diff --git a/actions/ost-compare-structures b/actions/ost-compare-structures
index 95e89e58a775495064f1f9ac1b26eefd22cd0994..a4a821a5a2dbc6d257c7fa568e83d68b4ddac392 100644
--- a/actions/ost-compare-structures
+++ b/actions/ost-compare-structures
@@ -304,19 +304,17 @@ def _ParseArgs():
"separation is higher than the provided parameter are\n"
"considered when computing the score"))
parser.add_argument(
- "-ic",
- "--ignore-consistency-checks",
- dest="ignore_consistency_checks",
+ "-cc",
+ "--consistency-checks",
+ dest="consistency_checks",
default=False,
action="store_true",
- help=("Ignore consistency checks. By default residue name\n"
+ help=("Take consistency checks into account. By default residue name\n"
"consistency between a model-reference pair would be checked\n"
- "and an error will be rised if no valid pair is found (For\n"
- "mmCIF there could be more than one biounit in one file).\n"
- "The pair that does not conform to the check will be skipped.\n"
- "If the option is selected consistency checks will also be\n"
- "performed but only a warning will be shown and the pair will\b"
- "evaluated."))
+ "but only a warning message will be displayed and the script\n"
+ "will continue to calculate scores. If this flag is ON, checks\n"
+ "will not be ignored and if the pair does not pass the test\n"
+ "all the scores for that pair will be marked as a FAILURE."))
parser.add_argument(
"-spr",
"--save-per-residue-scores",
@@ -595,7 +593,8 @@ def _Main():
model_results = dict()
for reference in references:
reference_name = reference.GetName()
- reference_results = dict()
+ reference_results = {
+ "info": dict()}
ost.LogInfo("#" * 80)
ost.LogInfo("Comparing %s to %s" % (
model_name,
@@ -617,16 +616,18 @@ def _Main():
reference,
model,
qs_scorer.chain_mapping,
- not opts.ignore_consistency_checks)
- if not opts.ignore_consistency_checks:
+ opts.consistency_checks)
+ reference_results["info"]["residue_names_consistent"] = is_cons
+ skip_score = False
+ if opts.consistency_checks:
if not is_cons:
msg = (("Residue names in model %s and in reference "
- "%s are inconsistent. Skipping.") % (
+ "%s are inconsistent.") % (
model_name,
reference_name))
ost.LogError(msg)
- skipped.append(True)
- continue
+ skip_score = True
+ skipped.append(skip_score)
else:
ost.LogInfo("Consistency check: OK")
skipped.append(False)
@@ -643,29 +644,39 @@ def _Main():
ost.LogInfo("Consistency check: OK")
if opts.qs_score:
ost.LogInfo("-" * 80)
- ost.LogInfo("Computing QS-score")
- try:
- reference_results["qs_score"] = {
- "status": "SUCCESS",
- "error": "",
- "model_name": model_name,
- "reference_name": reference_name,
- "global_score": qs_scorer.global_score,
- "best_score": qs_scorer.best_score,
- "chain_mapping": qs_scorer.chain_mapping
- }
- except qsscoring.QSscoreError as ex:
- # default handling: report failure and set score to 0
- ost.LogError('QSscore failed:', str(ex))
+ if skip_score:
+ ost.LogInfo(
+ "Skipping QS-score because consistency check failed")
reference_results["qs_score"] = {
"status": "FAILURE",
- "error": str(ex),
+ "error": "Consistency check failed.",
"model_name": model_name,
- "reference_name": reference.GetName(),
+ "reference_name": reference_name,
"global_score": 0.0,
"best_score": 0.0,
- "chain_mapping": qs_scorer.chain_mapping
- }
+ "chain_mapping": qs_scorer.chain_mapping}
+ else:
+ ost.LogInfo("Computing QS-score")
+ try:
+ reference_results["qs_score"] = {
+ "status": "SUCCESS",
