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1 files changed, 1756 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/networkx/drawing/tests/test_pylab.py b/.venv/lib/python3.12/site-packages/networkx/drawing/tests/test_pylab.py
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@@ -0,0 +1,1756 @@
+"""Unit tests for matplotlib drawing functions."""
+
+import itertools
+import os
+import warnings
+
+import pytest
+
+import networkx as nx
+
+mpl = pytest.importorskip("matplotlib")
+np = pytest.importorskip("numpy")
+mpl.use("PS")
+plt = pytest.importorskip("matplotlib.pyplot")
+plt.rcParams["text.usetex"] = False
+
+
+barbell = nx.barbell_graph(4, 6)
+
+defaults = {
+    "node_pos": None,
+    "node_visible": True,
+    "node_color": "#1f78b4",
+    "node_size": 300,
+    "node_label": {
+        "size": 12,
+        "color": "#000000",
+        "family": "sans-serif",
+        "weight": "normal",
+        "alpha": 1.0,
+        "background_color": None,
+        "background_alpha": None,
+        "h_align": "center",
+        "v_align": "center",
+        "bbox": None,
+    },
+    "node_shape": "o",
+    "node_alpha": 1.0,
+    "node_border_width": 1.0,
+    "node_border_color": "face",
+    "edge_visible": True,
+    "edge_width": 1.0,
+    "edge_color": "#000000",
+    "edge_label": {
+        "size": 12,
+        "color": "#000000",
+        "family": "sans-serif",
+        "weight": "normal",
+        "alpha": 1.0,
+        "bbox": {"boxstyle": "round", "ec": (1.0, 1.0, 1.0), "fc": (1.0, 1.0, 1.0)},
+        "h_align": "center",
+        "v_align": "center",
+        "pos": 0.5,
+        "rotate": True,
+    },
+    "edge_style": "-",
+    "edge_alpha": 1.0,
+    # These are for undirected-graphs. Directed graphs shouls use "-|>" and 10, respectively
+    "edge_arrowstyle": "-",
+    "edge_arrowsize": 0,
+    "edge_curvature": "arc3",
+    "edge_source_margin": 0,
+    "edge_target_margin": 0,
+}
+
+
+@pytest.mark.parametrize(
+    ("param_name", "param_value", "expected"),
+    (
+        ("node_color", None, defaults["node_color"]),
+        ("node_color", "#FF0000", "red"),
+        ("node_color", "color", "lime"),
+    ),
+)
+def test_display_arg_handling_node_color(param_name, param_value, expected):
+    G = nx.path_graph(4)
+    nx.set_node_attributes(G, "#00FF00", "color")
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas, **{param_name: param_value})
+    assert mpl.colors.same_color(canvas.get_children()[0].get_edgecolors()[0], expected)
+    plt.close()
+
+
+@pytest.mark.parametrize(
+    ("param_value", "expected"),
+    (
+        (None, (1, 1, 1, 1)),  # default value
+        (0.5, (0.5, 0.5, 0.5, 0.5)),
+        ("n_alpha", (1.0, 1 / 2, 1 / 3, 0.25)),
+    ),
+)
+def test_display_arg_handling_node_alpha(param_value, expected):
+    G = nx.path_graph(4)
+    nx.set_node_attributes(G, {n: 1 / (n + 1) for n in G.nodes()}, "n_alpha")
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas, node_alpha=param_value)
+    assert all(
+        canvas.get_children()[0].get_fc()[:, 3] == expected
+    )  # Extract just the alpha from the node colors
+    plt.close()
+
+
+def test_display_node_position():
+    G = nx.path_graph(4)
+    nx.set_node_attributes(G, {n: (n, n) for n in G.nodes()}, "pos")
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas, node_pos="pos")
+    assert np.all(
+        canvas.get_children()[0].get_offsets().data == [[0, 0], [1, 1], [2, 2], [3, 3]]
+    )
+    plt.close()
+
+
+@pytest.mark.mpl_image_compare
+def test_display_house_with_colors():
+    """
+    Originally, I wanted to use the exact samge image as test_house_with_colors.
+    But I can't seem to find the correct value for the margins to get the figures
+    to line up perfectly. To the human eye, these visualizations are basically the
+    same.
+    """
+    G = nx.house_graph()
+    fig, ax = plt.subplots()
+    nx.set_node_attributes(
+        G, {0: (0, 0), 1: (1, 0), 2: (0, 1), 3: (1, 1), 4: (0.5, 2.0)}, "pos"
+    )
+    nx.set_node_attributes(
+        G,
+        {
+            n: {
+                "size": 3000 if n != 4 else 2000,
+                "color": "tab:blue" if n != 4 else "tab:orange",
+            }
+            for n in G.nodes()
+        },
+    )
+    nx.display(
+        G,
+        node_pos="pos",
+        edge_alpha=0.5,
+        edge_width=6,
+        node_label=None,
+        node_border_color="k",
+    )
+    ax.margins(0.17)
+    plt.tight_layout()
+    plt.axis("off")
+    return fig
+
+
+def test_display_line_collection():
+    G = nx.karate_club_graph()
+    nx.set_edge_attributes(
+        G, {(u, v): "-|>" if (u + v) % 2 else "-" for u, v in G.edges()}, "arrowstyle"
+    )
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas, edge_arrowsize=10)
+    # There should only be one line collection in any given visualization
+    lc = [
+        l
+        for l in canvas.get_children()
+        if isinstance(l, mpl.collections.LineCollection)
+    ][0]
+    assert len(lc.get_paths()) == sum([1 for u, v in G.edges() if (u + v) % 2])
+    plt.close()
+
+
+@pytest.mark.mpl_image_compare
+def test_display_labels_and_colors():
+    """See 'Labels and Colors' gallery example"""
+    fig, ax = plt.subplots()
+    G = nx.cubical_graph()
+    pos = nx.spring_layout(G, seed=3113794652)  # positions for all nodes
+    nx.set_node_attributes(G, pos, "pos")  # Will not be needed after PR 7571
+    labels = iter(
+        [
+            r"$a$",
+            r"$b$",
+            r"$c$",
+            r"$d$",
+            r"$\alpha$",
+            r"$\beta$",
+            r"$\gamma$",
+            r"$\delta$",
+        ]
+    )
+    nx.set_node_attributes(
+        G,
+        {
+            n: {
+                "size": 800,
+                "alpha": 0.9,
+                "color": "tab:red" if n < 4 else "tab:blue",
+                "label": {"label": next(labels), "size": 22, "color": "whitesmoke"},
+            }
+            for n in G.nodes()
+        },
+    )
+
+    nx.display(G, node_pos="pos", edge_color="tab:grey")
+
+    # The tricky bit is the highlighted colors for the edges
+    edgelist = [(0, 1), (1, 2), (2, 3), (0, 3)]
+    nx.set_edge_attributes(
+        G,
+        {
+            (u, v): {
+                "width": 8,
+                "alpha": 0.5,
+                "color": "tab:red",
+                "visible": (u, v) in edgelist,
+            }
+            for u, v in G.edges()
+        },
+    )
+    nx.display(G, node_pos="pos", node_visible=False)
+    edgelist = [(4, 5), (5, 6), (6, 7), (4, 7)]
+    nx.set_edge_attributes(
+        G,
+        {
+            (u, v): {
+                "color": "tab:blue",
+                "visible": (u, v) in edgelist,
+            }
+            for u, v in G.edges()
+        },
+    )
+    nx.display(G, node_pos="pos", node_visible=False)
+
+    plt.tight_layout()
+    plt.axis("off")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_display_complex():
+    import itertools as it
+
+    fig, ax = plt.subplots()
+    G = nx.MultiDiGraph()
+    nodes = "ABC"
+    prod = list(it.product(nodes, repeat=2)) * 4
+    G = nx.MultiDiGraph()
+    for i, (u, v) in enumerate(prod):
+        G.add_edge(u, v, w=round(i / 3, 2))
+    nx.set_node_attributes(G, nx.spring_layout(G, seed=3113794652), "pos")
+    csi = it.cycle([f"arc3,rad={r}" for r in it.accumulate([0.15] * 4)])
+    nx.set_edge_attributes(G, {e: next(csi) for e in G.edges(keys=True)}, "curvature")
+    nx.set_edge_attributes(
+        G,
+        {
+            tuple(e): {"label": w, "bbox": {"alpha": 0}}
+            for *e, w in G.edges(keys=True, data="w")
+        },
+        "label",
+    )
+    nx.apply_matplotlib_colors(G, "w", "color", mpl.colormaps["inferno"], nodes=False)
+    nx.display(G, canvas=ax, node_pos="pos")
+
+    plt.tight_layout()
+    plt.axis("off")
+    return fig
+
+
+@pytest.mark.mpl_image_compare
+def test_display_shortest_path():
+    fig, ax = plt.subplots()
+    G = nx.Graph()
+    G.add_nodes_from(["A", "B", "C", "D", "E", "F", "G", "H"])
+    G.add_edge("A", "B", weight=4)
+    G.add_edge("A", "H", weight=8)
+    G.add_edge("B", "C", weight=8)
+    G.add_edge("B", "H", weight=11)
+    G.add_edge("C", "D", weight=7)
+    G.add_edge("C", "F", weight=4)
+    G.add_edge("C", "I", weight=2)
+    G.add_edge("D", "E", weight=9)
+    G.add_edge("D", "F", weight=14)
+    G.add_edge("E", "F", weight=10)
+    G.add_edge("F", "G", weight=2)
+    G.add_edge("G", "H", weight=1)
+    G.add_edge("G", "I", weight=6)
+    G.add_edge("H", "I", weight=7)
+
+    # Find the shortest path from node A to node E
+    path = nx.shortest_path(G, "A", "E", weight="weight")
+
+    # Create a list of edges in the shortest path
+    path_edges = list(zip(path, path[1:]))
+    nx.set_node_attributes(G, nx.spring_layout(G, seed=37), "pos")
