scipion-em-susantomo 3.0b5

Installation

You will need to use 3.0+ version of Scipion to be able to run these protocols. To install the plugin, you have two options:

1. Stable version

scipion installp -p scipion-em-susantomo

2. Developer’s version

   • download repository

   git clone -b devel https://github.com/scipion-em/scipion-em-susantomo.git

   • install

   scipion installp -p /path/to/scipion-em-susantomo --devel

• SUSAN sources will be downloaded and compiled automatically with the plugin, but you can also link an existing installation. Default installation path assumed is software/em/susan-0.1, if you want to change it, set SUSAN_HOME in scipion.conf file to the folder where the SUSAN is installed.

• SUSAN installation requires CUDA libraries, gcc >= 9.x and cmake 3.22.x. OpenMPI is optional amd only required for running SUSAN on more than one cluster node. MATLAB is not required as this plugin uses Python API.

• If you need to use CUDA different from the one used during Scipion installation (defined by CUDA_LIB), you can add SUSAN_CUDA_LIB variable to the config file.

• If you have to use a MPI for SUSAN different from Scipion MPI, you can set SUSAN_MPI_BIN and SUSAN_MPI_LIB variables in the config file. At the moment MPI support in the plugin is not working.

Verifying

To check the installation, simply run one of the tests. A complete list of tests can be displayed by executing scipion test --show --grep susantomo

Supported versions

0.1

Protocols

• ctf estimation

• multi-reference alignment

• average and reconstruct

• create a subset

References

1. Sánchez RM, Mester R, Kudryashev M. Fast Cross Correlation for Limited Angle Tomographic Data. In: Felsberg M., Forssén PE., Sintorn IM., Unger J. (eds) Image Analysis. SCIA 2019. Lecture Notes in Computer Science, vol 11482. Doi: 10.1007/978-3-030-20205-7_34

2. R.M. Sánchez, R. Mester and M. Kudryashev. Fast Alignment of Limited Angle Tomograms by projected Cross Correlation. 2019 27th European Signal Processing Conference (EUSIPCO), 2019, pp. 1-5, doi: 10.23919/EUSIPCO.2019.8903041