  Computational methods are driving high impact microscopy techniques such as
ptychography. However, the design and implementation of new algorithms is often
a laborious process, as many parts of the code are written in
close-to-the-hardware programming constructs to speed up the reconstruction. In
this paper, we present SciComPty, a new ptychography software framework aiming
at simulating ptychography datasets and testing state-of-the-art and new
reconstruction algorithms. Despite its simplicity, the software leverages GPU
accelerated processing through the PyTorch CUDA interface. This is essential to
design new methods that can readily be employed. As an example, we present an
improved position refinement method based on Adam and a new version of the rPIE
algorithm, adapted for partial coherence setups. Results are shown on both
synthetic and real datasets. The software is released as open-source.
