From 9355916fd92520b40446837a41f1b11a3faef827 Mon Sep 17 00:00:00 2001
From: Dilawar Singh <dilawars@ncbs.res.in>
Date: Thu, 22 Jun 2017 15:27:22 +0530
Subject: [PATCH] Squashed 'moose-core/' changes from 3498c1801a..0e0615c816

0e0615c816 Fixes to #186 are integrated into chamcham release.

git-subtree-dir: moose-core
git-subtree-split: 0e0615c8161f99ad294448e68c122b651da879e3
---
 python/moose/neuroml/NetworkML.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/python/moose/neuroml/NetworkML.py b/python/moose/neuroml/NetworkML.py
index e2e283f4..b96eeec8 100644
--- a/python/moose/neuroml/NetworkML.py
+++ b/python/moose/neuroml/NetworkML.py
@@ -156,7 +156,7 @@ class NetworkML():
                 cell_name = self.populationDict[population][0]
                 segment_path = self.populationDict[population][1][int(cell_id)].path+'/'+\
                     self.cellSegmentDict[cell_name][0][segment_id][0]
-                compartment = moose.Compartment(segment_path)
+                compartment = moose.element(segment_path)
                 _logger.debug("Adding pulse at {0}: {1}".format(
                     segment_path, pulsegen.firstLevel )
                     )
@@ -226,7 +226,7 @@ class NetworkML():
                 if childobj.className in ['Compartment','SymCompartment']:
                     ## SymCompartment inherits from Compartment,
                     ## so below wrapping by Compartment() is fine for both Compartment and SymCompartment
-                    child = moose.Compartment(childId)
+                    child = moose.element(childId)
                     x0 = child.x0
                     y0 = child.y0
                     x0new = x0*cos(ztheta)-y0*sin(ztheta)
@@ -316,7 +316,7 @@ class NetworkML():
                                     weight_override, threshold, delay_override)
 
     def connect(self, syn_name, pre_path, post_path, weight, threshold, delay):
-        postcomp = moose.Compartment(post_path)
+        postcomp = moose.element(post_path)
         ## We usually try to reuse an existing SynChan & SynHandler -
         ## event based SynHandlers have an array of weights and delays and can represent multiple synapses,
         ## so a new element of the weights and delays array is created
@@ -349,7 +349,7 @@ class NetworkML():
         if gradedchild is not None and gradedchild.value=='True': # graded synapse
             interpol = moose.element(syn.path+"/graded_table")
             #### always connect source to input - else 'cannot create message' error.
-            precomp = moose.Compartment(pre_path)
+            precomp = moose.element(pre_path)
             moose.connect(precomp,"VmOut",interpol,"input")
             try:
                 tau_table = moose.element(syn.path+'/tau_table')
-- 
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