The function gridFiltration computes the Persistence Diagram of a filtration of sublevel sets (or superlevel sets) of a function evaluated over a grid of points in arbitrary dimension d.
gridFiltration(
X = NULL, FUN = NULL, lim = NULL, by = NULL, FUNvalues = NULL,
maxdimension = max(NCOL(X), length(dim(FUNvalues))) - 1,
sublevel = TRUE, printProgress = FALSE, ...)The function gridFiltration returns a list with the following elements:
a list representing the complex. Its i-th element represents the vertices of i-th simplex.
a vector representing the filtration values. Its i-th element represents the filtration value of i-th simplex.
a logical variable indicating if the filtration values are in increasing order (TRUE) or in decreasing order (FALSE).
only if both lim and by are not NULL: a matrix representing the coordinates of vertices. Its i-th row represents the coordinate of i-th vertex.
an \(n\) by \(d\) matrix of coordinates, used by the function FUN, where \(n\) is the number of points stored in X and \(d\) is the dimension of the space. NULL if this option is not used. The default value is NULL.
a function whose inputs are 1) an \(n\) by \(d\) matrix of coordinates X, 2) an \(m\) by \(d\) matrix of coordinates Grid, 3) an optional smoothing parameter, and returns a numeric vector of length \(m\). For example see distFct, kde, and dtm which compute the distance function, the kernel density estimator and the distance to measure, over a grid of points using the input X. Note that Grid is not an input of gridFiltration, but is automatically computed by the function using lim, and by. NULL if this option is not used. The default value is NULL.
a \(2\) by \(d\) matrix, where each column specifying the range of each dimension of the grid, over which the function FUN is evaluated. NULL if this option is not used. The default value is NULL.
either a number or a vector of length \(d\) specifying space between points of the grid in each dimension. If a number is given, then same space is used in each dimension. NULL if this option is not used. The default value is NULL.
an \(m1 * m2 * ... * md\) array of function values over \(m1 * m2 * ... * md\) grid, where \(mi\) is the number of scales of grid on \(ith\) dimension. NULL if this option is not used. The default value is NULL.
a number that indicates the maximum dimension of the homological features to compute: 0 for connected components, 1 for loops, 2 for voids and so on. The default value is \(d - 1\), which is (dimension of embedding space - 1).
a logical variable indicating if the Persistence Diagram should be computed for sublevel sets (TRUE) or superlevel sets (FALSE) of the function. The default value is TRUE.
if TRUE a progress bar is printed. The default value is FALSE.
additional parameters for the function FUN.
Brittany T. Fasy, Jisu Kim, and Fabrizio Lecci
If the values of X, FUN are set, then FUNvalues should be NULL. In this case, gridFiltration evaluates the function FUN over a grid. If the value of FUNvalues is set, then X, FUN should be NULL. In this case, FUNvalues is used as function values over the grid.
Once function values are either computed or given, gridFiltration constructs a filtration by triangulating the grid and considering the simplices determined by the values of the function of dimension up to maxdimension+1.
Fasy B, Lecci F, Rinaldo A, Wasserman L, Balakrishnan S, Singh A (2013). "Statistical Inference For Persistent Homology." (arXiv:1303.7117). Annals of Statistics.
Morozov D (2007). "Dionysus, a C++ library for computing persistent homology." https://www.mrzv.org/software/dionysus/
Bauer U, Kerber M, Reininghaus J (2012). "PHAT, a software library for persistent homology." https://bitbucket.org/phat-code/phat/
summary.diagram, plot.diagram,
distFct, kde, kernelDist, dtm,
alphaComplexDiag, alphaComplexDiag, ripsDiag
# input data
n <- 10
XX <- circleUnif(n)
## Ranges of the grid
Xlim <- c(-1, 1)
Ylim <- c(-1, 1)
lim <- cbind(Xlim, Ylim)
by <- 1
#Distance Function Diagram of the sublevel sets
FltGrid <- gridFiltration(
XX, distFct, lim = lim, by = by, sublevel = TRUE, printProgress = TRUE)
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