+    nx.set_edge_attributes(
+        G,
+        {
+            (u, v): {
+                "color": (
+                    "red"
+                    if (u, v) in path_edges or tuple(reversed((u, v))) in path_edges
+                    else "black"
+                ),
+                "label": {"label": d["weight"], "rotate": False},
+            }
+            for u, v, d in G.edges(data=True)
+        },
+    )
+    nx.display(G, canvas=ax)
+    plt.tight_layout()
+    plt.axis("off")
+    return fig
+
+
+@pytest.mark.parametrize(
+    ("edge_color", "expected"),
+    (
+        (None, "black"),
+        ("r", "red"),
+        ((1.0, 1.0, 0.0), "yellow"),
+        ((0, 1, 0, 1), "lime"),
+        ("color", "blue"),
+        ("#0000FF", "blue"),
+    ),
+)
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_display_edge_single_color(edge_color, expected, graph_type):
+    G = nx.path_graph(3, create_using=graph_type)
+    nx.set_edge_attributes(G, "#0000FF", "color")
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, edge_color=edge_color, canvas=canvas)
+    if G.is_directed():
+        colors = [
+            f.get_fc()
+            for f in canvas.get_children()
+            if isinstance(f, mpl.patches.FancyArrowPatch)
+        ]
+    else:
+        colors = [
+            l
+            for l in canvas.collections
+            if isinstance(l, mpl.collections.LineCollection)
+        ][0].get_colors()
+    assert all(mpl.colors.same_color(c, expected) for c in colors)
+    plt.close()
+
+
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_display_edge_multiple_colors(graph_type):
+    G = nx.path_graph(3, create_using=graph_type)
+    nx.set_edge_attributes(G, {(0, 1): "#FF0000", (1, 2): (0, 0, 1)}, "color")
+    ax = plt.figure().add_subplot(111)
+    nx.display(G, canvas=ax)
+    expected = ["red", "blue"]
+    if G.is_directed():
+        colors = [
+            f.get_fc()
+            for f in ax.get_children()
+            if isinstance(f, mpl.patches.FancyArrowPatch)
+        ]
+    else:
+        colors = [
+            l for l in ax.collections if isinstance(l, mpl.collections.LineCollection)
+        ][0].get_colors()
+    assert mpl.colors.same_color(colors, expected)
+    plt.close()
+
+
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_display_edge_position(graph_type):
+    G = nx.path_graph(3, create_using=graph_type)
+    nx.set_node_attributes(G, {n: (n, n) for n in G.nodes()}, "pos")
+    ax = plt.figure().add_subplot(111)
+    nx.display(G, canvas=ax)
+    if G.is_directed():
+        end_points = [
+            (f.get_path().vertices[0, :], f.get_path().vertices[-2, :])
+            for f in ax.get_children()
+            if isinstance(f, mpl.patches.FancyArrowPatch)
+        ]
+    else:
+        line_collection = [
+            l for l in ax.collections if isinstance(l, mpl.collections.LineCollection)
+        ][0]
+        end_points = [
+            (p.vertices[0, :], p.vertices[-1, :]) for p in line_collection.get_paths()
+        ]
+    expected = [((0, 0), (1, 1)), ((1, 1), (2, 2))]
+    # Use the threshold to account for slight shifts in FancyArrowPatch margins to
+    # avoid covering the arrow head with the node.
+    threshold = 0.05
+    for a, e in zip(end_points, expected):
+        act_start, act_end = a
+        exp_start, exp_end = e
+        assert all(abs(act_start - exp_start) < (threshold, threshold)) and all(
+            abs(act_end - exp_end) < (threshold, threshold)
+        )
+    plt.close()
+
+
+def test_display_position_function():
+    G = nx.karate_club_graph()
+
+    def fixed_layout(G):
+        return nx.spring_layout(G, seed=314159)
+
+    pos = fixed_layout(G)
+    ax = plt.figure().add_subplot(111)
+    nx.display(G, node_pos=fixed_layout, canvas=ax)
+    # rebuild the position dictionary from the canvas
+    act_pos = {
+        n: tuple(p) for n, p in zip(G.nodes(), ax.get_children()[0].get_offsets().data)
+    }
+    for n in G.nodes():
+        assert all(pos[n] == act_pos[n])
+    plt.close()
+
+
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_display_edge_colormaps(graph_type):
+    G = nx.path_graph(3, create_using=graph_type)
+    nx.set_edge_attributes(G, {(0, 1): 0, (1, 2): 1}, "weight")
+    cmap = mpl.colormaps["plasma"]
+    nx.apply_matplotlib_colors(G, "weight", "color", cmap, nodes=False)
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas)
+    mapper = mpl.cm.ScalarMappable(cmap=cmap)
+    mapper.set_clim(0, 1)
+    expected = [mapper.to_rgba(0), mapper.to_rgba(1)]
+    if G.is_directed():
+        colors = [
+            f.get_facecolor()
+            for f in canvas.get_children()
+            if isinstance(f, mpl.patches.FancyArrowPatch)
+        ]
+    else:
+        colors = [
+            l
+            for l in canvas.collections
+            if isinstance(l, mpl.collections.LineCollection)
+        ][0].get_colors()
+    assert mpl.colors.same_color(expected[0], G.edges[0, 1]["color"])
+    assert mpl.colors.same_color(expected[1], G.edges[1, 2]["color"])
+    assert mpl.colors.same_color(expected, colors)
+    plt.close()
+
+
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_display_node_colormaps(graph_type):
+    G = nx.path_graph(3, create_using=graph_type)
+    nx.set_node_attributes(G, {0: 0, 1: 0.5, 2: 1}, "weight")
+    cmap = mpl.colormaps["plasma"]
+    nx.apply_matplotlib_colors(G, "weight", "color", cmap)
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas)
+    mapper = mpl.cm.ScalarMappable(cmap=cmap)
+    mapper.set_clim(0, 1)
+    expected = [mapper.to_rgba(0), mapper.to_rgba(0.5), mapper.to_rgba(1)]
+    colors = [
+        s for s in canvas.collections if isinstance(s, mpl.collections.PathCollection)
+    ][0].get_edgecolors()
+    assert mpl.colors.same_color(expected[0], G.nodes[0]["color"])
+    assert mpl.colors.same_color(expected[1], G.nodes[1]["color"])
+    assert mpl.colors.same_color(expected[2], G.nodes[2]["color"])
+    assert mpl.colors.same_color(expected, colors)
+    plt.close()
+
+
+@pytest.mark.parametrize(
+    ("param_value", "expected"),
+    (
+        (None, [defaults["edge_width"], defaults["edge_width"]]),
+        (5, [5, 5]),
+        ("width", [5, 10]),
+    ),
+)
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_display_edge_width(param_value, expected, graph_type):
+    G = nx.path_graph(3, create_using=graph_type)
+    nx.set_edge_attributes(G, {(0, 1): 5, (1, 2): 10}, "width")
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, edge_width=param_value, canvas=canvas)
+    if G.is_directed():
+        widths = [
+            f.get_linewidth()
+            for f in canvas.get_children()
+            if isinstance(f, mpl.patches.FancyArrowPatch)
+        ]
+    else:
+        widths = list(
+            [
+                l
+                for l in canvas.collections
+                if isinstance(l, mpl.collections.LineCollection)
+            ][0].get_linewidths()
+        )
+    assert widths == expected
+
+
+@pytest.mark.parametrize(
+    ("param_value", "expected"),
+    (
+        (None, [defaults["edge_style"], defaults["edge_style"]]),
+        (":", [":", ":"]),
+        ("style", ["-", ":"]),
+    ),
+)
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_display_edge_style(param_value, expected, graph_type):
+    G = nx.path_graph(3, create_using=graph_type)
+    nx.set_edge_attributes(G, {(0, 1): "-", (1, 2): ":"}, "style")
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, edge_style=param_value, canvas=canvas)
+    if G.is_directed():
+        styles = [
+            f.get_linestyle()
+            for f in canvas.get_children()
+            if isinstance(f, mpl.patches.FancyArrowPatch)
+        ]
+    else:
+        # Convert back from tuple description to character form
+        linestyles = {(0, None): "-", (0, (1, 1.65)): ":"}
+        styles = [
+            linestyles[(s[0], tuple(s[1]) if s[1] is not None else None)]
+            for s in [
+                l
+                for l in canvas.collections
+                if isinstance(l, mpl.collections.LineCollection)
+            ][0].get_linestyles()
+        ]
+    assert styles == expected
+    plt.close()
+
+
+def test_display_node_labels():
+    G = nx.path_graph(4)
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas, node_label={"size": 20})
+    labels = [t for t in canvas.get_children() if isinstance(t, mpl.text.Text)]
+    for n, l in zip(G.nodes(), labels):
+        assert l.get_text() == str(n)
+        assert l.get_size() == 20.0
+    plt.close()
+
+
+def test_display_edge_labels():
+    G = nx.path_graph(4)
+    canvas = plt.figure().add_subplot(111)
+    # While we can pass in dicts for edge label defaults without errors,
+    # this isn't helpful unless we want one label for all edges.
