fix backwards compatibility with inspiral_pipe-based workflows

gstlal-inspiral/bin/gstlal_inspiral_make_mc_vtplot

@@ -116,7 +116,12 @@ injs, inj_files = [], []
 if options.check_vt:
 	connection = {}
 	for f in options.injection_database:
-		inj_file = CacheEntry.from_T050017(f).description.rpartition(f"GSTLAL_TRIGGER_DATABASE")[2].lstrip("_")
+		# get injection tag from filename, supporting
+		# both old and new filename convention
+		if "GSTLAL_TRIGGER_DATABASE" in f:
+			inj_file = CacheEntry.from_T050017(f).description.rpartition(f"GSTLAL_TRIGGER_DATABASE")[2].lstrip("_")
+		else:
+			inj_file = f.split("-")[1].replace("ALL_LLOID_","")
 		inj_files.append(inj_file)
 		connection[inj_file] = sqlite3.connect(f)
 		injs += lsctables.SimInspiralTable.get_table(dbtables.get_xml(connection[inj_file]))

gstlal-inspiral/python/inspiral_pipe.py

@@ -62,6 +62,7 @@ from gstlal import dagparts
 from gstlal import datasource
 from gstlal import inspiral
 from gstlal import svd_bank
+from gstlal.datafind import DataType
 
 
 warnings.warn(
@@ -407,12 +408,13 @@ def injection_template_match_layer(dag, jobs, parent_nodes, options, instruments
 		sim_name = sim_tag_from_inj_file(inj)
 		inj_tmplt_match_nodes[sim_name] = {}
 		for nsplit in range(options.num_split_inj_files):
+			inj_filename = DataType.SPLIT_INJECTIONS.filename("H1K1L1V1", segments.segment(0, 0), f"{nsplit:04d}", sim_name)
 			inj_tmplt_match_nodes[sim_name][nsplit] = dagparts.DAGNode(
 				jobs['injTmpltMatch'],
 				dag,
 				parent_nodes = parent_nodes,
 				input_files = {
-					"injection-file": "%s/%s_INJ_SPLIT_%04d.xml"%(jobs['injSplitter'].output_path, sim_name, nsplit),
+					"injection-file": os.path.join(jobs['injSplitter'].output_path, inj_filename),
 					"template-bank": options.template_bank
 				},
 				output_files = {"output": "%s/%s-INJECTION_TEMPLATE_MATCH_%s_%04d.xml.gz"%(jobs['injTmpltMatch'].output_path, instruments, sim_name, nsplit)}
@@ -720,12 +722,13 @@ def inspiral_layer(dag, jobs, psd_nodes, svd_nodes, segsdict, options, channel_d
 def expected_snr_layer(dag, jobs, ref_psd_parent_nodes, options, num_split_inj_snr_jobs):
 	ligolw_add_nodes = []
 	for inj in options.injections:
+		sim_tag = sim_tag_from_inj_file(inj.split(":")[-1])
 		inj_snr_nodes = []
 
 		inj_splitter_node = dagparts.DAGNode(jobs['injSplitter'], dag, parent_nodes=[],
 			opts = {
 				"output-path":jobs['injSplitter'].output_path,
-				"usertag": sim_tag_from_inj_file(inj.split(":")[-1]),
+				"usertag": sim_tag,
 				"nsplit": num_split_inj_snr_jobs
 			},
 			input_files = {"": inj.split(":")[-1]}
@@ -733,8 +736,10 @@ def expected_snr_layer(dag, jobs, ref_psd_parent_nodes, options, num_split_inj_s
 		inj_splitter_node.set_priority(98)
 
