368 lines
13 KiB
Python
368 lines
13 KiB
Python
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"""Functions for generating grid graphs and lattices
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The :func:`grid_2d_graph`, :func:`triangular_lattice_graph`, and
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:func:`hexagonal_lattice_graph` functions correspond to the three
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`regular tilings of the plane`_, the square, triangular, and hexagonal
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tilings, respectively. :func:`grid_graph` and :func:`hypercube_graph`
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are similar for arbitrary dimensions. Useful relevant discussion can
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be found about `Triangular Tiling`_, and `Square, Hex and Triangle Grids`_
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.. _regular tilings of the plane: https://en.wikipedia.org/wiki/List_of_regular_polytopes_and_compounds#Euclidean_tilings
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.. _Square, Hex and Triangle Grids: http://www-cs-students.stanford.edu/~amitp/game-programming/grids/
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.. _Triangular Tiling: https://en.wikipedia.org/wiki/Triangular_tiling
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"""
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from itertools import repeat
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from math import sqrt
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import networkx as nx
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from networkx.classes import set_node_attributes
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from networkx.exception import NetworkXError
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from networkx.generators.classic import cycle_graph, empty_graph, path_graph
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from networkx.relabel import relabel_nodes
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from networkx.utils import flatten, nodes_or_number, pairwise
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__all__ = [
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"grid_2d_graph",
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"grid_graph",
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"hypercube_graph",
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"triangular_lattice_graph",
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"hexagonal_lattice_graph",
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]
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@nx._dispatchable(graphs=None, returns_graph=True)
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@nodes_or_number([0, 1])
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def grid_2d_graph(m, n, periodic=False, create_using=None):
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"""Returns the two-dimensional grid graph.
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The grid graph has each node connected to its four nearest neighbors.
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Parameters
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----------
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m, n : int or iterable container of nodes
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If an integer, nodes are from `range(n)`.
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If a container, elements become the coordinate of the nodes.
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periodic : bool or iterable
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If `periodic` is True, both dimensions are periodic. If False, none
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are periodic. If `periodic` is iterable, it should yield 2 bool
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values indicating whether the 1st and 2nd axes, respectively, are
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periodic.
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create_using : NetworkX graph constructor, optional (default=nx.Graph)
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Graph type to create. If graph instance, then cleared before populated.
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Returns
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-------
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NetworkX graph
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The (possibly periodic) grid graph of the specified dimensions.
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"""
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G = empty_graph(0, create_using)
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row_name, rows = m
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col_name, cols = n
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G.add_nodes_from((i, j) for i in rows for j in cols)
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G.add_edges_from(((i, j), (pi, j)) for pi, i in pairwise(rows) for j in cols)
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G.add_edges_from(((i, j), (i, pj)) for i in rows for pj, j in pairwise(cols))
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try:
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periodic_r, periodic_c = periodic
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except TypeError:
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periodic_r = periodic_c = periodic
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if periodic_r and len(rows) > 2:
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first = rows[0]
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last = rows[-1]
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G.add_edges_from(((first, j), (last, j)) for j in cols)
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if periodic_c and len(cols) > 2:
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first = cols[0]
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last = cols[-1]
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G.add_edges_from(((i, first), (i, last)) for i in rows)
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# both directions for directed
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if G.is_directed():
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G.add_edges_from((v, u) for u, v in G.edges())
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return G
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@nx._dispatchable(graphs=None, returns_graph=True)
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def grid_graph(dim, periodic=False):
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"""Returns the *n*-dimensional grid graph.
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The dimension *n* is the length of the list `dim` and the size in
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each dimension is the value of the corresponding list element.
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Parameters
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----------
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dim : list or tuple of numbers or iterables of nodes
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'dim' is a tuple or list with, for each dimension, either a number
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that is the size of that dimension or an iterable of nodes for
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that dimension. The dimension of the grid_graph is the length
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of `dim`.
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periodic : bool or iterable
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If `periodic` is True, all dimensions are periodic. If False all
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dimensions are not periodic. If `periodic` is iterable, it should
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yield `dim` bool values each of which indicates whether the
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corresponding axis is periodic.
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Returns
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-------
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NetworkX graph
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The (possibly periodic) grid graph of the specified dimensions.