+    nx.set_edge_attributes(G, {(u, v): {"label": u + v} for u, v in G.edges()})
+    nx.display(G, canvas=canvas, edge_label={"color": "r"}, node_label=None)
+    labels = [t for t in canvas.get_children() if isinstance(t, mpl.text.Text)]
+    print(labels)
+    for e, l in zip(G.edges(), labels):
+        assert l.get_text() == str(e[0] + e[1])
+        assert l.get_color() == "r"
+    plt.close()
+
+
+@pytest.mark.mpl_image_compare
+def test_display_empty_graph():
+    G = nx.empty_graph()
+    fig, ax = plt.subplots()
+    nx.display(G, canvas=ax)
+    plt.tight_layout()
+    plt.axis("off")
+    return fig
+
+
+def test_display_multigraph_non_integer_keys():
+    G = nx.MultiGraph()
+    G.add_nodes_from(["A", "B", "C", "D"])
+    G.add_edges_from(
+        [
+            ("A", "B", "0"),
+            ("A", "B", "1"),
+            ("B", "C", "-1"),
+            ("B", "C", "1"),
+            ("C", "D", "-1"),
+            ("C", "D", "0"),
+        ]
+    )
+    nx.set_edge_attributes(
+        G, {e: f"arc3,rad={0.2 * int(e[2])}" for e in G.edges(keys=True)}, "curvature"
+    )
+    canvas = plt.figure().add_subplot(111)
+    nx.display(G, canvas=canvas)
+    rads = [
+        f.get_connectionstyle().rad
+        for f in canvas.get_children()
+        if isinstance(f, mpl.patches.FancyArrowPatch)
+    ]
+    assert rads == [0.0, 0.2, -0.2, 0.2, -0.2, 0.0]
+    plt.close()
+
+
+def test_display_raises_for_bad_arg():
+    G = nx.karate_club_graph()
+    with pytest.raises(nx.NetworkXError):
+        nx.display(G, bad_arg="bad_arg")
+        plt.close()
+
+
+def test_display_arrow_size():
+    G = nx.path_graph(4, create_using=nx.DiGraph)
+    nx.set_edge_attributes(
+        G, {(u, v): (u + v + 2) ** 2 for u, v in G.edges()}, "arrowsize"
+    )
+    ax = plt.axes()
+    nx.display(G, canvas=ax)
+    assert [9, 25, 49] == [
+        f.get_mutation_scale()
+        for f in ax.get_children()
+        if isinstance(f, mpl.patches.FancyArrowPatch)
+    ]
+    plt.close()
+
+
+def test_display_mismatched_edge_position():
+    """
+    This test ensures that a error is raised for incomplete position data.
+    """
+    G = nx.path_graph(5)
+    # Notice that there is no position for node 3
+    nx.set_node_attributes(G, {0: (0, 0), 1: (1, 1), 2: (2, 2), 4: (4, 4)}, "pos")
+    # But that's not a problem since we don't want to show node 4, right?
+    nx.set_node_attributes(G, {n: n < 4 for n in G.nodes()}, "visible")
+    # However, if we try to visualize every edge (including 3 -> 4)...
+    # That's a problem since node 4 doesn't have a position
+    with pytest.raises(nx.NetworkXError):
+        nx.display(G)
+
+
+# NOTE: parametrizing on marker to test both branches of internal
+# to_marker_edge function
+@pytest.mark.parametrize("node_shape", ("o", "s"))
+def test_display_edge_margins(node_shape):
+    """
+    Test that there is a wider gap between the node and the start of an
+    incident edge when min_source_margin is specified.
+
+    This test checks that the use os min_{source/target}_margin edge
+    attributes result is shorter (more padding) between the edges and
+    source and target nodes.
+
+
+    As a crude visual example, let 's' and 't' represent source and target
+    nodes, respectively:
+
+       Default:
+       s-----------------------------t
+
+       With margins:
+       s   -----------------------   t
+
+    """
+    ax = plt.figure().add_subplot(111)
+    G = nx.DiGraph([(0, 1)])
+    nx.set_node_attributes(G, {0: (0, 0), 1: (1, 1)}, "pos")
+    # Get the default patches from the regular visualization
+    nx.display(G, canvas=ax, node_shape=node_shape)
+    default_arrow = [
+        f for f in ax.get_children() if isinstance(f, mpl.patches.FancyArrowPatch)
+    ][0]
+    default_extent = default_arrow.get_extents().corners()[::2, 0]
+    # Now plot again with margins
+    ax = plt.figure().add_subplot(111)
+    nx.display(
+        G,
+        canvas=ax,
+        edge_source_margin=100,
+        edge_target_margin=100,
+        node_shape=node_shape,
+    )
+    padded_arrow = [
+        f for f in ax.get_children() if isinstance(f, mpl.patches.FancyArrowPatch)
+    ][0]
+    padded_extent = padded_arrow.get_extents().corners()[::2, 0]
+
+    # With padding, the left-most extent of the edge should be further to the right
+    assert padded_extent[0] > default_extent[0]
+    # And the rightmost extent of the edge, further to the left
+    assert padded_extent[1] < default_extent[1]
+    plt.close()
+
+
+@pytest.mark.parametrize("ticks", [False, True])
+def test_display_hide_ticks(ticks):
+    G = nx.path_graph(3)
+    nx.set_node_attributes(G, {n: (n, n) for n in G.nodes()}, "pos")
+    ax = plt.axes()
+    nx.display(G, hide_ticks=ticks)
+    for axis in [ax.xaxis, ax.yaxis]:
+        assert bool(axis.get_ticklabels()) != ticks
+
+    plt.close()
+
+
+def test_display_self_loop():
+    ax = plt.axes()
+    G = nx.DiGraph()
+    G.add_node(0)
+    G.add_edge(0, 0)
+    nx.set_node_attributes(G, {0: (0, 0)}, "pos")
+    nx.display(G, canvas=ax)
+    arrow = [
+        f for f in ax.get_children() if isinstance(f, mpl.patches.FancyArrowPatch)
+    ][0]
+    bbox = arrow.get_extents()
+    print(bbox.width)
+    print(bbox.height)
+    assert bbox.width > 0 and bbox.height > 0
+
+    plt.delaxes(ax)
+    plt.close()
+
+
+def test_display_remove_pos_attr():
+    """
+    If the pos attribute isn't provided or is a function, display computes the layout
+    and adds it to the graph. We need to ensure that this new attribute is removed from
+    the returned graph.
