| Version: | 1.4.0 |
| Date: | 2023-04-09 |
| Title: | Intensity Analysis of Spatial Point Patterns on Complex Networks |
| Maintainer: | Pol Llagostera <pol.llagostera@udl.cat> |
| Depends: | R (≥ 3.6.0) |
| Suggests: | spatstat (≥ 2.3.0), testthat (≥ 3.0.0) |
| Imports: | ggplot2 (≥ 3.3.2), igraph (≥ 1.2.5), intergraph (≥ 2.0.2), Matrix (≥ 1.5.1), methods (≥ 3.6.3), sna (≥ 2.6), spatstat.geom (≥ 2.3.1), spdep (≥ 1.2.1), viridis (≥ 0.5.1) |
| Description: | Tools to analyze point patterns in space occurring over planar network structures derived from graph-related intensity measures for undirected, directed, and mixed networks. This package is based on the following research: Eckardt and Mateu (2018) <doi:10.1080/10618600.2017.1391695>. Eckardt and Mateu (2021) <doi:10.1007/s11749-020-00720-4>. |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.2.3 |
| LazyData: | true |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2023-04-10 09:55:40 UTC; usuari |
| Author: | Pol Llagostera [aut, cre], Matthias Eckardt [aut] |
| Repository: | CRAN |
| Date/Publication: | 2023-04-11 06:10:03 UTC |
Retrieve an intensitynet object focused on a given area
Description
Get the intensitynet object delimited by the given window
Usage
ApplyWindow(obj, x_coords, y_coords)
## S3 method for class 'intensitynet'
ApplyWindow(obj, x_coords, y_coords)
Arguments
obj |
intensitynet object |
x_coords |
vector containing the x coordinate limits of the window |
y_coords |
vector containing the y coordinate limits of the window |
Value
intensitynet object delimited by the window (sub-part of the original)
Examples
data("und_intnet_chicago")
sub_intnet_chicago <- ApplyWindow(und_intnet_chicago,
x_coords = c(300, 900),
y_coords = c(500, 1000))
Checks if events are related to the intensitynet object
Description
Checks if events are related to the intensitynet object
Usage
AreEventsRelated(obj)
## S3 method for class 'intensitynet'
AreEventsRelated(obj)
Arguments
obj |
Intensitynet object |
Value
TRUE if related, FALSE otherwise
Examples
data("und_intnet_chicago")
AreEventsRelated(und_intnet_chicago)
Calculates the distances between all pairs of nodes from the given network
Description
Calculates the distances between all pairs of nodes from the given network
Usage
## S3 method for class 'netTools'
CalculateDistancesMtx(obj)
Arguments
obj |
netTools object -> list(): with the node coordinates 'x' and 'y' |
Value
distances matrix
Calculate all the edge intensities of the graph.
Description
Calculate all the edge intensities of the graph. It's more fast than using iteratively the function EdgeIntensity for all edges.
Usage
## S3 method for class 'intensitynet'
EdgeIntensitiesAndProportions(obj)
Arguments
obj |
intensitynet object |
Value
intensitynet class object where the graph contains all the edge intensities as an attribute
Given two nodes, calculates its edge intensity
Description
If not calculated, calculates the intensity of the edge with nodes; node_id1, node_id2. If the edge already contains an intensity, the function gives it directly without re-calculation.
Usage
## S3 method for class 'intensitynet'
EdgeIntensity(obj, node_id1, node_id2)
Arguments
obj |
intensitynet object |
node_id1 |
First node ID of the edge |
node_id2 |
Second node ID of the edge |
Value
Intensity of the edge
Plot heatmaps of a network
Description
This function uses internally the package 'ggplot2' to plot heatmaps of a network
Usage
## S3 method for class 'netTools'
GeoreferencedGgplot2(obj, ...)
Arguments
obj |
netTools object -> list( intnet: intensitynet object, data_df: dataframe( xcoord: x coordinates of the nodes, ycoord: y coordinates of the nodes, value: vector values to plot ), net_vertices: chosen vertices to plot the heatmap (or its related edges in case to plot the edge heatmap), net_edges chosen edges to plot the heatmap, can be either the edge id's or its node endpoints (e.j. c(1,2, 2,3, 7,8)), heat_type: data which the heatmap will refer, mode: ('moran', 'getis', 'v_intensity', 'e_intensity' or mark), show_events: boolean to show or not the events as orange squares, alpha optional argument to set the transparency of the events (show_events = TRUE). The range is from 0.1 (transparent) to 1 (opaque). Default: alpha = 1 ) |
... |
extra arguments for the ggplot |
Plot the given network using its node coordinates
Description
Plot the given network using its node coordinates
Usage
## S3 method for class 'netTools'
GeoreferencedPlot(obj, ...)
