This function generates a connectivity matrix that is governed by a Laplacian
distribution: `D[i,j]=exp(abs(x[i]-y[i]-shift)/disp.dist)/2/disp.dist`

1 | ```
laplacianConnMat(num.sites, disp.dist, shift = 0, boundaries = "nothing")
``` |

`num.sites` |
number of sites. Sites are assumed to be aligned on a linear coastline. |

`disp.dist` |
dispersal distance in "site" units (i.e., 1 site = 1 unit of distance) |

`shift` |
advection distance in "site" units. Defaults to 0. |

`boundaries` |
string indicating what to do at boundaries. Defaults to "nothing". Possible values include: "nothing", "conservative" and "circular" |

The `boundary`

argument can have the following different values:
"nothing" meaning do nothing special with boundaries; "conservative" meaning force
columns of matrix to sum to 1; and "circular" meaning wrap edges.

A square connectivity matrix

David M. Kaplan dmkaplan2000@gmail.com

Kaplan, D. M., Botsford, L. W., and Jorgensen, S. 2006. Dispersal per recruit: An efficient method for assessing sustainability in marine reserve networks. Ecological Applications, 16: 2248-2263.

See also `DispersalPerRecruitModel`

1 2 3 | ```
library(ConnMatTools)
cm <- laplacianConnMat(100,10,15,"circular")
image(cm)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.