up follow livre

venv/lib/python3.13/site-packages/networkx/drawing/__init__.py

@@ -0,0 +1,7 @@
+# graph drawing and interface to graphviz
+
+from .layout import *
+from .nx_latex import *
+from .nx_pylab import *
+from . import nx_agraph
+from . import nx_pydot

venv/lib/python3.13/site-packages/networkx/drawing/nx_agraph.py

@@ -0,0 +1,464 @@
+"""
+***************
+Graphviz AGraph
+***************
+
+Interface to pygraphviz AGraph class.
+
+Examples
+--------
+>>> G = nx.complete_graph(5)
+>>> A = nx.nx_agraph.to_agraph(G)
+>>> H = nx.nx_agraph.from_agraph(A)
+
+See Also
+--------
+ - Pygraphviz: http://pygraphviz.github.io/
+ - Graphviz:      https://www.graphviz.org
+ - DOT Language:  http://www.graphviz.org/doc/info/lang.html
+"""
+
+import tempfile
+
+import networkx as nx
+
+__all__ = [
+    "from_agraph",
+    "to_agraph",
+    "write_dot",
+    "read_dot",
+    "graphviz_layout",
+    "pygraphviz_layout",
+    "view_pygraphviz",
+]
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def from_agraph(A, create_using=None):
+    """Returns a NetworkX Graph or DiGraph from a PyGraphviz graph.
+
+    Parameters
+    ----------
+    A : PyGraphviz AGraph
+      A graph created with PyGraphviz
+
+    create_using : NetworkX graph constructor, optional (default=None)
+       Graph type to create. If graph instance, then cleared before populated.
+       If `None`, then the appropriate Graph type is inferred from `A`.
+
+    Examples
+    --------
+    >>> K5 = nx.complete_graph(5)
+    >>> A = nx.nx_agraph.to_agraph(K5)
+    >>> G = nx.nx_agraph.from_agraph(A)
+
+    Notes
+    -----
+    The Graph G will have a dictionary G.graph_attr containing
+    the default graphviz attributes for graphs, nodes and edges.
+
+    Default node attributes will be in the dictionary G.node_attr
+    which is keyed by node.
+
+    Edge attributes will be returned as edge data in G.  With
+    edge_attr=False the edge data will be the Graphviz edge weight
+    attribute or the value 1 if no edge weight attribute is found.
+
+    """
+    if create_using is None:
+        if A.is_directed():
+            if A.is_strict():
+                create_using = nx.DiGraph
+            else:
+                create_using = nx.MultiDiGraph
+        else:
+            if A.is_strict():
+                create_using = nx.Graph
+            else:
+                create_using = nx.MultiGraph
+
+    # assign defaults
+    N = nx.empty_graph(0, create_using)
+    if A.name is not None:
+        N.name = A.name
+
+    # add graph attributes
+    N.graph.update(A.graph_attr)
+
+    # add nodes, attributes to N.node_attr
+    for n in A.nodes():
+        str_attr = {str(k): v for k, v in n.attr.items()}
+        N.add_node(str(n), **str_attr)
+
+    # add edges, assign edge data as dictionary of attributes
+    for e in A.edges():
+        u, v = str(e[0]), str(e[1])
+        attr = dict(e.attr)
+        str_attr = {str(k): v for k, v in attr.items()}
+        if not N.is_multigraph():
+            if e.name is not None:
+                str_attr["key"] = e.name
+            N.add_edge(u, v, **str_attr)
+        else:
+            N.add_edge(u, v, key=e.name, **str_attr)
+
+    # add default attributes for graph, nodes, and edges
+    # hang them on N.graph_attr
+    N.graph["graph"] = dict(A.graph_attr)
+    N.graph["node"] = dict(A.node_attr)
+    N.graph["edge"] = dict(A.edge_attr)
+    return N
+
+
+def to_agraph(N):
+    """Returns a pygraphviz graph from a NetworkX graph N.
+
+    Parameters
+    ----------
+    N : NetworkX graph
+      A graph created with NetworkX
+
+    Examples
+    --------
+    >>> K5 = nx.complete_graph(5)
+    >>> A = nx.nx_agraph.to_agraph(K5)
+
+    Notes
+    -----
+    If N has an dict N.graph_attr an attempt will be made first
+    to copy properties attached to the graph (see from_agraph)
+    and then updated with the calling arguments if any.
+
+    """
+    try:
+        import pygraphviz
+    except ImportError as err:
+        raise ImportError("requires pygraphviz http://pygraphviz.github.io/") from err
+    directed = N.is_directed()
+    strict = nx.number_of_selfloops(N) == 0 and not N.is_multigraph()
+
+    A = pygraphviz.AGraph(name=N.name, strict=strict, directed=directed)
+
+    # default graph attributes
+    A.graph_attr.update(N.graph.get("graph", {}))
+    A.node_attr.update(N.graph.get("node", {}))
+    A.edge_attr.update(N.graph.get("edge", {}))
+
+    A.graph_attr.update(
+        (k, v) for k, v in N.graph.items() if k not in ("graph", "node", "edge")
+    )
+
+    # add nodes
+    for n, nodedata in N.nodes(data=True):
+        A.add_node(n)
+        # Add node data
+        a = A.get_node(n)
+        for key, val in nodedata.items():
+            if key == "pos":
+                a.attr["pos"] = f"{val[0]},{val[1]}!"
+            else:
+                a.attr[key] = str(val)
+
+    # loop over edges
+    if N.is_multigraph():
+        for u, v, key, edgedata in N.edges(data=True, keys=True):
+            str_edgedata = {k: str(v) for k, v in edgedata.items() if k != "key"}
+            A.add_edge(u, v, key=str(key))
+            # Add edge data
+            a = A.get_edge(u, v)
+            a.attr.update(str_edgedata)
+
+    else:
+        for u, v, edgedata in N.edges(data=True):
+            str_edgedata = {k: str(v) for k, v in edgedata.items()}
+            A.add_edge(u, v)
+            # Add edge data
+            a = A.get_edge(u, v)
+            a.attr.update(str_edgedata)
+
+    return A
+
+
+def write_dot(G, path):
+    """Write NetworkX graph G to Graphviz dot format on path.
+
+    Parameters
+    ----------
+    G : graph
+       A networkx graph
+    path : filename
+       Filename or file handle to write
+
+    Notes
+    -----
+    To use a specific graph layout, call ``A.layout`` prior to `write_dot`.
+    Note that some graphviz layouts are not guaranteed to be deterministic,
+    see https://gitlab.com/graphviz/graphviz/-/issues/1767 for more info.
+    """
+    A = to_agraph(G)
+    A.write(path)
+    A.clear()
+    return
+
+
+@nx._dispatchable(name="agraph_read_dot", graphs=None, returns_graph=True)
+def read_dot(path):
+    """Returns a NetworkX graph from a dot file on path.
+
+    Parameters
+    ----------
+    path : file or string
+       File name or file handle to read.
+    """
+    try:
+        import pygraphviz
+    except ImportError as err:
+        raise ImportError(
+            "read_dot() requires pygraphviz http://pygraphviz.github.io/"
+        ) from err
+    A = pygraphviz.AGraph(file=path)
+    gr = from_agraph(A)
+    A.clear()
+    return gr
+
+
+def graphviz_layout(G, prog="neato", root=None, args=""):
+    """Create node positions for G using Graphviz.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+      A graph created with NetworkX
+    prog : string
+      Name of Graphviz layout program
+    root : string, optional
+      Root node for twopi layout
+    args : string, optional
+      Extra arguments to Graphviz layout program
+
+    Returns
+    -------
+    Dictionary of x, y, positions keyed by node.
+
+    Examples
+    --------
+    >>> G = nx.petersen_graph()
+    >>> pos = nx.nx_agraph.graphviz_layout(G)
+    >>> pos = nx.nx_agraph.graphviz_layout(G, prog="dot")
+
+    Notes
+    -----
+    This is a wrapper for pygraphviz_layout.
+
+    Note that some graphviz layouts are not guaranteed to be deterministic,
+    see https://gitlab.com/graphviz/graphviz/-/issues/1767 for more info.
+    """
+    return pygraphviz_layout(G, prog=prog, root=root, args=args)
+
+
+def pygraphviz_layout(G, prog="neato", root=None, args=""):
+    """Create node positions for G using Graphviz.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+      A graph created with NetworkX
+    prog : string
+      Name of Graphviz layout program
+    root : string, optional
+      Root node for twopi layout
+    args : string, optional
+      Extra arguments to Graphviz layout program
+
+    Returns
+    -------
+    node_pos : dict
+      Dictionary of x, y, positions keyed by node.
+
+    Examples
+    --------
+    >>> G = nx.petersen_graph()
+    >>> pos = nx.nx_agraph.graphviz_layout(G)
+    >>> pos = nx.nx_agraph.graphviz_layout(G, prog="dot")
+
+    Notes
+    -----
+    If you use complex node objects, they may have the same string
+    representation and GraphViz could treat them as the same node.
+    The layout may assign both nodes a single location. See Issue #1568
+    If this occurs in your case, consider relabeling the nodes just
+    for the layout computation using something similar to::
+
+        >>> H = nx.convert_node_labels_to_integers(G, label_attribute="node_label")
+        >>> H_layout = nx.nx_agraph.pygraphviz_layout(H, prog="dot")
+        >>> G_layout = {H.nodes[n]["node_label"]: p for n, p in H_layout.items()}
+
+    Note that some graphviz layouts are not guaranteed to be deterministic,
+    see https://gitlab.com/graphviz/graphviz/-/issues/1767 for more info.
+    """
+    try:
+        import pygraphviz
+    except ImportError as err:
+        raise ImportError("requires pygraphviz http://pygraphviz.github.io/") from err
+    if root is not None:
+        args += f"-Groot={root}"
+    A = to_agraph(G)
+    A.layout(prog=prog, args=args)
+    node_pos = {}
+    for n in G:
+        node = pygraphviz.Node(A, n)
+        try:
+            xs = node.attr["pos"].split(",")
+            node_pos[n] = tuple(float(x) for x in xs)
+        except:
+            print("no position for node", n)
+            node_pos[n] = (0.0, 0.0)
+    return node_pos
+
+
+@nx.utils.open_file(5, "w+b")
+def view_pygraphviz(
+    G, edgelabel=None, prog="dot", args="", suffix="", path=None, show=True
+):
+    """Views the graph G using the specified layout algorithm.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+        The machine to draw.
+    edgelabel : str, callable, None
+        If a string, then it specifies the edge attribute to be displayed
+        on the edge labels. If a callable, then it is called for each
+        edge and it should return the string to be displayed on the edges.
+        The function signature of `edgelabel` should be edgelabel(data),
+        where `data` is the edge attribute dictionary.
+    prog : string
+        Name of Graphviz layout program.
+    args : str
+        Additional arguments to pass to the Graphviz layout program.
+    suffix : str
+        If `filename` is None, we save to a temporary file.  The value of
+        `suffix` will appear at the tail end of the temporary filename.
+    path : str, None
+        The filename used to save the image.  If None, save to a temporary
+        file.  File formats are the same as those from pygraphviz.agraph.draw.
+        Filenames ending in .gz or .bz2 will be compressed.
+    show : bool, default = True
+        Whether to display the graph with :mod:`PIL.Image.show`,
+        default is `True`. If `False`, the rendered graph is still available
+        at `path`.
+
+    Returns
+    -------
+    path : str
+        The filename of the generated image.
+    A : PyGraphviz graph
+        The PyGraphviz graph instance used to generate the image.
+
+    Notes
+    -----
+    If this function is called in succession too quickly, sometimes the
+    image is not displayed. So you might consider time.sleep(.5) between
+    calls if you experience problems.
+
+    Note that some graphviz layouts are not guaranteed to be deterministic,
+    see https://gitlab.com/graphviz/graphviz/-/issues/1767 for more info.
+
+    """
+    if not len(G):
+        raise nx.NetworkXException("An empty graph cannot be drawn.")
+
+    # If we are providing default values for graphviz, these must be set
+    # before any nodes or edges are added to the PyGraphviz graph object.
+    # The reason for this is that default values only affect incoming objects.
+    # If you change the default values after the objects have been added,
+    # then they inherit no value and are set only if explicitly set.
+
+    # to_agraph() uses these values.
+    attrs = ["edge", "node", "graph"]
+    for attr in attrs:
+        if attr not in G.graph:
+            G.graph[attr] = {}
+
+    # These are the default values.
+    edge_attrs = {"fontsize": "10"}
+    node_attrs = {
+        "style": "filled",
+        "fillcolor": "#0000FF40",
+        "height": "0.75",
+        "width": "0.75",
+        "shape": "circle",
+    }
+    graph_attrs = {}
+
+    def update_attrs(which, attrs):
+        # Update graph attributes. Return list of those which were added.
+        added = []
+        for k, v in attrs.items():
+            if k not in G.graph[which]:
+                G.graph[which][k] = v
+                added.append(k)
+
+    def clean_attrs(which, added):
+        # Remove added attributes
+        for attr in added:
+            del G.graph[which][attr]
+        if not G.graph[which]:
+            del G.graph[which]
+
+    # Update all default values
+    update_attrs("edge", edge_attrs)
+    update_attrs("node", node_attrs)
+    update_attrs("graph", graph_attrs)
+
+    # Convert to agraph, so we inherit default values
+    A = to_agraph(G)
+
+    # Remove the default values we added to the original graph.
+    clean_attrs("edge", edge_attrs)
+    clean_attrs("node", node_attrs)
+    clean_attrs("graph", graph_attrs)
+
+    # If the user passed in an edgelabel, we update the labels for all edges.
+    if edgelabel is not None:
+        if not callable(edgelabel):
+
+            def func(data):
+                return "".join(["  ", str(data[edgelabel]), "  "])
+
+        else:
+            func = edgelabel
+
+        # update all the edge labels
+        if G.is_multigraph():
+            for u, v, key, data in G.edges(keys=True, data=True):
+                # PyGraphviz doesn't convert the key to a string. See #339
+                edge = A.get_edge(u, v, str(key))
+                edge.attr["label"] = str(func(data))
+        else:
+            for u, v, data in G.edges(data=True):
+                edge = A.get_edge(u, v)
+                edge.attr["label"] = str(func(data))
+
+    if path is None:
+        ext = "png"
+        if suffix:
+            suffix = f"_{suffix}.{ext}"
+        else:
+            suffix = f".{ext}"
+        path = tempfile.NamedTemporaryFile(suffix=suffix, delete=False)
+    else:
+        # Assume the decorator worked and it is a file-object.
+        pass
+
+    # Write graph to file
+    A.draw(path=path, format=None, prog=prog, args=args)
+    path.close()
+
+    # Show graph in a new window (depends on platform configuration)
+    if show:
+        from PIL import Image
+
+        Image.open(path.name).show()
+
+    return path.name, A

