A toolbox for analysing FLISM images
Project description
BrightEyes-FLISM
Installation
Install brighteyes-flism from PyPI:
pip install brighteyes-flism
You can also install the latest development version directly from GitHub:
pip install git+https://github.com/VicidominiLab/BrightEyes-Flism
In case of local development:
git clone https://github.com/VicidominiLab/BrightEyes-Flism.git
cd BrightEyes-Flism
pip install -e .
brighteyes_flism re-exports the fitting and calibration helpers from
brighteyes_mcs_file, including the optional model_fn, p0, bounds, and
parameter_names arguments for custom multi-parameter fit models. This includes
perform_fit_data, fit_data_with_ref_or_irf, calibrate_h5_file, and
generate_fit_maps.
The HDF5 helpers understand the BrightEyes MCS 0.0.6 layout, including
/raw/spad, /raw/aux, /calibration/results/<product>/..., and grouped
virtual channels under /output/virtual_channels/<kind>/channel_<index>.
Use load_raw(...) for current raw payloads and load_virtual_channel(...)
for grouped virtual channels. They keep reader support for older raw
acquisition files with root-level data and data_channels_extra datasets.
For plotting calibrated files, use load_calibration_summary(...) and
load_calibration_fit_traces(...) instead of hard-coding calibration paths.
Project details
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