Fix removal of 'core' submodule

This fixes a leftover bug from the removal of the 'core' submodule.

src/graph_tool/centrality/__init__.py

@@ -43,7 +43,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_centrality")
 
-from .. core import _prop, ungroup_vector_property
+from .. import _prop, ungroup_vector_property
 import sys
 import numpy
 

src/graph_tool/clustering/__init__.py

@@ -44,7 +44,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_clustering as _gt")
 
-from .. core import _degree, _prop, Graph
+from .. import _degree, _prop, Graph
 from .. topology import isomorphism
 from .. generation import random_rewire
 from .. stats import vertex_hist
@@ -463,7 +463,7 @@ def motif_significance(g, k, n_shuffles=100, p=1.0, motif_list=None,
         shuffled networks.
     shuffle_strategy : string (optional, default: "uncorrelated")
         Shuffle strategy to use. Can be either "correlated" or "uncorrelated".
-        See random_rewire() for details.
+        See :func:`~graph_tool.generation.random_rewire` for details.
 
     Returns
     -------

src/graph_tool/community/__init__.py

@@ -42,7 +42,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_community")
 
-from .. core import _degree, _prop, Graph, libcore
+from .. import _degree, _prop, Graph, libcore
 import random
 import sys
 

src/graph_tool/correlations/__init__.py

@@ -43,7 +43,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_correlations")
 
-from .. core import _degree, _prop
+from .. import _degree, _prop
 from numpy import *
 
 __all__ = ["assortativity", "scalar_assortativity", "corr_hist",

src/graph_tool/draw/__init__.py

@@ -37,7 +37,7 @@ Contents
 """
 
 import sys, os, os.path, time, warnings, tempfile
-from .. core import _degree, _prop, PropertyMap, _check_prop_vector,\
+from .. import _degree, _prop, PropertyMap, _check_prop_vector,\
      _check_prop_scalar, _check_prop_writable, group_vector_property,\
      ungroup_vector_property
 from .. decorators import _limit_args

src/graph_tool/flow/__init__.py

@@ -73,7 +73,7 @@ The following network will be used as an example throughout the documentation.
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_flow")
 
-from .. core import _prop, _check_prop_scalar, _check_prop_writable
+from .. import _prop, _check_prop_scalar, _check_prop_writable
 __all__ = ["edmonds_karp_max_flow", "push_relabel_max_flow",
            "boykov_kolmogorov_max_flow", "max_cardinality_matching"]
 

src/graph_tool/generation/__init__.py

@@ -45,7 +45,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_generation")
 
-from .. core import Graph, _check_prop_scalar, _prop, _limit_args
+from .. import Graph, _check_prop_scalar, _prop, _limit_args
 from .. stats import label_parallel_edges, label_self_loops
 import sys, numpy, numpy.random
 

src/graph_tool/run_action/inline.py

@@ -18,7 +18,7 @@
 # along with this program.  If not, see <http://www.gnu.org/licenses/>.
 
 import sys, string, hashlib, os.path, re, glob
-from .. import core
+from .. import *
 from .. import libgraph_tool_core
 import numpy
 import DLFCN
@@ -66,7 +66,7 @@ def clean_prop_type(t):
            replace("__", "_")
 
 for d in ["vertex", "edge", "graph"]:
-    for t in core.value_types():
+    for t in value_types():
         props += "typedef %s_prop_t::as<%s >::type %sprop_%s_t;\n" % \
                  (d, t.replace("bool", "uint8_t"), d[0], clean_prop_type(t))
 
@@ -158,7 +158,7 @@ def inline(code, arg_names=None, local_dict=None,
             arg_val = local_dict[arg]
         else:
             arg_val = global_dict[arg]
-        if issubclass(type(arg_val), core.Graph):
+        if issubclass(type(arg_val), Graph):
             alias = "__gt__" + arg
             gi = "__gt__" + arg + "__gi"
             graph_type = get_graph_type(arg_val)
@@ -170,7 +170,7 @@ def inline(code, arg_names=None, local_dict=None,
                         (arg, arg, graph_type, gi, gi)
             arg_alias.append(alias)
             alias_dict[alias] = gi_val
-        elif type(arg_val) == core.PropertyMap:
+        elif type(arg_val) == PropertyMap:
             alias = "__gt__" + arg
             if arg_val == arg_val.get_graph().vertex_index:
                 prop_name = "GraphInterface::vertex_index_map_t"
@@ -222,8 +222,8 @@ def inline(code, arg_names=None, local_dict=None,
         else:
             arg_val = global_dict[arg]
         if arg not in mask_ret and \
-               type(arg_val) not in [numpy.ndarray, core.PropertyMap] and \
-               not issubclass(type(arg_val), core.Graph):
+               type(arg_val) not in [numpy.ndarray, PropertyMap] and \
+               not issubclass(type(arg_val), Graph):
             return_vals += 'return_vals["%s"] = %s;\n' % (arg, arg)
 