venv/lib/python3.13/site-packages/networkx/drawing/nx_latex.py

@@ -0,0 +1,570 @@
+r"""
+*****
+LaTeX
+*****
+
+Export NetworkX graphs in LaTeX format using the TikZ library within TeX/LaTeX.
+Usually, you will want the drawing to appear in a figure environment so
+you use ``to_latex(G, caption="A caption")``. If you want the raw
+drawing commands without a figure environment use :func:`to_latex_raw`.
+And if you want to write to a file instead of just returning the latex
+code as a string, use ``write_latex(G, "filename.tex", caption="A caption")``.
+
+To construct a figure with subfigures for each graph to be shown, provide
+``to_latex`` or ``write_latex`` a list of graphs, a list of subcaptions,
+and a number of rows of subfigures inside the figure.
+
+To be able to refer to the figures or subfigures in latex using ``\\ref``,
+the keyword ``latex_label`` is available for figures and `sub_labels` for
+a list of labels, one for each subfigure.
+
+We intend to eventually provide an interface to the TikZ Graph
+features which include e.g. layout algorithms.
+
+Let us know via github what you'd like to see available, or better yet
+give us some code to do it, or even better make a github pull request
+to add the feature.
+
+The TikZ approach
+=================
+Drawing options can be stored on the graph as node/edge attributes, or
+can be provided as dicts keyed by node/edge to a string of the options
+for that node/edge. Similarly a label can be shown for each node/edge
+by specifying the labels as graph node/edge attributes or by providing
+a dict keyed by node/edge to the text to be written for that node/edge.
+
+Options for the tikzpicture environment (e.g. "[scale=2]") can be provided
+via a keyword argument. Similarly default node and edge options can be
+provided through keywords arguments. The default node options are applied
+to the single TikZ "path" that draws all nodes (and no edges). The default edge
+options are applied to a TikZ "scope" which contains a path for each edge.
+
+Examples
+========
+>>> G = nx.path_graph(3)
+>>> nx.write_latex(G, "just_my_figure.tex", as_document=True)
+>>> nx.write_latex(G, "my_figure.tex", caption="A path graph", latex_label="fig1")
+>>> latex_code = nx.to_latex(G)  # a string rather than a file
+
+You can change many features of the nodes and edges.
+
+>>> G = nx.path_graph(4, create_using=nx.DiGraph)
+>>> pos = {n: (n, n) for n in G}  # nodes set on a line
+
+>>> G.nodes[0]["style"] = "blue"
+>>> G.nodes[2]["style"] = "line width=3,draw"
+>>> G.nodes[3]["label"] = "Stop"
+>>> G.edges[(0, 1)]["label"] = "1st Step"
+>>> G.edges[(0, 1)]["label_opts"] = "near start"
+>>> G.edges[(1, 2)]["style"] = "line width=3"
+>>> G.edges[(1, 2)]["label"] = "2nd Step"
+>>> G.edges[(2, 3)]["style"] = "green"
+>>> G.edges[(2, 3)]["label"] = "3rd Step"
+>>> G.edges[(2, 3)]["label_opts"] = "near end"
+
+>>> nx.write_latex(G, "latex_graph.tex", pos=pos, as_document=True)
+
+Then compile the LaTeX using something like ``pdflatex latex_graph.tex``
+and view the pdf file created: ``latex_graph.pdf``.
+
+If you want **subfigures** each containing one graph, you can input a list of graphs.
+
+>>> H1 = nx.path_graph(4)
+>>> H2 = nx.complete_graph(4)
+>>> H3 = nx.path_graph(8)
+>>> H4 = nx.complete_graph(8)
+>>> graphs = [H1, H2, H3, H4]
+>>> caps = ["Path 4", "Complete graph 4", "Path 8", "Complete graph 8"]
+>>> lbls = ["fig2a", "fig2b", "fig2c", "fig2d"]
+>>> nx.write_latex(graphs, "subfigs.tex", n_rows=2, sub_captions=caps, sub_labels=lbls)
+>>> latex_code = nx.to_latex(graphs, n_rows=2, sub_captions=caps, sub_labels=lbls)
+
+>>> node_color = {0: "red", 1: "orange", 2: "blue", 3: "gray!90"}
+>>> edge_width = {e: "line width=1.5" for e in H3.edges}
+>>> pos = nx.circular_layout(H3)
+>>> latex_code = nx.to_latex(H3, pos, node_options=node_color, edge_options=edge_width)
+>>> print(latex_code)
+\documentclass{report}
+\usepackage{tikz}
+\usepackage{subcaption}
+<BLANKLINE>
+\begin{document}
+\begin{figure}
+  \begin{tikzpicture}
+      \draw
+        (1.0, 0.0) node[red] (0){0}
+        (0.707, 0.707) node[orange] (1){1}
+        (-0.0, 1.0) node[blue] (2){2}
+        (-0.707, 0.707) node[gray!90] (3){3}
+        (-1.0, -0.0) node (4){4}
+        (-0.707, -0.707) node (5){5}
+        (0.0, -1.0) node (6){6}
+        (0.707, -0.707) node (7){7};
+      \begin{scope}[-]
+        \draw[line width=1.5] (0) to (1);
+        \draw[line width=1.5] (1) to (2);
+        \draw[line width=1.5] (2) to (3);
+        \draw[line width=1.5] (3) to (4);
+        \draw[line width=1.5] (4) to (5);
+        \draw[line width=1.5] (5) to (6);
+        \draw[line width=1.5] (6) to (7);
+      \end{scope}
+    \end{tikzpicture}
+\end{figure}
+\end{document}
+
+Notes
+-----
+If you want to change the preamble/postamble of the figure/document/subfigure
+environment, use the keyword arguments: `figure_wrapper`, `document_wrapper`,
+`subfigure_wrapper`. The default values are stored in private variables
+e.g. ``nx.nx_layout._DOCUMENT_WRAPPER``
+
+References
+----------
+TikZ:          https://tikz.dev/
+
+TikZ options details:   https://tikz.dev/tikz-actions
+"""
+
+import networkx as nx
+
+__all__ = [
+    "to_latex_raw",
+    "to_latex",
+    "write_latex",
+]
+
+
+@nx.utils.not_implemented_for("multigraph")
+def to_latex_raw(
+    G,
+    pos="pos",
+    tikz_options="",
+    default_node_options="",
+    node_options="node_options",
+    node_label="label",
+    default_edge_options="",
+    edge_options="edge_options",
+    edge_label="label",
+    edge_label_options="edge_label_options",
+):
+    """Return a string of the LaTeX/TikZ code to draw `G`
+
+    This function produces just the code for the tikzpicture
+    without any enclosing environment.
+
+    Parameters
+    ==========
+    G : NetworkX graph
+        The NetworkX graph to be drawn
+    pos : string or dict (default "pos")
+        The name of the node attribute on `G` that holds the position of each node.
+        Positions can be sequences of length 2 with numbers for (x,y) coordinates.
+        They can also be strings to denote positions in TikZ style, such as (x, y)
+        or (angle:radius).
+        If a dict, it should be keyed by node to a position.
+        If an empty dict, a circular layout is computed by TikZ.
+    tikz_options : string
+        The tikzpicture options description defining the options for the picture.
+        Often large scale options like `[scale=2]`.
+    default_node_options : string
+        The draw options for a path of nodes. Individual node options override these.
+    node_options : string or dict
+        The name of the node attribute on `G` that holds the options for each node.
+        Or a dict keyed by node to a string holding the options for that node.
+    node_label : string or dict
+        The name of the node attribute on `G` that holds the node label (text)
+        displayed for each node. If the attribute is "" or not present, the node
+        itself is drawn as a string. LaTeX processing such as ``"$A_1$"`` is allowed.
+        Or a dict keyed by node to a string holding the label for that node.
+    default_edge_options : string
+        The options for the scope drawing all edges. The default is "[-]" for
+        undirected graphs and "[->]" for directed graphs.
+    edge_options : string or dict
+        The name of the edge attribute on `G` that holds the options for each edge.
+        If the edge is a self-loop and ``"loop" not in edge_options`` the option
+        "loop," is added to the options for the self-loop edge. Hence you can
+        use "[loop above]" explicitly, but the default is "[loop]".
+        Or a dict keyed by edge to a string holding the options for that edge.
+    edge_label : string or dict
+        The name of the edge attribute on `G` that holds the edge label (text)
+        displayed for each edge. If the attribute is "" or not present, no edge
+        label is drawn.
+        Or a dict keyed by edge to a string holding the label for that edge.
+    edge_label_options : string or dict
+        The name of the edge attribute on `G` that holds the label options for
+        each edge. For example, "[sloped,above,blue]". The default is no options.
+        Or a dict keyed by edge to a string holding the label options for that edge.
+
+    Returns
+    =======
+    latex_code : string
+       The text string which draws the desired graph(s) when compiled by LaTeX.
+
+    See Also
+    ========
+    to_latex
+    write_latex
+    """
+    i4 = "\n    "
+    i8 = "\n        "
+
+    # set up position dict
+    # TODO allow pos to be None and use a nice TikZ default
+    if not isinstance(pos, dict):
+        pos = nx.get_node_attributes(G, pos)
+    if not pos:
+        # circular layout with radius 2
+        pos = {n: f"({round(360.0 * i / len(G), 3)}:2)" for i, n in enumerate(G)}
+    for node in G:
+        if node not in pos:
+            raise nx.NetworkXError(f"node {node} has no specified pos {pos}")
+        posnode = pos[node]
+        if not isinstance(posnode, str):
+            try:
+                posx, posy = posnode
+                pos[node] = f"({round(posx, 3)}, {round(posy, 3)})"
+            except (TypeError, ValueError):
+                msg = f"position pos[{node}] is not 2-tuple or a string: {posnode}"
+                raise nx.NetworkXError(msg)
+
+    # set up all the dicts
+    if not isinstance(node_options, dict):
+        node_options = nx.get_node_attributes(G, node_options)
+    if not isinstance(node_label, dict):
+        node_label = nx.get_node_attributes(G, node_label)
+    if not isinstance(edge_options, dict):
+        edge_options = nx.get_edge_attributes(G, edge_options)
+    if not isinstance(edge_label, dict):
+        edge_label = nx.get_edge_attributes(G, edge_label)
+    if not isinstance(edge_label_options, dict):
+        edge_label_options = nx.get_edge_attributes(G, edge_label_options)
+
+    # process default options (add brackets or not)
+    topts = "" if tikz_options == "" else f"[{tikz_options.strip('[]')}]"
+    defn = "" if default_node_options == "" else f"[{default_node_options.strip('[]')}]"
+    linestyle = f"{'->' if G.is_directed() else '-'}"
+    if default_edge_options == "":
+        defe = "[" + linestyle + "]"
+    elif "-" in default_edge_options:
+        defe = default_edge_options
+    else:
+        defe = f"[{linestyle},{default_edge_options.strip('[]')}]"
+
+    # Construct the string line by line
+    result = "  \\begin{tikzpicture}" + topts
+    result += i4 + "  \\draw" + defn
+    # load the nodes
+    for n in G:
+        # node options goes inside square brackets
+        nopts = f"[{node_options[n].strip('[]')}]" if n in node_options else ""
+        # node text goes inside curly brackets {}
+        ntext = f"{{{node_label[n]}}}" if n in node_label else f"{{{n}}}"
+
+        result += i8 + f"{pos[n]} node{nopts} ({n}){ntext}"
+    result += ";\n"
+
+    # load the edges
+    result += "      \\begin{scope}" + defe
+    for edge in G.edges:
+        u, v = edge[:2]
+        e_opts = f"{edge_options[edge]}".strip("[]") if edge in edge_options else ""
+        # add loop options for selfloops if not present
+        if u == v and "loop" not in e_opts:
+            e_opts = "loop," + e_opts
+        e_opts = f"[{e_opts}]" if e_opts != "" else ""
+        # TODO -- handle bending of multiedges
+
+        els = edge_label_options[edge] if edge in edge_label_options else ""
+        # edge label options goes inside square brackets []
+        els = f"[{els.strip('[]')}]"
+        # edge text is drawn using the TikZ node command inside curly brackets {}
+        e_label = f" node{els} {{{edge_label[edge]}}}" if edge in edge_label else ""
+
+        result += i8 + f"\\draw{e_opts} ({u}) to{e_label} ({v});"
+
+    result += "\n      \\end{scope}\n    \\end{tikzpicture}\n"
+    return result
+
+
+_DOC_WRAPPER_TIKZ = r"""\documentclass{{report}}
+\usepackage{{tikz}}
+\usepackage{{subcaption}}
+
+\begin{{document}}
+{content}
+\end{{document}}"""
+
+
+_FIG_WRAPPER = r"""\begin{{figure}}
+{content}{caption}{label}
+\end{{figure}}"""
+
+
+_SUBFIG_WRAPPER = r"""  \begin{{subfigure}}{{{size}\textwidth}}
+{content}{caption}{label}
+  \end{{subfigure}}"""
+
+
+def to_latex(
+    Gbunch,
+    pos="pos",
+    tikz_options="",
+    default_node_options="",
+    node_options="node_options",
+    node_label="node_label",
+    default_edge_options="",
+    edge_options="edge_options",
+    edge_label="edge_label",
+    edge_label_options="edge_label_options",
+    caption="",
+    latex_label="",
+    sub_captions=None,
+    sub_labels=None,
+    n_rows=1,
+    as_document=True,
+    document_wrapper=_DOC_WRAPPER_TIKZ,
+    figure_wrapper=_FIG_WRAPPER,
+    subfigure_wrapper=_SUBFIG_WRAPPER,
+):
+    """Return latex code to draw the graph(s) in `Gbunch`
+
+    The TikZ drawing utility in LaTeX is used to draw the graph(s).
+    If `Gbunch` is a graph, it is drawn in a figure environment.
+    If `Gbunch` is an iterable of graphs, each is drawn in a subfigure environment
+    within a single figure environment.
+
+    If `as_document` is True, the figure is wrapped inside a document environment
+    so that the resulting string is ready to be compiled by LaTeX. Otherwise,
+    the string is ready for inclusion in a larger tex document using ``\\include``
+    or ``\\input`` statements.
+
+    Parameters
+    ==========
+    Gbunch : NetworkX graph or iterable of NetworkX graphs
+        The NetworkX graph to be drawn or an iterable of graphs
+        to be drawn inside subfigures of a single figure.
+    pos : string or list of strings
+        The name of the node attribute on `G` that holds the position of each node.
+        Positions can be sequences of length 2 with numbers for (x,y) coordinates.
+        They can also be strings to denote positions in TikZ style, such as (x, y)
+        or (angle:radius).
+        If a dict, it should be keyed by node to a position.
+        If an empty dict, a circular layout is computed by TikZ.
+        If you are drawing many graphs in subfigures, use a list of position dicts.
+    tikz_options : string
+        The tikzpicture options description defining the options for the picture.
+        Often large scale options like `[scale=2]`.
+    default_node_options : string
+        The draw options for a path of nodes. Individual node options override these.
+    node_options : string or dict
+        The name of the node attribute on `G` that holds the options for each node.
+        Or a dict keyed by node to a string holding the options for that node.
+    node_label : string or dict
+        The name of the node attribute on `G` that holds the node label (text)
+        displayed for each node. If the attribute is "" or not present, the node
+        itself is drawn as a string. LaTeX processing such as ``"$A_1$"`` is allowed.
+        Or a dict keyed by node to a string holding the label for that node.
+    default_edge_options : string
+        The options for the scope drawing all edges. The default is "[-]" for
+        undirected graphs and "[->]" for directed graphs.
+    edge_options : string or dict
+        The name of the edge attribute on `G` that holds the options for each edge.
+        If the edge is a self-loop and ``"loop" not in edge_options`` the option
+        "loop," is added to the options for the self-loop edge. Hence you can
+        use "[loop above]" explicitly, but the default is "[loop]".
+        Or a dict keyed by edge to a string holding the options for that edge.
+    edge_label : string or dict
+        The name of the edge attribute on `G` that holds the edge label (text)
+        displayed for each edge. If the attribute is "" or not present, no edge
+        label is drawn.
+        Or a dict keyed by edge to a string holding the label for that edge.
+    edge_label_options : string or dict
+        The name of the edge attribute on `G` that holds the label options for
+        each edge. For example, "[sloped,above,blue]". The default is no options.
+        Or a dict keyed by edge to a string holding the label options for that edge.
+    caption : string
+        The caption string for the figure environment
+    latex_label : string
+        The latex label used for the figure for easy referral from the main text
+    sub_captions : list of strings
+        The sub_caption string for each subfigure in the figure
+    sub_latex_labels : list of strings
+        The latex label for each subfigure in the figure
+    n_rows : int
+        The number of rows of subfigures to arrange for multiple graphs
+    as_document : bool
+        Whether to wrap the latex code in a document environment for compiling
+    document_wrapper : formatted text string with variable ``content``.
+        This text is called to evaluate the content embedded in a document
+        environment with a preamble setting up TikZ.
+    figure_wrapper : formatted text string
+        This text is evaluated with variables ``content``, ``caption`` and ``label``.
+        It wraps the content and if a caption is provided, adds the latex code for
+        that caption, and if a label is provided, adds the latex code for a label.
+    subfigure_wrapper : formatted text string
+        This text evaluate variables ``size``, ``content``, ``caption`` and ``label``.
+        It wraps the content and if a caption is provided, adds the latex code for
+        that caption, and if a label is provided, adds the latex code for a label.
+        The size is the vertical size of each row of subfigures as a fraction.
+
+    Returns
+    =======
+    latex_code : string
+        The text string which draws the desired graph(s) when compiled by LaTeX.
+
+    See Also
+    ========
+    write_latex
+    to_latex_raw
+    """
+    if hasattr(Gbunch, "adj"):
+        raw = to_latex_raw(
+            Gbunch,
+            pos,
+            tikz_options,
+            default_node_options,
+            node_options,
+            node_label,
+            default_edge_options,
+            edge_options,
+            edge_label,
+            edge_label_options,
+        )
+    else:  # iterator of graphs
+        sbf = subfigure_wrapper
+        size = 1 / n_rows
+
+        N = len(Gbunch)
+        if isinstance(pos, str | dict):
+            pos = [pos] * N
+        if sub_captions is None:
+            sub_captions = [""] * N
+        if sub_labels is None:
+            sub_labels = [""] * N
+        if not (len(Gbunch) == len(pos) == len(sub_captions) == len(sub_labels)):
+            raise nx.NetworkXError(
+                "length of Gbunch, sub_captions and sub_figures must agree"
+            )
+
+        raw = ""
+        for G, pos, subcap, sublbl in zip(Gbunch, pos, sub_captions, sub_labels):
+            subraw = to_latex_raw(
+                G,
+                pos,
+                tikz_options,
+                default_node_options,
+                node_options,
+                node_label,
+                default_edge_options,
+                edge_options,
+                edge_label,
+                edge_label_options,
+            )
+            cap = f"    \\caption{{{subcap}}}" if subcap else ""
+            lbl = f"\\label{{{sublbl}}}" if sublbl else ""
+            raw += sbf.format(size=size, content=subraw, caption=cap, label=lbl)
+            raw += "\n"
+
+    # put raw latex code into a figure environment and optionally into a document
+    raw = raw[:-1]
+    cap = f"\n  \\caption{{{caption}}}" if caption else ""
+    lbl = f"\\label{{{latex_label}}}" if latex_label else ""
+    fig = figure_wrapper.format(content=raw, caption=cap, label=lbl)
+    if as_document:
+        return document_wrapper.format(content=fig)
+    return fig
+
+
+@nx.utils.open_file(1, mode="w")
+def write_latex(Gbunch, path, **options):
+    """Write the latex code to draw the graph(s) onto `path`.
+
+    This convenience function creates the latex drawing code as a string
+    and writes that to a file ready to be compiled when `as_document` is True
+    or ready to be ``import`` ed or ``include`` ed into your main LaTeX document.
+
+    The `path` argument can be a string filename or a file handle to write to.
+
+    Parameters
+    ----------
+    Gbunch : NetworkX graph or iterable of NetworkX graphs
+        If Gbunch is a graph, it is drawn in a figure environment.
+        If Gbunch is an iterable of graphs, each is drawn in a subfigure
+        environment within a single figure environment.
+    path : string or file
+        Filename or file handle to write to.
+        Filenames ending in .gz or .bz2 will be compressed.
+    options : dict
+        By default, TikZ is used with options: (others are ignored)::
+
+            pos : string or dict or list
+                The name of the node attribute on `G` that holds the position of each node.
+                Positions can be sequences of length 2 with numbers for (x,y) coordinates.
+                They can also be strings to denote positions in TikZ style, such as (x, y)
+                or (angle:radius).
+                If a dict, it should be keyed by node to a position.
+                If an empty dict, a circular layout is computed by TikZ.
+                If you are drawing many graphs in subfigures, use a list of position dicts.
+            tikz_options : string
+                The tikzpicture options description defining the options for the picture.
+                Often large scale options like `[scale=2]`.
+            default_node_options : string
+                The draw options for a path of nodes. Individual node options override these.
+            node_options : string or dict
+                The name of the node attribute on `G` that holds the options for each node.
+                Or a dict keyed by node to a string holding the options for that node.
+            node_label : string or dict
+                The name of the node attribute on `G` that holds the node label (text)
+                displayed for each node. If the attribute is "" or not present, the node
+                itself is drawn as a string. LaTeX processing such as ``"$A_1$"`` is allowed.
+                Or a dict keyed by node to a string holding the label for that node.
+            default_edge_options : string
+                The options for the scope drawing all edges. The default is "[-]" for
+                undirected graphs and "[->]" for directed graphs.
+            edge_options : string or dict
+                The name of the edge attribute on `G` that holds the options for each edge.
+                If the edge is a self-loop and ``"loop" not in edge_options`` the option
+                "loop," is added to the options for the self-loop edge. Hence you can
+                use "[loop above]" explicitly, but the default is "[loop]".
+                Or a dict keyed by edge to a string holding the options for that edge.
+            edge_label : string or dict
+                The name of the edge attribute on `G` that holds the edge label (text)
+                displayed for each edge. If the attribute is "" or not present, no edge
+                label is drawn.
+                Or a dict keyed by edge to a string holding the label for that edge.
+            edge_label_options : string or dict
+                The name of the edge attribute on `G` that holds the label options for
+                each edge. For example, "[sloped,above,blue]". The default is no options.
+                Or a dict keyed by edge to a string holding the label options for that edge.
+            caption : string
+                The caption string for the figure environment
+            latex_label : string
+                The latex label used for the figure for easy referral from the main text
+            sub_captions : list of strings
+                The sub_caption string for each subfigure in the figure
+            sub_latex_labels : list of strings
+                The latex label for each subfigure in the figure
+            n_rows : int
+                The number of rows of subfigures to arrange for multiple graphs
+            as_document : bool
+                Whether to wrap the latex code in a document environment for compiling
+            document_wrapper : formatted text string with variable ``content``.
+                This text is called to evaluate the content embedded in a document
+                environment with a preamble setting up the TikZ syntax.
+            figure_wrapper : formatted text string
+                This text is evaluated with variables ``content``, ``caption`` and ``label``.
+                It wraps the content and if a caption is provided, adds the latex code for
+                that caption, and if a label is provided, adds the latex code for a label.
+            subfigure_wrapper : formatted text string
+                This text evaluate variables ``size``, ``content``, ``caption`` and ``label``.
+                It wraps the content and if a caption is provided, adds the latex code for
+                that caption, and if a label is provided, adds the latex code for a label.
+                The size is the vertical size of each row of subfigures as a fraction.
+
+    See Also
+    ========
+    to_latex
+    """
+    path.write(to_latex(Gbunch, **options))

