Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/diffnet-methods.r

After calculating infectiousness and susceptibility of each individual on the
network, it creates an `nlevels`

by `nlevels`

matrix indicating the
number of individuals that lie within each cell, and draws a heatmap.

1 2 3 4 5 6 7 8 9 | ```
plot_infectsuscep(graph, toa, t0 = NULL, normalize = TRUE, K = 1L,
r = 0.5, expdiscount = FALSE, bins = 20, nlevels = round(bins/2),
h = NULL, logscale = TRUE,
main = "Distribution of Infectiousness and\nSusceptibility",
xlab = "Infectiousness of ego", ylab = "Susceptibility of ego",
sub = ifelse(logscale, "(in log-scale)", NA),
color.palette = grDevices::colorRampPalette(c("skyblue", "tomato")),
include.grid = TRUE, exclude.zeros = FALSE,
valued = getOption("diffnet.valued", FALSE), ...)
``` |

`graph` |
A dynamic graph (see |

`toa` |
Integer vector of length |

`t0` |
Integer scalar. See |

`normalize` |
Logical scalar. Passed to infection/susceptibility. |

`K` |
Integer scalar. Passed to infection/susceptibility. |

`r` |
Numeric scalar. Passed to infection/susceptibility. |

`expdiscount` |
Logical scalar. Passed to infection/susceptibility. |

`bins` |
Integer scalar. Size of the grid ( |

`nlevels` |
Integer scalar. Number of levels to plot (see |

`h` |
Numeric vector of length 2. Passed to |

`logscale` |
Logical scalar. When TRUE the axis of the plot will be presented in log-scale. |

`main` |
Character scalar. Title of the graph. |

`xlab` |
Character scalar. Title of the x-axis. |

`ylab` |
Character scalar. Title of the y-axis. |

`sub` |
Character scalar. Subtitle of the graph. |

`color.palette` |
a color palette function to be used to assign colors in the plot (see |

`include.grid` |
Logical scalar. When TRUE, the grid of the graph is drawn. |

`exclude.zeros` |
Logical scalar. When TRUE, observations with zero values |

`valued` |
Logical scalar. When FALSE non-zero values in the adjmat are set to one.
in infect or suscept are excluded from the graph. This is done explicitly when |

`...` |
Additional parameters to be passed to |

This plotting function was inspired by Aral, S., & Walker, D. (2012).

By default the function will try to apply a kernel smooth function via
`kde2d`

. If not possible (because not enought data points), then
the user should try changing the parameter `h`

or set it equal to zero.

`toa`

is passed to `infection/susceptibility`

.

A list with three elements:

`infect` |
A numeric vector of size |

`suscep` |
A numeric vector of size |

`coords` |
A list containing the class marks and counts used to draw the
plot via |

`complete` |
A logical vector with |

George G. Vega Yon

Aral, S., & Walker, D. (2012). "Identifying Influential and Susceptible Members of Social Networks". Science, 337(6092), 337–341. http://doi.org/10.1126/science.1215842

Infectiousness and susceptibility are computed via `infection`

and
`susceptibility`

.

Other visualizations: `dgr`

,
`diffusionMap`

, `drawColorKey`

,
`grid_distribution`

,
`hazard_rate`

, `plot_adopters`

,
`plot_diffnet2`

, `plot_diffnet`

,
`plot_threshold`

,
`rescale_vertex_igraph`

1 2 3 4 5 6 7 8 9 | ```
# Generating a random graph -------------------------------------------------
set.seed(1234)
n <- 100
nper <- 20
graph <- rgraph_er(n,nper, p=.2, undirected = FALSE)
toa <- sample(1:(1+nper-1), n, TRUE)
# Visualizing distribution of suscep/infect
out <- plot_infectsuscep(graph, toa, K=3, logscale = FALSE)
``` |

netdiffuseR documentation built on Nov. 17, 2017, 3:59 a.m.

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