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Examples
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--------
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To produce a 2 by 3 by 4 grid graph, a graph on 24 nodes:
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>>> from networkx import grid_graph
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>>> G = grid_graph(dim=(2, 3, 4))
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>>> len(G)
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24
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>>> G = grid_graph(dim=(range(7, 9), range(3, 6)))
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>>> len(G)
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6
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"""
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from networkx.algorithms.operators.product import cartesian_product
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if not dim:
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return empty_graph(0)
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try:
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func = (cycle_graph if p else path_graph for p in periodic)
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except TypeError:
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func = repeat(cycle_graph if periodic else path_graph)
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G = next(func)(dim[0])
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for current_dim in dim[1:]:
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Gnew = next(func)(current_dim)
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G = cartesian_product(Gnew, G)
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# graph G is done but has labels of the form (1, (2, (3, 1))) so relabel
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H = relabel_nodes(G, flatten)
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return H
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@nx._dispatchable(graphs=None, returns_graph=True)
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def hypercube_graph(n):
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"""Returns the *n*-dimensional hypercube graph.
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The nodes are the integers between 0 and ``2 ** n - 1``, inclusive.
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For more information on the hypercube graph, see the Wikipedia
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article `Hypercube graph`_.
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.. _Hypercube graph: https://en.wikipedia.org/wiki/Hypercube_graph
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Parameters
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----------
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n : int
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The dimension of the hypercube.
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The number of nodes in the graph will be ``2 ** n``.
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Returns
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-------
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NetworkX graph
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The hypercube graph of dimension *n*.
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"""
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dim = n * [2]
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G = grid_graph(dim)
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return G
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@nx._dispatchable(graphs=None, returns_graph=True)
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def triangular_lattice_graph(
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m, n, periodic=False, with_positions=True, create_using=None
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):
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r"""Returns the $m$ by $n$ triangular lattice graph.
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The `triangular lattice graph`_ is a two-dimensional `grid graph`_ in
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which each square unit has a diagonal edge (each grid unit has a chord).
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The returned graph has $m$ rows and $n$ columns of triangles. Rows and
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columns include both triangles pointing up and down. Rows form a strip
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of constant height. Columns form a series of diamond shapes, staggered
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with the columns on either side. Another way to state the size is that
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the nodes form a grid of `m+1` rows and `(n + 1) // 2` columns.
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The odd row nodes are shifted horizontally relative to the even rows.
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Directed graph types have edges pointed up or right.
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Positions of nodes are computed by default or `with_positions is True`.
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The position of each node (embedded in a euclidean plane) is stored in
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the graph using equilateral triangles with sidelength 1.
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The height between rows of nodes is thus $\sqrt(3)/2$.
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Nodes lie in the first quadrant with the node $(0, 0)$ at the origin.
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.. _triangular lattice graph: http://mathworld.wolfram.com/TriangularGrid.html
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.. _grid graph: http://www-cs-students.stanford.edu/~amitp/game-programming/grids/
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.. _Triangular Tiling: https://en.wikipedia.org/wiki/Triangular_tiling
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Parameters
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----------
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m : int
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The number of rows in the lattice.
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n : int
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The number of columns in the lattice.
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periodic : bool (default: False)
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If True, join the boundary vertices of the grid using periodic
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boundary conditions. The join between boundaries is the final row
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and column of triangles. This means there is one row and one column
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fewer nodes for the periodic lattice. Periodic lattices require
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`m >= 3`, `n >= 5` and are allowed but misaligned if `m` or `n` are odd
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with_positions : bool (default: True)
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Store the coordinates of each node in the graph node attribute 'pos'.
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The coordinates provide a lattice with equilateral triangles.
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Periodic positions shift the nodes vertically in a nonlinear way so
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the edges don't overlap so much.
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create_using : NetworkX graph constructor, optional (default=nx.Graph)
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Graph type to create. If graph instance, then cleared before populated.
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Returns
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-------
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NetworkX graph
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The *m* by *n* triangular lattice graph.
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"""
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H = empty_graph(0, create_using)
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if n == 0 or m == 0:
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return H
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if periodic:
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if n < 5 or m < 3:
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msg = f"m > 2 and n > 4 required for periodic. m={m}, n={n}"
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raise NetworkXError(msg)
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N = (n + 1) // 2 # number of nodes in row
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rows = range(m + 1)
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cols = range(N + 1)
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# Make grid
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H.add_edges_from(((i, j), (i + 1, j)) for j in rows for i in cols[:N])
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H.add_edges_from(((i, j), (i, j + 1)) for j in rows[:m] for i in cols)
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# add diagonals
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H.add_edges_from(((i, j), (i + 1, j + 1)) for j in rows[1:m:2] for i in cols[:N])
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H.add_edges_from(((i + 1, j), (i, j + 1)) for j in rows[:m:2] for i in cols[:N])
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# identify boundary nodes if periodic
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from networkx.algorithms.minors import contracted_nodes
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if periodic is True:
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for i in cols:
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H = contracted_nodes(H, (i, 0), (i, m))
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for j in rows[:m]:
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H = contracted_nodes(H, (0, j), (N, j))
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elif n % 2:
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# remove extra nodes
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H.remove_nodes_from((N, j) for j in rows[1::2])
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# Add position node attributes
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if with_positions:
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ii = (i for i in cols for j in rows)
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jj = (j for i in cols for j in rows)
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xx = (0.5 * (j % 2) + i for i in cols for j in rows)
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h = sqrt(3) / 2
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if periodic:
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yy = (h * j + 0.01 * i * i for i in cols for j in rows)
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else:
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yy = (h * j for i in cols for j in rows)
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pos = {(i, j): (x, y) for i, j, x, y in zip(ii, jj, xx, yy) if (i, j) in H}
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set_node_attributes(H, pos, "pos")
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return H
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@nx._dispatchable(graphs=None, returns_graph=True)
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def hexagonal_lattice_graph(
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m, n, periodic=False, with_positions=True, create_using=None
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):
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"""Returns an `m` by `n` hexagonal lattice graph.