Arguments
obj |
netTools object -> list( intnet: intensitynet object, vertex_labels: list of labels for the vertices, edge_labels: list of labels for the edges, xy_axes: boolean to show or not the x and y axes, enable_grid: boolean to draw or not a background grid, show_events: boolean to show or not the events as orange squares, show_events option to show the events as orange squares, FALSE by default, alpha optional argument to set the transparency of the events (show_events = TRUE). The range is from 0.1 (transparent) to 1 (opaque). Default: alpha = 1, path: vector with the nodes of the path to be highlighted. Default NULL) |
... |
extra arguments for the plot |
Gives the event correction value related to the intensitynet object
Description
Gives the event correction value related to the intensitynet object
Usage
GetEventCorrection(obj)
## S3 method for class 'intensitynet'
GetEventCorrection(obj)
Arguments
obj |
intensitynet object |
Value
integer, event correction value
Examples
data("und_intnet_chicago")
GetEventCorrection(und_intnet_chicago)
Gives the events related to the intensitynet object
Description
Returns a matrix containing the events information, i.e. coordinates and categories
Usage
GetEvents(obj)
## S3 method for class 'intensitynet'
GetEvents(obj)
Arguments
obj |
intensitynet object |
Value
matrix containing the event information
Examples
data("und_intnet_chicago")
GetEvents(und_intnet_chicago)
Gives the graph related to the intensitynet object
Description
Returns the 'igraph' class network related to the intensitynet object
Usage
GetGraph(obj)
## S3 method for class 'intensitynet'
GetGraph(obj)
Arguments
obj |
intensitynet object |
Value
igraph class object
Examples
data("und_intnet_chicago")
GetGraph(und_intnet_chicago)
Gives the type of graph related to the intensitynet object
Description
Gives the type of graph related to the intensitynet object
Usage
GetGraphType(obj)
## S3 method for class 'intensitynet'
GetGraphType(obj)
Arguments
obj |
intensitynet object |
Value
graph type in characters
Examples
data("und_intnet_chicago")
GetGraphType(und_intnet_chicago)
Creates an igraph network with the given data
Description
Creates an igraph network with the given data
Set igraph network node coordinates as its attributes
Usage
## S3 method for class 'netTools'
InitGraph(obj)
## S3 method for class 'netTools'
SetNetCoords(obj)
Arguments
obj |
netTools object -> list(graph: igraph, list(): with the node coordinates 'x' and 'y') |
Value
igraph network
igraph network with the given coordinates as the attributes of the nodes
Is this class object intensitynet?
Description
Determine if the given object is from the class intensitynet
Usage
IsIntensitynet(obj)
Arguments
obj |
The object which will be checked if it belongs to the intensitynet class |
Value
boolean, 'TRUE' if the argument obj is a intensitynet object
Examples
data("und_intnet_chicago")
IsIntensitynet(und_intnet_chicago)
Calculate dependence statistics on the network
Description
It allows to compute different dependence statistics on the network for the given vector and for neighborhoods of distinct order. Such statistics are; correlation, covariance, Moran’s I and Geary’s C.
Usage
NodeGeneralCorrelation(
obj,
dep_type,
lag_max,
intensity,
partial_neighborhood = TRUE
)
## S3 method for class 'intensitynet'
NodeGeneralCorrelation(
obj,
dep_type = c("correlation", "covariance", "moran", "geary"),
lag_max,
intensity,
partial_neighborhood = TRUE
)
Arguments
obj |
intensitynet object |
dep_type |
'correlation', 'covariance', moran', 'geary'. The type of dependence statistic to be computed. |
lag_max |
Maximum geodesic lag at which to compute dependence |
intensity |
Vector containing the values to calculate the specified dependency in the network. Usually the node mean intensities. |
partial_neighborhood |
use partial neighborhood (TRUE) or cumulative (FALSE). TRUE by default |
Value
A vector containing the dependence statistics (ascending from order 0).
