v2.3.1 - merge 'beta' into 'main' (#371)

Browse Files

* Added input_features_callback to run() function to allow plotting MSA before structure predictions computation.

* Added lower level plot_pae() and plot_protein_backbone() functions to allow making individual plots instead of multi-pane composite plots.

* Fix typo in new protein backbone plotting code.

* testing v.2.3.0

* adding support for multimer_v3

* updating version number of alphafold-colabfold

* Update batch.py

convert unrelaxed protein features to numpy before saving (to speedup save function)

* add option to enable/disable fuse

* adding option to enable/disable fuse

* download v3 params by default

* adding option for iterating through random_seed(s)

* adding option to iterate through random seeds

* Update poetry.lock

* Delete poetry.lock

* Update batch.py

* Update test.yml

only run test on main branch

* fixing encoding error (when amber relax is used and notebook is run multiple times)

* refactoring code a bit to write the results to jobname directory

* add model_type into filename

* adding model_type to filename

* disable bfloat16 for old (v1, v2) multimer models

* select best view using plddt

* adding option to "save all" outputs of model

* adding option to save_all

* adding max_msa option to notebook

* allow max_msa settings for multimer

* adjust max settings

* updating dm-haiku to fix error in jax

* adding option to disable use_cluster_profile

* Created using Colaboratory

* code cleanup

* code cleanup

* Update models.py

* add option to enable bfloat16

* Fix tensorflow import

* making bfloat16 and fuse the default

* cleanup

* major bugfix for ptm + is_complex (#360)

* Update README.md

* adding option to control num of top models to relax

* control number of models to relax

* Update batch.py

* update pae filename

* remove whitespace from saved images

* addressing memory leak and pae bugfix

all outputs are saved as they are generated to avoid memory leaks. scores reloaded later for plotting.

bugfix: *_predicted_aligned_error_v1.json is now the best ranked output (before it was whichever model was saved first)

* adding leading zeros to rank id and seed id

* adding leading zeros to rank and seed id(s)

* Delete colabfold_alphafold.py

unused file

* monomers can now be predicted with multimer model!

* fix numbering

* Update batch.py

bugfix for custom msa input
run function updated to return model ranks and metrics

* update run function to print metrics and keep track of best model rank

* replacing max_msa

replacing max_msa option with max_seq and max_extra_seq to make easier to control.

* Update batch.py

* Update batch.py

rank_by wasn't computed correctly for multimer ranking

* Update AlphaFold2_batch.ipynb

* Update AlphaFold2_batch.ipynb

* adding TPU support

* remove TPU warning...

* disable BiopythonDeprecationWarning

* Move load_models_and_params to before the job loop (#368)

* Update batch.py

Move load_models_and_params to before the job loop to avoid issues when resuming from an existing directory with already finished jobs.

* Update batch.py

Change to check if it's the first job instead of moving load_models_and_params

* recompile_padding update

padding is now defined as a constant int instead of float

* Update README.md

* Created using Colaboratory

* Update batch.py

* Created using Colaboratory

* adding iptm support to ptm (for complexes)

* removing extra print out

* Update batch.py

* Update batch.py

* add option to save intermediate results

* add option to save_recycles

* Update batch.py

* updating pyproject.toml to use latest alphafold-colabfold v2.3

* Revert "updating pyproject.toml to use latest alphafold-colabfold v2.3"

This reverts commit bcf4ec9ea5.

* Update alphafold-colabfold to 2.3.1

* attempt to fix test

* Adding link back to old version

* update test data

* Update test_colabfold.py

* fix test (fingers crossed)

* Update test_colabfold.py

* Update README.md

* updating notebooks to use "main" instead of "beta"

---------

Co-authored-by: Tom Goddard <goddard@sonic.net>
Co-authored-by: YoshitakaMo <virgospica93@gmail.com>
Co-authored-by: Milot Mirdita <milot@mirdita.de>
Co-authored-by: Dennis Svedberg <densvedberg@gmail.com>
Co-authored-by: Martin Steinegger <martin.steinegger@mpibpc.mpg.de>
Co-authored-by: Martin Steinegger <themartinsteinegger@gmail.com>

skiptemplatesearch

Sergey O 2 years ago committed by GitHub

parent 5ec156f1cb

commit 5ebf2c5742

47 changed files (2.1 MiB → 79 MiB)

Split Unified

1. 9
     .github/workflows/test.yml
2. 1
     .gitignore
3. 277
     AlphaFold2.ipynb
4. 24
     README.md
5. 2
     batch/AlphaFold2_batch.ipynb
6. 2
     beta/AlphaFold2_advanced.ipynb
7. 0
     beta/AlphaFold2_complexes.ipynb
8. 202
     colabfold/alphafold/models.py
9. 1221
     colabfold/batch.py
10. 2
      colabfold/citations.py
11. 92
      colabfold/colabfold.py
12. 827
      colabfold/colabfold_alphafold.py
13. 17
      colabfold/download.py
14. 59
      colabfold/plot.py
15. 14
      colabfold/utils.py
16. 2984
      poetry.lock
17. 4
      pyproject.toml
18. 3
      test-data/batch/5AWL_1/model_feat.pkl.xz
19. 3
      test-data/batch/5AWL_1/model_input_fix.pkl.xz
20. 3
      test-data/batch/5AWL_1/model_pred.pkl.xz
21. 3
      test-data/batch/5AWL_1/model_prediction_result.pkl.xz
22. 3
      test-data/batch/6A5J/model_feat.pkl.xz
23. 3
      test-data/batch/6A5J/model_input_fix.pkl.xz
24. 3
      test-data/batch/6A5J/model_pred.pkl.xz
25. 3
      test-data/batch/6A5J/model_prediction_result.pkl.xz
26. 3
      test-data/complex/3G5O_A_3G5O_B/model_feat.pkl.xz
27. 3
      test-data/complex/3G5O_A_3G5O_B/model_input_fix.pkl.xz
28. 3
      test-data/complex/3G5O_A_3G5O_B/model_pred.pkl.xz
29. 3
      test-data/complex/3G5O_A_3G5O_B/model_prediction_result.pkl.xz
30. 3
      test-data/complex_monomer/A_A/model_feat.pkl.xz
31. 3
      test-data/complex_monomer/A_A/model_input_fix.pkl.xz
32. 3
      test-data/complex_monomer/A_A/model_pred.pkl.xz
33. 3
      test-data/complex_monomer/A_A/model_prediction_result.pkl.xz
34. 3
      test-data/complex_monomer_ptm/A_A/model_feat.pkl.xz
35. 3
      test-data/complex_monomer_ptm/A_A/model_input_fix.pkl.xz
36. 3
      test-data/complex_monomer_ptm/A_A/model_pred.pkl.xz
37. 3
      test-data/complex_monomer_ptm/A_A/model_prediction_result.pkl.xz
38. 3
      test-data/complex_ptm/3G5O_A_3G5O_B/model_feat.pkl.xz
39. 3
      test-data/complex_ptm/3G5O_A_3G5O_B/model_input_fix.pkl.xz
40. 3
      test-data/complex_ptm/3G5O_A_3G5O_B/model_pred.pkl.xz
41. 3
      test-data/complex_ptm/3G5O_A_3G5O_B/model_prediction_result.pkl.xz
42. 1
      test-data/mmseqs-api-reponses/single.json
43. 3
      test-data/single/5AWL_1/model_feat.pkl.xz
44. 3
      test-data/single/5AWL_1/model_pred.pkl.xz
45. 331
      tests/mock.py
46. 185
      tests/test_colabfold.py
47. 8
      tests/test_msa.py

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