Merge branch 'main' into develop

Author: ntamas

.all-contributorsrc

@@ -639,6 +639,15 @@
       "contributions": [
         "code"
       ]
+    },
+    {
+      "login": "SKG24",
+      "name": "Sanat Kumar Gupta",
+      "avatar_url": "https://avatars.githubusercontent.com/u/123228827?v=4",
+      "profile": "https://github.com/SKG24",
+      "contributions": [
+        "code"
+      ]
     }
   ],
   "contributorsPerLine": 7

CONTRIBUTORS.md

@@ -97,6 +97,9 @@ Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/d
       <td align="center" valign="top" width="14.28%"><a href="https://github.com/GenieTim"><img src="https://avatars.githubusercontent.com/u/8596965?v=4?s=100" width="100px;" alt="Tim Bernhard"/><br /><sub><b>Tim Bernhard</b></sub></a><br /><a href="https://github.com/igraph/python-igraph/commits?author=GenieTim" title="Code">💻</a></td>
       <td align="center" valign="top" width="14.28%"><a href="https://github.com/BeaMarton13"><img src="https://avatars.githubusercontent.com/u/204701577?v=4?s=100" width="100px;" alt="Bea Márton"/><br /><sub><b>Bea Márton</b></sub></a><br /><a href="https://github.com/igraph/python-igraph/commits?author=BeaMarton13" title="Code">💻</a></td>
     </tr>
+    <tr>
+      <td align="center" valign="top" width="14.28%"><a href="https://github.com/SKG24"><img src="https://avatars.githubusercontent.com/u/123228827?v=4?s=100" width="100px;" alt="Sanat Kumar Gupta"/><br /><sub><b>Sanat Kumar Gupta</b></sub></a><br /><a href="https://github.com/igraph/python-igraph/commits?author=SKG24" title="Code">💻</a></td>
+    </tr>
   </tbody>
 </table>
 

doc/examples_sphinx-gallery/articulation_points.py

@@ -8,6 +8,7 @@
 This example shows how to compute and visualize the `articulation points <https://en.wikipedia.org/wiki/Biconnected_component>`_ in a graph using :meth:`igraph.GraphBase.articulation_points`. For an example on bridges instead, see :ref:`tutorials-bridges`.
 
 """
+
 import igraph as ig
 import matplotlib.pyplot as plt
 
@@ -30,9 +31,9 @@
     vertex_size=30,
     vertex_color="lightblue",
     vertex_label=range(g.vcount()),
-    vertex_frame_color = ["red" if v in articulation_points else "black" for v in g.vs],
-    vertex_frame_width = [3 if v in articulation_points else 1 for v in g.vs],
+    vertex_frame_color=["red" if v in articulation_points else "black" for v in g.vs],
+    vertex_frame_width=[3 if v in articulation_points else 1 for v in g.vs],
     edge_width=0.8,
-    edge_color='gray'
+    edge_color="gray",
 )
 plt.show()

doc/examples_sphinx-gallery/betweenness.py

@@ -24,14 +24,14 @@
 # :meth:`igraph.utils.rescale` to rescale the betweennesses in the interval
 # ``[0, 1]``.
 def plot_betweenness(g, vertex_betweenness, edge_betweenness, ax, cax1, cax2):
-    '''Plot vertex/edge betweenness, with colorbars
+    """Plot vertex/edge betweenness, with colorbars
 
     Args:
         g: the graph to plot.
         ax: the Axes for the graph
         cax1: the Axes for the vertex betweenness colorbar
         cax2: the Axes for the edge betweenness colorbar
-    '''
+    """
 
     # Rescale betweenness to be between 0.0 and 1.0
     scaled_vertex_betweenness = ig.rescale(vertex_betweenness, clamp=True)
@@ -45,7 +45,7 @@ def plot_betweenness(g, vertex_betweenness, edge_betweenness, ax, cax1, cax2):
 