Examples
data("und_intnet_chicago")
g <- und_intnet_chicago$graph
gen_corr <- NodeGeneralCorrelation(und_intnet_chicago, dep_type = 'correlation', lag_max = 2,
intensity = igraph::vertex_attr(g)$intensity)
Calculates local correlations based on nodes
Description
Gives the node local Moran-I, Getis-Gstar or Geary-c correlations
Usage
NodeLocalCorrelation(obj, dep_type = "moran", intensity)
## S3 method for class 'intensitynet'
NodeLocalCorrelation(obj, dep_type = c("moran", "getis", "geary"), intensity)
Arguments
obj |
intensitynet object |
dep_type |
'moran', 'getis' or 'geary'. Type of local correlation to be computed (Moran-i, Getis-Gstar, Geary-c), default = 'moran'. |
intensity |
vector containing the values to calculate the specified correlation for each node in the network. |
Value
a vector containing two values. The first value is a vector with the specified local correlations for each node. The second values is the given intensitynet class object but with the correlations added to the node attributes of its network.
Source
*"A Local Indicator of Multivariate SpatialAssociation: Extending Geary's c, Geographical Analysis" Luc Anselin (2018) <doi:10.1111/gean.12164>
Examples
## Not run:
data("und_intnet_chicago")
g <- und_intnet_chicago$graph
data_moran <- NodeLocalCorrelation(und_intnet_chicago,
dep_type = 'moran',
intensity = igraph::vertex_attr(g)$intensity)
moran_i <- data_moran$correlation
intnet <- data_moran$intnet
## End(Not run)
Calculates the total weight of the given path
Description
Calculates the total weight of the given path
Usage
PathTotalWeight(obj, path_nodes, weight = NA)
## S3 method for class 'intensitynet'
PathTotalWeight(obj, path_nodes, weight = NA)
Arguments
obj |
intensitynet object |
path_nodes |
vector containing the node ID's of the path |
weight |
an string specifying the type of weight to be computed. If no weight type is provided, the function will calculate the total amount of edges. Default NA. |
Value
total weight of the path
Examples
data("und_intnet_chicago")
PathTotalWeight(und_intnet_chicago, c('V115', 'V123', 'V125', 'V134'), weight = 'intensity')
Given an intensitynet object, plot network heatmaps
Description
Plot the network correlations or intensities.
Usage
PlotHeatmap(
obj,
heat_type = "none",
intensity_type = "none",
net_vertices = NULL,
net_edges = NULL,
show_events = FALSE,
alpha = 1,
...
)
## S3 method for class 'intensitynet'
PlotHeatmap(
obj,
heat_type = c("none", "moran", "geary", "v_intensity", "e_intensity"),
intensity_type = c("none"),
net_vertices = NULL,
net_edges = NULL,
show_events = FALSE,
alpha = 1,
...
)
Arguments
obj |
intensitynet object |
heat_type |
a string with the desired heatmap to be plotted, the options are; 'moran': Local Moran-i correlation (with 999 permutations), 'geary': Local Geary-c correlation. The correlations will use the indicated intensity type, 'v_intensity': vertex mean intensity, 'e_intensity': edge intensity, mark name: name of the mark (string) to plot its edge proportion, 'none': plain map. |
intensity_type |
name of the vertex intensity used to plot the heatmap for moran, geary and v_intensity options (of the heat_type argument). The options are; For undirected networks: 'intensity'. For directed networks: 'intensity_in' or 'intensity_out'. For mixed networks: 'intensity_in', 'intensity_out', 'intensity_und' or 'intensity_all'. If the intensity parameter is 'none', the function will use, if exist, the intensity (undirected) or intensity_in (directed) values from the network nodes. If the heat_type is 'e_intensity', this parameter will be skipped and plot the edge intensities instead. |
net_vertices |
chosen vertices to plot the heatmap (or its related edges in case to plot the edge heatmap) |
net_edges |
chosen edges to plot the heatmap, can be either the edge id's or its node endpoints (e.j. c(1,2, 2,3, 7,8)) |
show_events |
option to show the events as orange squares, FALSE by default |
alpha |
optional argument to set the transparency of the events (show_events = TRUE). The range is from 0.1 (transparent) to 1 (opaque). Default: alpha = 1 |
... |
extra arguments for the class ggplot |
Value
The plot of the heatmap with class c("gg", "ggplot")
Examples
## Not run:
data("und_intnet_chicago")
PlotHeatmap(und_intnet_chicago, heat_type='moran')
## End(Not run)
Plot the neighbors of a node including the closer events
Description
Plot the net and the events in the neighborhood area of the given node
Usage
PlotNeighborhood(obj, node_id, ...)