+    """
+    G = nx.karate_club_graph()
+    nx.display(G)
+    assert nx.get_node_attributes(G, "display's position attribute name") == {}
+
+
+@pytest.fixture
+def subplots():
+    fig, ax = plt.subplots()
+    yield fig, ax
+    plt.delaxes(ax)
+    plt.close()
+
+
+def test_draw():
+    try:
+        functions = [
+            nx.draw_circular,
+            nx.draw_kamada_kawai,
+            nx.draw_planar,
+            nx.draw_random,
+            nx.draw_spectral,
+            nx.draw_spring,
+            nx.draw_shell,
+        ]
+        options = [{"node_color": "black", "node_size": 100, "width": 3}]
+        for function, option in itertools.product(functions, options):
+            function(barbell, **option)
+            plt.savefig("test.ps")
+    except ModuleNotFoundError:  # draw_kamada_kawai requires scipy
+        pass
+    finally:
+        try:
+            os.unlink("test.ps")
+        except OSError:
+            pass
+
+
+def test_draw_shell_nlist():
+    try:
+        nlist = [list(range(4)), list(range(4, 10)), list(range(10, 14))]
+        nx.draw_shell(barbell, nlist=nlist)
+        plt.savefig("test.ps")
+    finally:
+        try:
+            os.unlink("test.ps")
+        except OSError:
+            pass
+
+
+def test_draw_bipartite():
+    try:
+        G = nx.complete_bipartite_graph(2, 5)
+        nx.draw_bipartite(G)
+        plt.savefig("test.ps")
+    finally:
+        try:
+            os.unlink("test.ps")
+        except OSError:
+            pass
+
+
+def test_edge_colormap():
+    colors = range(barbell.number_of_edges())
+    nx.draw_spring(
+        barbell, edge_color=colors, width=4, edge_cmap=plt.cm.Blues, with_labels=True
+    )
+    # plt.show()
+
+
+def test_arrows():
+    nx.draw_spring(barbell.to_directed())
+    # plt.show()
+
+
+@pytest.mark.parametrize(
+    ("edge_color", "expected"),
+    (
+        (None, "black"),  # Default
+        ("r", "red"),  # Non-default color string
+        (["r"], "red"),  # Single non-default color in a list
+        ((1.0, 1.0, 0.0), "yellow"),  # single color as rgb tuple
+        ([(1.0, 1.0, 0.0)], "yellow"),  # single color as rgb tuple in list
+        ((0, 1, 0, 1), "lime"),  # single color as rgba tuple
+        ([(0, 1, 0, 1)], "lime"),  # single color as rgba tuple in list
+        ("#0000ff", "blue"),  # single color hex code
+        (["#0000ff"], "blue"),  # hex code in list
+    ),
+)
+@pytest.mark.parametrize("edgelist", (None, [(0, 1)]))
+def test_single_edge_color_undirected(edge_color, expected, edgelist):
+    """Tests ways of specifying all edges have a single color for edges
+    drawn with a LineCollection"""
+
+    G = nx.path_graph(3)
+    drawn_edges = nx.draw_networkx_edges(
+        G, pos=nx.random_layout(G), edgelist=edgelist, edge_color=edge_color
+    )
+    assert mpl.colors.same_color(drawn_edges.get_color(), expected)
+
+
+@pytest.mark.parametrize(
+    ("edge_color", "expected"),
+    (
+        (None, "black"),  # Default
+        ("r", "red"),  # Non-default color string
+        (["r"], "red"),  # Single non-default color in a list
+        ((1.0, 1.0, 0.0), "yellow"),  # single color as rgb tuple
+        ([(1.0, 1.0, 0.0)], "yellow"),  # single color as rgb tuple in list
+        ((0, 1, 0, 1), "lime"),  # single color as rgba tuple
+        ([(0, 1, 0, 1)], "lime"),  # single color as rgba tuple in list
+        ("#0000ff", "blue"),  # single color hex code
+        (["#0000ff"], "blue"),  # hex code in list
+    ),
+)
+@pytest.mark.parametrize("edgelist", (None, [(0, 1)]))
+def test_single_edge_color_directed(edge_color, expected, edgelist):
+    """Tests ways of specifying all edges have a single color for edges drawn
+    with FancyArrowPatches"""
+
+    G = nx.path_graph(3, create_using=nx.DiGraph)
+    drawn_edges = nx.draw_networkx_edges(
+        G, pos=nx.random_layout(G), edgelist=edgelist, edge_color=edge_color
+    )
+    for fap in drawn_edges:
+        assert mpl.colors.same_color(fap.get_edgecolor(), expected)
+
+
+def test_edge_color_tuple_interpretation():
+    """If edge_color is a sequence with the same length as edgelist, then each
+    value in edge_color is mapped onto each edge via colormap."""
+    G = nx.path_graph(6, create_using=nx.DiGraph)
+    pos = {n: (n, n) for n in range(len(G))}
+
+    # num edges != 3 or 4 --> edge_color interpreted as rgb(a)
+    for ec in ((0, 0, 1), (0, 0, 1, 1)):
+        # More than 4 edges
+        drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=ec)
+        for fap in drawn_edges:
+            assert mpl.colors.same_color(fap.get_edgecolor(), ec)
+        # Fewer than 3 edges
+        drawn_edges = nx.draw_networkx_edges(
+            G, pos, edgelist=[(0, 1), (1, 2)], edge_color=ec
+        )
+        for fap in drawn_edges:
+            assert mpl.colors.same_color(fap.get_edgecolor(), ec)
+
+    # num edges == 3, len(edge_color) == 4: interpreted as rgba
+    drawn_edges = nx.draw_networkx_edges(
+        G, pos, edgelist=[(0, 1), (1, 2), (2, 3)], edge_color=(0, 0, 1, 1)
+    )
+    for fap in drawn_edges:
+        assert mpl.colors.same_color(fap.get_edgecolor(), "blue")
+
+    # num edges == 4, len(edge_color) == 3: interpreted as rgb
+    drawn_edges = nx.draw_networkx_edges(
+        G, pos, edgelist=[(0, 1), (1, 2), (2, 3), (3, 4)], edge_color=(0, 0, 1)
+    )
+    for fap in drawn_edges:
+        assert mpl.colors.same_color(fap.get_edgecolor(), "blue")
+
+    # num edges == len(edge_color) == 3: interpreted with cmap, *not* as rgb
+    drawn_edges = nx.draw_networkx_edges(
+        G, pos, edgelist=[(0, 1), (1, 2), (2, 3)], edge_color=(0, 0, 1)
+    )
+    assert mpl.colors.same_color(
+        drawn_edges[0].get_edgecolor(), drawn_edges[1].get_edgecolor()
+    )
+    for fap in drawn_edges:
+        assert not mpl.colors.same_color(fap.get_edgecolor(), "blue")
+
+    # num edges == len(edge_color) == 4: interpreted with cmap, *not* as rgba
+    drawn_edges = nx.draw_networkx_edges(
+        G, pos, edgelist=[(0, 1), (1, 2), (2, 3), (3, 4)], edge_color=(0, 0, 1, 1)
+    )
+    assert mpl.colors.same_color(
+        drawn_edges[0].get_edgecolor(), drawn_edges[1].get_edgecolor()
+    )
+    assert mpl.colors.same_color(
+        drawn_edges[2].get_edgecolor(), drawn_edges[3].get_edgecolor()
+    )
+    for fap in drawn_edges:
+        assert not mpl.colors.same_color(fap.get_edgecolor(), "blue")
+
+
+def test_fewer_edge_colors_than_num_edges_directed():
+    """Test that the edge colors are cycled when there are fewer specified
+    colors than edges."""
+    G = barbell.to_directed()
+    pos = nx.random_layout(barbell)
+    edgecolors = ("r", "g", "b")
+    drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=edgecolors)
+    for fap, expected in zip(drawn_edges, itertools.cycle(edgecolors)):
+        assert mpl.colors.same_color(fap.get_edgecolor(), expected)
+
+
+def test_more_edge_colors_than_num_edges_directed():
+    """Test that extra edge colors are ignored when there are more specified
+    colors than edges."""
+    G = nx.path_graph(4, create_using=nx.DiGraph)  # 3 edges
+    pos = nx.random_layout(barbell)
+    edgecolors = ("r", "g", "b", "c")  # 4 edge colors
+    drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=edgecolors)
+    for fap, expected in zip(drawn_edges, edgecolors[:-1]):
+        assert mpl.colors.same_color(fap.get_edgecolor(), expected)
+
+
+def test_edge_color_string_with_global_alpha_undirected():
+    edge_collection = nx.draw_networkx_edges(
+        barbell,
+        pos=nx.random_layout(barbell),
+        edgelist=[(0, 1), (1, 2)],
+        edge_color="purple",
+        alpha=0.2,
+    )
+    ec = edge_collection.get_color().squeeze()  # as rgba tuple
+    assert len(edge_collection.get_paths()) == 2
+    assert mpl.colors.same_color(ec[:-1], "purple")
+    assert ec[-1] == 0.2
+
+
+def test_edge_color_string_with_global_alpha_directed():
+    drawn_edges = nx.draw_networkx_edges(
+        barbell.to_directed(),
+        pos=nx.random_layout(barbell),
+        edgelist=[(0, 1), (1, 2)],
+        edge_color="purple",
+        alpha=0.2,
+    )
+    assert len(drawn_edges) == 2
+    for fap in drawn_edges:
+        ec = fap.get_edgecolor()  # As rgba tuple
+        assert mpl.colors.same_color(ec[:-1], "purple")
+        assert ec[-1] == 0.2
+
+
+@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
+def test_edge_width_default_value(graph_type):
+    """Test the default linewidth for edges drawn either via LineCollection or
+    FancyArrowPatches."""
