"""
.. _tutorials-configuration:

======================
Configuration Instance
======================

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

# %%
# First we define the default plotting backend, layout, and color palette.
ig.config["plotting.backend"] = "matplotlib"
ig.config["plotting.layout"] = "fruchterman_reingold"
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 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:
random.seed(1)
g = ig.Graph.Barabasi(n=100, m=1)

# %%
# We now calculate a color value between 0-200 for all nodes, for instance by
# computing the vertex betweenness:
betweenness = g.betweenness()
colors = [int(i * 200 / max(betweenness)) for i in betweenness]

# %%
# Finally, we can plot the graph. You will notice that even though we did not
# create a dedicated figure and axes, matplotlib is now used by default:
ig.plot(g, vertex_color=colors, vertex_size=15, edge_width=0.3)
plt.show()

# %%
# The full list of config settings can be found at
# :class:`igraph.Configuration`.
#
# .. note::
#
#    You can have multiple config files: specify each location via
#    ``ig.config.save("./path/to/config/file")``. To load a specific config,
#    import igraph and then call ``ig.config.load("./path/to/config/file")``
#
#
# .. note::
#
#     To use a consistent style between individual plots (e.g. vertex sizes,
#     colors, layout etc.) check out :ref:`tutorials-visual-style`.