## S3 method for class 'intensitynet'
PlotNeighborhood(obj, node_id, ...)
Arguments
obj |
intensitynet object |
node_id |
Id of the node which the plot will be focused |
... |
Extra arguments for plotting |
Value
No return value, just plots the neighborhood and the events.
Examples
data("und_intnet_chicago")
PlotNeighborhood(und_intnet_chicago, node_id = 'V300')
Gives the distance between an event and the line formed by two nodes.
Description
Gives the distance between an event and the line (not segment) formed by two nodes.
Usage
## S3 method for class 'netTools'
PointToLine(obj)
Arguments
obj |
netTools object -> list(p1:c(coordx, coordy), p2:c(coordx, coordy), e:c(coordx, coordy)) |
Value
the distance to the line
Gives the shortest distance between an event and a set of segments.
Description
Gives the shortest distance between an event and a set of segments.
Usage
PointToSegment(obj)
Arguments
obj |
netTools object -> list(p1:matrix(coordx, coordy), p2:matrix(coordx, coordy), e:matrix(coordx, coordy)) |
Value
distance vector to each segment
Gives the shortest distance between an event and the segment formed by two nodes.
Description
Gives the shortest distance between an event and the segment formed by two nodes.
Usage
PointToSegment_deprecated(obj)
Arguments
obj |
netTools object -> list(p1:c(coordx, coordy), p2:c(coordx, coordy), e:c(coordx, coordy)) |
Value
distance to the segment
Calculates intensity statistics for the given intensitynet object
Description
Calculates edgewise and mean nodewise intensities for the given intensitynet object and, for each edge, the proportions of all event covariates.
Usage
RelateEventsToNetwork(obj)
Arguments
obj |
intensitynet object |
Value
proper intensitynet object (Undirected, Directed, or Mixed) with a graph containing the nodewise intensity in the node attributes and the edgewise intensities and event covariate proportions as edge attributes.
Examples
data("und_intnet_chicago")
intnet_chicago <- RelateEventsToNetwork(und_intnet_chicago)
Calculates intensity statistics for the given intensitynet object
Description
Calculates edgewise and mean nodewise intensities for Directed networks and, for each edge, the proportions of all event covariates.
Usage
## S3 method for class 'intensitynetDir'
RelateEventsToNetwork(obj)
Arguments
obj |
intensitynetDir object |
Value
proper intensitynetDir object with a graph containing the nodewise intensity in the node attributes and the edgewise intensities and event covariate proportions as edge attributes.
Calculates intensity statistics for the given intensitynet object
Description
Calculates edgewise and mean nodewise intensities for Mixed networks and, for each edge, the proportions of all event covariates.
Usage
## S3 method for class 'intensitynetMix'
RelateEventsToNetwork(obj)
Arguments
obj |
intensitynetMix object |
Value
proper intensitynetMix object with a graph containing the nodewise intensity in the node attributes and the edgewise intensities and event covariate proportions as edge attributes.
Calculates intensity statistics for the given intensitynet object
Description
Calculates edgewise and mean nodewise intensities for Undirected networks and, for each edge, the proportions of all event covariates.
Usage
## S3 method for class 'intensitynetUnd'
RelateEventsToNetwork(obj)
Arguments
obj |
intensitynetUnd object |
Value
proper intensitynetUnd object with a graph containing the nodewise intensity in the node attributes and the edgewise intensities and event covariate proportions as edge attributes.