venv/lib/python3.13/site-packages/networkx/drawing/nx_pydot.py

@@ -0,0 +1,361 @@
+"""
+*****
+Pydot
+*****
+
+Import and export NetworkX graphs in Graphviz dot format using pydot.
+
+Either this module or nx_agraph can be used to interface with graphviz.
+
+Examples
+--------
+>>> G = nx.complete_graph(5)
+>>> PG = nx.nx_pydot.to_pydot(G)
+>>> H = nx.nx_pydot.from_pydot(PG)
+
+See Also
+--------
+ - pydot:         https://github.com/erocarrera/pydot
+ - Graphviz:      https://www.graphviz.org
+ - DOT Language:  http://www.graphviz.org/doc/info/lang.html
+"""
+
+from locale import getpreferredencoding
+
+import networkx as nx
+from networkx.utils import open_file
+
+__all__ = [
+    "write_dot",
+    "read_dot",
+    "graphviz_layout",
+    "pydot_layout",
+    "to_pydot",
+    "from_pydot",
+]
+
+
+@open_file(1, mode="w")
+def write_dot(G, path):
+    """Write NetworkX graph G to Graphviz dot format on path.
+
+    Parameters
+    ----------
+    G : NetworkX graph
+
+    path : string or file
+       Filename or file handle for data output.
+       Filenames ending in .gz or .bz2 will be compressed.
+    """
+    P = to_pydot(G)
+    path.write(P.to_string())
+    return
+
+
+@open_file(0, mode="r")
+@nx._dispatchable(name="pydot_read_dot", graphs=None, returns_graph=True)
+def read_dot(path):
+    """Returns a NetworkX :class:`MultiGraph` or :class:`MultiDiGraph` from the
+    dot file with the passed path.
+
+    If this file contains multiple graphs, only the first such graph is
+    returned. All graphs _except_ the first are silently ignored.
+
+    Parameters
+    ----------
+    path : str or file
+        Filename or file handle to read.
+        Filenames ending in .gz or .bz2 will be decompressed.
+
+    Returns
+    -------
+    G : MultiGraph or MultiDiGraph
+        A :class:`MultiGraph` or :class:`MultiDiGraph`.
+
+    Notes
+    -----
+    Use `G = nx.Graph(nx.nx_pydot.read_dot(path))` to return a :class:`Graph` instead of a
+    :class:`MultiGraph`.
+    """
+    import pydot
+
+    data = path.read()
+
+    # List of one or more "pydot.Dot" instances deserialized from this file.
+    P_list = pydot.graph_from_dot_data(data)
+
+    # Convert only the first such instance into a NetworkX graph.
+    return from_pydot(P_list[0])
+
+
+@nx._dispatchable(graphs=None, returns_graph=True)
+def from_pydot(P):
+    """Returns a NetworkX graph from a Pydot graph.
+
+    Parameters
+    ----------
+    P : Pydot graph
+      A graph created with Pydot
+
+    Returns
+    -------
+    G : NetworkX multigraph
+        A MultiGraph or MultiDiGraph.
+
+    Examples
+    --------
+    >>> K5 = nx.complete_graph(5)
+    >>> A = nx.nx_pydot.to_pydot(K5)
+    >>> G = nx.nx_pydot.from_pydot(A)  # return MultiGraph
+
+    # make a Graph instead of MultiGraph
+    >>> G = nx.Graph(nx.nx_pydot.from_pydot(A))
+
+    """
+    # NOTE: Pydot v3 expects a dummy argument whereas Pydot v4 doesn't
+    # Remove the try-except when Pydot v4 becomes the minimum supported version
+    try:
+        strict = P.get_strict()
+    except TypeError:
+        strict = P.get_strict(None)  # pydot bug: get_strict() shouldn't take argument
+    multiedges = not strict
+
+    if P.get_type() == "graph":  # undirected
+        if multiedges:
+            N = nx.MultiGraph()
+        else:
+            N = nx.Graph()
+    else:
+        if multiedges:
+            N = nx.MultiDiGraph()
+        else:
+            N = nx.DiGraph()
+
+    # assign defaults
+    name = P.get_name().strip('"')
+    if name != "":
+        N.name = name
+
+    # add nodes, attributes to N.node_attr
+    for p in P.get_node_list():
+        n = p.get_name().strip('"')
+        if n in ("node", "graph", "edge"):
+            continue
+        N.add_node(n, **p.get_attributes())
+
+    # add edges
+    for e in P.get_edge_list():
+        u = e.get_source()
+        v = e.get_destination()
+        attr = e.get_attributes()
+        s = []
+        d = []
+
+        if isinstance(u, str):
+            s.append(u.strip('"'))
+        else:
+            for unodes in u["nodes"]:
+                s.append(unodes.strip('"'))
+
+        if isinstance(v, str):
+            d.append(v.strip('"'))
+        else:
+            for vnodes in v["nodes"]:
+                d.append(vnodes.strip('"'))
+
+        for source_node in s:
+            for destination_node in d:
+                N.add_edge(source_node, destination_node, **attr)
+
+    # add default attributes for graph, nodes, edges
+    pattr = P.get_attributes()
+    if pattr:
+        N.graph["graph"] = pattr
+    try:
+        N.graph["node"] = P.get_node_defaults()[0]
+    except (IndexError, TypeError):
+        pass  # N.graph['node']={}
+    try:
+        N.graph["edge"] = P.get_edge_defaults()[0]
+    except (IndexError, TypeError):
+        pass  # N.graph['edge']={}
+    return N
+
+
+def to_pydot(N):
+    """Returns a pydot graph from a NetworkX graph N.
+
+    Parameters
+    ----------
+    N : NetworkX graph
+      A graph created with NetworkX
+
+    Examples
+    --------
+    >>> K5 = nx.complete_graph(5)
+    >>> P = nx.nx_pydot.to_pydot(K5)
+
+    Notes
+    -----
+
+    """
+    import pydot
+
+    # set Graphviz graph type
+    if N.is_directed():
+        graph_type = "digraph"
+    else:
+        graph_type = "graph"
+    strict = nx.number_of_selfloops(N) == 0 and not N.is_multigraph()
+
+    name = N.name
+    graph_defaults = N.graph.get("graph", {})
+    if name == "":
+        P = pydot.Dot("", graph_type=graph_type, strict=strict, **graph_defaults)
+    else:
+        P = pydot.Dot(
+            f'"{name}"', graph_type=graph_type, strict=strict, **graph_defaults
+        )
+    try:
+        P.set_node_defaults(**N.graph["node"])
+    except KeyError:
+        pass
+    try:
+        P.set_edge_defaults(**N.graph["edge"])
+    except KeyError:
+        pass
+
+    for n, nodedata in N.nodes(data=True):
+        str_nodedata = {str(k): str(v) for k, v in nodedata.items()}
+        n = str(n)
+        p = pydot.Node(n, **str_nodedata)
+        P.add_node(p)
+
+    if N.is_multigraph():
+        for u, v, key, edgedata in N.edges(data=True, keys=True):
+            str_edgedata = {str(k): str(v) for k, v in edgedata.items() if k != "key"}
+            u, v = str(u), str(v)
+            edge = pydot.Edge(u, v, key=str(key), **str_edgedata)
+            P.add_edge(edge)
+
+    else:
+        for u, v, edgedata in N.edges(data=True):
+            str_edgedata = {str(k): str(v) for k, v in edgedata.items()}
+            u, v = str(u), str(v)
+            edge = pydot.Edge(u, v, **str_edgedata)
+            P.add_edge(edge)
+    return P
+
+
+def graphviz_layout(G, prog="neato", root=None):
+    """Create node positions using Pydot and Graphviz.
+
+    Returns a dictionary of positions keyed by node.
+
+    Parameters
+    ----------
+    G : NetworkX Graph
+        The graph for which the layout is computed.
+    prog : string (default: 'neato')
+        The name of the GraphViz program to use for layout.
+        Options depend on GraphViz version but may include:
+        'dot', 'twopi', 'fdp', 'sfdp', 'circo'
+    root : Node from G or None (default: None)
+        The node of G from which to start some layout algorithms.
+
+    Returns
+    -------
+      Dictionary of (x, y) positions keyed by node.
+
+    Examples
+    --------
+    >>> G = nx.complete_graph(4)
+    >>> pos = nx.nx_pydot.graphviz_layout(G)
+    >>> pos = nx.nx_pydot.graphviz_layout(G, prog="dot")
+
+    Notes
+    -----
+    This is a wrapper for pydot_layout.
+    """
+    return pydot_layout(G=G, prog=prog, root=root)
+
+
+def pydot_layout(G, prog="neato", root=None):
+    """Create node positions using :mod:`pydot` and Graphviz.
+
+    Parameters
+    ----------
+    G : Graph
+        NetworkX graph to be laid out.
+    prog : string  (default: 'neato')
+        Name of the GraphViz command to use for layout.
+        Options depend on GraphViz version but may include:
+        'dot', 'twopi', 'fdp', 'sfdp', 'circo'
+    root : Node from G or None (default: None)
+        The node of G from which to start some layout algorithms.
+
+    Returns
+    -------
+    dict
+        Dictionary of positions keyed by node.
+
+    Examples
+    --------
+    >>> G = nx.complete_graph(4)
+    >>> pos = nx.nx_pydot.pydot_layout(G)
+    >>> pos = nx.nx_pydot.pydot_layout(G, prog="dot")
+
+    Notes
+    -----
+    If you use complex node objects, they may have the same string
+    representation and GraphViz could treat them as the same node.
+    The layout may assign both nodes a single location. See Issue #1568
+    If this occurs in your case, consider relabeling the nodes just
+    for the layout computation using something similar to::
+
+        H = nx.convert_node_labels_to_integers(G, label_attribute="node_label")
+        H_layout = nx.nx_pydot.pydot_layout(H, prog="dot")
+        G_layout = {H.nodes[n]["node_label"]: p for n, p in H_layout.items()}
+
+    """
+    import pydot
+
+    P = to_pydot(G)
+    if root is not None:
+        P.set("root", str(root))
+
+    # List of low-level bytes comprising a string in the dot language converted
+    # from the passed graph with the passed external GraphViz command.
+    D_bytes = P.create_dot(prog=prog)
+
+    # Unique string decoded from these bytes with the preferred locale encoding
+    D = str(D_bytes, encoding=getpreferredencoding())
+
+    if D == "":  # no data returned
+        print(f"Graphviz layout with {prog} failed")
+        print()
+        print("To debug what happened try:")
+        print("P = nx.nx_pydot.to_pydot(G)")
+        print('P.write_dot("file.dot")')
+        print(f"And then run {prog} on file.dot")
+        return
+
+    # List of one or more "pydot.Dot" instances deserialized from this string.
+    Q_list = pydot.graph_from_dot_data(D)
+    assert len(Q_list) == 1
+
+    # The first and only such instance, as guaranteed by the above assertion.
+    Q = Q_list[0]
+
+    node_pos = {}
+    for n in G.nodes():
+        str_n = str(n)
+        node = Q.get_node(pydot.quote_id_if_necessary(str_n))
+
+        if isinstance(node, list):
+            node = node[0]
+        pos = node.get_pos()[1:-1]  # strip leading and trailing double quotes
+        if pos is not None:
+            xx, yy = pos.split(",")
+            node_pos[n] = (float(xx), float(yy))
+    return node_pos