     # Plot graph
     g.vs["color"] = [cmap1(betweenness) for betweenness in scaled_vertex_betweenness]
-    g.vs["size"]  = ig.rescale(vertex_betweenness, (10, 50))
+    g.vs["size"] = ig.rescale(vertex_betweenness, (10, 50))
     g.es["color"] = [cmap2(betweenness) for betweenness in scaled_edge_betweenness]
     g.es["width"] = ig.rescale(edge_betweenness, (0.5, 1.0))
     ig.plot(
@@ -58,8 +58,8 @@ def plot_betweenness(g, vertex_betweenness, edge_betweenness, ax, cax1, cax2):
     # Color bars
     norm1 = ScalarMappable(norm=Normalize(0, max(vertex_betweenness)), cmap=cmap1)
     norm2 = ScalarMappable(norm=Normalize(0, max(edge_betweenness)), cmap=cmap2)
-    plt.colorbar(norm1, cax=cax1, orientation="horizontal", label='Vertex Betweenness')
-    plt.colorbar(norm2, cax=cax2, orientation="horizontal", label='Edge Betweenness')
+    plt.colorbar(norm1, cax=cax1, orientation="horizontal", label="Vertex Betweenness")
+    plt.colorbar(norm2, cax=cax2, orientation="horizontal", label="Edge Betweenness")
 
 
 # %%

doc/examples_sphinx-gallery/bipartite_matching.py

@@ -7,6 +7,7 @@
 
 This example demonstrates an efficient way to find and visualise a maximum biparite matching using :meth:`igraph.Graph.maximum_bipartite_matching`.
 """
+
 import igraph as ig
 import matplotlib.pyplot as plt
 
@@ -16,7 +17,7 @@
 #  - nodes 5-8 to the other side
 g = ig.Graph.Bipartite(
     [0, 0, 0, 0, 0, 1, 1, 1, 1],
-    [(0, 5), (1, 6), (1, 7), (2, 5), (2, 8), (3, 6), (4, 5), (4, 6)]
+    [(0, 5), (1, 6), (1, 7), (2, 5), (2, 8), (3, 6), (4, 5), (4, 6)],
 )
 
 # %%

doc/examples_sphinx-gallery/bipartite_matching_maxflow.py

@@ -9,6 +9,7 @@
 
 .. note::  :meth:`igraph.Graph.maximum_bipartite_matching` is usually a better way to find the maximum bipartite matching. For a demonstration on how to use that method instead, check out :ref:`tutorials-bipartite-matching`.
 """
+
 import igraph as ig
 import matplotlib.pyplot as plt
 
@@ -17,7 +18,7 @@
 g = ig.Graph(
     9,
     [(0, 4), (0, 5), (1, 4), (1, 6), (1, 7), (2, 5), (2, 7), (2, 8), (3, 6), (3, 7)],
-    directed=True
+    directed=True,
 )
 
 # %%
@@ -62,6 +63,6 @@
     vertex_size=30,
     vertex_label=range(g.vcount()),
     vertex_color=["lightblue" if i < 9 else "orange" for i in range(11)],
-    edge_width=[1.0 + flow.flow[i] for i in range(g.ecount())]
+    edge_width=[1.0 + flow.flow[i] for i in range(g.ecount())],
 )
 plt.show()

doc/examples_sphinx-gallery/bridges.py

@@ -7,6 +7,7 @@
 
 This example shows how to compute and visualize the `bridges <https://en.wikipedia.org/wiki/Bridge_(graph_theory)>`_ in a graph using :meth:`igraph.GraphBase.bridges`. For an example on articulation points instead, see :ref:`tutorials-articulation-points`.
 """
+
 import igraph as ig
 import matplotlib.pyplot as plt
 
@@ -37,7 +38,7 @@
     target=ax,
     vertex_size=30,
     vertex_color="lightblue",
-    vertex_label=range(g.vcount())
+    vertex_label=range(g.vcount()),
 )
 plt.show()
 
@@ -72,9 +73,9 @@
     vertex_size=30,
     vertex_color="lightblue",
     vertex_label=range(g.vcount()),
-    edge_background="#FFF0",    # transparent background color
-    edge_align_label=True,      # make sure labels are aligned with the edge
+    edge_background="#FFF0",  # transparent background color
+    edge_align_label=True,  # make sure labels are aligned with the edge
     edge_label=g.es["label"],
-    edge_label_color="red"
+    edge_label_color="red",
 )
 plt.show()

doc/examples_sphinx-gallery/cluster_contraction.py

@@ -7,6 +7,7 @@
 
 This example shows how to find the communities in a graph, then contract each community into a single node using :class:`igraph.clustering.VertexClustering`. For this tutorial, we'll use the *Donald Knuth's Les Miserables Network*, which shows the coapperances of characters in the novel *Les Miserables*.
 """
+
 import igraph as ig
 import matplotlib.pyplot as plt
 