+ "error": "",
+ "model_name": model_name,
+ "reference_name": reference_name,
+ "global_score": qs_scorer.global_score,
+ "best_score": qs_scorer.best_score,
+ "chain_mapping": qs_scorer.chain_mapping}
+ except qsscoring.QSscoreError as ex:
+ # default handling: report failure and set score to 0
+ ost.LogError('QSscore failed:', str(ex))
+ reference_results["qs_score"] = {
+ "status": "FAILURE",
+ "error": str(ex),
+ "model_name": model_name,
+ "reference_name": reference_name,
+ "global_score": 0.0,
+ "best_score": 0.0,
+ "chain_mapping": qs_scorer.chain_mapping}
# Calculate lDDT
if opts.lddt:
ost.LogInfo("-" * 80)
@@ -694,91 +705,119 @@ def _Main():
for scorer_index, lddt_scorer in enumerate(
oligo_lddt_scorer.sc_lddt_scorers):
# Get chains and renumber according to alignment (for lDDT)
- try:
- model_chain = lddt_scorer.model.chains[0].GetName()
- reference_chain = \
- lddt_scorer.references[0].chains[0].GetName()
- ost.LogInfo((" --> Computing lDDT between model "
- "chain %s and reference chain %s") % (
- model_chain,
- reference_chain))
- ost.LogInfo("Global LDDT score: %.4f" %
- lddt_scorer.global_score)
+ model_chain = lddt_scorer.model.chains[0].GetName()
+ reference_chain = \
+ lddt_scorer.references[0].chains[0].GetName()
+ if skip_score:
ost.LogInfo(
- "(%i conserved distances out of %i checked, over "
- "%i thresholds)" % (lddt_scorer.conserved_contacts,
- lddt_scorer.total_contacts,
- len(lddt_settings.cutoffs)))
- sc_lddt_scores = {
- "status": "SUCCESS",
- "error": "",
- "model_chain": model_chain,
- "reference_chain": reference_chain,
- "global_score": lddt_scorer.global_score,
- "conserved_contacts":
- lddt_scorer.conserved_contacts,
- "total_contacts": lddt_scorer.total_contacts}
- if opts.save_per_residue_scores:
- per_residue_sc = \
- oligo_lddt_scorer.GetPerResidueScores(
- scorer_index)
- ost.LogInfo("Per residue local lDDT (reference):")
- ost.LogInfo("Chain\tResidue Number\tResidue Name"
- "\tlDDT\tConserved Contacts\tTotal "
- "Contacts")
- for prs_scores in per_residue_sc:
- ost.LogInfo("%s\t%i\t%s\t%.4f\t%i\t%i" % (
- reference_chain,
- prs_scores["residue_number"],
- prs_scores["residue_name"],
- prs_scores["lddt"],
- prs_scores["conserved_contacts"],
- prs_scores["total_contacts"]))
- sc_lddt_scores["per_residue_scores"] = \
- per_residue_sc
- lddt_results["single_chain_lddt"].append(
- sc_lddt_scores)
- except Exception as ex:
- ost.LogError('Single chain lDDT failed:', str(ex))
+ " --> Skipping signle chain lDDT because consistency check failed")
lddt_results["single_chain_lddt"].append({
"status": "FAILURE",
- "error": str(ex),
+ "error": "Consistency check failed.",
"model_chain": model_chain,
"reference_chain": reference_chain,
"global_score": 0.0,
"conserved_contacts": 0.0,
"total_contacts": 0.0})
+ else:
+ try:
+ ost.LogInfo((" --> Computing lDDT between model "
+ "chain %s and reference chain %s") % (
+ model_chain,
+ reference_chain))
+ ost.LogInfo("Global LDDT score: %.4f" %
+ lddt_scorer.global_score)
+ ost.LogInfo(
+ "(%i conserved distances out of %i checked, over "
+ "%i thresholds)" % (lddt_scorer.conserved_contacts,
+ lddt_scorer.total_contacts,
+ len(lddt_settings.cutoffs)))
+ sc_lddt_scores = {
+ "status": "SUCCESS",
+ "error": "",
+ "model_chain": model_chain,
+ "reference_chain": reference_chain,
+ "global_score": lddt_scorer.global_score,
+ "conserved_contacts":
+ lddt_scorer.conserved_contacts,
+ "total_contacts": lddt_scorer.total_contacts}