+    G = nx.path_graph(2, create_using=graph_type)
+    pos = {n: (n, n) for n in range(len(G))}
+    drawn_edges = nx.draw_networkx_edges(G, pos)
+    if isinstance(drawn_edges, list):  # directed case: list of FancyArrowPatch
+        drawn_edges = drawn_edges[0]
+    assert drawn_edges.get_linewidth() == 1
+
+
+@pytest.mark.parametrize(
+    ("edgewidth", "expected"),
+    (
+        (3, 3),  # single-value, non-default
+        ([3], 3),  # Single value as a list
+    ),
+)
+def test_edge_width_single_value_undirected(edgewidth, expected):
+    G = nx.path_graph(4)
+    pos = {n: (n, n) for n in range(len(G))}
+    drawn_edges = nx.draw_networkx_edges(G, pos, width=edgewidth)
+    assert len(drawn_edges.get_paths()) == 3
+    assert drawn_edges.get_linewidth() == expected
+
+
+@pytest.mark.parametrize(
+    ("edgewidth", "expected"),
+    (
+        (3, 3),  # single-value, non-default
+        ([3], 3),  # Single value as a list
+    ),
+)
+def test_edge_width_single_value_directed(edgewidth, expected):
+    G = nx.path_graph(4, create_using=nx.DiGraph)
+    pos = {n: (n, n) for n in range(len(G))}
+    drawn_edges = nx.draw_networkx_edges(G, pos, width=edgewidth)
+    assert len(drawn_edges) == 3
+    for fap in drawn_edges:
+        assert fap.get_linewidth() == expected
+
+
+@pytest.mark.parametrize(
+    "edgelist",
+    (
+        [(0, 1), (1, 2), (2, 3)],  # one width specification per edge
+        None,  #  fewer widths than edges - widths cycle
+        [(0, 1), (1, 2)],  # More widths than edges - unused widths ignored
+    ),
+)
+def test_edge_width_sequence(edgelist):
+    G = barbell.to_directed()
+    pos = nx.random_layout(G)
+    widths = (0.5, 2.0, 12.0)
+    drawn_edges = nx.draw_networkx_edges(G, pos, edgelist=edgelist, width=widths)
+    for fap, expected_width in zip(drawn_edges, itertools.cycle(widths)):
+        assert fap.get_linewidth() == expected_width
+
+
+def test_edge_color_with_edge_vmin_vmax():
+    """Test that edge_vmin and edge_vmax properly set the dynamic range of the
+    color map when num edges == len(edge_colors)."""
+    G = nx.path_graph(3, create_using=nx.DiGraph)
+    pos = nx.random_layout(G)
+    # Extract colors from the original (unscaled) colormap
+    drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=[0, 1.0])
+    orig_colors = [e.get_edgecolor() for e in drawn_edges]
+    # Colors from scaled colormap
+    drawn_edges = nx.draw_networkx_edges(
+        G, pos, edge_color=[0.2, 0.8], edge_vmin=0.2, edge_vmax=0.8
+    )
+    scaled_colors = [e.get_edgecolor() for e in drawn_edges]
+    assert mpl.colors.same_color(orig_colors, scaled_colors)
+
+
+def test_directed_edges_linestyle_default():
+    """Test default linestyle for edges drawn with FancyArrowPatches."""
+    G = nx.path_graph(4, create_using=nx.DiGraph)  # Graph with 3 edges
+    pos = {n: (n, n) for n in range(len(G))}
+
+    # edge with default style
+    drawn_edges = nx.draw_networkx_edges(G, pos)
+    assert len(drawn_edges) == 3
+    for fap in drawn_edges:
+        assert fap.get_linestyle() == "solid"
+
+
+@pytest.mark.parametrize(
+    "style",
+    (
+        "dashed",  # edge with string style
+        "--",  # edge with simplified string style
+        (1, (1, 1)),  # edge with (offset, onoffseq) style
+    ),
+)
+def test_directed_edges_linestyle_single_value(style):
+    """Tests support for specifying linestyles with a single value to be applied to
+    all edges in ``draw_networkx_edges`` for FancyArrowPatch outputs
+    (e.g. directed edges)."""
+
+    G = nx.path_graph(4, create_using=nx.DiGraph)  # Graph with 3 edges
+    pos = {n: (n, n) for n in range(len(G))}
+
+    drawn_edges = nx.draw_networkx_edges(G, pos, style=style)
+    assert len(drawn_edges) == 3
+    for fap in drawn_edges:
+        assert fap.get_linestyle() == style
+
+
+@pytest.mark.parametrize(
+    "style_seq",
+    (
+        ["dashed"],  # edge with string style in list
+        ["--"],  # edge with simplified string style in list
+        [(1, (1, 1))],  # edge with (offset, onoffseq) style in list
+        ["--", "-", ":"],  # edges with styles for each edge
+        ["--", "-"],  # edges with fewer styles than edges (styles cycle)
+        ["--", "-", ":", "-."],  # edges with more styles than edges (extra unused)
+    ),
+)
+def test_directed_edges_linestyle_sequence(style_seq):
+    """Tests support for specifying linestyles with sequences in
+    ``draw_networkx_edges`` for FancyArrowPatch outputs (e.g. directed edges)."""
+
+    G = nx.path_graph(4, create_using=nx.DiGraph)  # Graph with 3 edges
+    pos = {n: (n, n) for n in range(len(G))}
+
+    drawn_edges = nx.draw_networkx_edges(G, pos, style=style_seq)
+    assert len(drawn_edges) == 3
+    for fap, style in zip(drawn_edges, itertools.cycle(style_seq)):
+        assert fap.get_linestyle() == style
+
+
+def test_return_types():
+    from matplotlib.collections import LineCollection, PathCollection
+    from matplotlib.patches import FancyArrowPatch
+
+    G = nx.frucht_graph(create_using=nx.Graph)
+    dG = nx.frucht_graph(create_using=nx.DiGraph)
+    pos = nx.spring_layout(G)
+    dpos = nx.spring_layout(dG)
+    # nodes
+    nodes = nx.draw_networkx_nodes(G, pos)
+    assert isinstance(nodes, PathCollection)
+    # edges
+    edges = nx.draw_networkx_edges(dG, dpos, arrows=True)
+    assert isinstance(edges, list)
+    if len(edges) > 0:
+        assert isinstance(edges[0], FancyArrowPatch)
+    edges = nx.draw_networkx_edges(dG, dpos, arrows=False)
+    assert isinstance(edges, LineCollection)
+    edges = nx.draw_networkx_edges(G, dpos, arrows=None)
+    assert isinstance(edges, LineCollection)
+    edges = nx.draw_networkx_edges(dG, pos, arrows=None)
+    assert isinstance(edges, list)
+    if len(edges) > 0:
+        assert isinstance(edges[0], FancyArrowPatch)
+
+
+def test_labels_and_colors():
+    G = nx.cubical_graph()
+    pos = nx.spring_layout(G)  # positions for all nodes
+    # nodes
+    nx.draw_networkx_nodes(
+        G, pos, nodelist=[0, 1, 2, 3], node_color="r", node_size=500, alpha=0.75
+    )
+    nx.draw_networkx_nodes(
+        G,
+        pos,
+        nodelist=[4, 5, 6, 7],
+        node_color="b",
+        node_size=500,
+        alpha=[0.25, 0.5, 0.75, 1.0],
+    )
+    # edges
+    nx.draw_networkx_edges(G, pos, width=1.0, alpha=0.5)
+    nx.draw_networkx_edges(
+        G,
+        pos,
+        edgelist=[(0, 1), (1, 2), (2, 3), (3, 0)],
+        width=8,
+        alpha=0.5,
+        edge_color="r",
+    )
+    nx.draw_networkx_edges(
+        G,
+        pos,
+        edgelist=[(4, 5), (5, 6), (6, 7), (7, 4)],
+        width=8,
+        alpha=0.5,
+        edge_color="b",
+    )
+    nx.draw_networkx_edges(
+        G,
+        pos,
+        edgelist=[(4, 5), (5, 6), (6, 7), (7, 4)],
+        arrows=True,
+        min_source_margin=0.5,
+        min_target_margin=0.75,
+        width=8,
+        edge_color="b",
+    )
+    # some math labels
+    labels = {}
+    labels[0] = r"$a$"
+    labels[1] = r"$b$"
+    labels[2] = r"$c$"
+    labels[3] = r"$d$"
+    labels[4] = r"$\alpha$"
+    labels[5] = r"$\beta$"
+    labels[6] = r"$\gamma$"
+    labels[7] = r"$\delta$"
+    colors = {n: "k" if n % 2 == 0 else "r" for n in range(8)}
+    nx.draw_networkx_labels(G, pos, labels, font_size=16)
+    nx.draw_networkx_labels(G, pos, labels, font_size=16, font_color=colors)
+    nx.draw_networkx_edge_labels(G, pos, edge_labels=None, rotate=False)
+    nx.draw_networkx_edge_labels(G, pos, edge_labels={(4, 5): "4-5"})
+    # plt.show()
+
+
+@pytest.mark.mpl_image_compare
+def test_house_with_colors():
+    G = nx.house_graph()
+    # explicitly set positions
+    fig, ax = plt.subplots()
+    pos = {0: (0, 0), 1: (1, 0), 2: (0, 1), 3: (1, 1), 4: (0.5, 2.0)}
+
+    # Plot nodes with different properties for the "wall" and "roof" nodes
+    nx.draw_networkx_nodes(
+        G,
+        pos,
+        node_size=3000,
+        nodelist=[0, 1, 2, 3],
+        node_color="tab:blue",
+    )
+    nx.draw_networkx_nodes(
+        G, pos, node_size=2000, nodelist=[4], node_color="tab:orange"
+    )
+    nx.draw_networkx_edges(G, pos, alpha=0.5, width=6)
+    # Customize axes
+    ax.margins(0.11)
+    plt.tight_layout()
+    plt.axis("off")
+    return fig
+
+
+def test_axes(subplots):
+    fig, ax = subplots
+    nx.draw(barbell, ax=ax)
+    nx.draw_networkx_edge_labels(barbell, nx.circular_layout(barbell), ax=ax)
+
+
+def test_empty_graph():
+    G = nx.Graph()
+    nx.draw(G)
+
+
+def test_draw_empty_nodes_return_values():
+    # See Issue #3833
+    import matplotlib.collections  # call as mpl.collections
+
+    G = nx.Graph([(1, 2), (2, 3)])
+    DG = nx.DiGraph([(1, 2), (2, 3)])
+    pos = nx.circular_layout(G)
+    assert isinstance(
+        nx.draw_networkx_nodes(G, pos, nodelist=[]), mpl.collections.PathCollection
+    )
+    assert isinstance(
+        nx.draw_networkx_nodes(DG, pos, nodelist=[]), mpl.collections.PathCollection
+    )
+
+    # drawing empty edges used to return an empty LineCollection or empty list.