venv/lib/python3.13/site-packages/networkx/drawing/tests/test_agraph.py

@@ -0,0 +1,240 @@
+"""Unit tests for PyGraphviz interface."""
+
+import warnings
+
+import pytest
+
+import networkx as nx
+from networkx.utils import edges_equal, graphs_equal, nodes_equal
+
+pygraphviz = pytest.importorskip("pygraphviz")
+
+
+class TestAGraph:
+    def build_graph(self, G):
+        edges = [("A", "B"), ("A", "C"), ("A", "C"), ("B", "C"), ("A", "D")]
+        G.add_edges_from(edges)
+        G.add_node("E")
+        G.graph["metal"] = "bronze"
+        return G
+
+    def assert_equal(self, G1, G2):
+        assert nodes_equal(G1.nodes(), G2.nodes())
+        assert edges_equal(G1.edges(), G2.edges())
+        assert G1.graph["metal"] == G2.graph["metal"]
+
+    @pytest.mark.parametrize(
+        "G", (nx.Graph(), nx.DiGraph(), nx.MultiGraph(), nx.MultiDiGraph())
+    )
+    def test_agraph_roundtripping(self, G, tmp_path):
+        G = self.build_graph(G)
+        A = nx.nx_agraph.to_agraph(G)
+        H = nx.nx_agraph.from_agraph(A)
+        self.assert_equal(G, H)
+
+        fname = tmp_path / "test.dot"
+        nx.drawing.nx_agraph.write_dot(H, fname)
+        Hin = nx.nx_agraph.read_dot(fname)
+        self.assert_equal(H, Hin)
+
+        fname = tmp_path / "fh_test.dot"
+        with open(fname, "w") as fh:
+            nx.drawing.nx_agraph.write_dot(H, fh)
+
+        with open(fname) as fh:
+            Hin = nx.nx_agraph.read_dot(fh)
+        self.assert_equal(H, Hin)
+
+    def test_from_agraph_name(self):
+        G = nx.Graph(name="test")
+        A = nx.nx_agraph.to_agraph(G)
+        H = nx.nx_agraph.from_agraph(A)
+        assert G.name == "test"
+
+    @pytest.mark.parametrize(
+        "graph_class", (nx.Graph, nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph)
+    )
+    def test_from_agraph_create_using(self, graph_class):
+        G = nx.path_graph(3)
+        A = nx.nx_agraph.to_agraph(G)
+        H = nx.nx_agraph.from_agraph(A, create_using=graph_class)
+        assert isinstance(H, graph_class)
+
+    def test_from_agraph_named_edges(self):
+        # Create an AGraph from an existing (non-multi) Graph
+        G = nx.Graph()
+        G.add_nodes_from([0, 1])
+        A = nx.nx_agraph.to_agraph(G)
+        # Add edge (+ name, given by key) to the AGraph
+        A.add_edge(0, 1, key="foo")
+        # Verify a.name roundtrips out to 'key' in from_agraph
+        H = nx.nx_agraph.from_agraph(A)
+        assert isinstance(H, nx.Graph)
+        assert ("0", "1", {"key": "foo"}) in H.edges(data=True)
+
+    def test_to_agraph_with_nodedata(self):
+        G = nx.Graph()
+        G.add_node(1, color="red")
+        A = nx.nx_agraph.to_agraph(G)
+        assert dict(A.nodes()[0].attr) == {"color": "red"}
+
+    @pytest.mark.parametrize("graph_class", (nx.Graph, nx.MultiGraph))
+    def test_to_agraph_with_edgedata(self, graph_class):
+        G = graph_class()
+        G.add_nodes_from([0, 1])
+        G.add_edge(0, 1, color="yellow")
+        A = nx.nx_agraph.to_agraph(G)
+        assert dict(A.edges()[0].attr) == {"color": "yellow"}
+
+    def test_view_pygraphviz_path(self, tmp_path):
+        G = nx.complete_graph(3)
+        input_path = str(tmp_path / "graph.png")
+        out_path, A = nx.nx_agraph.view_pygraphviz(G, path=input_path, show=False)
+        assert out_path == input_path
+        # Ensure file is not empty
+        with open(input_path, "rb") as fh:
+            data = fh.read()
+        assert len(data) > 0
+
+    def test_view_pygraphviz_file_suffix(self, tmp_path):
+        G = nx.complete_graph(3)
+        path, A = nx.nx_agraph.view_pygraphviz(G, suffix=1, show=False)
+        assert path[-6:] == "_1.png"
+
+    def test_view_pygraphviz(self):
+        G = nx.Graph()  # "An empty graph cannot be drawn."
+        pytest.raises(nx.NetworkXException, nx.nx_agraph.view_pygraphviz, G)
+        G = nx.barbell_graph(4, 6)
+        nx.nx_agraph.view_pygraphviz(G, show=False)
+
+    def test_view_pygraphviz_edgelabel(self):
+        G = nx.Graph()
+        G.add_edge(1, 2, weight=7)
+        G.add_edge(2, 3, weight=8)
+        path, A = nx.nx_agraph.view_pygraphviz(G, edgelabel="weight", show=False)
+        for edge in A.edges():
+            assert edge.attr["weight"] in ("7", "8")
+
+    def test_view_pygraphviz_callable_edgelabel(self):
+        G = nx.complete_graph(3)
+
+        def foo_label(data):
+            return "foo"
+
+        path, A = nx.nx_agraph.view_pygraphviz(G, edgelabel=foo_label, show=False)
+        for edge in A.edges():
+            assert edge.attr["label"] == "foo"
+
+    def test_view_pygraphviz_multigraph_edgelabels(self):
+        G = nx.MultiGraph()
+        G.add_edge(0, 1, key=0, name="left_fork")
+        G.add_edge(0, 1, key=1, name="right_fork")
+        path, A = nx.nx_agraph.view_pygraphviz(G, edgelabel="name", show=False)
+        edges = A.edges()
+        assert len(edges) == 2
+        for edge in edges:
+            assert edge.attr["label"].strip() in ("left_fork", "right_fork")
+
+    def test_graph_with_reserved_keywords(self):
+        # test attribute/keyword clash case for #1582
+        # node: n
+        # edges: u,v
+        G = nx.Graph()
+        G = self.build_graph(G)
+        G.nodes["E"]["n"] = "keyword"
+        G.edges[("A", "B")]["u"] = "keyword"
+        G.edges[("A", "B")]["v"] = "keyword"
+        A = nx.nx_agraph.to_agraph(G)
+
+    def test_view_pygraphviz_no_added_attrs_to_input(self):
+        G = nx.complete_graph(2)
+        path, A = nx.nx_agraph.view_pygraphviz(G, show=False)
+        assert G.graph == {}
+
+    @pytest.mark.xfail(reason="known bug in clean_attrs")
+    def test_view_pygraphviz_leaves_input_graph_unmodified(self):
+        G = nx.complete_graph(2)
+        # Add entries to graph dict that to_agraph handles specially
+        G.graph["node"] = {"width": "0.80"}
+        G.graph["edge"] = {"fontsize": "14"}
+        path, A = nx.nx_agraph.view_pygraphviz(G, show=False)
+        assert G.graph == {"node": {"width": "0.80"}, "edge": {"fontsize": "14"}}
+
+    def test_graph_with_AGraph_attrs(self):
+        G = nx.complete_graph(2)
+        # Add entries to graph dict that to_agraph handles specially
+        G.graph["node"] = {"width": "0.80"}
+        G.graph["edge"] = {"fontsize": "14"}
+        path, A = nx.nx_agraph.view_pygraphviz(G, show=False)
+        # Ensure user-specified values are not lost
+        assert dict(A.node_attr)["width"] == "0.80"
+        assert dict(A.edge_attr)["fontsize"] == "14"
+
+    def test_round_trip_empty_graph(self):
+        G = nx.Graph()
+        A = nx.nx_agraph.to_agraph(G)
+        H = nx.nx_agraph.from_agraph(A)
+        # assert graphs_equal(G, H)
+        AA = nx.nx_agraph.to_agraph(H)
+        HH = nx.nx_agraph.from_agraph(AA)
+        assert graphs_equal(H, HH)
+        G.graph["graph"] = {}
+        G.graph["node"] = {}
+        G.graph["edge"] = {}
+        assert graphs_equal(G, HH)
+
+    @pytest.mark.xfail(reason="integer->string node conversion in round trip")
+    def test_round_trip_integer_nodes(self):
+        G = nx.complete_graph(3)
+        A = nx.nx_agraph.to_agraph(G)
+        H = nx.nx_agraph.from_agraph(A)
+        assert graphs_equal(G, H)
+
+    def test_graphviz_alias(self):
+        G = self.build_graph(nx.Graph())
+        pos_graphviz = nx.nx_agraph.graphviz_layout(G)
+        pos_pygraphviz = nx.nx_agraph.pygraphviz_layout(G)
+        assert pos_graphviz == pos_pygraphviz
+
+    @pytest.mark.parametrize("root", range(5))
+    def test_pygraphviz_layout_root(self, root):
+        # NOTE: test depends on layout prog being deterministic
+        G = nx.complete_graph(5)
+        A = nx.nx_agraph.to_agraph(G)
+        # Get layout with root arg is not None
+        pygv_layout = nx.nx_agraph.pygraphviz_layout(G, prog="circo", root=root)
+        # Equivalent layout directly on AGraph
+        A.layout(args=f"-Groot={root}", prog="circo")
+        # Parse AGraph layout
+        a1_pos = tuple(float(v) for v in dict(A.get_node("1").attr)["pos"].split(","))
+        assert pygv_layout[1] == a1_pos
+
+    def test_2d_layout(self):
+        G = nx.Graph()
+        G = self.build_graph(G)
+        G.graph["dimen"] = 2
+        pos = nx.nx_agraph.pygraphviz_layout(G, prog="neato")
+        pos = list(pos.values())
+        assert len(pos) == 5
+        assert len(pos[0]) == 2
+
+    def test_3d_layout(self):
+        G = nx.Graph()
+        G = self.build_graph(G)
+        G.graph["dimen"] = 3
+        pos = nx.nx_agraph.pygraphviz_layout(G, prog="neato")
+        pos = list(pos.values())
+        assert len(pos) == 5
+        assert len(pos[0]) == 3
+
+    def test_no_warnings_raised(self):
+        # Test that no warnings are raised when Networkx graph
+        # is converted to Pygraphviz graph and 'pos'
+        # attribute is given
+        G = nx.Graph()
+        G.add_node(0, pos=(0, 0))
+        G.add_node(1, pos=(1, 1))
+        A = nx.nx_agraph.to_agraph(G)
+        with warnings.catch_warnings(record=True) as record:
+            A.layout()
+        assert len(record) == 0