@@ -106,7 +107,10 @@
 # Finally, we can assign colors to the clusters and plot the cluster graph,
 # including a legend to make things clear:
 palette2 = ig.GradientPalette("gainsboro", "black")
-g.es["color"] = [palette2.get(int(i)) for i in ig.rescale(cluster_graph.es["size"], (0, 255), clamp=True)]
+g.es["color"] = [
+    palette2.get(int(i))
+    for i in ig.rescale(cluster_graph.es["size"], (0, 255), clamp=True)
+]
 
 fig2, ax2 = plt.subplots()
 ig.plot(
@@ -123,7 +127,8 @@
 legend_handles = []
 for i in range(num_communities):
     handle = ax2.scatter(
-        [], [],
+        [],
+        [],
         s=100,
         facecolor=palette1.get(i),
         edgecolor="k",
@@ -133,7 +138,7 @@
 
 ax2.legend(
     handles=legend_handles,
-    title='Community:',
+    title="Community:",
     bbox_to_anchor=(0, 1.0),
     bbox_transform=ax2.transAxes,
 )

doc/examples_sphinx-gallery/complement.py

@@ -7,6 +7,7 @@
 
 This example shows how to generate the `complement graph <https://en.wikipedia.org/wiki/Complement_graph>`_ of a graph (sometimes known as the anti-graph) using :meth:`igraph.GraphBase.complementer`.
 """
+
 import igraph as ig
 import matplotlib.pyplot as plt
 import random
@@ -49,27 +50,27 @@
     layout="circle",
     vertex_color="black",
 )
-axs[0, 0].set_title('Original graph')
+axs[0, 0].set_title("Original graph")
 ig.plot(
     g2,
     target=axs[0, 1],
     layout="circle",
     vertex_color="black",
 )
-axs[0, 1].set_title('Complement graph')
+axs[0, 1].set_title("Complement graph")
 
 ig.plot(
     g_full,
     target=axs[1, 0],
     layout="circle",
     vertex_color="black",
 )
-axs[1, 0].set_title('Union graph')
+axs[1, 0].set_title("Union graph")
 ig.plot(
     g_empty,
     target=axs[1, 1],
     layout="circle",
     vertex_color="black",
 )
-axs[1, 1].set_title('Complement of union graph')
+axs[1, 1].set_title("Complement of union graph")
 plt.show()

doc/examples_sphinx-gallery/configuration.py

@@ -7,6 +7,7 @@
 
 This example shows how to use igraph's :class:`configuration instance <igraph.Configuration>` to set default igraph settings. This is useful for setting global settings so that they don't need to be explicitly stated at the beginning of every igraph project you work on.
 """
+
 import igraph as ig
 import matplotlib.pyplot as plt
 import random
@@ -18,16 +19,16 @@
 ig.config["plotting.palette"] = "rainbow"
 
 # %%
-# Then, we save them. By default, ``ig.config.save()`` will save files to
-# ``~/.igraphrc`` on Linux and Max OS X systems, or in
-# ``%USERPROFILE%\.igraphrc`` for Windows systems:
-ig.config.save()
+# The updated configuration affects only the current session. Optionally, it
+# can be saved using ``ig.config.save()``. By default, this function writes the
+# configuration to ``~/.igraphrc`` on Linux and Max OS X systems, and in
+# ``%USERPROFILE%\.igraphrc`` on Windows systems.
 
 # %%
-# The code above only needs to be run once (to store the new config options
-# into the ``.igraphrc`` file). Whenever you use igraph and this file exists,
-# igraph will read its content and use those options as defaults. For
-# example, let's create and plot a new graph to demonstrate:
+# The configuration only needs to be saved to `.igraphrc` once, and it will
+# be automatically used in all future sessions. Whenever you use igraph and
+# this file exists, igraph will read its content and use those options as
+# defaults. For example, let's create and plot a new graph to demonstrate:
 random.seed(1)
 g = ig.Graph.Barabasi(n=100, m=1)