Module qute.preprocess

Preprocessing functions.

Functions

def extract_fft_stats(image_list: list) ‑> tuple

Returns global min and max values for the real and imaginary parts of the Fourier transforms of all images.

Parameters

image_list : list

List of paths for the intensity TIFF images.

Returns

mean_real: global mean of all real parts from all Fourier transforms. std_real: global std of all real parts from all Fourier transforms. mean_imag: global mean of all imaginary parts from all Fourier transforms. std_imag: global std of all imaginary parts from all Fourier transforms.

def extract_intensity_stats(image_list: list, mask_list: list, fg_classes: Optional[list] = None, low_perc: float = 0.5, high_perc: float = 99.5) ‑> tuple

Returns min, max, low and high percentile of intensities over foreground classes.

Parameters

image_list : list

List of paths for the intensity TIFF images.

mask_list : list

List of paths for the mask TIFF images. Importantly, label image at index i must correspond to intensity image at index i.

fg_classes : Optional[list[int]]

List of foreground classes to be considered to extract the intensities to process. If omitted, all classes but 0 (background) will be used.

low_perc : Optional[float]

Low percentile. Default 0.5

high_perc : Optional[float]

High percentile. Default 99.5

Please note: the image lists are supposed to be sorted so that the ith element of one list matches the ith element of the other.

Returns

mean : global mean foreground intensity

 

std : global standard deviation of the foreground intensities

 

p_low : low percentile of all foreground intensities

 

p_high : high percentile of all foreground intensities

 

def extract_median_object_size(label_list: list) ‑> tuple[float, float, float]

Returns the median size of all labels.

Parameters

label_list : list

List of paths for the label TIFF images.

Returns

mn : float

Min size of all objects.

med : float

Median size of all labels.

mx : float

Max size of all labels.