4 files changed, 21 insertions(+), 10 deletions(-)

M doc/developer/library_shipping.rst
M nngt/analysis/graph_analysis.py
M nngt/simulation/nest_graph.py
M nngt/simulation/nest_utils.py

@@ 75,7 75,7 @@ https://twine.readthedocs.io/en/latest/
 First test it:
 
     twine upload --repository-url https://test.pypi.org/legacy/ *
-    pip install --user --index-url https://test.pypi.org/simple/ nngt
+    pip install --index-url https://test.pypi.org/simple/ nngt
 
 Then upload "for real"
 

@@ 809,7 809,8 @@ def spectral_radius(graph, typed=True, weights=True):
     -------
     the spectral radius as a float.
     '''
-    mat_adj  = graph.adjacency_matrix(types=typed, weights=weights)
+    mat_adj  = graph.adjacency_matrix(types=typed,
+                                      weights=weights).astype(float)
     eigenval = []
 
     try:

@@ 108,7 108,7 @@ def make_nest_network(network, send_only=None, weights=True):
 
             for key, val in group.neuron_param.items():
                 if key in defaults and key != "model":
-                    if nonstring_container(val):
+                    if nonstring_container(val) and len(val) == group_size:
                         ns_param[key] = val
                     else:
                         scalar_param[key] = val


@@ 175,12 175,20 @@ def make_nest_network(network, send_only=None, weights=True):
                     syn_spec = _get_syn_param(
                         src_name, src_group, tgt_name, tgt_group, pop.syn_spec)
 
+                    # check whether sign must be given or not
+                    local_sign = syn_sign
+                    if "receptor_type" in syn_spec:
+                        if "cond" in tgt_group.neuron_model:
+                            # do not specify the sign for conductance-based
+                            # multisynapse model
+                            local_sign = 1
+
                     # using A1 to get data from matrix
                     if weights:
-                        syn_spec[WEIGHT] = syn_sign *\
+                        syn_spec[WEIGHT] = local_sign *\
                             csr_weights[local_src_ids, local_tgt_ids].A1
                     else:
-                        syn_spec[WEIGHT] = np.repeat(syn_sign, len(tgt_ids))
+                        syn_spec[WEIGHT] = np.repeat(local_sign, len(tgt_ids))
     
                     syn_spec[DELAY] = \
                         csr_delays[local_src_ids, local_tgt_ids].A1

@@ 502,14 502,16 @@ def save_spikes(filename, recorder=None, network=None, save_positions=True,
 
             if nest_version == 3:
                 if len(rcrdrs) == 1:
-                    assert recrdrs.model == spike_rec, \
+                    assert rcrdrs.model == spike_rec, \
                         'Only spike_detectors are supported.'
-                    assert recrdrs.model == (spike_rec,)*len(rcrdrs), \
+                else:
+                    assert rcrdrs.model == (spike_rec,)*len(rcrdrs), \
                         'Only spike_detectors are supported.'
             else:
-                assert (nest.GetStatus(rcrdrs, 'model')
-                        == ('spike_detector',)*len(rcrdrs)), \
-                       'Only spike_detectors are supported.'
+                for rec in rcrdrs:
+                    assert (nest.GetStatus(rec, 'model')
+                            == ('spike_detector',)*len(rec)), \
+                           'Only spike_detectors are supported.'
     else:
         if nest_version == 3:
             rcrdrs = nest.GetNodes(properties={'model': spike_rec})