nabu.io.utils module

nabu.io.utils.get_compacted_dataslices(urls, subsampling=None, begin=0)

Regroup urls to get the data more efficiently. Build a structure mapping files indices to information on how to load the data: {indices_set: data_location} where data_location contains contiguous indices.

Parameters:

• urls (dict) – Dictionary where the key is an integer and the value is a silx DataUrl.

• subsampling (int, optional) – Subsampling factor when reading the frames. If an integer n is provided, then one frame out of n will be read.

Returns:

merged_urls – Dictionary with the same keys as the urls parameter, and where the values are the corresponding silx.io.url.DataUrl with merged data_slice.

Return type:

dict

nabu.io.utils.get_first_hdf5_entry(fname)

nabu.io.utils.hdf5_entry_exists(fname, entry)

nabu.io.utils.get_h5_value(fname, h5_path, default_ret=None)

nabu.io.utils.get_h5_str_value(dataset_ptr)

Get a HDF5 field which can be bytes or str (depending on h5py version !).

nabu.io.utils.create_dict_of_indices(images_stack, images_indices)

From an image stack with the images indices, create a dictionary where each index is the image index, and the value is the corresponding image.

Parameters:

• images_stack (numpy.ndarray) – A 3D numpy array in the layout (n_images, n_y, n_x)

• images_indices (array or list of int) – Array containing the indices of images in the stack

Examples

Given a simple array stack:

>>> images_stack = np.arange(3*4*5).reshape((3,4,5))
... images_indices = [2, 7, 1]
... create_dict_of_indices(images_stack, images_indices)
... # returns {2: array1, 7: array2, 1: array3}

nabu.io.utils.convert_dict_values(dic, val_replacements, bytes_tostring=False)

Modify a dictionary to be able to export it with silx.io.dicttoh5

class nabu.io.utils.EntryReader(url: DataUrl)

Bases: _BaseReader

Context manager used to read a bliss node

class nabu.io.utils.DatasetReader(url: DataUrl)

Bases: _BaseReader

Context manager used to read a bliss node

nabu.io.utils.file_format_is_edf(file_format: str)

nabu.io.utils.file_format_is_jp2k(file_format: str)

nabu.io.utils.file_format_is_tiff(file_format: str)

nabu.io.utils.file_format_is_hdf5(file_format: str)

nabu.io.utils.get_output_volume(location: str, file_prefix: str | None, file_format: str, multitiff=False) → VolumeBase