diff options
| -rw-r--r-- | examples/algorithms/plot_rcm.py | 2 | ||||
| -rw-r--r-- | networkx/algorithms/assortativity/correlation.py | 2 | ||||
| -rw-r--r-- | networkx/algorithms/shortest_paths/dense.py | 4 | ||||
| -rw-r--r-- | networkx/algorithms/similarity.py | 6 | ||||
| -rw-r--r-- | networkx/classes/digraph.py | 8 | ||||
| -rw-r--r-- | networkx/classes/graph.py | 8 | ||||
| -rw-r--r-- | networkx/classes/multidigraph.py | 8 | ||||
| -rw-r--r-- | networkx/classes/multigraph.py | 8 | ||||
| -rw-r--r-- | networkx/convert.py | 5 | ||||
| -rw-r--r-- | networkx/linalg/laplacianmatrix.py | 2 |
10 files changed, 26 insertions, 27 deletions
diff --git a/examples/algorithms/plot_rcm.py b/examples/algorithms/plot_rcm.py index 91e7665e..fc08739b 100644 --- a/examples/algorithms/plot_rcm.py +++ b/examples/algorithms/plot_rcm.py @@ -15,7 +15,7 @@ import seaborn as sns import networkx as nx -# build low-bandwidth numpy matrix +# build low-bandwidth matrix G = nx.grid_2d_graph(3, 3) rcm = list(nx.utils.reverse_cuthill_mckee_ordering(G)) print("ordering", rcm) diff --git a/networkx/algorithms/assortativity/correlation.py b/networkx/algorithms/assortativity/correlation.py index 39ac2fab..b8f884e9 100644 --- a/networkx/algorithms/assortativity/correlation.py +++ b/networkx/algorithms/assortativity/correlation.py @@ -281,7 +281,7 @@ def attribute_ac(M): def numeric_ac(M, mapping): - # M is a numpy matrix or array + # M is a 2D numpy array # numeric assortativity coefficient, pearsonr import numpy as np diff --git a/networkx/algorithms/shortest_paths/dense.py b/networkx/algorithms/shortest_paths/dense.py index 818921ca..89651718 100644 --- a/networkx/algorithms/shortest_paths/dense.py +++ b/networkx/algorithms/shortest_paths/dense.py @@ -35,8 +35,8 @@ def floyd_warshall_numpy(G, nodelist=None, weight="weight"): Returns ------- - distance : NumPy matrix - A matrix of shortest path distances between nodes. + distance : 2D numpy.ndarray + A numpy array of shortest path distances between nodes. If there is no path between two nodes the value is Inf. Notes diff --git a/networkx/algorithms/similarity.py b/networkx/algorithms/similarity.py index 9966d76a..cc6d646a 100644 --- a/networkx/algorithms/similarity.py +++ b/networkx/algorithms/similarity.py @@ -1421,12 +1421,12 @@ def _simrank_similarity_numpy( Returns ------- - similarity : numpy matrix, numpy array or float + similarity : numpy array or float If ``source`` and ``target`` are both ``None``, this returns a - Matrix containing SimRank scores of the nodes. + 2D array containing SimRank scores of the nodes. If ``source`` is not ``None`` but ``target`` is, this returns an - Array containing SimRank scores of ``source`` and that + 1D array containing SimRank scores of ``source`` and that node. If neither ``source`` nor ``target`` is ``None``, this returns diff --git a/networkx/classes/digraph.py b/networkx/classes/digraph.py index 498c333c..336daab6 100644 --- a/networkx/classes/digraph.py +++ b/networkx/classes/digraph.py @@ -38,8 +38,8 @@ class DiGraph(Graph): Data to initialize graph. If None (default) an empty graph is created. The data can be any format that is supported by the to_networkx_graph() function, currently including edge list, - dict of dicts, dict of lists, NetworkX graph, NumPy matrix - or 2d ndarray, SciPy sparse matrix, or PyGraphviz graph. + dict of dicts, dict of lists, NetworkX graph, 2D NumPy array, SciPy + sparse matrix, or PyGraphviz graph. attr : keyword arguments, optional (default= no attributes) Attributes to add to graph as key=value pairs. @@ -274,8 +274,8 @@ class DiGraph(Graph): Data to initialize graph. If None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python - packages are installed the data can also be a NumPy matrix - or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph. + packages are installed the data can also be a 2D NumPy array, a + SciPy sparse matrix, or a PyGraphviz graph. attr : keyword arguments, optional (default= no attributes) Attributes to add to graph as key=value pairs. diff --git a/networkx/classes/graph.py b/networkx/classes/graph.py index d296bf3b..6c082176 100644 --- a/networkx/classes/graph.py +++ b/networkx/classes/graph.py @@ -39,8 +39,8 @@ class Graph: Data to initialize graph. If None (default) an empty graph is created. The data can be any format that is supported by the to_networkx_graph() function, currently including edge list, - dict of dicts, dict of lists, NetworkX graph, NumPy matrix - or 2d ndarray, SciPy sparse