+    # Now it is always an empty list (because edges are now lists of FancyArrows)
+    assert nx.draw_networkx_edges(G, pos, edgelist=[], arrows=True) == []
+    assert nx.draw_networkx_edges(G, pos, edgelist=[], arrows=False) == []
+    assert nx.draw_networkx_edges(DG, pos, edgelist=[], arrows=False) == []
+    assert nx.draw_networkx_edges(DG, pos, edgelist=[], arrows=True) == []
+
+
+def test_multigraph_edgelist_tuples():
+    # See Issue #3295
+    G = nx.path_graph(3, create_using=nx.MultiDiGraph)
+    nx.draw_networkx(G, edgelist=[(0, 1, 0)])
+    nx.draw_networkx(G, edgelist=[(0, 1, 0)], node_size=[10, 20, 0])
+
+
+def test_alpha_iter():
+    pos = nx.random_layout(barbell)
+    fig = plt.figure()
+    # with fewer alpha elements than nodes
+    fig.add_subplot(131)  # Each test in a new axis object
+    nx.draw_networkx_nodes(barbell, pos, alpha=[0.1, 0.2])
+    # with equal alpha elements and nodes
+    num_nodes = len(barbell.nodes)
+    alpha = [x / num_nodes for x in range(num_nodes)]
+    colors = range(num_nodes)
+    fig.add_subplot(132)
+    nx.draw_networkx_nodes(barbell, pos, node_color=colors, alpha=alpha)
+    # with more alpha elements than nodes
+    alpha.append(1)
+    fig.add_subplot(133)
+    nx.draw_networkx_nodes(barbell, pos, alpha=alpha)
+
+
+def test_multiple_node_shapes(subplots):
+    fig, ax = subplots
+    G = nx.path_graph(4)
+    nx.draw(G, node_shape=["o", "h", "s", "^"], ax=ax)
+    scatters = [
+        s for s in ax.get_children() if isinstance(s, mpl.collections.PathCollection)
+    ]
+    assert len(scatters) == 4
+
+
+def test_individualized_font_attributes(subplots):
+    G = nx.karate_club_graph()
+    fig, ax = subplots
+    nx.draw(
+        G,
+        ax=ax,
+        font_color={n: "k" if n % 2 else "r" for n in G.nodes()},
+        font_size={n: int(n / (34 / 15) + 5) for n in G.nodes()},
+    )
+    for n, t in zip(
+        G.nodes(),
+        [
+            t
+            for t in ax.get_children()
+            if isinstance(t, mpl.text.Text) and len(t.get_text()) > 0
+        ],
+    ):
+        expected = "black" if n % 2 else "red"
+
+        assert mpl.colors.same_color(t.get_color(), expected)
+        assert int(n / (34 / 15) + 5) == t.get_size()
+
+
+def test_individualized_edge_attributes(subplots):
+    G = nx.karate_club_graph()
+    fig, ax = subplots
+    arrowstyles = ["-|>" if (u + v) % 2 == 0 else "-[" for u, v in G.edges()]
+    arrowsizes = [10 * (u % 2 + v % 2) + 10 for u, v in G.edges()]
+    nx.draw(G, ax=ax, arrows=True, arrowstyle=arrowstyles, arrowsize=arrowsizes)
+    arrows = [
+        f for f in ax.get_children() if isinstance(f, mpl.patches.FancyArrowPatch)
+    ]
+    for e, a in zip(G.edges(), arrows):
+        assert a.get_mutation_scale() == 10 * (e[0] % 2 + e[1] % 2) + 10
+        expected = (
+            mpl.patches.ArrowStyle.BracketB
+            if sum(e) % 2
+            else mpl.patches.ArrowStyle.CurveFilledB
+        )
+        assert isinstance(a.get_arrowstyle(), expected)
+
+
+def test_error_invalid_kwds():
+    with pytest.raises(ValueError, match="Received invalid argument"):
+        nx.draw(barbell, foo="bar")
+
+
+def test_draw_networkx_arrowsize_incorrect_size():
+    G = nx.DiGraph([(0, 1), (0, 2), (0, 3), (1, 3)])
+    arrowsize = [1, 2, 3]
+    with pytest.raises(
+        ValueError, match="arrowsize should have the same length as edgelist"
+    ):
+        nx.draw(G, arrowsize=arrowsize)
+
+
+@pytest.mark.parametrize("arrowsize", (30, [10, 20, 30]))
+def test_draw_edges_arrowsize(arrowsize):
+    G = nx.DiGraph([(0, 1), (0, 2), (1, 2)])
+    pos = {0: (0, 0), 1: (0, 1), 2: (1, 0)}
+    edges = nx.draw_networkx_edges(G, pos=pos, arrowsize=arrowsize)
+
+    arrowsize = itertools.repeat(arrowsize) if isinstance(arrowsize, int) else arrowsize
+
+    for fap, expected in zip(edges, arrowsize):
+        assert isinstance(fap, mpl.patches.FancyArrowPatch)
+        assert fap.get_mutation_scale() == expected
+
+
+@pytest.mark.parametrize("arrowstyle", ("-|>", ["-|>", "-[", "<|-|>"]))
+def test_draw_edges_arrowstyle(arrowstyle):
+    G = nx.DiGraph([(0, 1), (0, 2), (1, 2)])
+    pos = {0: (0, 0), 1: (0, 1), 2: (1, 0)}
+    edges = nx.draw_networkx_edges(G, pos=pos, arrowstyle=arrowstyle)
+
+    arrowstyle = (
+        itertools.repeat(arrowstyle) if isinstance(arrowstyle, str) else arrowstyle
+    )
+
+    arrow_objects = {
+        "-|>": mpl.patches.ArrowStyle.CurveFilledB,
+        "-[": mpl.patches.ArrowStyle.BracketB,
+        "<|-|>": mpl.patches.ArrowStyle.CurveFilledAB,
+    }
+
+    for fap, expected in zip(edges, arrowstyle):
+        assert isinstance(fap, mpl.patches.FancyArrowPatch)
+        assert isinstance(fap.get_arrowstyle(), arrow_objects[expected])
+
+
+def test_np_edgelist():
+    # see issue #4129
+    nx.draw_networkx(barbell, edgelist=np.array([(0, 2), (0, 3)]))
+
+
+def test_draw_nodes_missing_node_from_position():
+    G = nx.path_graph(3)
+    pos = {0: (0, 0), 1: (1, 1)}  # No position for node 2
+    with pytest.raises(nx.NetworkXError, match="has no position"):
+        nx.draw_networkx_nodes(G, pos)
+
+
+# NOTE: parametrizing on marker to test both branches of internal
+# nx.draw_networkx_edges.to_marker_edge function
+@pytest.mark.parametrize("node_shape", ("o", "s"))
+def test_draw_edges_min_source_target_margins(node_shape, subplots):
+    """Test that there is a wider gap between the node and the start of an
+    incident edge when min_source_margin is specified.
