Denoising via adaptive binning for FLIM datasets.
Project description
pawFLIM: denoising via adaptive binning for FLIM datasets
Installation
pawFLIM can be installed from PyPI:
pip install pawflim
Usage
import numpy as np
from pawflim import pawflim
data = np.empty((3, *shape), dtype=complex)
data[0] = ... # number of photons
data[1] = ... # n-th fourier coefficient
data[2] = ... # 2n-th fourier coefficient
denoised = pawflim(data, n_sigmas=2)
phasor = denoised[1] / denoised[0]
See the notebook in examples for an example with simulated data.
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pawflim-1.0.2.tar.gz
(120.5 kB
view details)
Built Distribution
File details
Details for the file pawflim-1.0.2.tar.gz.
File metadata
- Download URL: pawflim-1.0.2.tar.gz
- Upload date:
- Size: 120.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e04154ea441888e0dc4d81ebe9ec454a3ea9dc0cbb295d50bad7574fdf92dc78 |
|
| MD5 | 0fb719b780b6087ed46ec6b23952e709 |
|
| BLAKE2b-256 | 0be2fc022b0f0b1add88e442a71a54eec59864cf836a5515ba8d18ec487aee75 |
File details
Details for the file pawflim-1.0.2-py3-none-any.whl.
File metadata
- Download URL: pawflim-1.0.2-py3-none-any.whl
- Upload date:
- Size: 5.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 9d5bee81e8309d18390d6959899254158b87e7b6ceeef4f4dfd8648545fa5f74 |
|
| MD5 | 0b43d8a18b7ffce84d65d2423e48370b |
|
| BLAKE2b-256 | 52ab60e9bddf08178a6ce86b2f03db33d09a07f57e7de016b1d2620826d5b6c4 |
