Updated shortest path determination to reflect networkx return struct…

…ure; updated requirements

setup.py

@@ -14,23 +14,23 @@
 
 
 setup(name='wishbone',
-      version='0.4.1.1',
+      version='0.4.2',
       description='Wishbone algorithm for identifying bifurcating trajectories from single-cell data',
       author='Manu Setty',
       author_email='manu.talanki@gmail.com',
       package_dir={'': 'src'},
       packages=['wishbone'],
       install_requires=[
-          'numpy>=1.10.0',
-          'pandas>=0.18.0',
-          'scipy>=0.14.0',
+          'numpy>=1.12.0',
+          'pandas>=0.19.2',
+          'scipy>=0.18.1',
           'bhtsne',
-          'matplotlib',
-          'seaborn',
+          'matplotlib>=1.5.1sn',
+          'seaborn>=0.7.1',
           'sklearn',
-          'networkx',
-          'fcsparser',
-          'statsmodels'],
+          'networkx>=1.11',
+          'fcsparser>=0.1.2',
+          'statsmodels>=0.8.0'],
       scripts=['src/wishbone/wishbone_gui.py'],
       )
 
@@ -43,8 +43,6 @@
 if os.path.isdir(tools_dir):
     shutil.rmtree(tools_dir)
 shutil.copytree(setup_dir + '/tools/', tools_dir)
-shutil.unpack_archive(tools_dir + '/DiffusionGeometry.zip', tools_dir +
-                      '/DiffusionGeometry/')
 shutil.unpack_archive(tools_dir + '/mouse_gene_sets.tar.gz', tools_dir)
 shutil.unpack_archive(tools_dir + '/human_gene_sets.tar.gz', tools_dir)
 

src/wishbone/__init__.py

@@ -3,4 +3,4 @@
 from . import wishbone_gui
 from . import autocomplete_entry
 
-__version__ = "0.4.1.1"
+__version__ = "0.4.2"

src/wishbone/core.py

@@ -250,22 +250,20 @@ def _trajectory_landmarks(spdists, data, s, waypoints, partial_order,
 	# # calculate all shortest paths
 	print('Determining shortest path distances and perspectives....')
 	graph = nx.Graph(spdists)
+	dist = np.zeros([len(l), data.shape[0]])
+	paths_l2l = list()
 
 	for i in range(len(l)):
+		# Shortest distances and paths
 		temp = nx.single_source_dijkstra(graph, l[i])
 		paths = temp[1]
-		# dist[i, :] = temp[0].values()
+		dist[i, list(temp[0].keys())] = list(temp[0].values())
+		paths_l2l.append( [paths[li] for li in l] )
 
-		if i == 0:
-			dist = [list(temp[0].values())]
-			paths_l2l = [[paths[li] for li in l]]
-		else:
-			dist.append(list(temp[0].values()))
-			paths_l2l.append([paths[li] for li in l])
-
-		unreachable = np.where(dist[i]==np.inf)[0]
+		# Update distances for unreachable cells
+		unreachable = np.where(dist[i, :]==np.inf)[0]
 		if(len(unreachable) > 0):
-			dist[i][unreachable] = max(max(dist))
+			dist[i, unreachable] = np.max(dist[i, dist[i, :] != np.inf])
 		if(verbose):
 			sys.stdout.write('.')
 	print("")