How to contribute

For those who are interested in contributing to HTTomo, we provide here steps to follow. All additional enquires can be left in the issues section on HTTomo’s Github page.

1. Write a new data processing method in Python.

   One needs to write a method and make it accessible in either a separate library or integrating it into the list of already Supported libraries. The latter option is preferred as some of the packages are maintained by HTTomo developers which will provide support during the integration.

2. Expose the method in the library file in HTTomo

   Then one needs to expose that method to HTTomo by editing the Library files. You would need to specify the main static descriptors of that method, such as, pattern, implementation, etc. If the implementation is cpu only, then memory_gpu must be set to None. However, if the method requires GPU, then you would need to provide more information so that HTTomo’s framework would account for the memory use on the device. See HTTomolibgpu library file for that. In a simple case, one can calculate the memory directly by providing multipliers in the library file. When memory calculation is more complicated, one needs to add a Python script that does this calculation. See more in GPU memory calculations.

3. Check the wrapper type

   Every method is executed by using Method Wrappers. Check that the method fits the existing wrapper type, and if not, then possibly more work required to accommodate it. In most of the cases the method should fit the existing types.

4. Generate the Yaml template

   HTTomo’s UI requires Methods YAML Templates to execute the created method. One can either construct that YAML template manually or employ YAML generator.