This repository hosts the pyqt based graphical 4D--STEM data browser that was originally part of py4DSTEM until version 0.13.11.
The GUI is available on PyPI and conda-forge:
pip install py4D-browser
conda install -c conda-forge py4d-browser
Run py4DGUI in your terminal to open the GUI. Then just drag and drop a 4D-STEM dataset into the window!
- Move the virtual detector and the real-space selector using the mouse or using the keyboard shortcuts: WASD moves the detector and IJKL moves the selector, and holding down shift moves 5 pixels at a time.
- Auto scaling of both views is on by default. Press the "Autoscale" buttons in the bottom right to disable. Press either button to apply automatic scaling once, or Shift + click to lock autoscaling back on.
- Different shapes of virtual detector are available in the "Detector Shape" menu, and different detector responses are available in the "Detector Response" menu.
- The information in the bottom bar contains the details of the virtual detector used to generate the images, and can be entered into py4DSTEM to generate the same image.
- The FFT pane can be switched between displaying the FFT of the virtual image and displaying the exit wave power cepstrum.
- Virtual images can be exported either as the scaled and clipped displays shown in the GUI or as raw data. The exact datatype stored in the raw TIFF image depends on both the datatype of the dataset and the type of virtual image being displayed (in particular, integer datatypes are converted internally to floating point to prevent overflows when generating any synthesized virtual images).
- If the EMPAD-G2 Raw Reader is installed in the same environment, an extra menu will appear that allows the concatenated binary format data to be background subtracted and calibrated in the GUI. You can also save the calibrated data as an HDF5 file for later analysis.
The keyboard map in the Help menu was made using this tool and the map file is in the top level of this repo.
py4DSTEM is an open source set of python tools for processing and analysis of four-dimensional scanning transmission electron microscopy (4D-STEM) data. Additional information:
- Our open access py4DSTEM publication in Microscopy and Microanalysis describing this project and demonstrating a variety of applications.
- The py4DSTEM documentation pages.
- Our open access 4D-STEM review in Microscopy and Microanalysis describing this project and demonstrating a variety of applications.
GNU GPLv3
py4DSTEM is open source software distributed under a GPLv3 license. It is free to use, alter, or build on, provided that any work derived from py4DSTEM is also kept free and open.