| Name | pawflim JSON |
| Version |
1.0.4
JSON |
| download |
| home_page | |
| Summary | Denoising via adaptive binning for FLIM datasets. |
| upload_time | 2023-11-30 16:14:00 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.7 |
| license | MIT License Copyright (c) 2023 Mauro Silberberg Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
flim
pawflim
binlets
denoising
adaptive
wavelets
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# pawFLIM: denoising via adaptive binning for FLIM datasets
[](https://pypi.python.org/pypi/pawflim)
[](https://opensource.org/licenses/MIT)
[](https://doi.org/10.1088/2050-6120/aa72ab)
## Installation
pawFLIM can be installed from PyPI:
```
pip install pawflim
```
## Usage
```python
import numpy as np
from pawflim import pawflim
data = np.empty((3, *shape), dtype=complex)
data[0] = ... # number of photons
data[1] = ... # n-th (conjugated) Fourier coefficient
data[2] = ... # 2n-th (conjugated) Fourier coefficient
denoised = pawflim(data, n_sigmas=2)
phasor = denoised[1] / denoised[0]
```
Note that we use the standard FLIM definition for the $n$-th phasor $r$:
$$ r_n = \\frac{R_n}{R_0} $$
where
$$ R_n = \\int I(t) , e^{i n \\omega t} dt $$
is the $n$-th (conjugated) Fourier coefficient.
See the notebook in
[examples](https://github.com/maurosilber/pawflim/blob/main/examples/simulated_data.ipynb)
for an example with simulated data.
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