View source: R/ppmlasso_functions.R

griddify | R Documentation |

This function ensures that the coordinates of the supplied geo-referenced matrix of environmental grids constitutes a rectangular grid.

griddify(envframe, tol = 0.01, coord = c("X", "Y"))

`envframe` |
The geo-referenced matrix of environmental grids. |

`tol` |
The tolerance level within which to correct coordinate errors. |

`coord` |
A vector containing the names of the longitude and latitude coordinates. |

The functions in the `ppmlasso`

package require a set of quadrature points along a rectangular grid. At times a set of quadrature points with a desired spatial resolution of *x_δ \times y_δ* will have some minor machine error in some coordinates such that the coordinates as supplied do not consistute a rectangular grid. The `griddify`

function corrects this error as follows:

Let *\{x_1, x_2, …, x_n\}* and *\{y_1, y_2, …, y_n\}* be the supplied coordinates contained in `envframe`

. The function first determines the spatial resolution *x_δ \times y_δ* based on the median of the differences in the unique values of *x_i* and *y_i* as well as the coordinates of a rectangular grid with this spatial resolution *\{x^{grid}_1, x^{grid}_2, …, x^{grid}_n\}* and *\{y^{grid}_1, y^{grid}_2, …, y^{grid}_n\}*. Given the tolerance *ε* supplied to `tol`

, any coordinate *x_i* for which *0 < ≤ft|x_i - x^{grid}_i\right| ≤q ε \times x_δ* will be adjusted to *x^{grid}_i*. Likewise, any coordinate *y_i* for which *0 < ≤ft|y_i - y^{grid}_i\right| ≤q ε \times y_δ* will be adjusted to *y^{grid}_i*.

Any environmental variables contained in `envframe`

are left unchanged.

A data frame containing the coordinates on a rectangular grid as well as any environmental variables left unchanged.

Ian W. Renner

X = seq(0, 5, 1) Y = seq(1, 11, 2) XY = expand.grid(X, Y) # generate 1 x 2 rectangular grid names(XY) = c("X", "Y") #move some coordinates off of rectangular grid XY$X[1] = XY$X[1] - 0.01 XY$Y[1] = XY$Y[1] - 0.01 XY$X[7] = XY$X[7] + 0.01 XY$Y[7] = XY$Y[7] + 0.01 #generate environmental variables XY$V1 = 0.1*XY$X + 0.2*XY$Y + rnorm(36, 0, 1) XY$V2 = -0.2*XY$X + 0.1*XY$Y + 0.05*XY$X*XY$Y + rnorm(36, 0, 5) XY_grid = griddify(XY)

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