extract_networks: Extract networks from a moving window
In tbonne/netTS: netTS: network time series

This function will create a time series of networks from a dataframe with relational events and a time stamp.

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extract_networks(data, windowsize, windowshift, directed = FALSE,
  SRI = FALSE, effortFun = NULL, effortData = NULL, winstart = NULL,
  winend = NULL)

`data`	A dataframe with relational data in the first two columns, and a time stamp in the third column. An optional column with a weight can be added if there is a duration or magnitude for each interaction (column name for this should be set to 'weight'). Note: time stamps should be in ymd or ymd_hms format. The lubridate package can be very helpful in organizing times.
`windowsize`	The size of each window in which to generate a network.
`windowshift`	The amount of time to shift the window when generating networks.
`directed`	Whether to consider the network as directed or not (TRUE/FALSE).
`SRI`	Whether to use the simple ratio index (Default=FALSE).
`effortFun`	This is a function that takes as input the data within a window of time and returns the total sampling effort.
`effortData`	This is a dataframe containing the data used to calculate sampling effort. The first column should contain timedate values.