+ if opts.save_per_residue_scores:
+ per_residue_sc = \
+ oligo_lddt_scorer.GetPerResidueScores(
+ scorer_index)
+ ost.LogInfo("Per residue local lDDT (reference):")
+ ost.LogInfo("Chain\tResidue Number\tResidue Name"
+ "\tlDDT\tConserved Contacts\tTotal "
+ "Contacts")
+ for prs_scores in per_residue_sc:
+ ost.LogInfo("%s\t%i\t%s\t%.4f\t%i\t%i" % (
+ reference_chain,
+ prs_scores["residue_number"],
+ prs_scores["residue_name"],
+ prs_scores["lddt"],
+ prs_scores["conserved_contacts"],
+ prs_scores["total_contacts"]))
+ sc_lddt_scores["per_residue_scores"] = \
+ per_residue_sc
+ lddt_results["single_chain_lddt"].append(
+ sc_lddt_scores)
+ except Exception as ex:
+ ost.LogError('Single chain lDDT failed:', str(ex))
+ lddt_results["single_chain_lddt"].append({
+ "status": "FAILURE",
+ "error": str(ex),
+ "model_chain": model_chain,
+ "reference_chain": reference_chain,
+ "global_score": 0.0,
+ "conserved_contacts": 0.0,
+ "total_contacts": 0.0})
# perform oligo lddt scoring
- try:
- ost.LogInfo(' --> Computing oligomeric lDDT score')
- lddt_results["oligo_lddt"] = {
- "status": "SUCCESS",
- "error": "",
- "global_score": oligo_lddt_scorer.oligo_lddt}
+ if skip_score:
ost.LogInfo(
- "Oligo lDDT score: %.4f" %
- oligo_lddt_scorer.oligo_lddt)
- except Exception as ex:
- ost.LogError('Oligo lDDT failed:', str(ex))
+ " --> Skipping oligomeric lDDT because consistency check failed")
lddt_results["oligo_lddt"] = {
"status": "FAILURE",
- "error": str(ex),
+ "error": "Consistency check failed.",
"global_score": 0.0}
- try:
- ost.LogInfo(' --> Computing weighted lDDT score')
- lddt_results["weighted_lddt"] = {
- "status": "SUCCESS",
- "error": "",
- "global_score": oligo_lddt_scorer.weighted_lddt}
+ else:
+ try:
+ ost.LogInfo(' --> Computing oligomeric lDDT score')
+ lddt_results["oligo_lddt"] = {
+ "status": "SUCCESS",
+ "error": "",
+ "global_score": oligo_lddt_scorer.oligo_lddt}
+ ost.LogInfo(
+ "Oligo lDDT score: %.4f" %
+ oligo_lddt_scorer.oligo_lddt)
+ except Exception as ex:
+ ost.LogError('Oligo lDDT failed:', str(ex))
+ lddt_results["oligo_lddt"] = {
+ "status": "FAILURE",
+ "error": str(ex),
+ "global_score": 0.0}
+ if skip_score:
ost.LogInfo(
- "Weighted lDDT score: %.4f" %
- oligo_lddt_scorer.weighted_lddt)
- except Exception as ex:
- ost.LogError('Weighted lDDT failed:', str(ex))
+ " --> Skipping weighted lDDT because consistency check failed")
lddt_results["weighted_lddt"] = {
"status": "FAILURE",
- "error": str(ex),
+ "error": "Consistency check failed.",
"global_score": 0.0}
+ else:
+ try:
+ ost.LogInfo(' --> Computing weighted lDDT score')
+ lddt_results["weighted_lddt"] = {
+ "status": "SUCCESS",
+ "error": "",
+ "global_score": oligo_lddt_scorer.weighted_lddt}
+ ost.LogInfo(
+ "Weighted lDDT score: %.4f" %
+ oligo_lddt_scorer.weighted_lddt)
+ except Exception as ex:
+ ost.LogError('Weighted lDDT failed:', str(ex))
+ lddt_results["weighted_lddt"] = {
+ "status": "FAILURE",
+ "error": str(ex),
+ "global_score": 0.0}
reference_results["lddt"] = lddt_results
model_results[reference_name] = reference_results
if opts.dump_structures:
@@ -806,8 +845,7 @@ def _Main():
result["result"][model_name] = model_results
if all(skipped) and len(skipped) > 0:
- raise RuntimeError("Consistency check failed for all model-reference "
- "pairs.")
+ ost.LogError("Consistency check failed for all model-reference pairs.")
if opts.output is not None:
ost.LogInfo("#" * 80)
ost.LogInfo("Saving output into %s" % opts.output)