Sets the given intensities as an edge attribute to the given igraph network
Description
Sets the given intensities as an edge attribute to the given igraph network
Usage
## S3 method for class 'netTools'
SetEdgeIntensity(obj)
Arguments
obj |
netTools object -> list(graph: igraph, node_id1: node id, node_id2: node id, intensity: edge intensity) |
Value
igraph network with the given intensities as attributes of the edges
Set attributes to the network edges or nodes
Description
Set attributes to the network edges or nodes
Usage
## S3 method for class 'intensitynet'
SetNetworkAttribute(obj, where, name, value)
Arguments
obj |
intensitynet object |
where |
'vertex' or 'edge', where to set the attribute |
name |
name of the attribute |
value |
vector containing the data for the attribute |
Value
intensitynet object containing the network with the added attributes
Sets the given intensities as a node attribute to the given igraph network
Description
Sets the given intensities as a node attribute to the given igraph network
Usage
## S3 method for class 'netTools'
SetNodeIntensity(obj)
Arguments
obj |
netTools object -> list(graph: igraph, node_id: node id, intensity: node intensity) |
Value
igraph network with the given intensities as attributes of the nodes
Given two nodes, gives its shortest distance based on the minimum amount of edges
Description
Calculates the shortest distance path between two nodes (based on the minimum amount of edges). The function also returns the total weight of the path, if the weight is not available, returns the number of edges.
Usage
## S3 method for class 'intensitynet'
ShortestNodeDistance(obj, node_id1, node_id2)
Arguments
obj |
intensitynet object |
node_id1 |
id of the starting node |
node_id2 |
id of the end node |
Value
distance of the path and the nodes of the path
Given two nodes, calculates the shortest path and its total weight
Description
Calculates the shortest path between two vertices (based on the minimum amount of edges) and calculates its total weight
Usage
ShortestPath(obj, node_id1, node_id2, weight = NA, mode = "all")
## S3 method for class 'intensitynet'
ShortestPath(obj, node_id1, node_id2, weight = NA, mode = "all")
Arguments
obj |
intensitynet object |
node_id1 |
starting node |
node_id2 |
ending node |
weight |
an string, calculate the shortest path based on this type of weight. If no weight type is provided, the function will calculate the shortest path based on the minimum amount of edges. Default NA. |
mode |
Character 'in', 'out', 'all' (default). Gives whether the shortest paths to or from the given vertices should be calculated for directed graphs. If out then the shortest paths from the vertex, if in then to it will be considered. If all, the default, then the corresponding undirected graph will be used, ie. not directed paths are searched. This argument is ignored for undirected graphs. |
Value
total weight of the shortest path and the path vertices with class igraph.vs
Examples
data("und_intnet_chicago")
ShortestPath(und_intnet_chicago, node_id1 = 'V1', node_id2 = 'V300', weight = 'intensity')
Converts a directed adjacency matrix to undirected
Description
Creates a directed adjacency matrix from an Undirected one with random directions (in-out edges) but with the same connections between nodes.
Usage
## S3 method for class 'netTools'
Undirected2RandomDirectedAdjMtx(obj)
Arguments
obj |
netTools object -> list(mtx: matrix) |
Value
directed adjacency matrix with random directions
This data is an intensitynet object containing a directed network. The base data used is from Chicago, extracted from the spatstat package.
Description
This data is an intensitynet object containing a directed network. The base data used is from Chicago, extracted from the spatstat package.
Usage
dir_intnet_chicago
Format
An object of class intensitynetDir (inherits from intensitynet) of length 6.
Source
https://rdrr.io/cran/spatstat.data/man/chicago.html
Constructor of the class intensitynet.
Description
This constructor creates an intensitynet object using an adjacency matrix, the coordinates of the nodes and the coordinates of the events.
Usage
intensitynet(
adjacency_mtx,
node_coords,
event_data,
graph_type = c("undirected", "directed", "mixed"),
event_correction = 5
)
Arguments
adjacency_mtx |
Network adjacency matrix |
node_coords |
Nodes latitude and longitude matrix (coordinates) |
event_data |
DataFrame with event latitude and longitude coordinates (mandatory columns) and optional attributes related to the events |
graph_type |
Network type: 'undirected' (default), 'directed' or 'mixed' |
event_correction |
Value that determines how far can be an event to be considered part of a segment (default 5). This value highly depends on the given coordinate system |
Value
intensitynet class object containing: graph = <igraph>, events = <matrix>, graph_type = c('directed', 'undirected', 'mixed'), distances = <matrix>, event_correction = <integer>, events_related = <boolean>
Examples
library(spatstat)
data(chicago)
chicago_df <- as.data.frame(chicago[["data"]]) # Get as dataframe the data from Chicago
