[ENH] update for networkx dev version (should fix #2159)

doc/users/install.rst

@@ -47,7 +47,7 @@ use the following command::
 While `all` installs everything, one can also install select components as
 listed below::
 
-    'doc': ['Sphinx>=1.4', 'matplotlib', 'pydotplus'],
+    'doc': ['Sphinx>=1.4', 'matplotlib', 'pydotplus', 'pydot>=1.2.3'],
     'tests': ['pytest-cov', 'codecov'],
     'nipy': ['nitime', 'nilearn', 'dipy', 'nipy', 'matplotlib'],
     'profiler': ['psutil'],

examples/dmri_dtk_dti.py

@@ -37,7 +37,6 @@
 
 package_check('numpy', '1.3', 'tutorial1')
 package_check('scipy', '0.7', 'tutorial1')
-package_check('networkx', '1.0', 'tutorial1')
 package_check('IPython', '0.10', 'tutorial1')
 
 

examples/dmri_dtk_odf.py

@@ -37,7 +37,6 @@
 
 package_check('numpy', '1.3', 'tutorial1')
 package_check('scipy', '0.7', 'tutorial1')
-package_check('networkx', '1.0', 'tutorial1')
 package_check('IPython', '0.10', 'tutorial1')
 
 

examples/dmri_fsl_dti.py

@@ -37,7 +37,6 @@
 
 package_check('numpy', '1.3', 'tutorial1')
 package_check('scipy', '0.7', 'tutorial1')
-package_check('networkx', '1.0', 'tutorial1')
 package_check('IPython', '0.10', 'tutorial1')
 
 

examples/fmri_slicer_coregistration.py

@@ -37,7 +37,6 @@
 
 package_check('numpy', '1.3', 'tutorial1')
 package_check('scipy', '0.7', 'tutorial1')
-package_check('networkx', '1.0', 'tutorial1')
 package_check('IPython', '0.10', 'tutorial1')
 
 """The nipype tutorial contains data for two subjects.  Subject data

nipype/info.py

@@ -107,6 +107,7 @@ def get_nipype_gitversion():
 SIMPLEJSON_MIN_VERSION = '3.8.0'
 PROV_VERSION = '1.5.0'
 CLICK_MIN_VERSION = '6.6.0'
+PYDOT_MIN_VERSION = '1.2.3'
 
 NAME = 'nipype'
 MAINTAINER = 'nipype developers'
@@ -142,6 +143,7 @@ def get_nipype_gitversion():
     'pytest>=%s' % PYTEST_MIN_VERSION,
     'mock',
     'pydotplus',
+    'pydot>=%s' % PYDOT_MIN_VERSION,
     'packaging',
 ]
 
@@ -154,7 +156,7 @@ def get_nipype_gitversion():
 ]
 
 EXTRA_REQUIRES = {
-    'doc': ['Sphinx>=1.4', 'matplotlib', 'pydotplus'],
+    'doc': ['Sphinx>=1.4', 'matplotlib', 'pydotplus', 'pydot>=1.2.3'],
     'tests': TESTS_REQUIRES,
     'nipy': ['nitime', 'nilearn', 'dipy', 'nipy', 'matplotlib'],
     'profiler': ['psutil'],

nipype/interfaces/cmtk/cmtk.py

@@ -214,16 +214,16 @@ def cmat(track_file, roi_file, resolution_network_file, matrix_name, matrix_mat_
     nROIs = len(gp.nodes())
 
     # add node information from parcellation
-    if 'dn_position' in gp.node[gp.nodes()[0]]:
+    if 'dn_position' in gp.nodes[list(gp.nodes())[0]]:
         G = gp.copy()
     else:
         G = nx.Graph()
-        for u, d in gp.nodes_iter(data=True):
-            G.add_node(int(u), d)
+        for u, d in gp.nodes(data=True):
+            G.add_node(int(u), **d)
             # compute a position for the node based on the mean position of the
             # ROI in voxel coordinates (segmentation volume )
             xyz = tuple(np.mean(np.where(np.flipud(roiData) == int(d["dn_correspondence_id"])), axis=1))
-            G.node[int(u)]['dn_position'] = tuple([xyz[0], xyz[2], -xyz[1]])
+            G.nodes[int(u)]['dn_position'] = tuple([xyz[0], xyz[2], -xyz[1]])
 
