pypty.dpc

get_curl

Compute the standard deviation of the curl of a rotated DPC vector field. This is the objective function for minimization. This particular function was copied from a DPC plugin written by Jordan Hachtel.

PARAMETER	DESCRIPTION
angle	Rotation angle in radians. TYPE: float
dpcx	X-component of the DPC signal. TYPE: ndarray
dpcy	Y-component of the DPC signal. TYPE: ndarray

RETURNS	DESCRIPTION
float	Standard deviation of the curl after rotation.

get_curl_derivative

Compute the derivative of the curl-based objective function with respect to rotation angle.

PARAMETER	DESCRIPTION
angle	Rotation angle in radians. TYPE: float
dpcx	X-component of the DPC signal. TYPE: ndarray
dpcy	Y-component of the DPC signal. TYPE: ndarray

RETURNS	DESCRIPTION
float	Derivative of the curl-based objective function.

GetPLRotation

Estimate rotation angle that minimizes the curl of the DPC signal.

PARAMETER	DESCRIPTION
dpcx	X-component of the DPC signal (2D array). TYPE: ndarray
dpcy	Y-component of the DPC signal (2D array). TYPE: ndarray

RETURNS	DESCRIPTION
float	Optimal rotation angle in radians.

fft_based_dpc

FFT-based DPC phase reconstruction. If you setted up the pypty_params properly, you would only need to specify the hpass and lpass values, both are non-negative floats.

PARAMETER	DESCRIPTION
pypty_params	PyPty parameter dictionary with dataset and calibration settings. TYPE: dict
hpass	High-pass filtering coefficient (default is 0). TYPE: float DEFAULT: 0
lpass	Low-pass filtering coefficient (default is 0). TYPE: float DEFAULT: 0
save	Whether to save the reconstructed phase (default is False). TYPE: bool DEFAULT: False
comx	Precomputed center-of-mass x-component. TYPE: ndarray or None DEFAULT: None
comy	Precomputed center-of-mass y-component. TYPE: ndarray or None DEFAULT: None
plot	If True, display the phase reconstruction. TYPE: bool DEFAULT: False

RETURNS	DESCRIPTION
pot	Reconstructed 2D phase image. TYPE: ndarray
pypty_params	Updated parameter dictionary with computed COM and rotation angle. TYPE: dict

iterative_dpc

Iterative DPC phase reconstruction. If you setted up the pypty_params properly, you would only need to specify the hpass and lpass values, both are non-negative floats.

PARAMETER	DESCRIPTION
pypty_params	PyPty parameter dictionary. TYPE: dict
num_iterations	Number of gradient descent iterations (default is 100). TYPE: int DEFAULT: 100
beta	Step reduction factor for backtracking (default is 0.5). TYPE: float DEFAULT: 0.5
hpass	High-pass filtering coefficient (default is 0). TYPE: float DEFAULT: 0
lpass	Low-pass filtering coefficient (default is 0). TYPE: float DEFAULT: 0
step_size	Initial gradient descent step size (default is 0.1). TYPE: float DEFAULT: 0.1
COMx	X-component of COM map. TYPE: ndarray or None DEFAULT: None
COMy	Y-component of COM map. TYPE: ndarray or None DEFAULT: None
px_size	Scan step size in Ångströms. TYPE: float or None DEFAULT: None
print_flag	Whether to print progress information (default is False). TYPE: bool DEFAULT: False
save	Whether to save the result to disk (default is False). TYPE: bool DEFAULT: False
select	Optional binary mask to constrain reconstruction. TYPE: ndarray or None DEFAULT: None
plot	If True, plot the reconstruction result. TYPE: bool DEFAULT: True
use_backtracking	Whether to use backtracking line search (default is True). TYPE: bool DEFAULT: True
pad_width	Padding width to suppress FFT boundary artifacts (default is 5). TYPE: int DEFAULT: 5

RETURNS	DESCRIPTION
padded_phase	Reconstructed 2D phase image. TYPE: ndarray

iterative_poisson_solver

Iterative solver for Poisson equation given a Laplacian map.

PARAMETER	DESCRIPTION
laplace	Input 2D array representing the Laplacian of the desired phase. TYPE: ndarray
num_iterations	Number of iterations (default is 100). TYPE: int DEFAULT: 100
beta	Step size reduction factor (default is 0.5). TYPE: float DEFAULT: 0.5
hpass	High-pass filtering parameter (default is 0). TYPE: float DEFAULT: 0
lpass	Low-pass filtering parameter (default is 0). TYPE: float DEFAULT: 0
select	Optional binary mask to restrict updates. TYPE: ndarray or None DEFAULT: None
px_size	Pixel size in Ångströms (default is 1). TYPE: float DEFAULT: 1
print_flag	If True, print convergence status (default is False). TYPE: bool DEFAULT: False
step_size	Initial gradient descent step size (default is 0.1). TYPE: float DEFAULT: 0.1
use_backtracking	Whether to use backtracking line search (default is True). TYPE: bool DEFAULT: True
pad_width	Number of pixels to pad around the solution (default is 1). TYPE: int DEFAULT: 1
xp	Backend array library (NumPy or CuPy, default is NumPy). TYPE: module DEFAULT: numpy

RETURNS	DESCRIPTION
ndarray	Reconstructed 2D phase from the input Laplacian.