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The *hexagonal lattice graph* is a graph whose nodes and edges are
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the `hexagonal tiling`_ of the plane.
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The returned graph will have `m` rows and `n` columns of hexagons.
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`Odd numbered columns`_ are shifted up relative to even numbered columns.
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Positions of nodes are computed by default or `with_positions is True`.
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Node positions creating the standard embedding in the plane
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with sidelength 1 and are stored in the node attribute 'pos'.
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`pos = nx.get_node_attributes(G, 'pos')` creates a dict ready for drawing.
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.. _hexagonal tiling: https://en.wikipedia.org/wiki/Hexagonal_tiling
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.. _Odd numbered columns: http://www-cs-students.stanford.edu/~amitp/game-programming/grids/
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Parameters
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----------
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m : int
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The number of rows of hexagons in the lattice.
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n : int
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The number of columns of hexagons in the lattice.
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periodic : bool
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Whether to make a periodic grid by joining the boundary vertices.
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For this to work `n` must be even and both `n > 1` and `m > 1`.
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The periodic connections create another row and column of hexagons
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so these graphs have fewer nodes as boundary nodes are identified.
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with_positions : bool (default: True)
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Store the coordinates of each node in the graph node attribute 'pos'.
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The coordinates provide a lattice with vertical columns of hexagons
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offset to interleave and cover the plane.
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Periodic positions shift the nodes vertically in a nonlinear way so
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the edges don't overlap so much.
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create_using : NetworkX graph constructor, optional (default=nx.Graph)
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Graph type to create. If graph instance, then cleared before populated.
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If graph is directed, edges will point up or right.
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Returns
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-------
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NetworkX graph
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The *m* by *n* hexagonal lattice graph.
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"""
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G = empty_graph(0, create_using)
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if m == 0 or n == 0:
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return G
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if periodic and (n % 2 == 1 or m < 2 or n < 2):
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msg = "periodic hexagonal lattice needs m > 1, n > 1 and even n"
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raise NetworkXError(msg)
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M = 2 * m # twice as many nodes as hexagons vertically
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rows = range(M + 2)
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cols = range(n + 1)
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# make lattice
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col_edges = (((i, j), (i, j + 1)) for i in cols for j in rows[: M + 1])
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row_edges = (((i, j), (i + 1, j)) for i in cols[:n] for j in rows if i % 2 == j % 2)
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G.add_edges_from(col_edges)
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G.add_edges_from(row_edges)
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# Remove corner nodes with one edge
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G.remove_node((0, M + 1))
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G.remove_node((n, (M + 1) * (n % 2)))
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# identify boundary nodes if periodic
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from networkx.algorithms.minors import contracted_nodes
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if periodic:
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for i in cols[:n]:
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G = contracted_nodes(G, (i, 0), (i, M))
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for i in cols[1:]:
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G = contracted_nodes(G, (i, 1), (i, M + 1))
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for j in rows[1:M]:
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G = contracted_nodes(G, (0, j), (n, j))
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G.remove_node((n, M))
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# calc position in embedded space
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ii = (i for i in cols for j in rows)
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|
jj = (j for i in cols for j in rows)
|
||
|
|
xx = (0.5 + i + i // 2 + (j % 2) * ((i % 2) - 0.5) for i in cols for j in rows)
|
||
|
|
h = sqrt(3) / 2
|
||
|
|
if periodic:
|
||
|
|
yy = (h * j + 0.01 * i * i for i in cols for j in rows)
|
||
|
|
else:
|
||
|
|
yy = (h * j for i in cols for j in rows)
|
||
|
|
# exclude nodes not in G
|
||
|
|
pos = {(i, j): (x, y) for i, j, x, y in zip(ii, jj, xx, yy) if (i, j) in G}
|
||
|
|
set_node_attributes(G, pos, "pos")
|
||
|
|
return G
|