A tool to normalize CryoET data by matching amplitude spectrums.

The tool works by extracting the radially averaged amplitude spectrum from a reference tomogram to use as a target for other tomograms. To match another tomogram to the reference, the target spectrum is divided by the tomogram's amplitude spectrum, resulting in a vector of frequency-wise equalization factors. The equalization vector is then turned into a rotationally symmetric kernel, which is then applied to the tomogram in fourier space.

• Install Miniconda3
• Clone the git repo
• Create a new conda environment and activate it

    $ conda env create -f requirements.yaml
    $ conda activate tsm

• Done!

The tool consists of two main components:

• Extraction of a tomogram's radially averaged amplitude spectrum
• Applying an extracted spectrum to other tomograms

To extract a tomogram's amplitude spectrum:

$ python extract_spectrum.py --input <input_tomo.mrc> --output <amp_spectrum.tsv>

To apply an extracted amplitude spectrum to another tomogram:

$ python match_spectrum.py --input <imput_tomo.mrc> --target <amp_spectrum.tsv> --output <filtered_tomo.mrc>