     support_code += globals()["support_template"]
@@ -241,7 +241,7 @@ def inline(code, arg_names=None, local_dict=None,
                                         extra_compile_args +\
                                         extra_objects + \
                                         extra_link_args) + \
-                               headers_hash + core.__version__).hexdigest()
+                               headers_hash + __version__).hexdigest()
     code += "\n// support code hash: " + support_hash
     inline_code = string.Template(globals()["code_template"]).\
                   substitute(var_defs=arg_def, var_extract=arg_conv,

src/graph_tool/search/__init__.py

@@ -78,7 +78,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_search")
 
-from .. core import _prop
+from .. import _prop
 from .. decorators import _wraps
 import sys
 import weakref
@@ -191,8 +191,7 @@ class BFSVisitor(object):
 @_perm_wrap(["initialize_vertex", "examine_vertex", "finish_vertex"],
             ["initialize_vertex"])
 def bfs_search(g, source, visitor=BFSVisitor()):
-    r"""This function performs a breadth-first traversal of the vertices in a
-    directed or undirected graph.
+    r"""Breadth-first traversal of a directed or undirected graph.
 
     Parameters
     ----------
@@ -401,8 +400,7 @@ class DFSVisitor(object):
 @_perm_wrap(["initialize_vertex", "discover_vertex", "finish_vertex",
              "start_vertex"], ["initialize_vertex"])
 def dfs_search(g, source, visitor=DFSVisitor()):
-    r"""This function performs a depth-first traversal of the vertices in a
-    directed or undirected graph.
+    r"""Depth-first traversal of a directed or undirected graph.
 
     Parameters
     ----------
@@ -631,7 +629,7 @@ class DijkstraVisitor(object):
 def dijkstra_search(g, source, weight, visitor=DijkstraVisitor(), dist_map=None,
                     pred_map=None, combine=lambda a, b: a + b,
                     compare=lambda a, b: a < b, zero=0, infinity=float('inf')):
-    r"""This function performs a Dijsktra traversal of the vertices in a directed or undirected graph, with non-negative weights.
+    r"""Dijsktra traversal of a directed or undirected graph, with non-negative weights.
 
     Parameters
     ----------
@@ -898,7 +896,7 @@ def bellman_ford_search(g, source, weight, visitor=BellmanFordVisitor(),
                         combine=lambda a, b: a + b,
                         compare=lambda a, b: a < b, zero=0,
                         infinity=float('inf')):
-    r"""This function performs a Bellman-Ford traversal of the vertices in a directed or undirected graph, with negative weights.
+    r"""Bellman-Ford traversal of a directed or undirected graph, with negative weights.
 
     Parameters
     ----------
@@ -1171,7 +1169,7 @@ def astar_search(g, source, weight, visitor=AStarVisitor(),
                  compare=lambda a, b: a < b, zero=0,
                  infinity=float('inf'), implicit=False):
     r"""
-    This algorithm implements a heuristic :math:`A^*` search on a weighted, directed or undirected graph for the case where all edge weights are non-negative.
+    Heuristic :math:`A^*` search on a weighted, directed or undirected graph for the case where all edge weights are non-negative.
 
     Parameters
     ----------

src/graph_tool/spectral/__init__.py

@@ -36,7 +36,7 @@ Contents
 ++++++++
 """
 
-from .. core import _degree, _prop, Graph, _limit_args
+from .. import _degree, _prop, Graph, _limit_args
 from numpy import *
 import scipy.sparse
 

src/graph_tool/stats/__init__.py

@@ -47,7 +47,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_stats")
 
-from .. core import _degree, _prop
+from .. import _degree, _prop
 from numpy import *
 import numpy
 import sys

src/graph_tool/topology/__init__.py

@@ -49,7 +49,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_topology")
 
-from .. core import _prop, Vector_int32_t, _check_prop_writable, \
+from .. import _prop, Vector_int32_t, _check_prop_writable, \
      _check_prop_scalar,  _check_prop_vector, Graph, PropertyMap
 import random, sys, numpy, weakref
 __all__ = ["isomorphism", "subgraph_isomorphism", "mark_subgraph",

src/graph_tool/util/__init__.py

@@ -41,7 +41,7 @@ Contents
 from .. dl_import import dl_import
 dl_import("import libgraph_tool_util")
 
-from .. core import _degree, _prop
+from .. import _degree, _prop
 import weakref
 
 __all__ = ["find_vertex", "find_vertex_range", "find_edge", "find_edge_range"]