nanopyx.core.transform.error_map

class ErrorMap:
ErrorMap(*args, **kwargs)
def optimise( self, img_ref: numpy.ndarray, img_sr: numpy.ndarray, fixedSigma=0) -> None:
def getRSE(self) -> float:
def getRSP(self) -> float:
def get_sigma(self) -> float:
imRSE
img_ref
img_sr
im_sr_intensity_scaled_blurred
def calculate_alpha_beta(sigma: float, imRef: numpy.ndarray, imSR: numpy.ndarray) -> tuple:

Gaussian blurs imSR image and calculates linear regressino again imRef

Args: sigma (float): gaussian blur sigma imRef (np.ndarray): reference image (generally a difraction limited equivalent) imSR (np.ndarray): super-resolution image

Returns: tuple[float, float]: alpha and beta for linear regression

def sigma_function_to_optimize(sigma: float, imRef: numpy.ndarray, imSR: numpy.ndarray) -> float: