Visualize adopters and cumulative adopters

1 2 3 4 5 6 | ```
plot_adopters(obj, freq = FALSE, what = c("adopt", "cumadopt"),
add = FALSE, include.legend = TRUE, include.grid = TRUE, pch = c(21,
24), type = c("b", "b"), ylim = if (!freq) c(0, 1) else NULL, lty = c(1,
1), col = c("black", "black"), bg = c("lightblue", "gray"),
xlab = "Time", ylab = ifelse(freq, "Frequency", "Proportion"),
main = "Adopters and Cumulative Adopters", ...)
``` |

`obj` |
Either a diffnet object or a cumulative a doption matrix. |

`freq` |
Logical scalar. When TRUE frequencies are plotted instead of proportions. |

`what` |
Character vector of length 2. What to plot. |

`add` |
Logical scalar. When TRUE lines and dots are added to the current graph. |

`include.legend` |
Logical scalar. When TRUE a legend of the graph is plotted. |

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

`pch` |
Integer vector of length 2. See |

`type` |
Character vector of length 2. See |

`ylim` |
Numeric vector of length 2. Sets the plotting limit for the y-axis. |

`lty` |
Numeric vector of length 2. See |

`col` |
Character vector of length 2. See |

`bg` |
Character vector of length 2. See |

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

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

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

`...` |
Further arguments passed to |

A matrix as described in `cumulative_adopt_count`

.

George G. Vega Yon

Other visualizations: `dgr`

,
`diffusionMap`

, `drawColorKey`

,
`grid_distribution`

,
`hazard_rate`

, `plot_diffnet2`

,
`plot_diffnet`

,
`plot_infectsuscep`

,
`plot_threshold`

,
`rescale_vertex_igraph`

1 2 3 4 5 6 7 8 9 10 | ```
# Generating a random diffnet -----------------------------------------------
set.seed(821)
diffnet <- rdiffnet(100, 5, seed.graph="small-world", seed.nodes="central")
plot_adopters(diffnet)
# Alternatively, we can use a TOA Matrix
toa <- sample(c(NA, 2010L,2015L), 20, TRUE)
mat <- toa_mat(toa)
plot_adopters(mat$cumadopt)
``` |

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