napari_dmc_brainmap.preprocessing package

Submodules

napari_dmc_brainmap.preprocessing.preprocessing module

DMC-BrainMap widget for preprocessing of .tif files.

2024 - FJ

class napari_dmc_brainmap.preprocessing.preprocessing.PreprocessingWidget(parent: QWidget | None = None)[source]

Bases: QWidget

QWidget for configuring and performing preprocessing operations.

progress_signal

Signal emitted to update the progress bar with an integer value.

napari_dmc_brainmap.preprocessing.preprocessing.create_general_widget(widget_type: str, channels: List[str], downsampling_default: int = 3, contrast_limits: Dict[str, str] | None = None) → Container[source]

Create a generalized MagicGUI widget for image processing.

Parameters:

  • widget_type (str) – The type of widget being created (e.g., ‘RGB’, ‘Single Channel’).

  • channels (List[str]) – List of available channels to select.

  • downsampling_default (int) – Default value for the downsampling factor.

  • contrast_limits (Optional[Dict[str, str]]) – Default contrast limit values for each channel.

Returns:

The created MagicGUI widget container.

Return type:

widgets.Container

napari_dmc_brainmap.preprocessing.preprocessing.do_preprocessing(input_path: Path, channels: List[str], img_list: List[str], preprocessing_params: Dict[str, str | dict], resolution: Tuple[int, int], save_dirs: Dict[str, str]) → str[source]

Perform preprocessing on a list of images in a multithreaded manner.

Parameters:

  • input_path (Path) – Path to the input directory containing images.

  • channels (List[str]) – List of channels to process.

  • img_list (List[str]) – List of image file names to process.

  • preprocessing_params (Dict[str, Union[str, dict]]) – Parameters for preprocessing operations.

  • resolution (Tuple[int, int]) – Tuple containing resolution information for preprocessing.

  • save_dirs (Dict[str, str]) – Dictionary containing paths to save preprocessed images.

Yields:

int – Progress of the preprocessing operation in percentage.

Returns:

Animal ID for which preprocessing was performed.

Return type:

str

napari_dmc_brainmap.preprocessing.preprocessing.initialize_header_widget() → FunctionGui[source]

Initialize a header widget for selecting the input path and imaged channels.

Returns:

The initialized header widget.

Return type:

FunctionGui

napari_dmc_brainmap.preprocessing.preprocessing_tools module

napari_dmc_brainmap.preprocessing.preprocessing_tools.chunk_list(input_list: List[str], chunk_size: int = 4) → List[List[str]][source]

Split a list into smaller chunks of a specified size.

Parameters:

  • input_list (List[str]) – The list to be divided into chunks.

  • chunk_size (int) – The maximum size of each chunk. Default is 4.

Returns:

A list containing smaller lists (chunks).

Return type:

List[List[str]]

napari_dmc_brainmap.preprocessing.preprocessing_tools.create_dirs(params: Dict[str, str | dict], input_path: str | Path) → Dict[str, Path][source]

Create directories for saving processed images based on given parameters.

Parameters:

  • params (Dict[str, Union[str, dict]]) – Preprocessing parameters including operations and channels.

  • input_path (Union[str, Path]) – The base path to the input directory.

Returns:

Dictionary with operation names as keys and created directory paths as values.

Return type:

Dict[str, Path]

napari_dmc_brainmap.preprocessing.preprocessing_tools.do_8bit(data: ndarray) → ndarray[source]

Convert a 16-bit image to 8-bit format.

Parameters:

data (np.ndarray) – Input image in 16-bit or 8-bit format.

Returns:

Converted 8-bit image.

Return type:

np.ndarray

Raises:

TypeError – If the input data is neither uint16 nor uint8.

napari_dmc_brainmap.preprocessing.preprocessing_tools.downsample_and_adjust_contrast(image: ndarray, params: Dict[str, str | list], scale_key: str, contrast_key: str) → ndarray[source]

Downsample and adjust contrast of an image.

Parameters:

  • image (np.ndarray) – Input image to process.

  • params (Dict[str, Union[str, list]]) – Parameters for scaling and contrast adjustment.

  • scale_key (str) – Key to retrieve downsampling factor.

  • contrast_key (str) – Key to retrieve contrast limits.

Returns:

Processed image after downsampling and contrast adjustment.

Return type:

np.ndarray

napari_dmc_brainmap.preprocessing.preprocessing_tools.get_channels(params: Dict[str, str | dict]) → List[str][source]

Extract a unique list of channels from preprocessing parameters.

Parameters:

params (Dict[str, Union[str, dict]]) – Preprocessing parameters including operations and channels.

Returns:

List of unique channels to be processed.

Return type:

List[str]

napari_dmc_brainmap.preprocessing.preprocessing_tools.load_stitched_images(input_path: str | Path, chan: str, image: str) → ndarray | bool[source]

Load a stitched image file from the specified directory.