matrix, or PyGraphviz graph. + dict of dicts, dict of lists, NetworkX graph, 2D NumPy array, SciPy + sparse matrix, or PyGraphviz graph. attr : keyword arguments, optional (default= no attributes) Attributes to add to graph as key=value pairs. @@ -295,8 +295,8 @@ class Graph: Data to initialize graph. If None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python - packages are installed the data can also be a NumPy matrix - or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph. + packages are installed the data can also be a 2D NumPy array, a + SciPy sparse matrix, or a PyGraphviz graph. attr : keyword arguments, optional (default= no attributes) Attributes to add to graph as key=value pairs. diff --git a/networkx/classes/multidigraph.py b/networkx/classes/multidigraph.py index b53fecf1..ee24ac55 100644 --- a/networkx/classes/multidigraph.py +++ b/networkx/classes/multidigraph.py @@ -38,8 +38,8 @@ class MultiDiGraph(MultiGraph, DiGraph): Data to initialize graph. If None (default) an empty graph is created. The data can be any format that is supported by the to_networkx_graph() function, currently including edge list, - dict of dicts, dict of lists, NetworkX graph, NumPy matrix - or 2d ndarray, SciPy sparse matrix, or PyGraphviz graph. + dict of dicts, dict of lists, NetworkX graph, 2D NumPy array, SciPy + sparse matrix, or PyGraphviz graph. multigraph_input : bool or None (default None) Note: Only used when `incoming_graph_data` is a dict. @@ -288,8 +288,8 @@ class MultiDiGraph(MultiGraph, DiGraph): Data to initialize graph. If incoming_graph_data=None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python - packages are installed the data can also be a NumPy matrix - or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph. + packages are installed the data can also be a 2D NumPy array, a + SciPy sparse matrix, or a PyGraphviz graph. multigraph_input : bool or None (default None) Note: Only used when `incoming_graph_data` is a dict. diff --git a/networkx/classes/multigraph.py b/networkx/classes/multigraph.py index 343befa4..07436ebd 100644 --- a/networkx/classes/multigraph.py +++ b/networkx/classes/multigraph.py @@ -32,8 +32,8 @@ class MultiGraph(Graph): Data to initialize graph. If None (default) an empty graph is created. The data can be any format that is supported by the to_networkx_graph() function, currently including edge list, - dict of dicts, dict of lists, NetworkX graph, NumPy matrix - or 2d ndarray, SciPy sparse matrix, or PyGraphviz graph. + dict of dicts, dict of lists, NetworkX graph, 2D NumPy array, + SciPy sparse matrix, or PyGraphviz graph. multigraph_input : bool or None (default None) Note: Only used when `incoming_graph_data` is a dict. @@ -297,8 +297,8 @@ class MultiGraph(Graph): Data to initialize graph. If incoming_graph_data=None (default) an empty graph is created. The data can be an edge list, or any NetworkX graph object. If the corresponding optional Python - packages are installed the data can also be a NumPy matrix - or 2d ndarray, a SciPy sparse matrix, or a PyGraphviz graph. + packages are installed the data can also be a 2D NumPy array, a + SciPy sparse matrix, or a PyGraphviz graph. multigraph_input : bool or None (default None) Note: Only used when `incoming_graph_data` is a dict. diff --git a/networkx/convert.py b/networkx/convert.py index 593eb1bc..c7468b84 100644 --- a/networkx/convert.py +++ b/networkx/convert.py @@ -55,8 +55,7 @@ def to_networkx_graph(data, create_using=None, multigraph_input=False): iterator (e.g. itertools.chain) that produces edges generator of edges Pandas DataFrame (row per edge) - numpy matrix - numpy ndarray + 2D numpy array scipy sparse matrix pygraphviz agraph @@ -144,7 +143,7 @@ def to_networkx_graph(data, create_using=None, multigraph_input=False): return nx.from_numpy_array(data, create_using=create_using) except Exception as err: raise nx.NetworkXError( - "Input is not a correct numpy matrix or array." + f"Failed to interpret array as an adjacency matrix." ) from err except ImportError: warnings.warn("numpy not found, skipping conversion test.", ImportWarning) diff --git a/networkx/linalg/laplacianmatrix.py b/networkx/linalg/laplacianmatrix.py index 4fe3daaa..e1986ec9 100644 --- a/networkx/linalg/laplacianmatrix.py +++ b/networkx/linalg/laplacianmatrix.py @@ -367,7 +367,7 @@ def _transition_matrix(G, nodelist=None, weight="weight", walk_type=None, alpha= Returns ------- - P : NumPy matrix + P : numpy.ndarray transition matrix of G. Raises |