public RMatGraph<T> setConstants(float a, float b, float c) {
		Preconditions.checkArgument(a >= 0.0f && b >= 0.0f && c >= 0.0f && a + b + c <= 1.0f,
			"RMat parameters A, B, and C must be non-negative and sum to less than or equal to one");

		this.a = a;
		this.b = b;
		this.c = c;

		return this;
	}
public RMatGraph < T > setConstants ( float a , float b , float c ) { Preconditions . checkArgument ( a >= 0.0f && b >= 0.0f && c >= 0.0f && a + b + c <= 1.0f , "RMat parameters A, B, and C must be non-negative and sum to less than or equal to one" ) ; this . a = a ; this . b = b ; this . c = c ; return this ; }
The parameters for recursively subdividing the adjacency matrix.

<p>Setting A = B = C = 0.25 emulates the Erdős–Rényi model.

<p>Graph500 uses A = 0.57, B = C = 0.19.

@param a likelihood of source bit = 0, target bit = 0
@param b likelihood of source bit = 0, target bit = 1
@param c likelihood of source bit = 1, target bit = 0
@return this