Extensible Real-Time Data Processing with Python in DigitalMicrograph

Modern electron microscopy can generate large amounts of data. While this may reveal details of the sample in unprecedented detail, collecting more data can also obscure what’s most important. In-situ experiments where data is acquired continuously further increase the data volume. In-situ experiments may also require the user to make decisions about what to do next based on the changes observed in the microscope. However, depending on the sample and the software setup, these changes are not always obvious from a default live view of the data displayed in real-time. Given the large data volume, enhanced flexibility to process and visualize data in a variety of ways is valuable, especially if this can be done in real-time to understand the changes occurring to the sample. This enables informed decision making during the experiment, increasing the chances that valuable data is collected.