explore_lif
Load 3D confocal images from lif files as numpy arrays.
Install
- The most convenient way would be:
pip install -e .from the directory where you have cloned or downloaded the code. - You can also Include the file
explore_lifin your project directory
How to Use It
For 3D Image
from explore_lif import Reader
reader = Reader('lif_file.lif')
series = reader.getSeries()
chosen = series[0] # choose first image in the lif file
# get a numpy array corresponding to the 1st time point & 1st channel
# the shape is (x, y, z)
image = chosen.getXYZ(T=0, channel=0)
For 2D Image with Multiple Channels
from explore_lif import Reader
reader = Reader('lif_file.lif')
series = reader.getSeries()
chosen = series[0] # choose first image in the lif file
# get a numpy array corresponding to the 1st time point
# the shape is (x, y, channel_number)
image = chosen.getXYC(T=0)
Metadata
Release files for explore-lif 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| explore_lif-0.1.1.tar.gz | 23.9 kB | Details |
Release files / explore_lif-0.1.1.tar.gz
| Download URL | explore_lif-0.1.1.tar.gz |
|---|---|
| Size | 23.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7e6df7ac4a6a98cc8474b8a39ce9b5f37e8ebaae5d3aac5b88ba22d91e7ac016
|
|
BLAKE2b-256 checksum How to use checksums |
9d41a153d11df106c69881af1379065c877ecb43b3d4e0592bdbb6522a6a0158
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.5.0.1 requests/2.24.0 requests-toolbelt/0.9.1 tqdm/4.49.0 CPython/3.7.7
|