Live FFT color map
Python - Gatan
Code to process the live-view image in DigitalMicrograph, producing a series of maps of crystalline regions in real-time. It computes a grid of small FFTs from each image. It then treats this grid similar to a 4D STEM data cube, where it finds the brightest spot in each FFT and displays its orientation and intensity as an updating color map.
Live difference
Python - Gatan
Code to process the live-view image in DigitalMicrograph, producing a difference image. Two exponentially weighted moving averages are computed, and the absolute value of the difference between them is returned.
Launching an external application and regularly checking if it is still running
DigitalMicrograph - Gatan
Example script showing how the external application Notepad.exe can be launched. The script regularly polls whether or not Notepad.exe is still open so that actions can be performed once the external application is closed.
Iterate layouts
DigitalMicrograph - Gatan
Command example showing how ImageDocument layouts are set.
IS dataset radial FFT profile
Python - Gatan
Compute radial-max profiles over time from the FFT of in-situ video datasets in Gatan Microscopy Suite.
Interactive histogram
DigitalMicrograph - Gatan
Compute a histogram of the frontmost image and allow interactive change of histogram bins.
InGaN bandgap to concentration
DigitalMicrograph - Gatan
A basic script that uses an equation and parameters to estimate the concentration of In in an InGaN spectrum image. Requires as input: Map of bandgap estimation (output from NLLS fitting).
In-situ dataset radial profile Diff or FFT
Python - Gatan
Compute radial-max profiles from an in-situ dataset in DigitalMicrograph. The data can be HRTEM images (from which the FFT will be computed) or diffraction patterns over time. The primary result is a single 2D display of these profiles over time, with time as one dimension and radius as the other. The script also generates an automatically synced in-situ dataset of the 1D radial profiles.
In-situ 4D STEM maximum spot mapping
Python - Gatan
Produce a series of colorful maps of crystalline regions from an in-situ 4D STEM dataset open in DigitalMicrograph. This uses a simple algorithm that finds the location and intensity of the maximum pixel in each pattern. The resulting in-situ video of color maps automatically syncs with the original data in DigitalMicrograph. While the results look like orientation maps, the script does not perform proper orientation mapping.