This function is the equivalent of ggplot2::ggplot()
in ggplot2.
It takes care of setting up the plot object along with creating the layout
for the plot based on the graph and the specification passed in.
Alternatively a layout can be prepared in advance using
create_layout
and passed as the data argument. See Details for
a description of all available layouts.
ggraph(graph, layout = "auto", ...)
create_layout(graph, layout, circular, ...)
# S3 method for default
create_layout(graph, layout, ...)
# S3 method for layout_ggraph
create_layout(graph, ...)
# S3 method for tbl_graph
create_layout(graph, layout, circular = FALSE, ...)
The object containing the graph. See Details for a list
of supported classes. Or a layout_ggraph
object as returned from
create_layout
in which case all subsequent arguments is ignored.
The type of layout to create. Either a valid string, a function, a matrix, or a data.frame (see Details)
Arguments passed on to the layout function.
Should the layout be transformed into a radial
representation. Only possible for some layouts. Defaults to FALSE
For ggraph()
an object of class gg onto which layers, scales,
etc. can be added. For create_layout()
an object inheriting from
layout_ggraph
. layout_ggraph
itself inherits from
data.frame
and can be considered as such. The data.frame contains
the node positions in the x
and y
column along with
additional columns generated by the specific layout, as well as node
parameters inherited from the graph. Additional information is stored as
attributes to the data.frame. The original graph object is stored in the
graph
attribute and the circular
attribute contains a logical
indicating whether the layout has been transformed to a circular
representation.
Following is a short description of the different layout types available in
ggraph. Each layout is further described in its own help pages. Any type of
regular graph/network data can be represented as a tbl_graph object. Because
of this the different layouts that can be applied to tbl_graph
objects are quite diverse, but not all layouts makes sense to all types of
graphs. It is up to the user to understand their data and choose an
appropriate layout. For standard node-edge diagrams igraph defines a
long range of different layout functions that are all available through the
igraph
layout where the specific layout is specified using the
algorithm
argument. In order to minimize typing all igraph algorithms
can also be passed directly into the layout
argument.
Any object that has an appropriate as_tbl_graph
method can be passed
into ggraph()
and will automatically be converted underneath.
auto
The default layout. See layout_tbl_graph_auto()
for further
details
igraph
Use one of the internal igraph layout algorithms.
The algorithm is specified using the algorithm
argument. All strings
accepted by the algorithm
argument can also be supplied directly
into layout
. See layout_tbl_graph_igraph()
for further
details
dendrogram
Lays out the nodes in a tree-like graph as a
dendrogram with leaves set at 0 and parents 1 unit above its tallest child.
See layout_tbl_graph_dendrogram()
for further details
manual
Lets the user manually specify the location of each
node. See layout_tbl_graph_manual()
for further details
linear
Arranges the nodes linearly or circularly in order to
make an arc diagram. See layout_tbl_graph_linear()
for further
details
matrix
Arranges nodes on a diagonal thus preparing it for use with
geom_edge_point()
to make a matrix plot. See layout_tbl_graph_matrix()
for further details
treemap
Creates a treemap from the graph, that is, a
space-filing subdivision of rectangles showing a weighted hierarchy. See
layout_tbl_graph_treemap()
for further details
circlepack
Creates a layout showing a hierarchy as circles
within circles. Conceptually equal to treemaps. See
layout_tbl_graph_circlepack()
for further details
partition
Create icicle or sunburst charts, where each layer
subdivides the division given by the preceding layer. See
layout_tbl_graph_partition()
for further details
hive
Positions nodes on axes spreading out from the center
based on node attributes. See layout_tbl_graph_hive()
for further
details
cactustree
Positions nodes as circles on the periphery of their
parent circle. See layout_tbl_graph_cactustree()
for further
details
backbone
Layout optimised for highly connected small-world graphs
such as social networks. See layout_tbl_graph_backbone()
for further
details
centrality
Place nodes around origin based on their centrality.
See layout_tbl_graph_centrality()
for further
details
eigen
Spectral layout based on the eigenvector of a matrix
representation of the graph. See layout_tbl_graph_eigen()
for further
details
fabric
Draw nodes as horizontal lines and connect them with
vertical lines if an edge exists between them. See
layout_tbl_graph_fabric()
for further
details
focus
Place nodes around a focus node based on their distance to
that node. See layout_tbl_graph_focus()
for further
details
pmds
Layout based on multidimensional scaling of a set of pivot
nodes, allowing MDS layout to be used on larger graphs. See
layout_tbl_graph_pmds()
for further
details
stress
Layout based on stress minimisation with better stability
than Kamada-Kawai layout. See layout_tbl_graph_stress()
for further
details
unrooted
Draws unrooted trees based on equal angle with optional
equal daylight modification. See layout_tbl_graph_unrooted()
for further
details
htree
Draws binary trees as a space filling fractal. See
layout_tbl_graph_htree()
for further details
Alternatively a matrix or a data.frame can be provided to the layout
argument. In the former case the first column will be used as x coordinates
and the second column will by used as y coordinates, further columns are
dropped. In the latter case the data.frame is used as the layout table and
must thus contain a numeric x and y column.
Lastly a function can be provided to the layout
argument. It will be called
with the graph object as its first argument and any additional argument
passed into ggraph()
/create_layout()
. The function must return either a
data.frame or an object coercible to one and have an x
and y
column, or
an object coercible to a tbl_graph
. In the latter case the node data is
extracted and used as layout (and must thus contain an x
and y
column)
and the graph will be added as the graph
attribute.
get_edges()
for extracting edge information from the
layout and get_con()
for extracting path information.
require(tidygraph)
gr <- create_notable('bull')
layout <- create_layout(gr, layout = 'igraph', algorithm = 'kk')