755 lines
26 KiB
Python
755 lines
26 KiB
Python
"""Unit tests for matplotlib drawing functions."""
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import itertools
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import os
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import pytest
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mpl = pytest.importorskip("matplotlib")
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np = pytest.importorskip("numpy")
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mpl.use("PS")
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plt = pytest.importorskip("matplotlib.pyplot")
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plt.rcParams["text.usetex"] = False
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import networkx as nx
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barbell = nx.barbell_graph(4, 6)
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def test_draw():
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try:
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functions = [
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nx.draw_circular,
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nx.draw_kamada_kawai,
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nx.draw_planar,
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nx.draw_random,
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nx.draw_spectral,
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nx.draw_spring,
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nx.draw_shell,
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]
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options = [{"node_color": "black", "node_size": 100, "width": 3}]
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for function, option in itertools.product(functions, options):
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function(barbell, **option)
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plt.savefig("test.ps")
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finally:
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try:
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os.unlink("test.ps")
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except OSError:
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pass
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def test_draw_shell_nlist():
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try:
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nlist = [list(range(4)), list(range(4, 10)), list(range(10, 14))]
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nx.draw_shell(barbell, nlist=nlist)
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plt.savefig("test.ps")
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finally:
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try:
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os.unlink("test.ps")
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except OSError:
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pass
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def test_edge_colormap():
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colors = range(barbell.number_of_edges())
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nx.draw_spring(
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barbell, edge_color=colors, width=4, edge_cmap=plt.cm.Blues, with_labels=True
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)
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# plt.show()
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def test_arrows():
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nx.draw_spring(barbell.to_directed())
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# plt.show()
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@pytest.mark.parametrize(
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("edge_color", "expected"),
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(
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(None, "black"), # Default
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("r", "red"), # Non-default color string
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(["r"], "red"), # Single non-default color in a list
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((1.0, 1.0, 0.0), "yellow"), # single color as rgb tuple
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([(1.0, 1.0, 0.0)], "yellow"), # single color as rgb tuple in list
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((0, 1, 0, 1), "lime"), # single color as rgba tuple
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([(0, 1, 0, 1)], "lime"), # single color as rgba tuple in list
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("#0000ff", "blue"), # single color hex code
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(["#0000ff"], "blue"), # hex code in list
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),
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)
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@pytest.mark.parametrize("edgelist", (None, [(0, 1)]))
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def test_single_edge_color_undirected(edge_color, expected, edgelist):
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"""Tests ways of specifying all edges have a single color for edges
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drawn with a LineCollection"""
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G = nx.path_graph(3)
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drawn_edges = nx.draw_networkx_edges(
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G, pos=nx.random_layout(G), edgelist=edgelist, edge_color=edge_color
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)
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assert mpl.colors.same_color(drawn_edges.get_color(), expected)
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@pytest.mark.parametrize(
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("edge_color", "expected"),
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(
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(None, "black"), # Default
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("r", "red"), # Non-default color string
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(["r"], "red"), # Single non-default color in a list
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((1.0, 1.0, 0.0), "yellow"), # single color as rgb tuple
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([(1.0, 1.0, 0.0)], "yellow"), # single color as rgb tuple in list
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((0, 1, 0, 1), "lime"), # single color as rgba tuple
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([(0, 1, 0, 1)], "lime"), # single color as rgba tuple in list
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("#0000ff", "blue"), # single color hex code
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(["#0000ff"], "blue"), # hex code in list
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),
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)
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@pytest.mark.parametrize("edgelist", (None, [(0, 1)]))
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def test_single_edge_color_directed(edge_color, expected, edgelist):
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"""Tests ways of specifying all edges have a single color for edges drawn
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with FancyArrowPatches"""
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G = nx.path_graph(3, create_using=nx.DiGraph)
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drawn_edges = nx.draw_networkx_edges(
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G, pos=nx.random_layout(G), edgelist=edgelist, edge_color=edge_color
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)
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for fap in drawn_edges:
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assert mpl.colors.same_color(fap.get_edgecolor(), expected)
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def test_edge_color_tuple_interpretation():
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"""If edge_color is a sequence with the same length as edgelist, then each
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value in edge_color is mapped onto each edge via colormap."""
