diff --git a/modules/mol/alg/pymod/chain_mapping.py b/modules/mol/alg/pymod/chain_mapping.py
index f862513d7b3bd26227ed3018dae1c6fcd1bf1061..89ccbc21b5eddc987dada59bb74f3acea9b736bc 100644
--- a/modules/mol/alg/pymod/chain_mapping.py
+++ b/modules/mol/alg/pymod/chain_mapping.py
@@ -839,10 +839,6 @@ class ChainMapper:
* **naive**: Enumerates all possible mappings and returns best
- * **greedy_fast**: perform all vs. all single chain lDDTs within the
- respective ref/mdl chem groups. The mapping with highest number of
- conserved contacts is selected as seed for greedy extension
-
* **greedy_full**: try multiple seeds for greedy extension, i.e. try
all ref/mdl chain combinations within the respective chem groups and
retain the mapping leading to the best lDDT.
@@ -868,7 +864,7 @@ class ChainMapper:
:param thresholds: Thresholds for lDDT
:type thresholds: :class:`list` of :class:`float`
:param strategy: Strategy to find mapping. Must be in ["naive",
- "greedy_fast", "greedy_full", "greedy_block"]
+ "greedy_full", "greedy_block"]
:type strategy: :class:`str`
:param steep_opt_rate: Only relevant for greedy strategies.
If set, every *steep_opt_rate* mappings, a simple
@@ -895,8 +891,7 @@ class ChainMapper:
:returns: A :class:`MappingResult`
"""
- strategies = ["naive", "greedy_fast", "greedy_full", "greedy_block",
- "heuristic"]
+ strategies = ["naive", "greedy_full", "greedy_block", "heuristic"]
if strategy not in strategies:
raise RuntimeError(f"Strategy must be in {strategies}")
@@ -946,9 +941,7 @@ class ChainMapper:
inclusion_radius=inclusion_radius,
thresholds=thresholds,
steep_opt_rate=steep_opt_rate)
- if strategy == "greedy_fast":
- mapping = _lDDTGreedyFast(the_greed)
- elif strategy == "greedy_full":
+ if strategy == "greedy_full":
mapping = _lDDTGreedyFull(the_greed)
elif strategy == "greedy_block":
mapping = _lDDTGreedyBlock(the_greed, block_seed_size,
@@ -984,11 +977,6 @@ class ChainMapper:
* **naive**: Naively iterate all possible mappings and return best based
on QS score.
- * **greedy_fast**: perform all vs. all single chain lDDTs within the
- respective ref/mdl chem groups. The mapping with highest number of
- conserved contacts is selected as seed for greedy extension.
- Extension is based on QS-score.
-
* **greedy_full**: try multiple seeds for greedy extension, i.e. try
all ref/mdl chain combinations within the respective chem groups and
retain the mapping leading to the best QS-score.
@@ -1013,7 +1001,7 @@ class ChainMapper:
contact in qs scoring
:type contact_d: :class:`float`
:param strategy: Strategy for sampling, must be in ["naive",
- "greedy_fast", "greedy_full", "greedy_block"]
+ greedy_full", "greedy_block"]
:type strategy: :class:`str`
:param chem_mapping_result: Pro param. The result of
:func:`~GetChemMapping` where you provided
@@ -1034,7 +1022,7 @@ class ChainMapper:
:returns: A :class:`MappingResult`
"""
- strategies = ["naive", "greedy_fast", "greedy_full", "greedy_block", "heuristic"]
+ strategies = ["naive", "greedy_full", "greedy_block", "heuristic"]
if strategy not in strategies:
raise RuntimeError(f"strategy must be {strategies}")
@@ -1083,9 +1071,7 @@ class ChainMapper:
contact_d = contact_d,
steep_opt_rate=steep_opt_rate,
greedy_prune_contact_map = greedy_prune_contact_map)
- if strategy == "greedy_fast":
- mapping = _QSScoreGreedyFast(the_greed)
- elif strategy == "greedy_full":
+ if strategy == "greedy_full":
mapping = _QSScoreGreedyFull(the_greed)
elif strategy == "greedy_block":
mapping = _QSScoreGreedyBlock(the_greed, block_seed_size,
@@ -2626,47 +2612,6 @@ def _GetSeeds(ref_chem_groups, mdl_chem_groups, mapped_ref_chains = set(),
seeds.append((ref_ch, mdl_ch))
return seeds
-
-def _lDDTGreedyFast(the_greed):
-
- something_happened = True
- mapping = dict()
-
- while something_happened:
- something_happened = False
- seeds = _GetSeeds(the_greed.ref_chem_groups,
- the_greed.mdl_chem_groups,
- mapped_ref_chains = set(mapping.keys()),
- mapped_mdl_chains = set(mapping.values()))
- # search for best scoring starting point
- n_best = 0
- best_seed = None
- for seed in seeds:
- n = the_greed._NSCConserved(seed[0], seed[1]).sum()
- if n > n_best:
- n_best = n
- best_seed = seed
- if n_best == 0:
- break # no proper seed found anymore...
