Commit 641d0024 authored by Tiago Peixoto's avatar Tiago Peixoto

Fix removal of 'core' submodule

This fixes a leftover bug from the removal of the 'core' submodule.
parent 011d7b65
......@@ -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
......
......@@ -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
-------
......
......@@ -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
......
......@@ -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",
......
......@@ -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
......
......@@ -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"]
......
......@@ -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
......
......@@ -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,
......
......@@ -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
----------
......
......@@ -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
......
......@@ -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
......
......@@ -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",
......
......@@ -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"]
......
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