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G = nx.path_graph(6, create_using=nx.DiGraph)
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pos = {n: (n, n) for n in range(len(G))}
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# num edges != 3 or 4 --> edge_color interpreted as rgb(a)
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for ec in ((0, 0, 1), (0, 0, 1, 1)):
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# More than 4 edges
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drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=ec)
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for fap in drawn_edges:
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assert mpl.colors.same_color(fap.get_edgecolor(), ec)
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# Fewer than 3 edges
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drawn_edges = nx.draw_networkx_edges(
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G, pos, edgelist=[(0, 1), (1, 2)], edge_color=ec
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)
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for fap in drawn_edges:
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assert mpl.colors.same_color(fap.get_edgecolor(), ec)
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# num edges == 3, len(edge_color) == 4: interpreted as rgba
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drawn_edges = nx.draw_networkx_edges(
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G, pos, edgelist=[(0, 1), (1, 2), (2, 3)], edge_color=(0, 0, 1, 1)
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)
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for fap in drawn_edges:
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assert mpl.colors.same_color(fap.get_edgecolor(), "blue")
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# num edges == 4, len(edge_color) == 3: interpreted as rgb
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drawn_edges = nx.draw_networkx_edges(
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G, pos, edgelist=[(0, 1), (1, 2), (2, 3), (3, 4)], edge_color=(0, 0, 1)
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)
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for fap in drawn_edges:
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assert mpl.colors.same_color(fap.get_edgecolor(), "blue")
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# num edges == len(edge_color) == 3: interpreted with cmap, *not* as rgb
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drawn_edges = nx.draw_networkx_edges(
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G, pos, edgelist=[(0, 1), (1, 2), (2, 3)], edge_color=(0, 0, 1)
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)
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assert mpl.colors.same_color(
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drawn_edges[0].get_edgecolor(), drawn_edges[1].get_edgecolor()
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)
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for fap in drawn_edges:
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assert not mpl.colors.same_color(fap.get_edgecolor(), "blue")
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# num edges == len(edge_color) == 4: interpreted with cmap, *not* as rgba
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drawn_edges = nx.draw_networkx_edges(
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G, pos, edgelist=[(0, 1), (1, 2), (2, 3), (3, 4)], edge_color=(0, 0, 1, 1)
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)
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assert mpl.colors.same_color(
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drawn_edges[0].get_edgecolor(), drawn_edges[1].get_edgecolor()
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)
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assert mpl.colors.same_color(
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drawn_edges[2].get_edgecolor(), drawn_edges[3].get_edgecolor()
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)
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for fap in drawn_edges:
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assert not mpl.colors.same_color(fap.get_edgecolor(), "blue")
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def test_fewer_edge_colors_than_num_edges_directed():
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"""Test that the edge colors are cycled when there are fewer specified
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colors than edges."""
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G = barbell.to_directed()
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pos = nx.random_layout(barbell)
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edgecolors = ("r", "g", "b")
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drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=edgecolors)
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for fap, expected in zip(drawn_edges, itertools.cycle(edgecolors)):
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assert mpl.colors.same_color(fap.get_edgecolor(), expected)
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def test_more_edge_colors_than_num_edges_directed():
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"""Test that extra edge colors are ignored when there are more specified
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colors than edges."""
