Skip to main content

Read Leica image files (LIF)

Project description

Liffile is a Python library to read image and metadata from Leica image files (LIF). LIF files are written by LAS X software to store collections of images and metadata from microscopy experiments.

Author:

Christoph Gohlke

License:

BSD 3-Clause

Version:

2025.1.30

DOI:

10.5281/zenodo.14740657

Quickstart

Install the liffile package and all dependencies from the Python Package Index:

python -m pip install -U liffile[all]

See Examples for using the programming interface.

Source code and support are available on GitHub.

Requirements

This revision was tested with the following requirements and dependencies (other versions may work):

Revisions

2025.1.30

  • Remove LifFile.flim_rawdata (breaking).

  • Add index, guid, and xml_element_smd properties to LifImage.

2025.1.26

  • Fix image coordinate values.

  • Prompt for file name if main is called without arguments.

2025.1.25

  • Initial alpha release.

Notes

Leica Microsystems GmbH is a manufacturer of microscopes and scientific instruments for the analysis of micro and nanostructures.

This library is in its early stages of development. It is not feature-complete. Large, backwards-incompatible changes may occur between revisions.

Specifically, the following features are currently not implemented: related Leica file formats (XLEF, XLLF, LOF, LIFEXT), image mosaics and pyramids, partial image reads, reading non-image data like FLIM/TCSPC, and heterogeneous channels.

This library has been tested with a limited number of version 2 files only.

The Leica Image File format is documented at:

  • Leica Image File Formats - LIF, XLEF, XLLF, LOF. Version 3.2. Leica Microsystems GmbH. 21 September 2016.

  • Annotations to Leica Image File Formats for LAS X Version 3.x. Version 1.4. Leica Microsystems GmbH. 24 August 2016.

  • TSC SP8 FALCON File Format Description. LAS X Version 3.5.0.

Other implementations for reading Leica LIF files are readlif and Bio-Formats .

Examples

Read a FLIM lifetime image and metadata from a LIF file:

>>> with LifFile('tests/data/FLIM.lif') as lif:
...     for image in lif.series:
...         name = image.name
...     image = lif.series['Fast Flim']
...     assert image.shape == (1024, 1024)
...     assert image.dims == ('Y', 'X')
...     lifetimes = image.asxarray()
...
>>> lifetimes
<xarray.DataArray 'Fast Flim' (Y: 1024, X: 1024)> Size: 2MB
array([[...]],
      shape=(1024, 1024), dtype=float16)
    Coordinates:
      * Y        (Y) float64... 0.0005564
      * X        (X) float64... 0.0005564
Attributes...
    path:           FLIM_testdata.lif/sample1_slice1/FLIM Compressed/Fast Flim
    F16:            {'Name': 'F16',...
    TileScanInfo:   {'Tile': {'FieldX': 0,...
    ViewerScaling:  {'ChannelScalingInfo': {...

View the image and metadata in a LIF file from the console:

$ python -m liffile tests/data/FLIM.lif

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

liffile-2025.1.30.tar.gz (23.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

liffile-2025.1.30-py3-none-any.whl (16.9 kB view details)

Uploaded Python 3

File details

Details for the file liffile-2025.1.30.tar.gz.

File metadata

  • Download URL: liffile-2025.1.30.tar.gz
  • Upload date:
  • Size: 23.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.1

File hashes

Hashes for liffile-2025.1.30.tar.gz
Algorithm Hash digest
SHA256 d6e451ff25c5d3e3ad58171c68a1973f0d7b220949d13e25e6c9f0ede96d78c7
MD5 d19d5650534ced3635d2b6e8a7dfd496
BLAKE2b-256 94221f1c7e1f7601f666d5c6cd7f571333ca4fae6ee1dbe103d1dd03cf1a4591

See more details on using hashes here.

File details

Details for the file liffile-2025.1.30-py3-none-any.whl.

File metadata

  • Download URL: liffile-2025.1.30-py3-none-any.whl
  • Upload date:
  • Size: 16.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.1

File hashes

Hashes for liffile-2025.1.30-py3-none-any.whl
Algorithm Hash digest
SHA256 edbd617ae78d202c7b0f2bea60d16c5d2b1e72226a9984649fa883ac91094ea7
MD5 3cb609b49eee327ddf602cb03da8ff40
BLAKE2b-256 92eeb24b06375f5f2e49de0e27101b50145812c23faf00b68c907e46f5ed4824

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page