Bugfix and improvements for connect_* functions (#145)

* fix connector calls (**kwargs)
* fix mutlithreading/mpi reload issue
* improve attribute generation support
* correct all_to_all edge type to int

.gitignore

@@ -3,6 +3,8 @@ doc/.build/
 doc/_build/
 doc/examples/sp_graph
 doc/examples/.ipynb_checkpoints/
+doc/gallery/graph_properties/
+doc/gallery/graph_structure/
 
 # generated rst
 doc/modules/examples

nngt/generation/cconnect.pyx

@@ -191,7 +191,7 @@ def _all_to_all(cnp.ndarray[size_t, ndim=1] source_ids,
 def _total_degree_list(cnp.ndarray[int64, ndim=1] source_ids,
                        cnp.ndarray[int64, ndim=1] target_ids,
                        cnp.ndarray[int64, ndim=1] degree_list,
-                       bool directed=True, bool multigraph=False):
+                       bool directed=True, bool multigraph=False, **kwargs):
     ''' Called from _from_degree_list '''
     cdef:
         size_t num_source = len(source_ids)

nngt/generation/connect_algorithms.py

@@ -96,7 +96,7 @@ def _all_to_all(source_ids, target_ids, directed=True, multigraph=False,
                 edges[current_edges:next_enum, 1] = target_ids
                 current_edges = next_enum
     else:
-        edges       = np.empty((num_edges, 2))
+        edges       = np.empty((num_edges, 2), dtype=int)
         edges[:, 0] = np.repeat(source_ids, num_targets)
         edges[:, 1] = np.tile(target_ids, num_sources)
 
@@ -111,7 +111,7 @@ def _all_to_all(source_ids, target_ids, directed=True, multigraph=False,
 
 
 def _total_degree_list(source_ids, target_ids, degree_list, directed=True,
-                       multigraph=False):
+                       multigraph=False, **kwargs):
     ''' Called from _from_degree_list '''
     degree_list = np.array(degree_list, dtype=int)
 
@@ -532,7 +532,8 @@ def _erdos_renyi(source_ids, target_ids, density=None, edges=None,
     return ia_edges
 
 
-def _price_scale_free(ids, m, c, gamma, reciprocity, directed, multigraph):
+def _price_scale_free(ids, m, c, gamma, reciprocity, directed, multigraph,
+                      **kwargs):
     '''
     Generate a Price network.
     '''
@@ -595,8 +596,8 @@ def _price_scale_free(ids, m, c, gamma, reciprocity, directed, multigraph):
     return edges
 
 
-def _circular(source_ids, target_ids, coord_nb, reciprocity, directed,
-              reciprocity_choice="random"):
+def _circular(source_ids, target_ids, coord_nb, reciprocity=1, directed=True,
+              reciprocity_choice="random", **kwargs):
     '''
     Circular graph.
 
@@ -625,7 +626,7 @@ def _circular(source_ids, target_ids, coord_nb, reciprocity, directed,
 
 
 def _circular_directed_recip(node_ids, coord_nb, reciprocity,
-                             reciprocity_choice="random"):
+                             reciprocity_choice="random", **kwargs):
     ''' Circular graph with given reciprocity '''
     nodes    = len(node_ids)
     edges    = int(0.5*nodes*coord_nb*(1 + reciprocity))
@@ -698,7 +699,7 @@ def _circular_directed_recip(node_ids, coord_nb, reciprocity,
     return np.array([sources, targets], dtype=int).T
 
 
-def _circular_full(node_ids, coord_nb, directed):
+def _circular_full(node_ids, coord_nb, directed, **kwargs):
     ''' Create a circular graph with all possible edges '''
     nodes = len(node_ids)
 

nngt/generation/connectors.py

@@ -27,6 +27,7 @@
 from nngt.generation import graph_connectivity as gc
 from nngt.lib import is_iterable, nonstring_container
 from nngt.lib.test_functions import deprecated
+from nngt.lib.rng_tools import _generate_random
 