+
+    This test checks that the use of min_{source/target}_margin kwargs result
+    in shorter (more padding) between the edges and source and target nodes.
+    As a crude visual example, let 's' and 't' represent source and target
+    nodes, respectively:
+
+       Default:
+       s-----------------------------t
+
+       With margins:
+       s   -----------------------   t
+
+    """
+    # Create a single axis object to get consistent pixel coords across
+    # multiple draws
+    fig, ax = subplots
+    G = nx.DiGraph([(0, 1)])
+    pos = {0: (0, 0), 1: (1, 0)}  # horizontal layout
+    # Get leftmost and rightmost points of the FancyArrowPatch object
+    # representing the edge between nodes 0 and 1 (in pixel coordinates)
+    default_patch = nx.draw_networkx_edges(G, pos, ax=ax, node_shape=node_shape)[0]
+    default_extent = default_patch.get_extents().corners()[::2, 0]
+    # Now, do the same but with "padding" for the source and target via the
+    # min_{source/target}_margin kwargs
+    padded_patch = nx.draw_networkx_edges(
+        G,
+        pos,
+        ax=ax,
+        node_shape=node_shape,
+        min_source_margin=100,
+        min_target_margin=100,
+    )[0]
+    padded_extent = padded_patch.get_extents().corners()[::2, 0]
+
+    # With padding, the left-most extent of the edge should be further to the
+    # right
+    assert padded_extent[0] > default_extent[0]
+    # And the rightmost extent of the edge, further to the left
+    assert padded_extent[1] < default_extent[1]
+
+
+# NOTE: parametrizing on marker to test both branches of internal
+# nx.draw_networkx_edges.to_marker_edge function
+@pytest.mark.parametrize("node_shape", ("o", "s"))
+def test_draw_edges_min_source_target_margins_individual(node_shape, subplots):
+    """Test that there is a wider gap between the node and the start of an
+    incident edge when min_source_margin is specified.
+
+    This test checks that the use of min_{source/target}_margin kwargs result
+    in shorter (more padding) between the edges and source and target nodes.
+    As a crude visual example, let 's' and 't' represent source and target
+    nodes, respectively:
+
+       Default:
+       s-----------------------------t
+
+       With margins:
+       s   -----------------------   t
+
+    """
+    # Create a single axis object to get consistent pixel coords across
+    # multiple draws
+    fig, ax = subplots
+    G = nx.DiGraph([(0, 1), (1, 2)])
+    pos = {0: (0, 0), 1: (1, 0), 2: (2, 0)}  # horizontal layout
+    # Get leftmost and rightmost points of the FancyArrowPatch object
+    # representing the edge between nodes 0 and 1 (in pixel coordinates)
+    default_patch = nx.draw_networkx_edges(G, pos, ax=ax, node_shape=node_shape)
+    default_extent = [d.get_extents().corners()[::2, 0] for d in default_patch]
+    # Now, do the same but with "padding" for the source and target via the
+    # min_{source/target}_margin kwargs
+    padded_patch = nx.draw_networkx_edges(
+        G,
+        pos,
+        ax=ax,
+        node_shape=node_shape,
+        min_source_margin=[98, 102],
+        min_target_margin=[98, 102],
+    )
+    padded_extent = [p.get_extents().corners()[::2, 0] for p in padded_patch]
+    for d, p in zip(default_extent, padded_extent):
+        # With padding, the left-most extent of the edge should be further to the
+        # right
+        assert p[0] > d[0]
+        # And the rightmost extent of the edge, further to the left
+        assert p[1] < d[1]
+
+
+def test_nonzero_selfloop_with_single_node(subplots):
+    """Ensure that selfloop extent is non-zero when there is only one node."""
+    # Create explicit axis object for test
+    fig, ax = subplots
+    # Graph with single node + self loop
+    G = nx.DiGraph()
+    G.add_node(0)
+    G.add_edge(0, 0)
+    # Draw
+    patch = nx.draw_networkx_edges(G, {0: (0, 0)})[0]
+    # The resulting patch must have non-zero extent
+    bbox = patch.get_extents()
+    assert bbox.width > 0 and bbox.height > 0
+
+
+def test_nonzero_selfloop_with_single_edge_in_edgelist(subplots):
+    """Ensure that selfloop extent is non-zero when only a single edge is
+    specified in the edgelist.
+    """
+    # Create explicit axis object for test
+    fig, ax = subplots
+    # Graph with selfloop
+    G = nx.path_graph(2, create_using=nx.DiGraph)
+    G.add_edge(1, 1)
+    pos = {n: (n, n) for n in G.nodes}
+    # Draw only the selfloop edge via the `edgelist` kwarg
+    patch = nx.draw_networkx_edges(G, pos, edgelist=[(1, 1)])[0]
+    # The resulting patch must have non-zero extent
+    bbox = patch.get_extents()
+    assert bbox.width > 0 and bbox.height > 0
+
+
+def test_apply_alpha():
+    """Test apply_alpha when there is a mismatch between the number of
+    supplied colors and elements.
+    """
+    nodelist = [0, 1, 2]
+    colorlist = ["r", "g", "b"]
+    alpha = 0.5
+    rgba_colors = nx.drawing.nx_pylab.apply_alpha(colorlist, alpha, nodelist)
+    assert all(rgba_colors[:, -1] == alpha)
+
+
+def test_draw_edges_toggling_with_arrows_kwarg():
+    """
+    The `arrows` keyword argument is used as a 3-way switch to select which
+    type of object to use for drawing edges:
+      - ``arrows=None`` -> default (FancyArrowPatches for directed, else LineCollection)
+      - ``arrows=True`` -> FancyArrowPatches
+      - ``arrows=False`` -> LineCollection
+    """
+    import matplotlib.collections
+    import matplotlib.patches
+
+    UG = nx.path_graph(3)
+    DG = nx.path_graph(3, create_using=nx.DiGraph)
+    pos = {n: (n, n) for n in UG}
+
+    # Use FancyArrowPatches when arrows=True, regardless of graph type
+    for G in (UG, DG):
+        edges = nx.draw_networkx_edges(G, pos, arrows=True)
+        assert len(edges) == len(G.edges)
+        assert isinstance(edges[0], mpl.patches.FancyArrowPatch)
+
+    # Use LineCollection when arrows=False, regardless of graph type
+    for G in (UG, DG):
+        edges = nx.draw_networkx_edges(G, pos, arrows=False)
+        assert isinstance(edges, mpl.collections.LineCollection)
+
+    # Default behavior when arrows=None: FAPs for directed, LC's for undirected
+    edges = nx.draw_networkx_edges(UG, pos)
+    assert isinstance(edges, mpl.collections.LineCollection)
+    edges = nx.draw_networkx_edges(DG, pos)
+    assert len(edges) == len(G.edges)
+    assert isinstance(edges[0], mpl.patches.FancyArrowPatch)
+
+
+@pytest.mark.parametrize("drawing_func", (nx.draw, nx.draw_networkx))
+def test_draw_networkx_arrows_default_undirected(drawing_func, subplots):
+    import matplotlib.collections
+
+    G = nx.path_graph(3)
+    fig, ax = subplots
+    drawing_func(G, ax=ax)
+    assert any(isinstance(c, mpl.collections.LineCollection) for c in ax.collections)
+    assert not ax.patches
+
+
+@pytest.mark.parametrize("drawing_func", (nx.draw, nx.draw_networkx))
+def test_draw_networkx_arrows_default_directed(drawing_func, subplots):
+    import matplotlib.collections
+
+    G = nx.path_graph(3, create_using=nx.DiGraph)
+    fig, ax = subplots
+    drawing_func(G, ax=ax)
+    assert not any(
+        isinstance(c, mpl.collections.LineCollection) for c in ax.collections
+    )
+    assert ax.patches
+
+
+def test_edgelist_kwarg_not_ignored(subplots):
+    # See gh-4994
+    G = nx.path_graph(3)