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G = nx.path_graph(4, create_using=nx.DiGraph) # 3 edges
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pos = nx.random_layout(barbell)
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edgecolors = ("r", "g", "b", "c") # 4 edge colors
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drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=edgecolors)
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for fap, expected in zip(drawn_edges, edgecolors[:-1]):
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assert mpl.colors.same_color(fap.get_edgecolor(), expected)
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def test_edge_color_string_with_gloabl_alpha_undirected():
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edge_collection = nx.draw_networkx_edges(
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barbell,
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pos=nx.random_layout(barbell),
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edgelist=[(0, 1), (1, 2)],
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edge_color="purple",
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alpha=0.2,
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)
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ec = edge_collection.get_color().squeeze() # as rgba tuple
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assert len(edge_collection.get_paths()) == 2
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assert mpl.colors.same_color(ec[:-1], "purple")
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assert ec[-1] == 0.2
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def test_edge_color_string_with_global_alpha_directed():
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drawn_edges = nx.draw_networkx_edges(
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barbell.to_directed(),
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pos=nx.random_layout(barbell),
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edgelist=[(0, 1), (1, 2)],
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edge_color="purple",
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alpha=0.2,
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)
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assert len(drawn_edges) == 2
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for fap in drawn_edges:
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ec = fap.get_edgecolor() # As rgba tuple
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assert mpl.colors.same_color(ec[:-1], "purple")
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assert ec[-1] == 0.2
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@pytest.mark.parametrize("graph_type", (nx.Graph, nx.DiGraph))
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def test_edge_width_default_value(graph_type):
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"""Test the default linewidth for edges drawn either via LineCollection or
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FancyArrowPatches."""
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G = nx.path_graph(2, create_using=graph_type)
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pos = {n: (n, n) for n in range(len(G))}
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drawn_edges = nx.draw_networkx_edges(G, pos)
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if isinstance(drawn_edges, list): # directed case: list of FancyArrowPatch
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drawn_edges = drawn_edges[0]
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assert drawn_edges.get_linewidth() == 1
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@pytest.mark.parametrize(
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("edgewidth", "expected"),
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(
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(3, 3), # single-value, non-default
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([3], 3), # Single value as a list
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),
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)
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def test_edge_width_single_value_undirected(edgewidth, expected):
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G = nx.path_graph(4)
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pos = {n: (n, n) for n in range(len(G))}
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drawn_edges = nx.draw_networkx_edges(G, pos, width=edgewidth)
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assert len(drawn_edges.get_paths()) == 3
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assert drawn_edges.get_linewidth() == expected
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@pytest.mark.parametrize(
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("edgewidth", "expected"),
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(
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(3, 3), # single-value, non-default
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([3], 3), # Single value as a list
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),
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)
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def test_edge_width_single_value_directed(edgewidth, expected):
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G = nx.path_graph(4, create_using=nx.DiGraph)
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pos = {n: (n, n) for n in range(len(G))}
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drawn_edges = nx.draw_networkx_edges(G, pos, width=edgewidth)
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assert len(drawn_edges) == 3
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for fap in drawn_edges:
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assert fap.get_linewidth() == expected
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@pytest.mark.parametrize(
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"edgelist",
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(
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[(0, 1), (1, 2), (2, 3)], # one width specification per edge
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None, # fewer widths than edges - widths cycle
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[(0, 1), (1, 2)], # More widths than edges - unused widths ignored
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),
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)
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def test_edge_width_sequence(edgelist):
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G = barbell.to_directed()
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pos = nx.random_layout(G)
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widths = (0.5, 2.0, 12.0)
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drawn_edges = nx.draw_networkx_edges(G, pos, edgelist=edgelist, width=widths)
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for fap, expected_width in zip(drawn_edges, itertools.cycle(widths)):
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assert fap.get_linewidth() == expected_width
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def test_edge_color_with_edge_vmin_vmax():
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"""Test that edge_vmin and edge_vmax properly set the dynamic range of the
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color map when num edges == len(edge_colors)."""
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G = nx.path_graph(3, create_using=nx.DiGraph)
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pos = nx.random_layout(G)
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# Extract colors from the original (unscaled) colormap
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drawn_edges = nx.draw_networkx_edges(G, pos, edge_color=[0, 1.0])
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orig_colors = [e.get_edgecolor() for e in drawn_edges]
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# Colors from scaled colormap
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drawn_edges = nx.draw_networkx_edges(
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G, pos, edge_color=[0.2, 0.8], edge_vmin=0.2, edge_vmax=0.8
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)
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scaled_colors = [e.get_edgecolor() for e in drawn_edges]
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assert mpl.colors.same_color(orig_colors, scaled_colors)
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def test_directed_edges_linestyle_default():
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"""Test default linestyle for edges drawn with FancyArrowPatches."""
