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.

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 = function(n) viridisLite::viridis(n), include.grid = TRUE, exclude.zeros = FALSE, valued = getOption("diffnet.valued", FALSE), ... )

graph | A dynamic graph (see |
---|---|

toa | Integer vector of length \(n\) with the times of adoption. |

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 (\(n\)). |

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 |

A list with three elements:

A numeric vector of size \(n\) with infectiousness levels

A numeric vector of size \(n\) with susceptibility levels

A list containing the class marks and counts used to draw the
plot via `filled.contour`

(see `grid_distribution`

)

A logical vector with `TRUE`

when the case was included in
the plot. (this is relevant whenever `logscale=TRUE`

)

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`

.

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()`

# 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)