simplify

README.md

@@ -21,7 +21,7 @@ After installing DockQ with `pip`, the `DockQ` binary will be in your path. Just
 
 **Example**
 
-When running DockQ on model/native complexes with one or more interfaces, you will get a result for each interface. Results are computed to maximise the average DockQ across all interface:
+When running DockQ on model/native complexes with one or more interfaces, you will get a result for each interface. Results are computed to maximise the average DockQ across all interfaces:
 
 ```
 
@@ -144,30 +144,29 @@ Run DockQ with `-h/--help` to see a list of the available flags:
 ```
 bash$ DockQ -h
 
-usage: DockQ [-h] [--capri_peptide] [--short] [--verbose] [--use_CA] [--no_align] [--optDockQF1] [--allowed_mismatches ALLOWED_MISMATCHES] [--mapping MODELCHAINS:NATIVECHAINS]
+usage: DockQ [-h] [--capri_peptide] [--short] [--verbose] [--no_align] [--n_cpu n_cpu] [--optDockQF1] [--allowed_mismatches ALLOWED_MISMATCHES] [--mapping MODELCHAINS:NATIVECHAINS]
              <model> <native>
 
 DockQ - Quality measure for protein-protein docking models
 
 positional arguments:
-  <model>               path to model file
-  <native>              path to native file
+  <model>               Path to model file
+  <native>              Path to native file
 
 optional arguments:
   -h, --help            show this help message and exit
   --capri_peptide       use version for capri_peptide (DockQ cannot not be trusted for this setting)
-  --short               short output
-  --verbose, -v         talk a lot!
-  --use_CA, -ca         use CA instead of backbone
+  --short               Short output
+  --verbose, -v         Verbose output
   --no_align            Do not align native and model using sequence alignments, but use the numbering of residues instead
-  --optDockQF1          optimize on DockQ_F1 instead of DockQ
+  --n_cpu n_cpu         Number of cores to use
+  --optDockQF1          Optimize on DockQ_F1 instead of DockQ
   --allowed_mismatches ALLOWED_MISMATCHES
-                        number of allowed mismatches when mapping model sequence to native sequence.
+                        Number of allowed mismatches when mapping model sequence to native sequence.
   --mapping MODELCHAINS:NATIVECHAINS
                         Specify a chain mapping between model and native structure. If the native contains two chains "H" and "L" while the model contains two chains "A" and "B",
                         and chain A is a model of native chain H and chain B is a model of native chain L, the flag can be set as: '--mapping AB:HL'. This can also help limit the
                         search to specific native interfaces. For example, if the native is a tetramer (ABCD) but the user is only interested in the interface between chains B and
                         C, the flag can be set as: '--mapping :BC' or the equivalent '--mapping *:BC'.
-
 ```
 

src/DockQ/DockQ.py

@@ -7,6 +7,7 @@
 import warnings
 import traceback
 import itertools
+from collections import Counter
 from argparse import ArgumentParser
 from functools import lru_cache, wraps, partial
 
@@ -669,13 +670,8 @@ def product_without_dupl(*args, repeat=1):
 
 
 def count_chain_combinations(chain_clusters):
-    counts = {}
-    for chain in chain_clusters:
-        chains = tuple(chain_clusters[chain])
-        if chains not in counts:
-            counts[chains] = 0
-        counts[chains] += 1
-    number_of_combinations = np.prod([math.factorial(a) for a in counts.values()])
+    tuples = [tuple(l) for l in chain_clusters.values()]
+    number_of_combinations = np.prod([math.factorial(a) for a in Counter(tuples).values()])
     return number_of_combinations
 
 
@@ -743,7 +739,6 @@ def main():
         native_chains_to_combo,
         args.allowed_mismatches,
     )
-
     num_chain_combinations = count_chain_combinations(chain_clusters)
     chain_maps = get_all_chain_maps(
         chain_clusters,
@@ -793,29 +788,24 @@ def main():
                 best_dockq = total_dockq
                 best_result = result_this_mapping
                 best_mapping = chain_map
-
-    else:  # skip multi-threading for single jobs (skip the bar basically)
-        for chain_map in chain_maps:
-            result_this_mapping = run_chain_map(chain_map)
-            total_dockq = sum(
-                [
-                    result["DockQ_F1" if args.optDockQF1 else "DockQ"]
-                    for result in result_this_mapping.values()
-                ]
+        if low_memory:  # retrieve the full output by rerunning the best chain mapping
+            best_result = run_on_all_native_interfaces(
+                model_structure,
+                native_structure,
+                best_mapping,
+                args.no_align,
+                args.capri_peptide,
+                low_memory=False,
             )
-            if total_dockq > best_dockq:
-                best_dockq = total_dockq
-                best_result = result_this_mapping
-                best_mapping = chain_map
 
-    if low_memory:  # retrieve the full output by reruning the best chain mapping
-        best_result = run_on_all_native_interfaces(
-            model_structure,
-            native_structure,
-            best_mapping,
-            args.no_align,
-            args.capri_peptide,
-            low_memory=False,
+    else:  # skip multi-threading for single jobs (skip the bar basically)
+        best_mapping = next(chain_maps)
+        best_result = run_chain_map(best_mapping)
+        best_dockq = sum(
+            [
+                result["DockQ_F1" if args.optDockQF1 else "DockQ"]
+                for result in best_result.values()
+            ]
         )
 
     info["model"] = args.model