venv/lib/python3.13/site-packages/networkx/drawing/tests/test_latex.py

@@ -0,0 +1,285 @@
+import pytest
+
+import networkx as nx
+
+
+def test_tikz_attributes():
+    G = nx.path_graph(4, create_using=nx.DiGraph)
+    pos = {n: (n, n) for n in G}
+
+    G.add_edge(0, 0)
+    G.edges[(0, 0)]["label"] = "Loop"
+    G.edges[(0, 0)]["label_options"] = "midway"
+
+    G.nodes[0]["style"] = "blue"
+    G.nodes[1]["style"] = "line width=3,draw"
+    G.nodes[2]["style"] = "circle,draw,blue!50"
+    G.nodes[3]["label"] = "Stop"
+    G.edges[(0, 1)]["label"] = "1st Step"
+    G.edges[(0, 1)]["label_options"] = "near end"
+    G.edges[(2, 3)]["label"] = "3rd Step"
+    G.edges[(2, 3)]["label_options"] = "near start"
+    G.edges[(2, 3)]["style"] = "bend left,green"
+    G.edges[(1, 2)]["label"] = "2nd"
+    G.edges[(1, 2)]["label_options"] = "pos=0.5"
+    G.edges[(1, 2)]["style"] = ">->,bend right,line width=3,green!90"
+
+    output_tex = nx.to_latex(
+        G,
+        pos=pos,
+        as_document=False,
+        tikz_options="[scale=3]",
+        node_options="style",
+        edge_options="style",
+        node_label="label",
+        edge_label="label",
+        edge_label_options="label_options",
+    )
+    expected_tex = r"""\begin{figure}
+  \begin{tikzpicture}[scale=3]
+      \draw
+        (0, 0) node[blue] (0){0}
+        (1, 1) node[line width=3,draw] (1){1}
+        (2, 2) node[circle,draw,blue!50] (2){2}
+        (3, 3) node (3){Stop};
+      \begin{scope}[->]
+        \draw (0) to node[near end] {1st Step} (1);
+        \draw[loop,] (0) to node[midway] {Loop} (0);
+        \draw[>->,bend right,line width=3,green!90] (1) to node[pos=0.5] {2nd} (2);
+        \draw[bend left,green] (2) to node[near start] {3rd Step} (3);
+      \end{scope}
+    \end{tikzpicture}
+\end{figure}"""
+
+    # First, check for consistency line-by-line - if this fails, the mismatched
+    # line will be shown explicitly in the failure summary
+    for expected, actual in zip(expected_tex.split("\n"), output_tex.split("\n")):
+        assert expected == actual
+
+    assert output_tex == expected_tex
+
+
+def test_basic_multiple_graphs():
+    H1 = nx.path_graph(4)
+    H2 = nx.complete_graph(4)
+    H3 = nx.path_graph(8)
+    H4 = nx.complete_graph(8)
+    captions = [
+        "Path on 4 nodes",
+        "Complete graph on 4 nodes",
+        "Path on 8 nodes",
+        "Complete graph on 8 nodes",
+    ]
+    labels = ["fig2a", "fig2b", "fig2c", "fig2d"]
+    latex_code = nx.to_latex(
+        [H1, H2, H3, H4],
+        n_rows=2,
+        sub_captions=captions,
+        sub_labels=labels,
+    )
+    assert "begin{document}" in latex_code
+    assert "begin{figure}" in latex_code
+    assert latex_code.count("begin{subfigure}") == 4
+    assert latex_code.count("tikzpicture") == 8
+    assert latex_code.count("[-]") == 4
+
+
+def test_basic_tikz():
+    expected_tex = r"""\documentclass{report}
+\usepackage{tikz}
+\usepackage{subcaption}
+
+\begin{document}
+\begin{figure}
+  \begin{subfigure}{0.5\textwidth}
+  \begin{tikzpicture}[scale=2]
+      \draw[gray!90]
+        (0.749, 0.702) node[red!90] (0){0}
+        (1.0, -0.014) node[red!90] (1){1}
+        (-0.777, -0.705) node (2){2}
+        (-0.984, 0.042) node (3){3}
+        (-0.028, 0.375) node[cyan!90] (4){4}
+        (-0.412, 0.888) node (5){5}
+        (0.448, -0.856) node (6){6}
+        (0.003, -0.431) node[cyan!90] (7){7};
+      \begin{scope}[->,gray!90]
+        \draw (0) to (4);
+        \draw (0) to (5);
+        \draw (0) to (6);
+        \draw (0) to (7);
+        \draw (1) to (4);
+        \draw (1) to (5);
+        \draw (1) to (6);
+        \draw (1) to (7);
+        \draw (2) to (4);
+        \draw (2) to (5);
+        \draw (2) to (6);
+        \draw (2) to (7);
+        \draw (3) to (4);
+        \draw (3) to (5);
+        \draw (3) to (6);
+        \draw (3) to (7);
+      \end{scope}
+    \end{tikzpicture}
+    \caption{My tikz number 1 of 2}\label{tikz_1_2}
+  \end{subfigure}
+  \begin{subfigure}{0.5\textwidth}
+  \begin{tikzpicture}[scale=2]
+      \draw[gray!90]
+        (0.749, 0.702) node[green!90] (0){0}
+        (1.0, -0.014) node[green!90] (1){1}
+        (-0.777, -0.705) node (2){2}
+        (-0.984, 0.042) node (3){3}
+        (-0.028, 0.375) node[purple!90] (4){4}
+        (-0.412, 0.888) node (5){5}
+        (0.448, -0.856) node (6){6}
+        (0.003, -0.431) node[purple!90] (7){7};
+      \begin{scope}[->,gray!90]
+        \draw (0) to (4);
+        \draw (0) to (5);
+        \draw (0) to (6);
+        \draw (0) to (7);
+        \draw (1) to (4);
+        \draw (1) to (5);
+        \draw (1) to (6);
+        \draw (1) to (7);
+        \draw (2) to (4);
+        \draw (2) to (5);
+        \draw (2) to (6);
+        \draw (2) to (7);
+        \draw (3) to (4);
+        \draw (3) to (5);
+        \draw (3) to (6);
+        \draw (3) to (7);
+      \end{scope}
+    \end{tikzpicture}
+    \caption{My tikz number 2 of 2}\label{tikz_2_2}
+  \end{subfigure}
+  \caption{A graph generated with python and latex.}
+\end{figure}
+\end{document}"""
+
+    edges = [
+        (0, 4),
+        (0, 5),
+        (0, 6),
+        (0, 7),
+        (1, 4),
+        (1, 5),
+        (1, 6),
+        (1, 7),
+        (2, 4),
+        (2, 5),
+        (2, 6),
+        (2, 7),
+        (3, 4),
+        (3, 5),
+        (3, 6),
+        (3, 7),
+    ]
+    G = nx.DiGraph()
+    G.add_nodes_from(range(8))
+    G.add_edges_from(edges)
+    pos = {
+        0: (0.7490296171687696, 0.702353520257394),
+        1: (1.0, -0.014221357723796535),
+        2: (-0.7765783344161441, -0.7054170966808919),
+        3: (-0.9842690223417624, 0.04177547602465483),
+        4: (-0.02768523817180917, 0.3745724439551441),
+        5: (-0.41154855146767433, 0.8880106515525136),
+        6: (0.44780153389148264, -0.8561492709269164),
+        7: (0.0032499953371383505, -0.43092436645809945),
+    }
+
+    rc_node_color = {0: "red!90", 1: "red!90", 4: "cyan!90", 7: "cyan!90"}
+    gp_node_color = {0: "green!90", 1: "green!90", 4: "purple!90", 7: "purple!90"}
+
+    H = G.copy()
+    nx.set_node_attributes(G, rc_node_color, "color")
+    nx.set_node_attributes(H, gp_node_color, "color")
+
+    sub_captions = ["My tikz number 1 of 2", "My tikz number 2 of 2"]
+    sub_labels = ["tikz_1_2", "tikz_2_2"]
+
+    output_tex = nx.to_latex(
+        [G, H],
+        [pos, pos],
+        tikz_options="[scale=2]",
+        default_node_options="gray!90",
+        default_edge_options="gray!90",
+        node_options="color",
+        sub_captions=sub_captions,
+        sub_labels=sub_labels,
+        caption="A graph generated with python and latex.",
+        n_rows=2,
+        as_document=True,
+    )
+
+    # First, check for consistency line-by-line - if this fails, the mismatched
+    # line will be shown explicitly in the failure summary
+    for expected, actual in zip(expected_tex.split("\n"), output_tex.split("\n")):
+        assert expected == actual
+    # Double-check for document-level consistency
+    assert output_tex == expected_tex
+
+
+def test_exception_pos_single_graph(to_latex=nx.to_latex):
+    # smoke test that pos can be a string
+    G = nx.path_graph(4)
+    to_latex(G, pos="pos")
+
+    # must include all nodes
+    pos = {0: (1, 2), 1: (0, 1), 2: (2, 1)}
+    with pytest.raises(nx.NetworkXError):
+        to_latex(G, pos)
+
+    # must have 2 values
+    pos[3] = (1, 2, 3)
+    with pytest.raises(nx.NetworkXError):
+        to_latex(G, pos)
+    pos[3] = 2
+    with pytest.raises(nx.NetworkXError):
+        to_latex(G, pos)
+
+    # check that passes with 2 values
+    pos[3] = (3, 2)
+    to_latex(G, pos)
+
+
+def test_exception_multiple_graphs(to_latex=nx.to_latex):
+    G = nx.path_graph(3)
+    pos_bad = {0: (1, 2), 1: (0, 1)}
+    pos_OK = {0: (1, 2), 1: (0, 1), 2: (2, 1)}
+    fourG = [G, G, G, G]
+    fourpos = [pos_OK, pos_OK, pos_OK, pos_OK]
+
+    # input single dict to use for all graphs
+    to_latex(fourG, pos_OK)
+    with pytest.raises(nx.NetworkXError):
+        to_latex(fourG, pos_bad)
+
+    # input list of dicts to use for all graphs
+    to_latex(fourG, fourpos)
+    with pytest.raises(nx.NetworkXError):
+        to_latex(fourG, [pos_bad, pos_bad, pos_bad, pos_bad])
+
+    # every pos dict must include all nodes
+    with pytest.raises(nx.NetworkXError):
+        to_latex(fourG, [pos_OK, pos_OK, pos_bad, pos_OK])
+
+    # test sub_captions and sub_labels (len must match Gbunch)
+    with pytest.raises(nx.NetworkXError):
+        to_latex(fourG, fourpos, sub_captions=["hi", "hi"])
+
+    with pytest.raises(nx.NetworkXError):
+        to_latex(fourG, fourpos, sub_labels=["hi", "hi"])
+
+    # all pass
+    to_latex(fourG, fourpos, sub_captions=["hi"] * 4, sub_labels=["lbl"] * 4)
+
+
+def test_exception_multigraph():
+    G = nx.path_graph(4, create_using=nx.MultiGraph)
+    G.add_edge(1, 2)
+    with pytest.raises(nx.NetworkXNotImplemented):
+        nx.to_latex(G)