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G = nx.path_graph(4, create_using=nx.DiGraph) # Graph with 3 edges
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pos = {n: (n, n) for n in range(len(G))}
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# edge with default style
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drawn_edges = nx.draw_networkx_edges(G, pos)
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assert len(drawn_edges) == 3
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for fap in drawn_edges:
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assert fap.get_linestyle() == "solid"
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@pytest.mark.parametrize(
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"style",
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(
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"dashed", # edge with string style
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"--", # edge with simplified string style
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(1, (1, 1)), # edge with (offset, onoffseq) style
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),
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)
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def test_directed_edges_linestyle_single_value(style):
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"""Tests support for specifying linestyles with a single value to be applied to
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all edges in ``draw_networkx_edges`` for FancyArrowPatch outputs
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(e.g. directed edges)."""
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G = nx.path_graph(4, create_using=nx.DiGraph) # Graph with 3 edges
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pos = {n: (n, n) for n in range(len(G))}
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drawn_edges = nx.draw_networkx_edges(G, pos, style=style)
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assert len(drawn_edges) == 3
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for fap in drawn_edges:
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assert fap.get_linestyle() == style
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@pytest.mark.parametrize(
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"style_seq",
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(
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["dashed"], # edge with string style in list
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["--"], # edge with simplified string style in list
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[(1, (1, 1))], # edge with (offset, onoffseq) style in list
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["--", "-", ":"], # edges with styles for each edge
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["--", "-"], # edges with fewer styles than edges (styles cycle)
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["--", "-", ":", "-."], # edges with more styles than edges (extra unused)
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),
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)
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def test_directed_edges_linestyle_sequence(style_seq):
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"""Tests support for specifying linestyles with sequences in
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``draw_networkx_edges`` for FancyArrowPatch outputs (e.g. directed edges)."""
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G = nx.path_graph(4, create_using=nx.DiGraph) # Graph with 3 edges
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pos = {n: (n, n) for n in range(len(G))}
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drawn_edges = nx.draw_networkx_edges(G, pos, style=style_seq)
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assert len(drawn_edges) == 3
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for fap, style in zip(drawn_edges, itertools.cycle(style_seq)):
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assert fap.get_linestyle() == style
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def test_labels_and_colors():
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G = nx.cubical_graph()
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pos = nx.spring_layout(G) # positions for all nodes
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# nodes
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nx.draw_networkx_nodes(
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G, pos, nodelist=[0, 1, 2, 3], node_color="r", node_size=500, alpha=0.75
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)
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nx.draw_networkx_nodes(
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G,
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pos,
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nodelist=[4, 5, 6, 7],
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node_color="b",
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node_size=500,
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alpha=[0.25, 0.5, 0.75, 1.0],
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)
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# edges
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nx.draw_networkx_edges(G, pos, width=1.0, alpha=0.5)
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nx.draw_networkx_edges(
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G,
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pos,
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edgelist=[(0, 1), (1, 2), (2, 3), (3, 0)],
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width=8,
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alpha=0.5,
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edge_color="r",
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)
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nx.draw_networkx_edges(
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G,
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pos,
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edgelist=[(4, 5), (5, 6), (6, 7), (7, 4)],
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width=8,
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alpha=0.5,
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edge_color="b",
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)
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nx.draw_networkx_edges(
