spatial_morphers  R Documentation 
Spatial morphers form spatial addons to the set of
morphers
provided by tidygraph
. These
functions are not meant to be called directly. They should either be passed
into morph
to create a temporary alternative
representation of the input network. Such an alternative representation is a
list of one or more network objects. Single elements of that list can be
extracted directly as a new network by passing the morpher to
convert
instead, to make the changes lasting rather
than temporary. Alternatively, if the morphed state contains multiple
elements, all of them can be extracted together inside a
tbl_df
by passing the morpher to
crystallise
.
to_spatial_contracted( x, ..., simplify = FALSE, summarise_attributes = "ignore", store_original_data = FALSE ) to_spatial_directed(x) to_spatial_explicit(x, ...) to_spatial_neighborhood(x, node, threshold, weights = NULL, from = TRUE, ...) to_spatial_shortest_paths(x, ...) to_spatial_simple( x, remove_multiple = TRUE, remove_loops = TRUE, summarise_attributes = "first", store_original_data = FALSE ) to_spatial_smooth(x, store_original_data = FALSE) to_spatial_subdivision(x) to_spatial_subset(x, ..., subset_by = NULL) to_spatial_transformed(x, ...)
x 
An object of class 
... 
Arguments to be passed on to other functions. See the description of each morpher for details. 
simplify 
Should the network be simplified after contraction? This
means that multiple edges and loop edges will be removed. Multiple edges
are introduced by contraction when there are several connections between
the same groups of nodes. Loop edges are introduced by contraction when
there are connections within a group. Note however that setting this to

summarise_attributes 
Whenever multiple features (i.e. nodes and/or
edges) are merged into a single feature during morphing, how should their
attributes be combined? Several options are possible, see

store_original_data 
Whenever multiple features (i.e. nodes and/or
edges) are merged into a single feature during morphing, should the data of
the original features be stored as an attribute of the new feature, in a
column named 
node 
The geospatial point for which the neighborhood will be
calculated. Can be an integer, referring to the index of the node for which
the neighborhood will be calculated. Can also be an object of class

threshold 
The threshold distance to be used. Only nodes within the threshold distance from the reference node will be included in the neighborhood. Should be a numeric value in the same units as the weight values used for distance calculation. 
weights 
The edge weights used to calculate distances on the network.
Can be a numeric vector giving edge weights, or a column name referring to
an attribute column in the edges table containing those weights. If set to

from 
Should distances be calculated from the reference node towards
the other nodes? Defaults to 
remove_multiple 
Should multiple edges be merged into one. Defaults
to 
remove_loops 
Should loop edges be removed. Defaults to 
subset_by 
Whether to create subgraphs based on nodes or edges. 
It also possible to create your own morphers. See the documentation
of morph
for the requirements for custom morphers.
Either a morphed_sfnetwork
, which is a list of one or more
sfnetwork
objects, or a morphed_tbl_graph
, which is a
list of one or more tbl_graph
objects. See the
description of each morpher for details.
to_spatial_contracted
: Combine groups of nodes into a single node per
group. ...
is forwarded to group_by
to
create the groups. The centroid of the group of nodes will be used as
geometry of the contracted node. If edge are spatially explicit, edge
geometries are updated accordingly such that the valid spatial network
structure is preserved. Returns a morphed_sfnetwork
containing a
single element of class sfnetwork
.
to_spatial_directed
: Make a network directed in the direction given
by the linestring geometries of the edges. Differs from
to_directed
, which makes a network directed based
on the node indices given in the from
and to
columns. In
undirected networks these indices may not correspond with the endpoints of
the linestring geometries. Returns a morphed_sfnetwork
containing a
single element of class sfnetwork
. This morpher requires edges
to be spatially explicit. If not, use to_directed
.
to_spatial_explicit
: Create linestring geometries between source
and target nodes of edges. If the edges data can be directly converted to
an object of class sf
using st_as_sf
,
extra arguments can be provided as ...
and will be forwarded to
st_as_sf
internally. Otherwise, straight lines will be
drawn between the source and target node of each edge. Returns a
morphed_sfnetwork
containing a single element of class
sfnetwork
.
to_spatial_neighborhood
: Limit a network to the spatial neighborhood of
a specific node. ...
is forwarded to
node_distance_from
(if from
is TRUE
)
or node_distance_to
(if from
is
FALSE
). Returns a morphed_sfnetwork
containing a single
element of class sfnetwork
.
to_spatial_shortest_paths
: Limit a network to those nodes and edges that
are part of the shortest path between two nodes. ...
is evaluated in
the same manner as st_network_paths
with
type = 'shortest'
. Returns a morphed_sfnetwork
that may
contain multiple elements of class sfnetwork
, depending on
the number of requested paths. When unmorphing only the first instance of
both the node and edge data will be used, as the the same node and/or edge
can be present in multiple paths.
to_spatial_simple
: Remove loop edges and/or merges multiple edges
into a single edge. Multiple edges are edges that have the same source and
target nodes (in directed networks) or edges that are incident to the same
nodes (in undirected networks). When merging them into a single edge, the
geometry of the first edge is preserved. The order of the edges can be
influenced by calling arrange
before simplifying.
Returns a morphed_sfnetwork
containing a single element of class
sfnetwork
.
to_spatial_smooth
: Construct a smoothed version of the network by
iteratively removing pseudo nodes, while preserving the connectivity of the
network. In the case of directed networks, pseudo nodes are those nodes that
have only one incoming and one outgoing edge. In undirected networks, pseudo
nodes are those nodes that have two incident edges. Connectivity of the
network is preserved by concatenating the incident edges of each removed
pseudo node. Returns a morphed_sfnetwork
containing a single element
of class sfnetwork
.
to_spatial_subdivision
: Construct a subdivision of the network by
subdividing edges at each interior point that is equal to any
other interior or boundary point in the edges table. Interior points in this
sense are those points that are included in their linestring geometry
feature but are not endpoints of it, while boundary points are the endpoints
of the linestrings. The network is reconstructed after subdivision such that
edges are connected at the points of subdivision. Returns a
morphed_sfnetwork
containing a single element of class
sfnetwork
. This morpher requires edges to be spatially
explicit.
to_spatial_subset
: Subset the network by applying a spatial
filter, i.e. a filter on the geometry column based on a spatial predicate.
...
is evaluated in the same manner as st_filter
.
Returns a morphed_sfnetwork
containing a single element of class
sfnetwork
. For filters on an attribute column, use
to_subgraph
.
to_spatial_transformed
: Transform the geospatial coordinates of the
network into a different coordinate reference system. ...
is
evaluated in the same manner as st_transform
.
Returns a morphed_sfnetwork
containing a single element of class
sfnetwork
.
The vignette on spatial morphers.
library(sf, quietly = TRUE) library(tidygraph, quietly = TRUE) net = as_sfnetwork(roxel, directed = FALSE) %>% st_transform(3035) # Temporary changes with morph and unmorph. net %>% activate("edges") %>% mutate(weight = edge_length()) %>% morph(to_spatial_shortest_paths, from = 1, to = 10) %>% mutate(in_paths = TRUE) %>% unmorph() # Lasting changes with convert. net %>% activate("edges") %>% mutate(weight = edge_length()) %>% convert(to_spatial_shortest_paths, from = 1, to = 10)
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