linumpy.io.thorlabs#

ThorOCT module for handling OCT data from ThorLabs PSOCT microscopes.

Classes#

`PreprocessingConfig`	Configuration for preprocessing OCT data.
`ThorOCT`	Handle OCT data from ThorLabs PSOCT microscopes.

Module Contents#

class linumpy.io.thorlabs.PreprocessingConfig[source]#

Configuration for preprocessing OCT data.

Variables:

(bool) (return_complex) – If True, return the raw complex data. If False, return its magnitude instead.
default=320) (crop_first_index (int,) – Index along the first dimension (depth) at which to start cropping.
default=750) (crop_second_index (int,) – Index along the first dimension (depth) at which to end cropping.
default=True) (erase_polarization_2 (bool,) – If True, discard the original raw data array after extracting the complex data.
default=False) (erase_polarization_1 (bool,) – If True, do not keep polarization-1 data in memory.
default=True) – If True, do not keep polarization-2 data in memory.

return_complex: bool[source]#

crop_first_index: int = 320[source]#

crop_second_index: int = 750[source]#

erase_raw_data: bool = True[source]#

erase_polarization_1: bool = False[source]#

erase_polarization_2: bool = True[source]#

class linumpy.io.thorlabs.ThorOCT(path=None, compressed_data=None, config=None)[source]#

Handle OCT data from ThorLabs PSOCT microscopes.

Provides methods to load, process, and extract metadata and data from compressed files.

Parameters:

(str) (path)
(zipfile.ZipFile) (compressed_data)
(PreprocessingConfig) (config)
path (pathlib.Path | None)
compressed_data (zipfile.ZipFile | None)
config (PreprocessingConfig | None)

Variables:

(np.ndarray) (second_polarization)
(np.ndarray)
(int) (ascan_averaging_value)
(int)
(int)
(xml.dom.minidom.Document) (header)
(list) (resolution)
(int)

path = None[source]#

compressed_data[source]#

first_polarization: numpy.ndarray | None = None[source]#

second_polarization: numpy.ndarray | None = None[source]#

size_x = None[source]#

size_y = None[source]#

size_z = None[source]#

header = None[source]#

resolution = [][source]#

ascan_averaging_value = None[source]#

config = None[source]#

load()[source]#

Load the data from the compressed file and extract the header and the complex data.

Raises:: ValueError – If no valid data source is provided.:
Return type:: None

load_and_process(file)[source]#

Load raw data from the file and preprocess it.

Parameters:: file (str) – File path in the compressed data.
Returns:: Fully processed data array.
Return type:: np.ndarray

static extract_positions_from_scan(scan_file_path=None)[source]#

Extract the raw and index x, y positions from the .scan file.

Parameters:: scan_file_path (str or None) – Path to the .scan file.
Returns:: - tuple
Return type:: A tuple containing two lists - index positions and raw positions.

static get_psoct_tiles_ids(tiles_directory, number_of_angles=2)[source]#

Get the .scan file and all .oct files from the tiles_directory.

Parameters:

tiles_directory (str) – Path to the directory containing the OCT tiles.
number_of_angles (int) – Number of acquisition angles.

Returns:

- positions (positions of the tiles in 3d)
- grouped_files (list of file paths ordered by angles.)

Raises:

- ValueError – If the directory or required files are missing.:

Return type:

tuple

static orient_volume_psoct(vol)[source]#

Transform the volume to RAS orientation.

Parameters:: vol (numpy.ndarray)
Return type:: numpy.ndarray