     if intersections:
         iflogger.info("Filtering tractography from intersections")
@@ -304,7 +304,7 @@ def cmat(track_file, roi_file, resolution_network_file, matrix_name, matrix_mat_
     fibmean = numfib.copy()
     fibmedian = numfib.copy()
     fibdev = numfib.copy()
-    for u, v, d in G.edges_iter(data=True):
+    for u, v, d in G.edges(data=True):
         G.remove_edge(u, v)
         di = {}
         if 'fiblist' in d:
@@ -319,7 +319,7 @@ def cmat(track_file, roi_file, resolution_network_file, matrix_name, matrix_mat_
             di['fiber_length_median'] = 0
             di['fiber_length_std'] = 0
         if not u == v:  # Fix for self loop problem
-            G.add_edge(u, v, di)
+            G.add_edge(u, v, **di)
             if 'fiblist' in d:
                 numfib.add_edge(u, v, weight=di['number_of_fibers'])
                 fibmean.add_edge(u, v, weight=di['fiber_length_mean'])
@@ -747,10 +747,10 @@ def create_nodes(roi_file, resolution_network_file, out_filename):
     roi_image = nb.load(roi_file, mmap=NUMPY_MMAP)
     roiData = roi_image.get_data()
     nROIs = len(gp.nodes())
-    for u, d in gp.nodes_iter(data=True):
-        G.add_node(int(u), d)
+    for u, d in gp.nodes(data=True):
+        G.add_node(int(u), **d)
         xyz = tuple(np.mean(np.where(np.flipud(roiData) == int(d["dn_correspondence_id"])), axis=1))
-        G.node[int(u)]['dn_position'] = tuple([xyz[0], xyz[2], -xyz[1]])
+        G.nodes[int(u)]['dn_position'] = tuple([xyz[0], xyz[2], -xyz[1]])
     nx.write_gpickle(G, out_filename)
     return out_filename
 

nipype/interfaces/cmtk/nbs.py

@@ -113,9 +113,9 @@ def _run_interface(self, runtime):
         node_network = nx.read_gpickle(node_ntwk_name)
         iflogger.info('Populating node dictionaries with attributes from {node}'.format(node=node_ntwk_name))
 
-        for nid, ndata in node_network.nodes_iter(data=True):
-            nbsgraph.node[nid] = ndata
-            nbs_pval_graph.node[nid] = ndata
+        for nid, ndata in node_network.nodes(data=True):
+            nbsgraph.nodes[nid] = ndata
+            nbs_pval_graph.nodes[nid] = ndata
 
         path = op.abspath('NBS_Result_' + details)
         iflogger.info(path)

nipype/interfaces/cmtk/nx.py

@@ -48,7 +48,7 @@ def read_unknown_ntwk(ntwk):
 
 def remove_all_edges(ntwk):
     ntwktmp = ntwk.copy()
-    edges = ntwktmp.edges_iter()
+    edges = list(ntwktmp.edges())
     for edge in edges:
         ntwk.remove_edge(edge[0], edge[1])
     return ntwk
@@ -60,20 +60,20 @@ def fix_keys_for_gexf(orig):
     """
     import networkx as nx
     ntwk = nx.Graph()
-    nodes = orig.nodes_iter()
-    edges = orig.edges_iter()
+    nodes = list(orig.nodes())
+    edges = list(orig.edges())
     for node in nodes:
         newnodedata = {}
-        newnodedata.update(orig.node[node])
-        if 'dn_fsname' in orig.node[node]:
-            newnodedata['label'] = orig.node[node]['dn_fsname']
-        ntwk.add_node(str(node), newnodedata)
-        if 'dn_position' in ntwk.node[str(node)] and 'dn_position' in newnodedata:
-            ntwk.node[str(node)]['dn_position'] = str(newnodedata['dn_position'])
+        newnodedata.update(orig.nodes[node])
+        if 'dn_fsname' in orig.nodes[node]:
+            newnodedata['label'] = orig.nodes[node]['dn_fsname']
+        ntwk.add_node(str(node), **newnodedata)
+        if 'dn_position' in ntwk.nodes[str(node)] and 'dn_position' in newnodedata:
+            ntwk.nodes[str(node)]['dn_position'] = str(newnodedata['dn_position'])
     for edge in edges:
         data = {}
         data = orig.edge[edge[0]][edge[1]]
-        ntwk.add_edge(str(edge[0]), str(edge[1]), data)
+        ntwk.add_edge(str(edge[0]), str(edge[1]), **data)
         if 'fiber_length_mean' in ntwk.edge[str(edge[0])][str(edge[1])]:
             ntwk.edge[str(edge[0])][str(edge[1])]['fiber_length_mean'] = str(data['fiber_length_mean'])
         if 'fiber_length_std' in ntwk.edge[str(edge[0])][str(edge[1])]:
@@ -125,7 +125,7 @@ def average_networks(in_files, ntwk_res_file, group_id):
             tmp = nx.read_gpickle(subject)
             iflogger.info(('File {s} has {n} '
                            'edges').format(s=subject, n=tmp.number_of_edges()))
-            edges = tmp.edges_iter()
+            edges = list(tmp.edges())
             for edge in edges:
                 data = {}
                 data = tmp.edge[edge[0]][edge[1]]
@@ -134,29 +134,29 @@ def average_networks(in_files, ntwk_res_file, group_id):
                     current = {}
                     current = ntwk.edge[edge[0]][edge[1]]
                     data = add_dicts_by_key(current, data)
-                ntwk.add_edge(edge[0], edge[1], data)
-            nodes = tmp.nodes_iter()
+                ntwk.add_edge(edge[0], edge[1], **data)
+            nodes = list(nodes())
             for node in nodes:
                 data = {}
-                data = ntwk.node[node]
-                if 'value' in tmp.node[node]:
-                    data['value'] = data['value'] + tmp.node[node]['value']
-                ntwk.add_node(node, data)
+                data = ntwk.nodes[node]
+                if 'value' in tmp.nodes[node]:
+                    data['value'] = data['value'] + tmp.nodes[node]['value']
+                ntwk.add_node(node, **data)
 
