In general, GonioAnalysis can be used for data following the hierarchy
data_directory
├── specimen_01
│ ├── experiment_01
│ │ ├── image_001.tif
│ │ └── image_002.tif
│ └── ...
└── ...
but special (GonioImsoft) naming scheme is needed for some functionality. Tiff files or stacks are the preferred image format.
WARNING! GonioAnalysis is still in early development!
Two installation methods are supported:
- The stand-alone installer (Windows only)
- Python packaging (all platforms)
A Windows installer bundles together the Gonio Analysis suite and all its depencies, including a complete Python runtime. It is ideal for users not having Python installed before.
The installer can be found at Releases.
The installer creates a start menu shorcut called Gonio Analysis, which can be used to launch the program.
To uninstall the program, use the Windows Add or Remove programs.
The latest version from PyPi can be installed with the command
pip install gonio-analysis
This should install all the required dependencies. On Windows, OpenCV may require Visual C++ Runtime 2015 to be installed.
Some Linux distributions have separated tkinter (Python interface to the Tcl/Tk GUI toolkit) and pillow's ImageTk module their own packages that are not installed by default. Please make sure to have them installed.
# Example on Debian/Ubuntu/Mint/...
sudo apt install python3-tk python3-pil.imagetk
Launch the program by
python -m gonioanalysis.tkgui
Upgrade to the latest version
pip install --upgrade gonio-analysis
Downgrade to a selected version
pip install gonio-analysis==0.1.2
Start by opening your data directory (this should contain the folders containing the images). Next, select the regions of interest (ROIs), and then, run the motion analysis. This may take a while. The ROIs and movements are saved on disk (C:\Users\USER\GonioAnalysis or /home/USER/.gonioanalysis), meaning that this part of the analysis (ROIs and movement analysis) has to be performed only once per specimen (unless you want to re-analyse).
After the initial steps you, can perform further analyses in the program or export the data by
- copy-pasting the results to an external program or 2) exporting CSV files.
Many other features are present but yet undocumented.
-
Any problems or missing features, Issues.
-
For general chatting, Discussions
See also below for the project's future plans.
This program was created in the University of Sheffield to analyse the photomechanical photoreceptor microsaccades that occur in the insect compound eyes. For more information, please see our GHS-DPP methods @ Communications Biology, or visit the lab's website.
Currently, it is maintained the original developer jkemppainen. Future efforts are mainly targeted towards ease-of-use (UI redesign/cleaning, exposing settings, documentation), bug-clearing (especially with non-GonioImsoft data) and performance (cross-correlation analysis).