 
 __all__ = [
@@ -118,9 +119,19 @@ def connect_nodes(network, sources, targets, graph_model, density=None,
     attr = {}
 
     if 'weights' in kwargs:
-        attr['weight'] = kwargs['weights']
+        ww = kwargs['weights']
+
+        if isinstance(ww, dict):
+            attr['weight'] = _generate_random(len(elist), ww)
+        else:
+            attr['weight'] = ww
     if 'delays' in kwargs:
-        attr['delay'] = kwargs['delays']
+        dd = kwargs['delays']
+
+        if isinstance(ww, dict):
+            attr['delay'] = _generate_random(len(elist), dd)
+        else:
+            attr['delay'] = dd
     if network.is_spatial() and distance:
         attr['distance'] = distance
 

nngt/generation/graph_connectivity.py

@@ -34,6 +34,21 @@
                                      on_master_process)
 
 
+__all__ = [
+    'all_to_all',
+    'circular',
+    'distance_rule',
+    'erdos_renyi',
+    'fixed_degree',
+    'from_degree_list',
+    'gaussian_degree',
+    'newman_watts',
+    'random_scale_free',
+    'price_scale_free',
+    'watts_strogatz',
+]
+
+
 # do default import
 
 from .connect_algorithms import *
@@ -96,21 +111,6 @@
         raise e
 
 
-__all__ = [
-    'all_to_all',
-    'circular',
-	'distance_rule',
-	'erdos_renyi',
-    'fixed_degree',
-    'from_degree_list',
-    'gaussian_degree',
-	'newman_watts',
-	'random_scale_free',
-	'price_scale_free',
-    'watts_strogatz',
-]
-
-
 # ----------------------------- #
 # Specific degree distributions #
 # ----------------------------- #
@@ -149,7 +149,7 @@ def all_to_all(nodes=0, weighted=True, directed=True, multigraph=False,
 
     Note
     ----
-	`nodes` is required unless `population` is provided.
+    `nodes` is required unless `population` is provided.
 
     Returns
     -------
@@ -269,7 +269,7 @@ def fixed_degree(degree, degree_type='in', nodes=0, reciprocity=-1.,
         The type of the fixed degree, among ``'in'``, ``'out'`` or ``'total'``.
 
         @todo
-			`'total'` not implemented yet.
+            `'total'` not implemented yet.
 
     nodes : int, optional (default: None)
         The number of nodes in the graph.
@@ -299,9 +299,9 @@ def fixed_degree(degree, degree_type='in', nodes=0, reciprocity=-1.,
 
     Note
     ----
-	`nodes` is required unless `from_graph` or `population` is provided.
-	If an `from_graph` is provided, all preexistant edges in the
-	object will be deleted before the new connectivity is implemented.
+    `nodes` is required unless `from_graph` or `population` is provided.
+    If an `from_graph` is provided, all preexistant edges in the
+    object will be deleted before the new connectivity is implemented.
 
     Returns
     -------
@@ -352,7 +352,7 @@ def gaussian_degree(avg, std, degree_type='in', nodes=0, reciprocity=-1.,
     avg : float
         The value of the average degree.
     std : float
-		The standard deviation of the Gaussian distribution.
+        The standard deviation of the Gaussian distribution.
     degree_type : str, optional (default: 'in')
         The type of the fixed degree, among 'in', 'out' or 'total' (or the
         full version: 'in-degree'...)
@@ -390,9 +390,9 @@ def gaussian_degree(avg, std, degree_type='in', nodes=0, reciprocity=-1.,
 
     Note
     ----
-	`nodes` is required unless `from_graph` or `population` is provided.
-	If an `from_graph` is provided, all preexistant edges in the object
-	will be deleted before the new connectivity is implemented.
+    `nodes` is required unless `from_graph` or `population` is provided.
+    If an `from_graph` is provided, all preexistant edges in the object
+    will be deleted before the new connectivity is implemented.
     """
     # set node number and library graph
     graph_gd = from_graph
@@ -477,9 +477,9 @@ def erdos_renyi(density=None, nodes=0, edges=None, avg_deg=None,
 
     Note
     ----
-	`nodes` is required unless `from_graph` or `population` is provided.
-	If an `from_graph` is provided, all preexistant edges in the
-	object will be deleted before the new connectivity is implemented.
+    `nodes` is required unless `from_graph` or `population` is provided.
+    If an `from_graph` is provided, all preexistant edges in the
+    object will be deleted before the new connectivity is implemented.
     """
     # set node number and library graph
     graph_er = from_graph
@@ -563,11 +563,11 @@ def random_scale_free(in_exp, out_exp, nodes=0, density=None, edges=None,
 