venv/lib/python3.13/site-packages/networkx/drawing/tests/test_layout.py

@@ -0,0 +1,631 @@
+"""Unit tests for layout functions."""
+
+import pytest
+
+import networkx as nx
+
+np = pytest.importorskip("numpy")
+pytest.importorskip("scipy")
+
+
+class TestLayout:
+    @classmethod
+    def setup_class(cls):
+        cls.Gi = nx.grid_2d_graph(5, 5)
+        cls.Gs = nx.Graph()
+        nx.add_path(cls.Gs, "abcdef")
+        cls.bigG = nx.grid_2d_graph(25, 25)  # > 500 nodes for sparse
+
+    def test_spring_fixed_without_pos(self):
+        G = nx.path_graph(4)
+        # No pos dict at all
+        with pytest.raises(ValueError, match="nodes are fixed without positions"):
+            nx.spring_layout(G, fixed=[0])
+
+        pos = {0: (1, 1), 2: (0, 0)}
+        # Node 1 not in pos dict
+        with pytest.raises(ValueError, match="nodes are fixed without positions"):
+            nx.spring_layout(G, fixed=[0, 1], pos=pos)
+
+        # All fixed nodes in pos dict
+        out = nx.spring_layout(G, fixed=[0, 2], pos=pos)  # No ValueError
+        assert all(np.array_equal(out[n], pos[n]) for n in (0, 2))
+
+    def test_spring_init_pos(self):
+        # Tests GH #2448
+        import math
+
+        G = nx.Graph()
+        G.add_edges_from([(0, 1), (1, 2), (2, 0), (2, 3)])
+
+        init_pos = {0: (0.0, 0.0)}
+        fixed_pos = [0]
+        pos = nx.fruchterman_reingold_layout(G, pos=init_pos, fixed=fixed_pos)
+        has_nan = any(math.isnan(c) for coords in pos.values() for c in coords)
+        assert not has_nan, "values should not be nan"
+
+    def test_smoke_empty_graph(self):
+        G = []
+        nx.random_layout(G)
+        nx.circular_layout(G)
+        nx.planar_layout(G)
+        nx.spring_layout(G)
+        nx.fruchterman_reingold_layout(G)
+        nx.spectral_layout(G)
+        nx.shell_layout(G)
+        nx.bipartite_layout(G, G)
+        nx.spiral_layout(G)
+        nx.multipartite_layout(G)
+        nx.kamada_kawai_layout(G)
+
+    def test_smoke_int(self):
+        G = self.Gi
+        nx.random_layout(G)
+        nx.circular_layout(G)
+        nx.planar_layout(G)
+        nx.spring_layout(G)
+        nx.forceatlas2_layout(G)
+        nx.fruchterman_reingold_layout(G)
+        nx.fruchterman_reingold_layout(self.bigG)
+        nx.spectral_layout(G)
+        nx.spectral_layout(G.to_directed())
+        nx.spectral_layout(self.bigG)
+        nx.spectral_layout(self.bigG.to_directed())
+        nx.shell_layout(G)
+        nx.spiral_layout(G)
+        nx.kamada_kawai_layout(G)
+        nx.kamada_kawai_layout(G, dim=1)
+        nx.kamada_kawai_layout(G, dim=3)
+        nx.arf_layout(G)
+
+    def test_smoke_string(self):
+        G = self.Gs
+        nx.random_layout(G)
+        nx.circular_layout(G)
+        nx.planar_layout(G)
+        nx.spring_layout(G)
+        nx.forceatlas2_layout(G)
+        nx.fruchterman_reingold_layout(G)
+        nx.spectral_layout(G)
+        nx.shell_layout(G)
+        nx.spiral_layout(G)
+        nx.kamada_kawai_layout(G)
+        nx.kamada_kawai_layout(G, dim=1)
+        nx.kamada_kawai_layout(G, dim=3)
+        nx.arf_layout(G)
+
+    def check_scale_and_center(self, pos, scale, center):
+        center = np.array(center)
+        low = center - scale
+        hi = center + scale
+        vpos = np.array(list(pos.values()))
+        length = vpos.max(0) - vpos.min(0)
+        assert (length <= 2 * scale).all()
+        assert (vpos >= low).all()
+        assert (vpos <= hi).all()
+
+    def test_scale_and_center_arg(self):
+        sc = self.check_scale_and_center
+        c = (4, 5)
+        G = nx.complete_graph(9)
+        G.add_node(9)
+        sc(nx.random_layout(G, center=c), scale=0.5, center=(4.5, 5.5))
+        # rest can have 2*scale length: [-scale, scale]
+        sc(nx.spring_layout(G, scale=2, center=c), scale=2, center=c)
+        sc(nx.spectral_layout(G, scale=2, center=c), scale=2, center=c)
+        sc(nx.circular_layout(G, scale=2, center=c), scale=2, center=c)
+        sc(nx.shell_layout(G, scale=2, center=c), scale=2, center=c)
+        sc(nx.spiral_layout(G, scale=2, center=c), scale=2, center=c)
+        sc(nx.kamada_kawai_layout(G, scale=2, center=c), scale=2, center=c)
+
+        c = (2, 3, 5)
+        sc(nx.kamada_kawai_layout(G, dim=3, scale=2, center=c), scale=2, center=c)
+
+    def test_planar_layout_non_planar_input(self):
+        G = nx.complete_graph(9)
+        pytest.raises(nx.NetworkXException, nx.planar_layout, G)
+
+    def test_smoke_planar_layout_embedding_input(self):
+        embedding = nx.PlanarEmbedding()
+        embedding.set_data({0: [1, 2], 1: [0, 2], 2: [0, 1]})
+        nx.planar_layout(embedding)
+
+    def test_default_scale_and_center(self):
+        sc = self.check_scale_and_center
+        c = (0, 0)
+        G = nx.complete_graph(9)
+        G.add_node(9)
+        sc(nx.random_layout(G), scale=0.5, center=(0.5, 0.5))
+        sc(nx.spring_layout(G), scale=1, center=c)
+        sc(nx.spectral_layout(G), scale=1, center=c)
+        sc(nx.circular_layout(G), scale=1, center=c)
+        sc(nx.shell_layout(G), scale=1, center=c)
+        sc(nx.spiral_layout(G), scale=1, center=c)
+        sc(nx.kamada_kawai_layout(G), scale=1, center=c)
+
+        c = (0, 0, 0)
+        sc(nx.kamada_kawai_layout(G, dim=3), scale=1, center=c)
+
+    def test_circular_planar_and_shell_dim_error(self):
+        G = nx.path_graph(4)
+        pytest.raises(ValueError, nx.circular_layout, G, dim=1)
+        pytest.raises(ValueError, nx.shell_layout, G, dim=1)
+        pytest.raises(ValueError, nx.shell_layout, G, dim=3)
+        pytest.raises(ValueError, nx.planar_layout, G, dim=1)
+        pytest.raises(ValueError, nx.planar_layout, G, dim=3)
+
+    def test_adjacency_interface_numpy(self):
+        A = nx.to_numpy_array(self.Gs)
+        pos = nx.drawing.layout._fruchterman_reingold(A)
+        assert pos.shape == (6, 2)
+        pos = nx.drawing.layout._fruchterman_reingold(A, dim=3)
+        assert pos.shape == (6, 3)
+        pos = nx.drawing.layout._sparse_fruchterman_reingold(A)
+        assert pos.shape == (6, 2)
+
+    def test_adjacency_interface_scipy(self):
+        A = nx.to_scipy_sparse_array(self.Gs, dtype="d")
+        pos = nx.drawing.layout._sparse_fruchterman_reingold(A)
+        assert pos.shape == (6, 2)
+        pos = nx.drawing.layout._sparse_spectral(A)
+        assert pos.shape == (6, 2)
+        pos = nx.drawing.layout._sparse_fruchterman_reingold(A, dim=3)
+        assert pos.shape == (6, 3)
+
+    def test_single_nodes(self):
+        G = nx.path_graph(1)
+        vpos = nx.shell_layout(G)
+        assert not vpos[0].any()
+        G = nx.path_graph(4)
+        vpos = nx.shell_layout(G, [[0], [1, 2], [3]])
+        assert not vpos[0].any()
+        assert vpos[3].any()  # ensure node 3 not at origin (#3188)
+        assert np.linalg.norm(vpos[3]) <= 1  # ensure node 3 fits (#3753)
+        vpos = nx.shell_layout(G, [[0], [1, 2], [3]], rotate=0)
+        assert np.linalg.norm(vpos[3]) <= 1  # ensure node 3 fits (#3753)
+
+    def test_smoke_initial_pos_forceatlas2(self):
+        pos = nx.circular_layout(self.Gi)
+        npos = nx.forceatlas2_layout(self.Gi, pos=pos)
+
+    def test_smoke_initial_pos_fruchterman_reingold(self):
+        pos = nx.circular_layout(self.Gi)
+        npos = nx.fruchterman_reingold_layout(self.Gi, pos=pos)
+
+    def test_smoke_initial_pos_arf(self):
+        pos = nx.circular_layout(self.Gi)
+        npos = nx.arf_layout(self.Gi, pos=pos)
+
+    def test_fixed_node_fruchterman_reingold(self):
+        # Dense version (numpy based)
+        pos = nx.circular_layout(self.Gi)
+        npos = nx.spring_layout(self.Gi, pos=pos, fixed=[(0, 0)])
+        assert tuple(pos[(0, 0)]) == tuple(npos[(0, 0)])
+        # Sparse version (scipy based)
+        pos = nx.circular_layout(self.bigG)
+        npos = nx.spring_layout(self.bigG, pos=pos, fixed=[(0, 0)])
+        for axis in range(2):
+            assert pos[(0, 0)][axis] == pytest.approx(npos[(0, 0)][axis], abs=1e-7)
+
+    def test_center_parameter(self):
+        G = nx.path_graph(1)
+        nx.random_layout(G, center=(1, 1))
+        vpos = nx.circular_layout(G, center=(1, 1))
+        assert tuple(vpos[0]) == (1, 1)
+        vpos = nx.planar_layout(G, center=(1, 1))
+        assert tuple(vpos[0]) == (1, 1)
+        vpos = nx.spring_layout(G, center=(1, 1))
+        assert tuple(vpos[0]) == (1, 1)
+        vpos = nx.fruchterman_reingold_layout(G, center=(1, 1))
+        assert tuple(vpos[0]) == (1, 1)
+        vpos = nx.spectral_layout(G, center=(1, 1))
+        assert tuple(vpos[0]) == (1, 1)
+        vpos = nx.shell_layout(G, center=(1, 1))
+        assert tuple(vpos[0]) == (1, 1)
+        vpos = nx.spiral_layout(G, center=(1, 1))
+        assert tuple(vpos[0]) == (1, 1)
+
+    def test_center_wrong_dimensions(self):
+        G = nx.path_graph(1)
+        assert id(nx.spring_layout) == id(nx.fruchterman_reingold_layout)
+        pytest.raises(ValueError, nx.random_layout, G, center=(1, 1, 1))
+        pytest.raises(ValueError, nx.circular_layout, G, center=(1, 1, 1))
+        pytest.raises(ValueError, nx.planar_layout, G, center=(1, 1, 1))
+        pytest.raises(ValueError, nx.spring_layout, G, center=(1, 1, 1))
+        pytest.raises(ValueError, nx.spring_layout, G, dim=3, center=(1, 1))
+        pytest.raises(ValueError, nx.spectral_layout, G, center=(1, 1, 1))
+        pytest.raises(ValueError, nx.spectral_layout, G, dim=3, center=(1, 1))
+        pytest.raises(ValueError, nx.shell_layout, G, center=(1, 1, 1))
+        pytest.raises(ValueError, nx.spiral_layout, G, center=(1, 1, 1))
+        pytest.raises(ValueError, nx.kamada_kawai_layout, G, center=(1, 1, 1))
+
+    def test_empty_graph(self):
+        G = nx.empty_graph()
+        vpos = nx.random_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.circular_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.planar_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.bipartite_layout(G, G)
+        assert vpos == {}
+        vpos = nx.spring_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.fruchterman_reingold_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.spectral_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.shell_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.spiral_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.multipartite_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.kamada_kawai_layout(G, center=(1, 1))
+        assert vpos == {}
+        vpos = nx.forceatlas2_layout(G)
+        assert vpos == {}
+        vpos = nx.arf_layout(G)
+        assert vpos == {}
+
+    def test_bipartite_layout(self):
+        G = nx.complete_bipartite_graph(3, 5)
+        top, bottom = nx.bipartite.sets(G)
+
+        vpos = nx.bipartite_layout(G, top)
+        assert len(vpos) == len(G)
+
+        top_x = vpos[list(top)[0]][0]
+        bottom_x = vpos[list(bottom)[0]][0]
+        for node in top:
+            assert vpos[node][0] == top_x
+        for node in bottom:
+            assert vpos[node][0] == bottom_x
+
+        vpos = nx.bipartite_layout(
+            G, top, align="horizontal", center=(2, 2), scale=2, aspect_ratio=1
+        )
+        assert len(vpos) == len(G)
+
+        top_y = vpos[list(top)[0]][1]
+        bottom_y = vpos[list(bottom)[0]][1]
+        for node in top:
+            assert vpos[node][1] == top_y
+        for node in bottom:
+            assert vpos[node][1] == bottom_y
+
+        pytest.raises(ValueError, nx.bipartite_layout, G, top, align="foo")
+
+    def test_multipartite_layout(self):
+        sizes = (0, 5, 7, 2, 8)
+        G = nx.complete_multipartite_graph(*sizes)
+
+        vpos = nx.multipartite_layout(G)
+        assert len(vpos) == len(G)
+
+        start = 0
+        for n in sizes:
+            end = start + n
+            assert all(vpos[start][0] == vpos[i][0] for i in range(start + 1, end))
+            start += n
+
+        vpos = nx.multipartite_layout(G, align="horizontal", scale=2, center=(2, 2))
+        assert len(vpos) == len(G)
+
+        start = 0
+        for n in sizes:
