enable reuse of resource_monitor.json, write it in base_dir

Author: oesteban

nipype/pipeline/engine/utils.py

@@ -1297,7 +1297,7 @@ def write_workflow_prov(graph, filename=None, format='all'):
     return ps.g
 
 
-def write_workflow_resources(graph, filename=None):
+def write_workflow_resources(graph, filename=None, append=True):
     """
     Generate a JSON file with profiling traces that can be loaded
     in a pandas DataFrame or processed with JavaScript like D3.js
@@ -1316,14 +1316,21 @@ def write_workflow_resources(graph, filename=None):
         'params': [],
     }
 
+    # If file exists, just append new profile information
+    # If we append different runs, then we will see different
+    # "bursts" of timestamps corresponding to those executions.
+    if append and os.path.isfile(filename):
+        with open(filename, 'r' if PY3 else 'rb') as rsf:
+            big_dict = json.load(rsf)
+
     for idx, node in enumerate(graph.nodes()):
         nodename = node.fullname
         classname = node._interface.__class__.__name__
 
         params = ''
         if node.parameterization:
             params = '_'.join(['{}'.format(p)
-                              for p in node.parameterization])
+                               for p in node.parameterization])
 
         try:
             rt_list = node.result.runtime

nipype/pipeline/engine/workflows.py

@@ -596,7 +596,10 @@ def run(self, plugin=None, plugin_args=None, updatehash=False):
             write_workflow_prov(execgraph, prov_base, format='all')
 
         if config.resource_monitor:
-            write_workflow_resources(execgraph)
+            write_workflow_resources(
+                execgraph,
+                filename=op.join(self.base_dir, self.name, 'resource_monitor.json')
+            )
         return execgraph
 
     # PRIVATE API AND FUNCTIONS