     Note
     ----
-	As reciprocity increases, requested values of `in_exp` and `out_exp`
-	will be less and less respected as the distribution will converge to a
-	common exponent :math:`\gamma = (\gamma_i + \gamma_o) / 2`.
-	Parameter `nodes` is required unless `from_graph` or `population` is
-	provided.
+    As reciprocity increases, requested values of `in_exp` and `out_exp`
+    will be less and less respected as the distribution will converge to a
+    common exponent :math:`\gamma = (\gamma_i + \gamma_o) / 2`.
+    Parameter `nodes` is required unless `from_graph` or `population` is
+    provided.
     """
     # set node number and library graph
     graph_rsf = from_graph
@@ -858,7 +858,7 @@ def newman_watts(coord_nb, proba_shortcut=None, reciprocity_circular=1.,
 
     Note
     ----
-	`nodes` is required unless `from_graph` or `population` is provided.
+    `nodes` is required unless `from_graph` or `population` is provided.
     """
     if multigraph:
         raise ValueError("`multigraph` is not supported for Watts-Strogatz.")
@@ -954,7 +954,7 @@ def watts_strogatz(coord_nb, proba_shortcut=None, reciprocity_circular=1.,
 
     Note
     ----
-	`nodes` is required unless `from_graph` or `population` is provided.
+    `nodes` is required unless `from_graph` or `population` is provided.
     """
     if multigraph:
         raise ValueError("`multigraph` is not supported for Newman-Watts.")

nngt/lib/nngt_config.py

@@ -355,10 +355,9 @@ def _post_update_parallelism(new_config, old_gl, old_msd, old_mt, old_mpi):
     new_multithreading = new_config.get("multithreading", old_mt)
 
     if new_multithreading != old_mt:
-        # connectors.py and rewiring.py use directly
-        # nngt.generation.graph_connectivity so they always access the reloaded
-        # version and we don't need to reload them
         reload(sys.modules["nngt"].generation.graph_connectivity)
+        reload(sys.modules["nngt"].generation.connectors)
+        reload(sys.modules["nngt"].generation.rewiring)
 
     # if multithreading loading failed, set omp back to 1
     if not nngt._config['multithreading']:
@@ -389,10 +388,9 @@ def _post_update_parallelism(new_config, old_gl, old_msd, old_mt, old_mpi):
 
     # reload for mpi
     if new_config.get('mpi', old_mpi) != old_mpi:
-        # connectors.py and rewiring.py use directly
-        # nngt.generation.graph_connectivity so they always access the reloaded
-        # version and we don't need to reload them
         reload(sys.modules["nngt"].generation.graph_connectivity)
+        reload(sys.modules["nngt"].generation.connectors)
+        reload(sys.modules["nngt"].generation.rewiring)
 
     # set graph-tool config
     _set_gt_config(old_gl, new_config)

nngt/lib/rng_tools.py

@@ -88,13 +88,33 @@ def seed(msd=None, seeds=None):
 # ----------------------------- #
 
 def _generate_random(number, instructions):
-    name = instructions[0]
-    if name in di_dfunc:
-        return di_dfunc[name](None, None, number, *instructions[1:])
-    else:
+    name = "not defined"
+
+    if isinstance(instructions, dict):
+        name = instructions["distribution"]
+
+        instructions = {
+            k: v for k, v in instructions.items() if k != "distribution"
+        }
+
+        if name in di_dfunc:
+            return di_dfunc[name](None, None, number, **instructions)
+
         raise NotImplementedError(
             "Unknown distribution: '{}'. Supported distributions " \
             "are {}".format(name, ", ".join(di_dfunc.keys())))
+    elif nonstring_container(instructions):
+        name = instructions[0]
+
+        if name in di_dfunc:
+            return di_dfunc[name](None, None, number, *instructions[1:])
+
+        raise NotImplementedError(
+            "Unknown distribution: '{}'. Supported distributions " \
+            "are {}".format(name, ", ".join(di_dfunc.keys())))
+
+    raise NotImplementedError(
+        "Unknown instructions: '{}'".format(instructions))
 
 
 def _eprop_distribution(graph, distrib_type, matrix=False, elist=None,

testing/test_attributes.py

@@ -418,7 +418,6 @@ def test_attributes_are_copied():
 
     assert np.all(np.isclose(vv, g.node_attributes["ntest"]))
     assert not np.all(np.isclose(vv, ntest))
-
 
 
 # ---------- #