+            end = start + n
+            assert all(vpos[start][1] == vpos[i][1] for i in range(start + 1, end))
+            start += n
+
+        pytest.raises(ValueError, nx.multipartite_layout, G, align="foo")
+
+    def test_kamada_kawai_costfn_1d(self):
+        costfn = nx.drawing.layout._kamada_kawai_costfn
+
+        pos = np.array([4.0, 7.0])
+        invdist = 1 / np.array([[0.1, 2.0], [2.0, 0.3]])
+
+        cost, grad = costfn(pos, np, invdist, meanweight=0, dim=1)
+
+        assert cost == pytest.approx(((3 / 2.0 - 1) ** 2), abs=1e-7)
+        assert grad[0] == pytest.approx((-0.5), abs=1e-7)
+        assert grad[1] == pytest.approx(0.5, abs=1e-7)
+
+    def check_kamada_kawai_costfn(self, pos, invdist, meanwt, dim):
+        costfn = nx.drawing.layout._kamada_kawai_costfn
+
+        cost, grad = costfn(pos.ravel(), np, invdist, meanweight=meanwt, dim=dim)
+
+        expected_cost = 0.5 * meanwt * np.sum(np.sum(pos, axis=0) ** 2)
+        for i in range(pos.shape[0]):
+            for j in range(i + 1, pos.shape[0]):
+                diff = np.linalg.norm(pos[i] - pos[j])
+                expected_cost += (diff * invdist[i][j] - 1.0) ** 2
+
+        assert cost == pytest.approx(expected_cost, abs=1e-7)
+
+        dx = 1e-4
+        for nd in range(pos.shape[0]):
+            for dm in range(pos.shape[1]):
+                idx = nd * pos.shape[1] + dm
+                ps = pos.flatten()
+
+                ps[idx] += dx
+                cplus = costfn(ps, np, invdist, meanweight=meanwt, dim=pos.shape[1])[0]
+
+                ps[idx] -= 2 * dx
+                cminus = costfn(ps, np, invdist, meanweight=meanwt, dim=pos.shape[1])[0]
+
+                assert grad[idx] == pytest.approx((cplus - cminus) / (2 * dx), abs=1e-5)
+
+    def test_kamada_kawai_costfn(self):
+        invdist = 1 / np.array([[0.1, 2.1, 1.7], [2.1, 0.2, 0.6], [1.7, 0.6, 0.3]])
+        meanwt = 0.3
+
+        # 2d
+        pos = np.array([[1.3, -3.2], [2.7, -0.3], [5.1, 2.5]])
+
+        self.check_kamada_kawai_costfn(pos, invdist, meanwt, 2)
+
+        # 3d
+        pos = np.array([[0.9, 8.6, -8.7], [-10, -0.5, -7.1], [9.1, -8.1, 1.6]])
+
+        self.check_kamada_kawai_costfn(pos, invdist, meanwt, 3)
+
+    def test_spiral_layout(self):
+        G = self.Gs
+
+        # a lower value of resolution should result in a more compact layout
+        # intuitively, the total distance from the start and end nodes
+        # via each node in between (transiting through each) will be less,
+        # assuming rescaling does not occur on the computed node positions
+        pos_standard = np.array(list(nx.spiral_layout(G, resolution=0.35).values()))
+        pos_tighter = np.array(list(nx.spiral_layout(G, resolution=0.34).values()))
+        distances = np.linalg.norm(pos_standard[:-1] - pos_standard[1:], axis=1)
+        distances_tighter = np.linalg.norm(pos_tighter[:-1] - pos_tighter[1:], axis=1)
+        assert sum(distances) > sum(distances_tighter)
+
+        # return near-equidistant points after the first value if set to true
+        pos_equidistant = np.array(list(nx.spiral_layout(G, equidistant=True).values()))
+        distances_equidistant = np.linalg.norm(
+            pos_equidistant[:-1] - pos_equidistant[1:], axis=1
+        )
+        assert np.allclose(
+            distances_equidistant[1:], distances_equidistant[-1], atol=0.01
+        )
+
+    def test_spiral_layout_equidistant(self):
+        G = nx.path_graph(10)
+        nx.spiral_layout(G, equidistant=True, store_pos_as="pos")
+        pos = nx.get_node_attributes(G, "pos")
+        # Extract individual node positions as an array
+        p = np.array(list(pos.values()))
+        # Elementwise-distance between node positions
+        dist = np.linalg.norm(p[1:] - p[:-1], axis=1)
+        assert np.allclose(np.diff(dist), 0, atol=1e-3)
+
+    def test_forceatlas2_layout_partial_input_test(self):
+        # check whether partial pos input still returns a full proper position
+        G = self.Gs
+        node = nx.utils.arbitrary_element(G)
+        pos = nx.circular_layout(G)
+        del pos[node]
+        pos = nx.forceatlas2_layout(G, pos=pos)
+        assert len(pos) == len(G)
+
+    def test_rescale_layout_dict(self):
+        G = nx.empty_graph()
+        vpos = nx.random_layout(G, center=(1, 1))
+        assert nx.rescale_layout_dict(vpos) == {}
+
+        G = nx.empty_graph(2)
+        vpos = {0: (0.0, 0.0), 1: (1.0, 1.0)}
+        s_vpos = nx.rescale_layout_dict(vpos)
+        assert np.linalg.norm([sum(x) for x in zip(*s_vpos.values())]) < 1e-6
+
+        G = nx.empty_graph(3)
+        vpos = {0: (0, 0), 1: (1, 1), 2: (0.5, 0.5)}
+        s_vpos = nx.rescale_layout_dict(vpos)
+
+        expectation = {
+            0: np.array((-1, -1)),
+            1: np.array((1, 1)),
+            2: np.array((0, 0)),
+        }
+        for k, v in expectation.items():
+            assert (s_vpos[k] == v).all()
+        s_vpos = nx.rescale_layout_dict(vpos, scale=2)
+        expectation = {
+            0: np.array((-2, -2)),
+            1: np.array((2, 2)),
+            2: np.array((0, 0)),
+        }
+        for k, v in expectation.items():
+            assert (s_vpos[k] == v).all()
+
+    def test_arf_layout_partial_input_test(self):
+        # Checks whether partial pos input still returns a proper position.
+        G = self.Gs
+        node = nx.utils.arbitrary_element(G)
+        pos = nx.circular_layout(G)
+        del pos[node]
+        pos = nx.arf_layout(G, pos=pos)
+        assert len(pos) == len(G)
+
+    def test_arf_layout_negative_a_check(self):
+        """
+        Checks input parameters correctly raises errors. For example,  `a` should be larger than 1
+        """
+        G = self.Gs
+        pytest.raises(ValueError, nx.arf_layout, G=G, a=-1)
+
+    def test_smoke_seed_input(self):
+        G = self.Gs
+        nx.random_layout(G, seed=42)
+        nx.spring_layout(G, seed=42)
+        nx.arf_layout(G, seed=42)
+        nx.forceatlas2_layout(G, seed=42)
+
+    def test_node_at_center(self):
+        # see gh-7791 avoid divide by zero
+        G = nx.path_graph(3)
+        orig_pos = {i: [i - 1, 0.0] for i in range(3)}
+        new_pos = nx.forceatlas2_layout(G, pos=orig_pos)
+
+    def test_initial_only_some_pos(self):
+        G = nx.path_graph(3)
+        orig_pos = {i: [i - 1, 0.0] for i in range(2)}
+        new_pos = nx.forceatlas2_layout(G, pos=orig_pos, seed=42)
+
+
+def test_multipartite_layout_nonnumeric_partition_labels():
+    """See gh-5123."""
+    G = nx.Graph()
+    G.add_node(0, subset="s0")
+    G.add_node(1, subset="s0")
+    G.add_node(2, subset="s1")
+    G.add_node(3, subset="s1")
+    G.add_edges_from([(0, 2), (0, 3), (1, 2)])
+    pos = nx.multipartite_layout(G)
+    assert len(pos) == len(G)
+
+
+def test_multipartite_layout_layer_order():
+    """Return the layers in sorted order if the layers of the multipartite
+    graph are sortable. See gh-5691"""
+    G = nx.Graph()
+    node_group = dict(zip(("a", "b", "c", "d", "e"), (2, 3, 1, 2, 4)))
+    for node, layer in node_group.items():
+        G.add_node(node, subset=layer)
+
+    # Horizontal alignment, therefore y-coord determines layers
+    pos = nx.multipartite_layout(G, align="horizontal")
+
+    layers = nx.utils.groups(node_group)
+    pos_from_layers = nx.multipartite_layout(G, align="horizontal", subset_key=layers)
+    for (n1, p1), (n2, p2) in zip(pos.items(), pos_from_layers.items()):
+        assert n1 == n2 and (p1 == p2).all()
+
+    # Nodes "a" and "d" are in the same layer
+    assert pos["a"][-1] == pos["d"][-1]
+    # positions should be sorted according to layer
+    assert pos["c"][-1] < pos["a"][-1] < pos["b"][-1] < pos["e"][-1]
+
+    # Make sure that multipartite_layout still works when layers are not sortable
+    G.nodes["a"]["subset"] = "layer_0"  # Can't sort mixed strs/ints
+    pos_nosort = nx.multipartite_layout(G)  # smoke test: this should not raise
+    assert pos_nosort.keys() == pos.keys()
+
+
+def _num_nodes_per_bfs_layer(pos):
+    """Helper function to extract the number of nodes in each layer of bfs_layout"""
+    x = np.array(list(pos.values()))[:, 0]  # node positions in layered dimension
+    _, layer_count = np.unique(x, return_counts=True)
+    return layer_count
+
+
+@pytest.mark.parametrize("n", range(2, 7))
+def test_bfs_layout_complete_graph(n):
+    """The complete graph should result in two layers: the starting node and
+    a second layer containing all neighbors."""
+    G = nx.complete_graph(n)
+    nx.bfs_layout(G, start=0, store_pos_as="pos")
+    pos = nx.get_node_attributes(G, "pos")
+    assert np.array_equal(_num_nodes_per_bfs_layer(pos), [1, n - 1])
+
+
+def test_bfs_layout_barbell():
+    G = nx.barbell_graph(5, 3)
+    # Start in one of the "bells"
+    pos = nx.bfs_layout(G, start=0)
+    # start, bell-1, [1] * len(bar)+1, bell-1
+    expected_nodes_per_layer = [1, 4, 1, 1, 1, 1, 4]
+    assert np.array_equal(_num_nodes_per_bfs_layer(pos), expected_nodes_per_layer)
+    # Start in the other "bell" - expect same layer pattern
+    pos = nx.bfs_layout(G, start=12)
+    assert np.array_equal(_num_nodes_per_bfs_layer(pos), expected_nodes_per_layer)
+    # Starting in the center of the bar, expect layers to be symmetric
+    pos = nx.bfs_layout(G, start=6)
+    # Expected layers: {6 (start)}, {5, 7}, {4, 8}, {8 nodes from remainder of bells}
+    expected_nodes_per_layer = [1, 2, 2, 8]
+    assert np.array_equal(_num_nodes_per_bfs_layer(pos), expected_nodes_per_layer)
+
+
+def test_bfs_layout_disconnected():
+    G = nx.complete_graph(5)
+    G.add_edges_from([(10, 11), (11, 12)])
+    with pytest.raises(nx.NetworkXError, match="bfs_layout didn't include all nodes"):
+        nx.bfs_layout(G, start=0)
+
+
+def test_bipartite_layout_default_nodes_raises_non_bipartite_input():
+    G = nx.complete_graph(5)
+    with pytest.raises(nx.NetworkXError, match="Graph is not bipartite"):
+        nx.bipartite_layout(G)
+    # No exception if nodes are explicitly specified
+    pos = nx.bipartite_layout(G, nodes=[2, 3])
+
+
+def test_bipartite_layout_default_nodes():
+    G = nx.complete_bipartite_graph(3, 3)
+    pos = nx.bipartite_layout(G)  # no nodes specified
+    # X coords of nodes should be the same within the bipartite sets
+    for nodeset in nx.bipartite.sets(G):
+        xs = [pos[k][0] for k in nodeset]
+        assert all(x == pytest.approx(xs[0]) for x in xs)
+
+
+@pytest.mark.parametrize(
+    "layout",
+    [
+        nx.random_layout,
+        nx.circular_layout,
+        nx.shell_layout,
+        nx.spring_layout,
+        nx.kamada_kawai_layout,
+        nx.spectral_layout,
+        nx.planar_layout,
+        nx.spiral_layout,
+        nx.forceatlas2_layout,
+    ],
+)
+def test_layouts_negative_dim(layout):
+    """Test all layouts that support dim kwarg handle invalid inputs."""
+    G = nx.path_graph(4)
+    valid_err_msgs = "|".join(
+        [
+            "negative dimensions.*not allowed",
+            "can only handle 2",
+            "cannot handle.*2",
+        ]
+    )
+    with pytest.raises(ValueError, match=valid_err_msgs):
+        layout(G, dim=-1)
+
+
+@pytest.mark.parametrize(
+    ("num_nodes", "expected_method"), [(100, "force"), (501, "energy")]
+)
+@pytest.mark.parametrize(
+    "extra_layout_kwargs",
+    [
+        {},  # No extra kwargs
+        {"pos": {0: (0, 0)}, "fixed": [0]},  # Fixed node position
+        {"dim": 3},  # 3D layout
+    ],
+)
+def test_spring_layout_graph_size_heuristic(
+    num_nodes, expected_method, extra_layout_kwargs
+):
+    """Expect 'force' layout for n < 500 and 'energy' for n >= 500"""
+    G = nx.cycle_graph(num_nodes)
+    # Seeded layout to compare explicit method to one determined by "auto"
+    seed = 163674319
+
+    # Compare explicit method to auto method
+    expected = nx.spring_layout(
+        G, method=expected_method, seed=seed, **extra_layout_kwargs
+    )
+    actual = nx.spring_layout(G, method="auto", seed=seed, **extra_layout_kwargs)
+    assert np.allclose(list(expected.values()), list(actual.values()), atol=1e-5)

