Quickstart¶
This short quickstart gets playNano running quickly (recommended: conda) using the CLI and GUI. For full details see the linked pages (Installation, Command Line Interface (CLI), GUI: Interactive Playback, Processing, Analysis).
1. Create a conda environment (recommended)¶
Ensure you have Anaconda or Miniconda installed (see Installation for links) and open the terminal (Anaconda PowerShel Pront for Windows).
conda create -n playnano_env python=3.11
conda activate playnano_env
2. Install playNano from PyPi¶
Install the latest release of playNano from PyPi using pip.
pip install playnano
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. There is a preset processing pipeline can can be applied by pressing the “F” key or the “Apply Filters” button in the GUI. You can find out more about using the GUI in GUI: Interactive Playback.
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;polynomial_flatten:order=2" \
--export h5,tif,npz --make-gif --output-folder ./results --output-name sample_processed
This will load demo data, apply a processing pipeline, export the processed data as an HDF5 file (h5), a
NumPy zipped archive (npz) and a multi-page OME-TIFF (tif) to the ./results folder. It will also
generate an animated GIF (from --make-gif) with scale bar and frame timestamp annotations.
Note
_filtered is automatically appended to the output name when processing is applied.
Run analysis (detection + tracking):
playnano analyze ./results/sample_processed_filtered.h5 \
--analysis-steps "feature_detection:mask_fn=mask_mean_offset,factor=0.5,threshold=5;particle_tracking: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
Exporting data and GIFs: Exporting Data
Analysis API and CLI usage: Analysis
Step-by-step Jupyter demo: Notebooks