Output external clusterings with visualisations

PopPUNK/__init__.py

@@ -3,7 +3,7 @@
 
 '''PopPUNK (POPulation Partitioning Using Nucleotide Kmers)'''
 
-__version__ = '2.6.4'
+__version__ = '2.6.5'
 
 # Minimum sketchlib version
 SKETCHLIB_MAJOR = 2

PopPUNK/visualise.py

@@ -235,7 +235,7 @@ def generate_visualisations(query_db,
         sys.stderr.write("Must specify at least one type of visualisation to output\n")
         sys.exit(1)
     if cytoscape and not (microreact or phandango or grapetree):
-        if rank_fit == None and not os.path.isfile(network_file):
+        if rank_fit == None and (network_file == None or not os.path.isfile(network_file)):
             sys.stderr.write("For cytoscape, specify either a network file to visualise "
                              "with --network-file or a lineage model with --rank-fit\n")
             sys.exit(1)
@@ -396,13 +396,13 @@ def generate_visualisations(query_db,
     isolateClustering = {}
     # Use external clustering if specified
     if external_clustering:
+        mode = 'external'
         cluster_file = external_clustering
-        isolateClustering = readIsolateTypeFromCsv(cluster_file,
-                                                   mode = 'external',
-                                                   return_dict = True)
-
+        if cluster_file.endswith('_lineages.csv'):
+            suffix = "_lineages.csv"
+        else:
+            suffix = "_clusters.csv"
     else:
-
         # Load previous clusters
         if previous_clustering is not None:
             cluster_file = previous_clustering
@@ -419,14 +419,15 @@ def generate_visualisations(query_db,
                 mode = "lineages"
                 suffix = "_lineages.csv"
             cluster_file = os.path.join(model_prefix, os.path.basename(model_prefix) + suffix)
-        isolateClustering = readIsolateTypeFromCsv(cluster_file,
-                                                   mode = mode,
-                                                   return_dict = True)
+
+    isolateClustering = readIsolateTypeFromCsv(cluster_file,
+                                               mode = mode,
+                                               return_dict = True)
 
     # Add individual refinement clusters if they exist
     if model.indiv_fitted:
-        for type, suffix in zip(['Core','Accessory'],['_core_clusters.csv','_accessory_clusters.csv']):
-            indiv_clustering = os.path.join(model_prefix, os.path.basename(model_prefix) + suffix)
+        for type, indiv_suffix in zip(['Core','Accessory'],['_core_clusters.csv','_accessory_clusters.csv']):
+            indiv_clustering = os.path.join(model_prefix, os.path.basename(model_prefix) + indiv_suffix)
             if os.path.isfile(indiv_clustering):
                 indiv_isolateClustering = readIsolateTypeFromCsv(indiv_clustering,
                                                                    mode = mode,

test/run_test.py

@@ -118,6 +118,12 @@
     sys.stderr.write('Failed to query lineages from strain database\n')
     sys.exit(1)
 
+# beebop test
+subprocess.run(python_cmd + " ../poppunk-runner.py --create-db --r-files rfile12.txt --output batch12 --overwrite", shell=True, check=True)
+subprocess.run(python_cmd + " ../poppunk-runner.py --fit-model bgmm --D 2 --ref-db batch12 --overwrite", shell=True, check=True)
+subprocess.run(python_cmd + " ../poppunk_assign-runner.py --db batch12 --query rfile3.txt --output batch3 --external-clustering batch12_external_clusters.csv  --overwrite", shell=True, check=True)
+subprocess.run(python_cmd + " ../poppunk_visualise-runner.py --ref-db batch12 --query-db batch3 --output batch123_viz --external-clustering batch12_external_clusters.csv --previous-query-clustering batch3/batch3_external_clusters.csv --cytoscape --rapidnj rapidnj --network-file ./batch12/batch12_graph.gt --overwrite", shell=True, check=True)
+
 # citations
 sys.stderr.write("Printing citations\n")
 subprocess.run(python_cmd + " ../poppunk-runner.py --citation --fit-model bgmm --ref-db example_db --K 4", shell=True, check=True)