Parameters:

  • input_path (Union[str, Path]) – Path to the directory containing images.

  • chan (str) – Channel name.

  • image (str) – Image name (excluding suffix).

Returns:

Loaded image as a NumPy array, or False if the image is not found.

Return type:

Union[np.ndarray, bool]

napari_dmc_brainmap.preprocessing.preprocessing_tools.make_binary(stack_dict: Dict[str, ndarray], params: Dict[str, str | dict], im: str, save_dirs: Dict[str, Path], resolution_tuple: Tuple[int, int]) → None[source]

Create binary images for each channel based on a threshold.

Parameters:

  • stack_dict (Dict[str, np.ndarray]) – Dictionary containing channel image stacks.

  • params (Dict[str, Union[str, dict]]) – Parameters for processing.

  • im (str) – Image name.

  • save_dirs (Dict[str, Path]) – Directories for saving processed images.

  • resolution_tuple (Tuple[int, int]) – Desired resolution for the output image.

napari_dmc_brainmap.preprocessing.preprocessing_tools.make_rgb(stack_dict: Dict[str, ndarray], params: Dict[str, str | dict], im: str, save_dirs: Dict[str, Path], resolution_tuple) → None[source]

Create an RGB image from a stack of different channel images.

Parameters:

  • stack_dict (Dict[str, np.ndarray]) – Dictionary containing channel image stacks.

  • params (Dict[str, Union[str, dict]]) – Parameters for processing.

  • im (str) – Image name.

  • save_dirs (Dict[str, Path]) – Save directories for processed images.

  • resolution_tuple – Tuple indicating the resolution.

napari_dmc_brainmap.preprocessing.preprocessing_tools.make_sharpy_track(stack_dict: Dict[str, ndarray], params: Dict[str, str | dict], im: str, save_dirs: Dict[str, str], resolution_tuple) → None[source]

Create Sharpy-track images from a stack of channel images.

Parameters: - stack_dict (Dict[str, np.ndarray]): Dictionary containing channel image stacks. - params (Dict[str, Union[str, dict]]): Parameters for processing. - im (str): Image name. - save_dirs (Dict[str, str]): Save directories for processed images. - resolution_tuple: Tuple indicating the resolution.

napari_dmc_brainmap.preprocessing.preprocessing_tools.make_single_channel(stack_dict: Dict[str, ndarray], params: Dict[str, str | dict], im: str, save_dirs: Dict[str, Path], resolution_tuple) → None[source]

Create single-channel images from a stack of channel images.

Parameters:

  • stack_dict (Dict[str, np.ndarray]) – Dictionary containing channel image stacks.

  • params (Dict[str, Union[str, dict]]) – Parameters for processing.

  • im (str) – Image name.

  • save_dirs (Dict[str, Path]) – Save directories for processed images.

  • resolution_tuple – Tuple indicating the resolution.

napari_dmc_brainmap.preprocessing.preprocessing_tools.make_stack(stack_dict: Dict[str, ndarray], params: Dict[str, str | dict], im: str, save_dirs: Dict[str, Path], resolution_tuple) → None[source]

Create a z-stack of images from a dictionary of channel images.

Parameters:

  • stack_dict (Dict[str, np.ndarray]) – Dictionary containing channel image stacks.

  • params (Dict[str, Union[str, dict]]) – Parameters for processing.

  • im (str) – Image name.

  • save_dirs (Dict[str, Path]) – Save directories for processed images.

  • resolution_tuple – Tuple indicating the resolution.

napari_dmc_brainmap.preprocessing.preprocessing_tools.preprocess_images(im: str, channels: List[str], input_path, params: Dict[str, str | dict], save_dirs: Dict[str, str], resolution_tuple) → None[source]

Preprocess images for a given set of operations and channels.

Parameters:

  • im (str) – Image name.

  • channels (List[str]) – List of channels to process.

  • input_path (Union[str, Path]) – Path to the input directory containing images.

  • params (Dict[str, Union[str, dict]]) – Parameters for preprocessing operations.

  • save_dirs (Dict[str, Path]) – Directories for saving processed images.

  • resolution_tuple (Tuple[int, int]) – Desired resolution for the output images.

napari_dmc_brainmap.preprocessing.preprocessing_tools.save_zstack(path: str | Path, stack_dict: Dict[str, ndarray]) → None[source]

Save a z-stack of images to a file.

Parameters:

  • path (Union[str, Path]) – File path to save the z-stack.

  • stack_dict (Dict[str, np.ndarray]) – Dictionary of z-stack images.

napari_dmc_brainmap.preprocessing.preprocessing_tools.select_chans(chan_list: List[str], filter_list: List[str], operation: str) → List[str][source]

Select valid channels for a given operation.

Parameters:

  • chan_list (List[str]) – List of requested channels.

  • filter_list (List[str]) – List of available channels.

  • operation (str) – Name of the operation.

Returns:

List of selected channels.

Return type:

List[str]

Module contents