Electron ptychography is a rapidly growing diffractive imaging technique providing superior image contrast, high resolution, efficient dose usage and versatile imaging conditions. Originally coming from the physical sciences, it has also become a method of interest in the life sciences. Regardless of the scientific field, the successful ptychographic reconstruction relies on various combinations of adjustable experimental parameters, along with the choice of the reconstruction algorithm. In this work we present ptychoScopy, a Python-based tool developed to simplify the selection of these parameters and aid successful experimental design. Using a [Formula: see text] sample, we show the influence of key parameters such as probe convergence angle, defocus and electron dose on the reconstruction quality using direct and iterative reconstruction algorithms. We investigate the influence of real and reciprocal space sampling and their influence on the speed and quality of ptychographic reconstructions. PtychoScopy simplifies experimental design and guides the researchers across diverse scientific fields in setting up successful ptychographic experiments.

Electron ptychography; Experimental design; Real- and reciprocal space sampling; Experimental design; Real- and reciprocal space sampling