Quickstart¶
This short quickstart gets playNano running quickly (recommended: conda). For full details see the linked pages (Installation, Command Line Interface (CLI), GUI: Interactive Playback, Processing, Analysis).
Before you start ensure you have a copy of the playNano source code, either clone the repository or downlaod a relase from github.
A simnple way to clone the playNano repository:
- ..clode-block:: bash
git clone https://github.com/derollins/playNano.git # Clones the repo to a folder called playNano
1. Create a conda environment (recommended)¶
# from the project root (where pyproject.toml / src/ live)
conda create -n playnano python=3.12 -c conda-forge
conda activate playnano
2. Install playNano (editable)¶
Navigate to the playNano project root (where pyproject.toml
/ src/
live) and run:
pip install -e .
Optional extras (docs, notebooks):
pip install -e ".[docs]" ".[notebooks]"
Note
The -e
flag installs playNano in editable mode, allowing you to
modify the source code and see changes immediately—recommended for development
and experimentation.
3. Quick verification¶
playnano --help
python -c "import playNano; print(playNano.__version__)"
4. Most common actions (one-liners)¶
Launch interactive GUI:¶
To open a sample file in the GUI, run:
playnano play ./tests/resources/sample_0.h5-jpk # Opens GUI with loaded file
This opens a sample AFM file when run in the project root. Change the path to your own data to view other files.
Batch process, analyis and export (no GUI):¶
For batch processing and analysis the processing and analyis pipelines are run through seperate commands. To run these commands on example data, these commands can be run from the project root.
playnano process ./tests/resources/sample_0.h5-jpk\
--processing "remove_plane;mask_mean_offset:factor=1;row_median_align" \
--export h5,tif,npz --make-gif --output-folder ./results --output-name sample_processed
Run analysis (detection + tracking):
playnano analyze ./results/sample_processed.h5 \
--analysis-steps "feature_detection:threshold=5;track_particles:max_distance=3"
5. Where to go next¶
Full installation instructions and platform notes: Installation
CLI reference and flags: Command Line Interface (CLI)
GUI overview and shortcuts: GUI: Interactive Playback
Processing pipeline details + YAML schema: Processing
Analysis API and CLI usage: Analysis
Step-by-step Jupyter demo: Notebooks