Updating ColabFold to 3.1.11

colabfold/batch.py

@@ -405,6 +405,13 @@ def get(self, x: str, ext:str) -> Path:
         self.files[self.tag].append([x,ext,file])
         return file
 
+    def exists(self, x: str, ext:str) -> Path:
+        file = self.result_dir.joinpath(f"{self.prefix}_{x}_{self.tag}.{ext}")
+        if file.is_file():
+            return True
+        else:
+            return False
+
     def set_tag(self, tag):
         self.tag = tag
 
@@ -435,6 +442,7 @@ def predict_structure(
     save_single_representations: bool = False,
     save_pair_representations: bool = False,
     save_recycles: bool = False,
+    keep_existing_results: bool = True,
     calc_extra_ptm: bool = False,
     use_probs_extra: bool = True,
 ):
@@ -526,6 +534,32 @@ def callback(result, recycles):
 
             return_representations = save_all or save_single_representations or save_pair_representations
 
+            if keep_existing_results and files.exists("unrelaxed","pdb"):
+                logger.info(f"{tag} was found. Loading scores and skipping!")
+                if files.exists("scores","json"):
+                    with files.get("scores","json").open("r") as handle:
+                        _scores = json.load(handle)
+                        if is_complex:
+                            mean_scores.append(0.8 * _scores['iptm'] + 0.2 * _scores['ptm'])
+                        else:
+                            mean_scores.append(np.mean(_scores['plddt']))
+                        print_line = ""
+                        conf.append({})
+                        for x,y in [["plddt","pLDDT"],["ptm","pTM"],["iptm","ipTM"]]:
+                            if x in _scores:
+                                if x == "plddt":
+                                    print_line += f" {y}={np.mean(_scores[x]):.3g}"
+                                    _scores["mean_plddt"] = np.mean(_scores[x])
+                                    x = "mean_plddt"
+                                else:
+                                    print_line += f" {y}={_scores[x]:.3g}"
+                                conf[-1][x] = float(_scores[x])
+                        conf[-1]["print_line"] = print_line
+                    files.get("unrelaxed","pdb")
+                    continue
+                else:
+                    logger.error(f"Scores file for {tag} not found")
+
             # predict
             result, recycles = \
             model_runner.predict(input_features,
@@ -648,6 +682,9 @@ def callback(result, recycles):
 
     rank, metric = [],[]
     result_files = []
+    if rank_by == "skip":
+        logger.info(f"Skipping ranking and exiting")
+        exit()
     logger.info(f"reranking models by '{rank_by}' metric")
     model_rank = np.array(mean_scores).argsort()[::-1]
     for n, key in enumerate(model_rank):
@@ -2079,7 +2116,7 @@ def main():
         help='Choose metric to rank the "--num-models" predicted models.',
         type=str,
         default="auto",
-        choices=["auto", "plddt", "ptm", "iptm", "multimer"],
+        choices=["auto", "plddt", "ptm", "iptm", "multimer", "skip"],
     )
     output_group.add_argument(
         "--stop-at-score",
@@ -2239,6 +2276,7 @@ def comma_separated_list(arg_string):
         version += f" ({commit})"
 
     logger.info(f"Running colabfold {version}")
+    logger.info(f"Version modded by SSchott to use CBCSrv local MMSeqs2 and keep existing results!")
 
     data_dir = Path(args.data or default_data_dir)
 

colabfold/download.py

@@ -9,7 +9,7 @@
 
 # The data dir location logic switches between a version with and one without "params" because alphafold
 # always internally joins "params". (We should probably patch alphafold)
-default_data_dir = Path(appdirs.user_cache_dir(__package__ or "colabfold"))
+default_data_dir = Path("/apps/local/cbclab/COLABFOLD/colabfold")
 
 def download(url, params_dir, size_queue, progress_queue):
     try:

colabfold/utils.py

@@ -22,15 +22,15 @@
 
 If you're sure you want to run without a GPU, pass `--cpu`"""
 
-DEFAULT_API_SERVER = "https://api.colabfold.com"
+DEFAULT_API_SERVER = "http://192.168.62.51:9091"
 
 ACCEPT_DEFAULT_TERMS = \
 """
-WARNING: You are welcome to use the default MSA server, however keep in mind that it's a
-limited shared resource only capable of processing a few thousand MSAs per day. Please
-submit jobs only from a single IP address. We reserve the right to limit access to the
-server case-by-case when usage exceeds fair use. If you require more MSAs: You can 
-precompute all MSAs with `colabfold_search` or host your own API and pass it to `--host-url`
+WARNING: You are using the internal CBCSRV MMseqs2 server, with a local ColabFold 1.5.5 installation.
+This server was last updated 22.10.2024. The databases or the ColabFold installation might be too old
+at the time of use. Please be aware, and consider getting a newer version by youself if that is the case!
+You can use the internal MMseqs2 server API by using http://192.168.62.51:9091 as the host url in the
+colabfold_batch script. If the server does not respond, ask around!
 """
 
 class TqdmHandler(logging.StreamHandler):