+    G.add_edge(0, 0)
+    fig, ax = subplots
+    nx.draw(G, edgelist=[(0, 1), (1, 2)], ax=ax)  # Exclude self-loop from edgelist
+    assert not ax.patches
+
+
+@pytest.mark.parametrize(
+    ("G", "expected_n_edges"),
+    ([nx.DiGraph(), 2], [nx.MultiGraph(), 4], [nx.MultiDiGraph(), 4]),
+)
+def test_draw_networkx_edges_multiedge_connectionstyle(G, expected_n_edges):
+    """Draws edges correctly for 3 types of graphs and checks for valid length"""
+    for i, (u, v) in enumerate([(0, 1), (0, 1), (0, 1), (0, 2)]):
+        G.add_edge(u, v, weight=round(i / 3, 2))
+    pos = {n: (n, n) for n in G}
+    # Raises on insufficient connectionstyle length
+    for conn_style in [
+        "arc3,rad=0.1",
+        ["arc3,rad=0.1", "arc3,rad=0.1"],
+        ["arc3,rad=0.1", "arc3,rad=0.1", "arc3,rad=0.2"],
+    ]:
+        nx.draw_networkx_edges(G, pos, connectionstyle=conn_style)
+        arrows = nx.draw_networkx_edges(G, pos, connectionstyle=conn_style)
+        assert len(arrows) == expected_n_edges
+
+
+@pytest.mark.parametrize(
+    ("G", "expected_n_edges"),
+    ([nx.DiGraph(), 2], [nx.MultiGraph(), 4], [nx.MultiDiGraph(), 4]),
+)
+def test_draw_networkx_edge_labels_multiedge_connectionstyle(G, expected_n_edges):
+    """Draws labels correctly for 3 types of graphs and checks for valid length and class names"""
+    for i, (u, v) in enumerate([(0, 1), (0, 1), (0, 1), (0, 2)]):
+        G.add_edge(u, v, weight=round(i / 3, 2))
+    pos = {n: (n, n) for n in G}
+    # Raises on insufficient connectionstyle length
+    arrows = nx.draw_networkx_edges(
+        G, pos, connectionstyle=["arc3,rad=0.1", "arc3,rad=0.1", "arc3,rad=0.1"]
+    )
+    for conn_style in [
+        "arc3,rad=0.1",
+        ["arc3,rad=0.1", "arc3,rad=0.2"],
+        ["arc3,rad=0.1", "arc3,rad=0.1", "arc3,rad=0.1"],
+    ]:
+        text_items = nx.draw_networkx_edge_labels(G, pos, connectionstyle=conn_style)
+        assert len(text_items) == expected_n_edges
+        for ti in text_items.values():
+            assert ti.__class__.__name__ == "CurvedArrowText"
+
+
+def test_draw_networkx_edge_label_multiedge():
+    G = nx.MultiGraph()
+    G.add_edge(0, 1, weight=10)
+    G.add_edge(0, 1, weight=20)
+    edge_labels = nx.get_edge_attributes(G, "weight")  # Includes edge keys
+    pos = {n: (n, n) for n in G}
+    text_items = nx.draw_networkx_edge_labels(
+        G,
+        pos,
+        edge_labels=edge_labels,
+        connectionstyle=["arc3,rad=0.1", "arc3,rad=0.2"],
+    )
+    assert len(text_items) == 2
+
+
+def test_draw_networkx_edge_label_empty_dict():
+    """Regression test for draw_networkx_edge_labels with empty dict. See
+    gh-5372."""
+    G = nx.path_graph(3)
+    pos = {n: (n, n) for n in G.nodes}
+    assert nx.draw_networkx_edge_labels(G, pos, edge_labels={}) == {}
+
+
+def test_draw_networkx_edges_undirected_selfloop_colors(subplots):
+    """When an edgelist is supplied along with a sequence of colors, check that
+    the self-loops have the correct colors."""
+    fig, ax = subplots
+    # Edge list and corresponding colors
+    edgelist = [(1, 3), (1, 2), (2, 3), (1, 1), (3, 3), (2, 2)]
+    edge_colors = ["pink", "cyan", "black", "red", "blue", "green"]
+
+    G = nx.Graph(edgelist)
+    pos = {n: (n, n) for n in G.nodes}
+    nx.draw_networkx_edges(G, pos, ax=ax, edgelist=edgelist, edge_color=edge_colors)
+
+    # Verify that there are three fancy arrow patches (1 per self loop)
+    assert len(ax.patches) == 3
+
+    # These are points that should be contained in the self loops. For example,
+    # sl_points[0] will be (1, 1.1), which is inside the "path" of the first
+    # self-loop but outside the others
+    sl_points = np.array(edgelist[-3:]) + np.array([0, 0.1])
+
+    # Check that the mapping between self-loop locations and their colors is
+    # correct
+    for fap, clr, slp in zip(ax.patches, edge_colors[-3:], sl_points):
+        assert fap.get_path().contains_point(slp)
+        assert mpl.colors.same_color(fap.get_edgecolor(), clr)
+
+
+@pytest.mark.parametrize(
+    "fap_only_kwarg",  # Non-default values for kwargs that only apply to FAPs
+    (
+        {"arrowstyle": "-"},
+        {"arrowsize": 20},
+        {"connectionstyle": "arc3,rad=0.2"},
+        {"min_source_margin": 10},
+        {"min_target_margin": 10},
+    ),
+)
+def test_user_warnings_for_unused_edge_drawing_kwargs(fap_only_kwarg, subplots):
+    """Users should get a warning when they specify a non-default value for
+    one of the kwargs that applies only to edges drawn with FancyArrowPatches,
+    but FancyArrowPatches aren't being used under the hood."""
+    G = nx.path_graph(3)
+    pos = {n: (n, n) for n in G}
+    fig, ax = subplots
+    # By default, an undirected graph will use LineCollection to represent
+    # the edges
+    kwarg_name = list(fap_only_kwarg.keys())[0]
+    with pytest.warns(
+        UserWarning, match=f"\n\nThe {kwarg_name} keyword argument is not applicable"
+    ):
+        nx.draw_networkx_edges(G, pos, ax=ax, **fap_only_kwarg)
+    # FancyArrowPatches are always used when `arrows=True` is specified.
+    # Check that warnings are *not* raised in this case
+    with warnings.catch_warnings():
+        # Escalate warnings -> errors so tests fail if warnings are raised
+        warnings.simplefilter("error")
+        warnings.filterwarnings("ignore", category=DeprecationWarning)
+        nx.draw_networkx_edges(G, pos, ax=ax, arrows=True, **fap_only_kwarg)
+
+
+@pytest.mark.parametrize("draw_fn", (nx.draw, nx.draw_circular))
+def test_no_warning_on_default_draw_arrowstyle(draw_fn, subplots):
+    # See gh-7284
+    fig, ax = subplots
+    G = nx.cycle_graph(5)
+    with warnings.catch_warnings(record=True) as w:
+        draw_fn(G, ax=ax)
+    assert len(w) == 0
+
+
+@pytest.mark.parametrize("hide_ticks", [False, True])
+@pytest.mark.parametrize(
+    "method",
+    [
+        nx.draw_networkx,
+        nx.draw_networkx_edge_labels,
+        nx.draw_networkx_edges,
+        nx.draw_networkx_labels,
+        nx.draw_networkx_nodes,
+    ],
+)
+def test_hide_ticks(method, hide_ticks, subplots):
+    G = nx.path_graph(3)
+    pos = {n: (n, n) for n in G.nodes}
+    _, ax = subplots
+    method(G, pos=pos, ax=ax, hide_ticks=hide_ticks)
+    for axis in [ax.xaxis, ax.yaxis]:
+        assert bool(axis.get_ticklabels()) != hide_ticks
+
+
+def test_edge_label_bar_connectionstyle(subplots):
+    """Check that FancyArrowPatches with `bar` connectionstyle are also supported
+    in edge label rendering. See gh-7735."""
+    fig, ax = subplots
+    edge = (0, 1)
+    G = nx.DiGraph([edge])
+    pos = {n: (n, 0) for n in G}  # Edge is horizontal line between (0, 0) and (1, 0)
+
+    style_arc = "arc3,rad=0.0"
+    style_bar = "bar,fraction=0.1"
+
+    arc_lbl = nx.draw_networkx_edge_labels(
+        G, pos, edge_labels={edge: "edge"}, connectionstyle=style_arc
+    )
+    # This would fail prior to gh-7739
+    bar_lbl = nx.draw_networkx_edge_labels(
+        G, pos, edge_labels={edge: "edge"}, connectionstyle=style_bar
+    )
+
+    # For the "arc" style, the label should be at roughly the midpoint
+    assert arc_lbl[edge].x, arc_lbl[edge].y == pytest.approx((0.5, 0))
+    # The label should be below the x-axis for the "bar" style
+    assert bar_lbl[edge].y < arc_lbl[edge].y