LIP_CREATE_HILBERT_DISTRIBUTION_IN_CORE

LIP_CREATE_HILBERT_DISTRIBUTION_IN_CORE(datamap,new_datamap, coordinatesX, coordinatesY, coordinatesZ, vertex, edge, minedge, sample_count)

IN	datamap	current distribution (handle)
OUT	new_datamap	new (irregular) distribution (handle)
IN	coordinatesX	X coordinates of points in data array(double)
IN	coordinatesY	Y coordinates of points in data array (double)
IN	coordinatesZ	Z coordinates of points in data array
		can be null in 2D case (double)
IN	vertex	the coordinates of the vertex needed for counting
		Hilbert's indices (handle)
IN	edge	the length of edge of the square 2D (or cube 3D)
		needed for counting Hilbert indices (double)
IN	minedge	resolution of the indexing scheme
		(the length of the minimal distance between points
		that are distinguished by Hilbert's
		indexing scheme)
IN	sample_count	the quantity of the sample
		needed for counting Hilbert indices (integer)

C syntax:

int LIP_create_hilbert_distribution_in_core (LIP_Datamap datamap, LIP_Datamap *new_datamap, double *coX, double *coY, double *coZ, double* vertex, double edge, double minedge, int sample_count)

Java syntax:
Class Datamap:

public void create_hilbert_distribution_in_core (Datamap datamap, VDouble coX, VDouble coY, VDouble coZ, VDouble vertex, double edge, double minedge, int samplecount)

LIP_CREATE_HILBERT_DISTRIBUTION_IN_CORE creates a new_datamap object which contains a translation table that describes how a data array is partitioned among processors. Only a part of the translation table is filled - the ranks of processors that are the new owners of the data are written to the new_datamap. This is the in-core version of the algorithm that assumes that the data arrays and the translation table are in-core. To obtain the local indices of the data one should call remap function(see below).