Comments (1)
Sure! I think the easiest way to do this is with a slight modification of the Colab notebook that is linked in the README. There's a function in that notebook called _get_score
under the "Import Libraries" header. If you replace that with this very slightly modified version:
def _get_score(self):
score = copy_dict(self.model.aux["log"])
score["plddt"] = score["plddt"]
score["pae"] = 31.0 * score["pae"]
score["rmsd_io"] = score.pop("rmsd",None)
i_xyz = self.model._inputs["batch"]["all_atom_positions"][:,1]
o_xyz = np.array(self.model.aux["atom_positions"][:,1])
# TMscore to input/output
if hasattr(self,"wt_batch"):
n_xyz = self.wt_batch["all_atom_positions"][:,1]
score["tm_i"] = tmscore(n_xyz,i_xyz)["tms"]
score["tm_o"] = tmscore(n_xyz,o_xyz)["tms"]
# TMscore between input and output
score["tm_io"] = tmscore(i_xyz,o_xyz)["tms"]
# composite score
score["composite"] = score["ptm"] * score["plddt"] * score["tm_io"]
score["pae_full"] = np.copy(self.model.aux["pae"])
return score
then the full PAE matrix will be part of the output. The only modification here is in the second-to-last line. Then, after running the rest of the notebook, the SCORES
variable will have pae_full
as one of its features, which you can use however you want. Let me know if that helps!
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Related Issues (8)
- "decoy_set/***.txt" files HOT 1
- Runs on Multimeric Structures HOT 2
- Args to reproduce main functionality? HOT 1
- Colab notebook: Template used in ranking structures and Runs on multimers HOT 4
- Dealing with templates that have missing residues HOT 3
- Multimer functions HOT 1
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