venv/lib/python3.13/site-packages/networkx/drawing/tests/test_pydot.py

@@ -0,0 +1,146 @@
+"""Unit tests for pydot drawing functions."""
+
+from io import StringIO
+
+import pytest
+
+import networkx as nx
+from networkx.utils import graphs_equal
+
+pydot = pytest.importorskip("pydot")
+
+
+class TestPydot:
+    @pytest.mark.parametrize("G", (nx.Graph(), nx.DiGraph()))
+    @pytest.mark.parametrize("prog", ("neato", "dot"))
+    def test_pydot(self, G, prog, tmp_path):
+        """
+        Validate :mod:`pydot`-based usage of the passed NetworkX graph with the
+        passed basename of an external GraphViz command (e.g., `dot`, `neato`).
+        """
+
+        # Set the name of this graph to... "G". Failing to do so will
+        # subsequently trip an assertion expecting this name.
+        G.graph["name"] = "G"
+
+        # Add arbitrary nodes and edges to the passed empty graph.
+        G.add_edges_from([("A", "B"), ("A", "C"), ("B", "C"), ("A", "D")])
+        G.add_node("E")
+
+        # Validate layout of this graph with the passed GraphViz command.
+        graph_layout = nx.nx_pydot.pydot_layout(G, prog=prog)
+        assert isinstance(graph_layout, dict)
+
+        # Convert this graph into a "pydot.Dot" instance.
+        P = nx.nx_pydot.to_pydot(G)
+
+        # Convert this "pydot.Dot" instance back into a graph of the same type.
+        G2 = G.__class__(nx.nx_pydot.from_pydot(P))
+
+        # Validate the original and resulting graphs to be the same.
+        assert graphs_equal(G, G2)
+
+        fname = tmp_path / "out.dot"
+
+        # Serialize this "pydot.Dot" instance to a temporary file in dot format
+        P.write_raw(fname)
+
+        # Deserialize a list of new "pydot.Dot" instances back from this file.
+        Pin_list = pydot.graph_from_dot_file(path=fname, encoding="utf-8")
+
+        # Validate this file to contain only one graph.
+        assert len(Pin_list) == 1
+
+        # The single "pydot.Dot" instance deserialized from this file.
+        Pin = Pin_list[0]
+
+        # Sorted list of all nodes in the original "pydot.Dot" instance.
+        n1 = sorted(p.get_name() for p in P.get_node_list())
+
+        # Sorted list of all nodes in the deserialized "pydot.Dot" instance.
+        n2 = sorted(p.get_name() for p in Pin.get_node_list())
+
+        # Validate these instances to contain the same nodes.
+        assert n1 == n2
+
+        # Sorted list of all edges in the original "pydot.Dot" instance.
+        e1 = sorted((e.get_source(), e.get_destination()) for e in P.get_edge_list())
+
+        # Sorted list of all edges in the original "pydot.Dot" instance.
+        e2 = sorted((e.get_source(), e.get_destination()) for e in Pin.get_edge_list())
+
+        # Validate these instances to contain the same edges.
+        assert e1 == e2
+
+        # Deserialize a new graph of the same type back from this file.
+        Hin = nx.nx_pydot.read_dot(fname)
+        Hin = G.__class__(Hin)
+
+        # Validate the original and resulting graphs to be the same.
+        assert graphs_equal(G, Hin)
+
+    def test_read_write(self):
+        G = nx.MultiGraph()
+        G.graph["name"] = "G"
+        G.add_edge("1", "2", key="0")  # read assumes strings
+        fh = StringIO()
+        nx.nx_pydot.write_dot(G, fh)
+        fh.seek(0)
+        H = nx.nx_pydot.read_dot(fh)
+        assert graphs_equal(G, H)
+
+
+def test_pydot_issue_7581(tmp_path):
+    """Validate that `nx_pydot.pydot_layout` handles nodes
+    with characters like "\n", " ".
+
+    Those characters cause `pydot` to escape and quote them on output,
+    which caused #7581.
+    """
+    G = nx.Graph()
+    G.add_edges_from([("A\nbig test", "B"), ("A\nbig test", "C"), ("B", "C")])
+
+    graph_layout = nx.nx_pydot.pydot_layout(G, prog="dot")
+    assert isinstance(graph_layout, dict)
+
+    # Convert the graph to pydot and back into a graph. There should be no difference.
+    P = nx.nx_pydot.to_pydot(G)
+    G2 = nx.Graph(nx.nx_pydot.from_pydot(P))
+    assert graphs_equal(G, G2)
+
+
+@pytest.mark.parametrize(
+    "graph_type", [nx.Graph, nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph]
+)
+def test_hashable_pydot(graph_type):
+    # gh-5790
+    G = graph_type()
+    G.add_edge("5", frozenset([1]), t='"Example:A"', l=False)
+    G.add_edge("1", 2, w=True, t=("node1",), l=frozenset(["node1"]))
+    G.add_edge("node", (3, 3), w="string")
+
+    assert [
+        {"t": '"Example:A"', "l": "False"},
+        {"w": "True", "t": "('node1',)", "l": "frozenset({'node1'})"},
+        {"w": "string"},
+    ] == [
+        attr
+        for _, _, attr in nx.nx_pydot.from_pydot(nx.nx_pydot.to_pydot(G)).edges.data()
+    ]
+
+    assert {str(i) for i in G.nodes()} == set(
+        nx.nx_pydot.from_pydot(nx.nx_pydot.to_pydot(G)).nodes
+    )
+
+
+def test_pydot_numerical_name():
+    G = nx.Graph()
+    G.add_edges_from([("A", "B"), (0, 1)])
+    graph_layout = nx.nx_pydot.pydot_layout(G, prog="dot")
+    assert isinstance(graph_layout, dict)
+    assert "0" not in graph_layout
+    assert 0 in graph_layout
+    assert "1" not in graph_layout
+    assert 1 in graph_layout
+    assert "A" in graph_layout
+    assert "B" in graph_layout