- # add seed to mapping and start the greed
- mapping[best_seed[0]] = best_seed[1]
- mapping = the_greed.ExtendMapping(mapping)
- something_happened = True
-
- # translate mapping format and return
- final_mapping = list()
- for ref_chains in the_greed.ref_chem_groups:
- mapped_mdl_chains = list()
- for ref_ch in ref_chains:
- if ref_ch in mapping:
- mapped_mdl_chains.append(mapping[ref_ch])
- else:
- mapped_mdl_chains.append(None)
- final_mapping.append(mapped_mdl_chains)
-
- return final_mapping
-
-
def _lDDTGreedyFull(the_greed):
""" Uses each reference chain as starting point for expansion
"""
@@ -3053,46 +2998,6 @@ def _QSScoreNaive(trg, mdl, chem_groups, chem_mapping, ref_mdl_alns, contact_d,
best_score = score_result.QS_global
return (best_mapping, best_score)
-
-def _QSScoreGreedyFast(the_greed):
-
- something_happened = True
- mapping = dict()
- while something_happened:
- something_happened = False
- # search for best scoring starting point, we're using lDDT here
- n_best = 0
- best_seed = None
- seeds = _GetSeeds(the_greed.ref_chem_groups,
- the_greed.mdl_chem_groups,
- mapped_ref_chains = set(mapping.keys()),
- mapped_mdl_chains = set(mapping.values()))
- for seed in seeds:
- n = the_greed.SCCounts(seed[0], seed[1])
- if n > n_best:
- n_best = n
- best_seed = seed
- if n_best == 0:
- break # no proper seed found anymore...
- # add seed to mapping and start the greed
- mapping[best_seed[0]] = best_seed[1]
- mapping = the_greed.ExtendMapping(mapping)
- something_happened = True
-
- # translate mapping format and return
- final_mapping = list()
- for ref_chains in the_greed.ref_chem_groups:
- mapped_mdl_chains = list()
- for ref_ch in ref_chains:
- if ref_ch in mapping:
- mapped_mdl_chains.append(mapping[ref_ch])
- else:
- mapped_mdl_chains.append(None)
- final_mapping.append(mapped_mdl_chains)
-
- return final_mapping
-
-
def _QSScoreGreedyFull(the_greed):
""" Uses each reference chain as starting point for expansion
"""
diff --git a/modules/mol/alg/tests/test_chain_mapping.py b/modules/mol/alg/tests/test_chain_mapping.py
index 48bd5ede1648f5b79c13cbdfa264947aea022675..b14213c97f31fec5f2bee98fe8fde59378e9e0e6 100644
--- a/modules/mol/alg/tests/test_chain_mapping.py
+++ b/modules/mol/alg/tests/test_chain_mapping.py
@@ -220,10 +220,6 @@ class TestChainMapper(unittest.TestCase):
naive_lddt_res = mapper.GetlDDTMapping(mdl, strategy="naive")
self.assertEqual(naive_lddt_res.mapping, [['X', 'Y'],[None],['Z']])
- # the "fast" strategy produces actually a suboptimal mapping in this case...
- greedy_lddt_res = mapper.GetlDDTMapping(mdl, strategy="greedy_fast")
- self.assertEqual(greedy_lddt_res.mapping, [['Y', 'X'],[None],['Z']])
-
greedy_lddt_res = mapper.GetlDDTMapping(mdl, strategy="greedy_full")
self.assertEqual(greedy_lddt_res.mapping, [['X', 'Y'],[None],['Z']])
@@ -238,9 +234,6 @@ class TestChainMapper(unittest.TestCase):
naive_qsscore_res = mapper.GetQSScoreMapping(mdl, strategy="naive")
self.assertEqual(naive_qsscore_res.mapping, [['X', 'Y'],[None],['Z']])
- greedy_qsscore_res = mapper.GetQSScoreMapping(mdl, strategy="greedy_fast")
- self.assertEqual(naive_qsscore_res.mapping, [['X', 'Y'],[None],['Z']])
-
greedy_qsscore_res = mapper.GetQSScoreMapping(mdl, strategy="greedy_full")
self.assertEqual(naive_qsscore_res.mapping, [['X', 'Y'],[None],['Z']])