TEMPy has a range of functions to assess the similarity between a range of data types.

TEMPy’s scoring functions have diverse applicability and can be used to assess the similarity between two cryo EM maps, between a model (e.g. from a pdb file) and a cryo EM map or between two models. All map to map scores can also be used to score models in maps, after a simulated map has been calculated using the StructureBlurrer class.

Additionally, TEMPy has local scoring functions (e.g. SMOC), that score only a portion of the input data at a time, for example producing a unique score for each residue in a protein, in addition to global scoring functions that average across the whole input map or model.

Global Scores

TEMPy scoring functions to assess the overall agreements between two data types include:

Segment Scores

There are also scoring functions to assess the fit of models at the level of segments. These segments are generally multiple

Residue Scores

Finally, there are also scoring functions for assessing model fit at the level of single residues. These scores include:


A faster version of the sliding window SMOC score.


Calculate the local Mander's Overlap for each residue in a protein model