are accepted:
- bar_size : Average bar’s size [um].
- bar_sigma : Bar bluriness width [um].
- bar_atn : Bar’s attenuation coefficient [0.0 - 1.0].
- bulk_atn : Barcode’s bulk attenuation coefficient [0.0 - 1.0].
- bar_rnd : Bar’s coordinates random deviation [0.0 - 1.0].
- offsetBarcode’s offset at the beginning and at the end
  of the scan from the detector’s bounds [um].
detector –
A dictionary of detector parameters. The following elements are accepted:
- detx_size : Detector’s size along the horizontal axis in pixels.
- dety_size : Detector’s size along the vertical axis in pixels.
- pix_size : Detector’s pixel size [um].
exp_geom –
A dictionary of experimental geometry parameters. The following elements are accepted:
- defocus : Lens’ defocus distance [um].
- det_dist : Distance between the barcode and the detector [um].
- step_size : Scan step size [um].
- n_frames : Number of frames.
lens –
A dictionary of lens parameters. The following elements are accepted:
- ap_x : Lens’ aperture size along the x axis [um].
- ap_y : Lens’ aperture size along the y axis [um].
- focus : Focal distance [um].
- alpha : Third order aberrations coefficient [rad / mrad^3].
- ab_cnt : Lens’ aberrations center point [0.0 - 1.0].
source –
A dictionary of X-ray source parameters. The following elements are accepted:
- p0 : Source beam flux [cnt / s].
- wl : Source beam’s wavelength [um].
- th_s : Source rocking curve width [rad].
system –
A dictionary of calculation parameters. The following elements are accepted:
- seed : Seed used in all the pseudo-random number generations.
- num_threads : Number of threads used in the calculations.

See also

pyrost.bin.barcode_profile() : Full details of barcode’s transmission profile generation algorithm.

beam_span(dist)#

Return beam span along the x axis at distance dist from the focal plane.

Parameters

dist (float) – Distance from the focal plane [um].

Return type

Tuple[float, float]

Returns

Tuple of two items (‘th_lb’, ‘th_ub’). The elements are the following:

th_lb : Beam’s lower bound [um].
th_ub : Beam’s upper bound [um].

contents()#

Return a list of the attributes stored in the container that are initialised.

Return type: List[str]
Returns: List of the attributes stored in the container.

get(attr, value=None)#

Retrieve a dataset, return value if the attribute is not found.

Parameters

attr (str) – Data attribute.
value (Optional[Any]) – Data which is returned if the attribute is not found.

Return type

Any

Returns

Attribute’s data stored in the container, value if attr is not found.

classmethod import_default()#

Return the default STParams. Extra arguments override the default values if provided.

Return type: STParams
Returns: An STParams object with the default parameters.

classmethod import_ini(ini_file)#

Initialize the container object with an INI file ini_file.

Parameters: ini_file (str) – Path to the ini file.
Return type: ~I
Returns: A new container with all the attributes imported from the ini file.

items()#

Return (key, value) pairs of the datasets stored in the container.

Return type: ItemsView
Returns: (key, value) pairs of the datasets stored in the container.

keys()#

Return a list of the attributes available in the container.

Return type: List[str]
Returns: List of the attributes available in the container.

lens_x_wavefront(n_x=None, return_step=False)#

Return wavefields at the lens plane along x axis.

Parameters

n_x (Optional[int]) – Array size along the x axis. Equals to STParams.x_wavefront_size() if it’s None.
return_step (bool) – Return the step size along x axis if it’s True.

Return type

Tuple[ndarray, float]

Returns

A tuple of two elements (‘u0_x’, ‘dx’). The elements are the following:

u0_x : Wavefront along the x axis.
dx : Step size along the x axis [um]. Only if return_step is True.

Notes

The exit-surface at the lens plane:

\[U_0(x) = \Pi(a_x x) \exp \left[ -\frac{j \pi x^2}{\lambda f} + j \alpha \left( \frac{x - x_{ab_cnt}}{f} \right)^3 \right]\]

lens_y_wavefront(n_y=None, return_step=False)#

Return wavefields at the lens plane along y axis.

Parameters

n_y (Optional[int]) – Array size along the y axis. Equals to STParams.y_wavefront_size() if it’s None.
return_step (bool) – Return the step size along y axis if it’s True.

Return type

Tuple[ndarray, float]

Returns

A tuple of two elements (‘u0_y’, ‘dy’). The elements are the following:

u0_y : Wavefront along the y axis.
dy : Step size along the y axis [um]. Only if return_step is True.

Notes

The exit-surface at the lens plane:

\[U_0(y) = \Pi(a_y y)\]

replace(**kwargs)#

Return a new container object with a set of attributes replaced.

Parameters: kwargs (Any) – A set of attributes and the values to to replace.
Return type: ~D
Returns: A new container object with updated attributes.

sample_positions()#

Generate an array of sample’s translations with random deviation.

Return type: ndarray
Returns: Array of sample translations [um].

source_curve(dist, step)#

Return source’s rocking curve profile at dist distance from the lens.

Parameters

dist (float) – Distance from the lens to the rocking curve profile [um].
step (float) – Sampling interval [um].

Return type

ndarray

Returns

Source’s rocking curve profile.

static str_to_list(strings)#

Convert strings to a list of strings.

Parameters: strings (Union[str, List[str]]) – String or a list of strings
Return type: List[str]
Returns: List of strings.

to_ini(ini_file)#

Save all the attributes stored in the container to an INI file ini_file.

Parameters: ini_file (str) – Path to the ini file.

update_seed(seed=None)#

Update seed used in pseudo-random number generation.

Parameters: seed (Optional[int]) – New seed value. Chosen randomly if None.

update_threads(num_threads=None)#

Update number of threads used in calculcations.

Parameters: num_threads (Optional[int]) – Number of threads used in the computations.

values()#

Return the attributes’ data stored in the container.

Return type: ValuesView
Returns: List of data stored in the container.

x_wavefront_size()#

Return wavefront array size along the x axis, that satisfies the sampling condition.

Return type: int
Returns: Array size.

Notes

The sampling condition when we propagate the wavefield from the lens plane to the sample plane is as follows:

\[N_x >= \frac{\mathrm{max} \left( \Delta x_{lens}, \Delta x_{sample} \right) (\Delta x_{lens} + \Delta x_{sample})}{\lambda d} = \frac{4 a_x^2 \mathrm{max} \left( f, df \right)}{f^2 \lambda}\]

Whereupon, the sampling condition when we propagate the wavefield to the detector plane is:

\[N_x >= \frac{\Delta x_{sample} \Delta x_{det}}{\lambda d} = \frac{2 a_x n_{x} \Delta_{pix} df}{f \lambda d_{det}}\]

y_wavefront_size()#

Return wavefront array size along the y axis, that satisfies the sampling condition.

Return type: int
Returns: Array size.

Notes

The sampling condition when we propagate the wavefield from the lens plane to the sample plane is as follows:

\[N_y >= \frac{\mathrm{max} \left( \Delta y_{lens}, \Delta y_{sample} \right) (\Delta y_{lens} + \Delta y_{sample})}{\lambda d} = \frac{8 a_y^2}{(f + df) \lambda}\]

Whereupon, the sampling condition when we propagate the wavefield to the detector plane is:

\[N_y >= \frac{\Delta y_{sample} \Delta y_{det}}{\lambda d} = \frac{2 a_y n_{y} \Delta_{pix}}{\lambda d_{det}}\]