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G,
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pos,
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edgelist=[(4, 5), (5, 6), (6, 7), (7, 4)],
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min_source_margin=0.5,
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min_target_margin=0.75,
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width=8,
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edge_color="b",
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)
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# some math labels
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labels = {}
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labels[0] = r"$a$"
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labels[1] = r"$b$"
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labels[2] = r"$c$"
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labels[3] = r"$d$"
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labels[4] = r"$\alpha$"
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labels[5] = r"$\beta$"
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labels[6] = r"$\gamma$"
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labels[7] = r"$\delta$"
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nx.draw_networkx_labels(G, pos, labels, font_size=16)
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nx.draw_networkx_edge_labels(G, pos, edge_labels=None, rotate=False)
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nx.draw_networkx_edge_labels(G, pos, edge_labels={(4, 5): "4-5"})
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# plt.show()
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@pytest.mark.mpl_image_compare
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def test_house_with_colors():
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G = nx.house_graph()
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# explicitly set positions
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fig, ax = plt.subplots()
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pos = {0: (0, 0), 1: (1, 0), 2: (0, 1), 3: (1, 1), 4: (0.5, 2.0)}
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# Plot nodes with different properties for the "wall" and "roof" nodes
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nx.draw_networkx_nodes(
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G,
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pos,
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node_size=3000,
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nodelist=[0, 1, 2, 3],
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node_color="tab:blue",
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)
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nx.draw_networkx_nodes(
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G, pos, node_size=2000, nodelist=[4], node_color="tab:orange"
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)
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nx.draw_networkx_edges(G, pos, alpha=0.5, width=6)
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# Customize axes
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ax.margins(0.11)
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plt.tight_layout()
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plt.axis("off")
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return fig
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def test_axes():
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fig, ax = plt.subplots()
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nx.draw(barbell, ax=ax)
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nx.draw_networkx_edge_labels(barbell, nx.circular_layout(barbell), ax=ax)
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def test_empty_graph():
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G = nx.Graph()
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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_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
|
|
|
|
|
|
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):
|
|
"""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 = plt.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]
|
|
|
|
|
|
def test_nonzero_selfloop_with_single_node():
|
|
"""Ensure that selfloop extent is non-zero when there is only one node."""
|
|
# Create explicit axis object for test
|
|
fig, ax = plt.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
|
|
# Cleanup
|
|
plt.delaxes(ax)
|
|
|
|
|
|
def test_nonzero_selfloop_with_single_edge_in_edgelist():
|
|
"""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 = plt.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
|
|
# Cleanup
|
|
plt.delaxes(ax)
|
|
|
|
|
|
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):
|
|
import matplotlib.collections
|
|
|
|
G = nx.path_graph(3)
|
|
fig, ax = plt.subplots()
|
|
drawing_func(G, ax=ax)
|
|
assert any(isinstance(c, mpl.collections.LineCollection) for c in ax.collections)
|
|
assert not ax.patches
|
|
plt.delaxes(ax)
|
|
|
|
|
|
@pytest.mark.parametrize("drawing_func", (nx.draw, nx.draw_networkx))
|
|
def test_draw_networkx_arrows_default_directed(drawing_func):
|
|
import matplotlib.collections
|
|
|
|
G = nx.path_graph(3, create_using=nx.DiGraph)
|
|
fig, ax = plt.subplots()
|
|
drawing_func(G, ax=ax)
|
|
assert not any(
|
|
isinstance(c, mpl.collections.LineCollection) for c in ax.collections
|
|
)
|
|
assert ax.patches
|
|
plt.delaxes(ax)
|
|
|
|
|
|
def test_edgelist_kwarg_not_ignored():
|
|
# See gh-4994
|
|
G = nx.path_graph(3)
|
|
G.add_edge(0, 0)
|
|
fig, ax = plt.subplots()
|
|
nx.draw(G, edgelist=[(0, 1), (1, 2)], ax=ax) # Exclude self-loop from edgelist
|
|
assert not ax.patches
|
|
plt.delaxes(ax)
|
|
|
|
|
|
def test_draw_networkx_edge_label_multiedge_exception():
|
|
"""
|
|
draw_networkx_edge_labels should raise an informative error message when
|
|
the edge label includes keys
|
|
"""
|
|
exception_msg = "draw_networkx_edge_labels does not support multiedges"
|
|
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}
|
|
with pytest.raises(nx.NetworkXError, match=exception_msg):
|
|
nx.draw_networkx_edge_labels(G, pos, edge_labels=edge_labels)
|
|
|
|
|
|
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():
|
|
"""When an edgelist is supplied along with a sequence of colors, check that
|
|
the self-loops have the correct colors."""
|
|
fig, ax = plt.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)
|