# Get the adjacency matrix. One way is to create an igraph object from the edge coordinates.
edges <- cbind(chicago[["domain"]][["from"]], chicago[["domain"]][["to"]])
chicago_net <- igraph::graph_from_edgelist(edges)
# And then use the igraph function 'as_adjacency_matrix'
chicago_adj_mtx <- as.matrix(igraph::as_adjacency_matrix(chicago_net))
chicago_node_coords <- data.frame(xcoord = chicago[["domain"]][["vertices"]][["x"]],
ycoord = chicago[["domain"]][["vertices"]][["y"]])
# Create the intensitynet object, in this case will be undirected
intnet_chicago <- intensitynet(chicago_adj_mtx,
node_coords = chicago_node_coords,
event_data = chicago_df)
This data is an intensitynet object containing an mixed network. The base data used is from Chicago, extracted from the spatstat package.
Description
This data is an intensitynet object containing an mixed network. The base data used is from Chicago, extracted from the spatstat package.
Usage
mix_intnet_chicago
Format
An object of class intensitynetMix (inherits from intensitynet) of length 6.
Source
https://rdrr.io/cran/spatstat.data/man/chicago.html
Calculates the mean intensity of the given node (for directed networks)
Description
Given a node, calculates its mean intensities regarding in and out edges associated with the node.
Usage
## S3 method for class 'intensitynetDir'
MeanNodeIntensity(obj, node_id)
Arguments
obj |
intensitynetDir object |
node_id |
ID of the node |
Value
mean intensities of the given node for in and out edges
Calculates the mean intensity of the given node (for mixed networks)
Description
Given a node, calculates its mean intensities depending on the edges associated with the node, those intensities are: in, out (for directed edges), undirected and total intensity.
Usage
## S3 method for class 'intensitynetMix'
MeanNodeIntensity(obj, node_id)
Arguments
obj |
intensitynetMix object |
node_id |
ID of the node |
Value
mean intensities of the given node for undirected edges, in and out directed and total intensity.
Calculates the mean intensity of the given node (for undirected networks)
Description
Calculates the mean intensity of the given node (intensity of all the edges of the node/number of edges of the node)
Usage
## S3 method for class 'intensitynetUnd'
MeanNodeIntensity(obj, node_id)
Arguments
obj |
intensitynetUnd object |
node_id |
ID of the node |
Value
mean intensity of the given node
Plot intensitynet object
Description
Plot intensitynet object
Usage
## S3 method for class 'intensitynet'
plot(
x,
vertex_labels = "none",
edge_labels = "none",
xy_axes = TRUE,
enable_grid = FALSE,
show_events = FALSE,
alpha = 1,
path = NULL,
...
)
Arguments
x |
intensitynet object |
vertex_labels |
list -> labels for the vertices |
edge_labels |
list -> labels for the edges |
xy_axes |
show the x and y axes |
enable_grid |
draw a background grid |
show_events |
option to show the events as orange squares, FALSE by default |
alpha |
optional argument to set the transparency of the events (show_events = TRUE). The range is from 0.1 (transparent) to 1 (opaque). Default: alpha = 1 |
path |
vector with the nodes of the path to be highlighted. Default NULL |
... |
extra arguments for the plot |
Value
No return value, same as graphics::plot.
Examples
data("und_intnet_chicago")
plot(und_intnet_chicago) # basic plot
plot(und_intnet_chicago, enable_grid = TRUE) # with grid
plot(und_intnet_chicago, xy_axes = FALSE) # without axes
plot(und_intnet_chicago, path = c("V1","V2","V24","V25","V26","V48")) # highlight a path
Summary of the intensitynet object
Description
Give information about the intensytinet object specific class (intensitynetUnd, intensitynetDir, or intensitynetMix), the network number of nodes, edges and events, the event correction value and, if the events had been related to the intensitynet object network.
Usage
## S3 method for class 'intensitynet'
summary(object, ...)
Arguments
object |
Intensitynet object |
... |
Extra parameters for the summary function |
Value
list containing the displayed information
Examples
data("und_intnet_chicago")
summary(und_intnet_chicago)
This data is an intensitynet object containing an undirected network. The base data used is from Chicago, extracted from the spatstat package.
Description
This data is an intensitynet object containing an undirected network. The base data used is from Chicago, extracted from the spatstat package.
Usage
und_intnet_chicago
Format
An object of class intensitynetUnd (inherits from intensitynet) of length 6.