 		# FIXME Use machinery in inspiral_pipe.py to create reference_psd.cache
-		injection_files = ["%s/%s_INJ_SPLIT_%04d.xml" % (jobs['injSplitter'].output_path, sim_tag_from_inj_file(inj.split(":")[-1]), i) for i in range(num_split_inj_snr_jobs)]
-		for injection_file in injection_files:
+		injection_files = []
+		for i in range(num_split_inj_snr_jobs):
+			inj_filename = DataType.SPLIT_INJECTIONS.filename("H1K1L1V1", segments.segment(0, 0), f"{i:04d}", sim_tag)
+			injection_file = os.path.join(jobs['injSplitter'].output_path, inj_filename)
 			injSNRnode = dagparts.DAGNode(jobs['gstlalInjSnr'], dag, parent_nodes=ref_psd_parent_nodes + [inj_splitter_node],
 				# FIXME somehow choose the actual flow based on mass?
 				# max(flow) is chosen for performance not
@@ -748,6 +753,7 @@ def expected_snr_layer(dag, jobs, ref_psd_parent_nodes, options, num_split_inj_s
 			)
 			injSNRnode.set_priority(98)
 			inj_snr_nodes.append(injSNRnode)
+			injection_files.append(injection_file)
 
 		addnode = dagparts.DAGNode(jobs['ligolwAdd'], dag, parent_nodes=inj_snr_nodes,
 			input_files = {"": ' '.join(injection_files)},
@@ -1225,7 +1231,7 @@ def sql_cluster_and_merge_layer(dag, jobs, likelihood_nodes, ligolw_add_nodes, o
 			injdb = dagparts.T050017_filename(instruments, 'PART_LLOID_%s_CHUNK_%04d' % (sim_tag_from_inj_file(injections), chunk), boundary_seg, '.sqlite')
 
 			# merge and cluster
-			clusternode = merge_cluster_layer(dag, jobs, injnodes, injdb, [node.input_files[""] for node in injnodes], options.cluster_sql_file)
+			clusternode = merge_cluster_layer(dag, jobs, injnodes, injdb, [node.input_files[""] for node in injnodes], options.injection_sql_file)
 			final_nodes.append(clusternode)
 
 		# Setup the final output names, etc.
@@ -1239,7 +1245,7 @@ def sql_cluster_and_merge_layer(dag, jobs, likelihood_nodes, ligolw_add_nodes, o
 		parent_nodes = final_nodes + ligolw_add_nodes
 		input_files = (vetoes + [options.frame_segments_file, injections])
 		input_cache_files = [node.input_files[""] for node in final_nodes]
-		clusternode = merge_cluster_layer(dag, jobs, parent_nodes, injdb, input_cache_files, options.cluster_sql_file, input_files=input_files)
+		clusternode = merge_cluster_layer(dag, jobs, parent_nodes, injdb, input_cache_files, options.injection_sql_file, input_files=input_files)
 
 		clusternode = dagparts.DAGNode(jobs['toXML'], dag, parent_nodes = [clusternode],
 			opts = {"tmp-space":dagparts.condor_scratch_space()},
@@ -1379,8 +1385,11 @@ def make_mc_vtplot_layer(dag, jobs, parent_nodes, add_parent_node, options, inst
 		lnlrcdf_cache = dagparts.group_T050017_filename_from_T050017_files(lnlrcdf_caches, '.xml.gz', path = jobs['makeMcVtplot'].output_path)
 		input_files = {
 			"ranking-stat-pdf": "post_marginalized_likelihood.xml.gz",
-			"": inj
 		}
+		if injdbs:
+			input_files["injection-database"] = inj
+		else:
+			input_files["injection-files"] = inj
 
 		if injdbs:
 			job = jobs['makeMcVtplotCheck']
@@ -1407,7 +1416,7 @@ def horizon_dist_layer(dag, jobs, psd_nodes, options, boundary_seg, output_dir,
 	dagparts.DAGNode(jobs['horizon'], dag,
 		parent_nodes = list(psd_nodes.values()),
 		input_files = {"":[node.output_files["write-psd"] for node in psd_nodes.values()]},
-		output_files = {"":dagparts.T050017_filename(instruments, "HORIZON", boundary_seg, '.png', path = output_dir)}
+		output_files = {"output":dagparts.T050017_filename(instruments, "HORIZON", boundary_seg, '.png', path = output_dir)}
 	)