         # Divides each value by the number of files
-        nodes = ntwk.nodes_iter()
-        edges = ntwk.edges_iter()
+        nodes = list(ntwk.nodes())
+        edges = list(ntwk.edges())
         iflogger.info(('Total network has {n} '
                        'edges').format(n=ntwk.number_of_edges()))
         avg_ntwk = nx.Graph()
         newdata = {}
         for node in nodes:
-            data = ntwk.node[node]
+            data = ntwk.nodes[node]
             newdata = data
             if 'value' in data:
                 newdata['value'] = data['value'] / len(in_files)
-                ntwk.node[node]['value'] = newdata
-            avg_ntwk.add_node(node, newdata)
+                ntwk.nodes[node]['value'] = newdata
+            avg_ntwk.add_node(node, **newdata)
 
         edge_dict = {}
         edge_dict['count'] = np.zeros((avg_ntwk.number_of_nodes(),
@@ -168,12 +168,12 @@ def average_networks(in_files, ntwk_res_file, group_id):
                     if not key == 'count':
                         data[key] = data[key] / len(in_files)
                 ntwk.edge[edge[0]][edge[1]] = data
-                avg_ntwk.add_edge(edge[0], edge[1], data)
+                avg_ntwk.add_edge(edge[0], edge[1], **data)
             edge_dict['count'][edge[0] - 1][edge[1] - 1] = ntwk.edge[edge[0]][edge[1]]['count']
 
         iflogger.info('After thresholding, the average network has has {n} edges'.format(n=avg_ntwk.number_of_edges()))
 
-        avg_edges = avg_ntwk.edges_iter()
+        avg_edges = avg_ntwk.edges()
         for edge in avg_edges:
             data = avg_ntwk.edge[edge[0]][edge[1]]
             for key in list(data.keys()):
@@ -319,11 +319,11 @@ def compute_network_measures(ntwk):
 def add_node_data(node_array, ntwk):
     node_ntwk = nx.Graph()
     newdata = {}
-    for idx, data in ntwk.nodes_iter(data=True):
+    for idx, data in ntwk.nodes(data=True):
         if not int(idx) == 0:
             newdata['value'] = node_array[int(idx) - 1]
             data.update(newdata)
-            node_ntwk.add_node(int(idx), data)
+            node_ntwk.add_node(int(idx), **data)
     return node_ntwk
 
 
@@ -339,7 +339,7 @@ def add_edge_data(edge_array, ntwk, above=0, below=0):
                         old_edge_dict = edge_ntwk.edge[x + 1][y + 1]
                         edge_ntwk.remove_edge(x + 1, y + 1)
                         data.update(old_edge_dict)
-                    edge_ntwk.add_edge(x + 1, y + 1, data)
+                    edge_ntwk.add_edge(x + 1, y + 1, **data)
     return edge_ntwk
 
 

nipype/interfaces/cmtk/parcellation.py

@@ -213,7 +213,7 @@ def create_roi(subject_id, subjects_dir, fs_dir, parcellation_name, dilation):
     rois = np.zeros((256, 256, 256), dtype=np.int16)
 
     count = 0
-    for brk, brv in pg.nodes_iter(data=True):
+    for brk, brv in pg.nodes(data=True):
         count = count + 1
         iflogger.info(brv)
         iflogger.info(brk)
@@ -429,7 +429,7 @@ def create_wm_mask(subject_id, subjects_dir, fs_dir, parcellation_name):
     roid = roi.get_data()
     assert roid.shape[0] == wmmask.shape[0]
     pg = nx.read_graphml(pgpath)
-    for brk, brv in pg.nodes_iter(data=True):
+    for brk, brv in pg.nodes(data=True):
         if brv['dn_region'] == 'cortical':
             iflogger.info("Subtracting region %s with intensity value %s" %
                           (brv['dn_region'], brv['dn_correspondence_id']))

nipype/pipeline/engine/tests/test_engine.py

@@ -316,7 +316,7 @@ def test_disconnect():
     flow1 = pe.Workflow(name='test')
     flow1.connect(a, 'a', b, 'a')
     flow1.disconnect(a, 'a', b, 'a')
-    assert flow1._graph.edges() == []
+    assert list(flow1._graph.edges()) == []
 
 
 def test_doubleconnect():
@@ -637,7 +637,7 @@ def func1(in1):
     n1.inputs.in1 = [1]
     eg = w1.run()
 
-    node = eg.nodes()[0]
+    node = list(eg.nodes())[0]
     outjson = glob(os.path.join(node.output_dir(), '_0x*.json'))
     assert len(outjson) == 1