(N, D)
return result
Generate (N x D) numpy array of Sobol sequence samples
Generate (N x D) numpy array of Sobol sequence samples
Generate ( N x D ) numpy array of Sobol sequence samples
def sample(N, D):
    """Generate (N x D) numpy array of Sobol sequence samples"""
    scale = 31
    result = np.zeros([N, D])
    
    if D > len(directions) + 1:
        raise ValueError("Error in Sobol sequence: not enough dimensions")

    L = int(math.ceil(math.log(N) / math.log(2)))

    if L > scale:
        raise ValueError("Error in Sobol sequence: not enough bits")

    for i in range(D):
        V = np.zeros(L + 1, dtype=long)

        if i == 0:
            for j in range(1, L + 1):
                V[j] = 1 << (scale - j)  # all m's = 1
        else:
            m = np.array(directions[i - 1], dtype=int)
            a = m[0]
            s = len(m) - 1

            # The following code discards the first row of the ``m`` array
            # Because it has floating point errors, e.g. values of 2.24e-314
            if L <= s:
                for j in range(1, L + 1):
                    V[j] = m[j] << (scale - j)
            else:
                for j in range(1, s + 1):
                    V[j] = m[j] << (scale - j)
                for j in range(s + 1, L + 1):
                    V[j] = V[j - s] ^ (V[j - s] >> s)
                    for k in range(1, s):
                        V[j] ^= ((a >> (s - 1 - k)) & 1) * V[j - k]

        X = long(0)
        for j in range(1, N):
            X ^= V[index_of_least_significant_zero_bit(j - 1)]
            result[j][i] = float(X / math.pow(2, scale))

    return result
def sample ( N , D ) : scale = 31 result = np . zeros ( [ N , D ] ) if D > len ( directions ) + 1 : raise ValueError ( "Error in Sobol sequence: not enough dimensions" ) L = int ( math . ceil ( math . log ( N ) / math . log ( 2 ) ) ) if L > scale : raise ValueError ( "Error in Sobol sequence: not enough bits" ) for i in range ( D ) : V = np . zeros ( L + 1 , dtype = long ) if i == 0 : for j in range ( 1 , L + 1 ) : V [ j ] = 1 << ( scale - j ) # all m's = 1 else : m = np . array ( directions [ i - 1 ] , dtype = int ) a = m [ 0 ] s = len ( m ) - 1 # The following code discards the first row of the ``m`` array # Because it has floating point errors, e.g. values of 2.24e-314 if L <= s : for j in range ( 1 , L + 1 ) : V [ j ] = m [ j ] << ( scale - j ) else : for j in range ( 1 , s + 1 ) : V [ j ] = m [ j ] << ( scale - j ) for j in range ( s + 1 , L + 1 ) : V [ j ] = V [ j - s ] ^ ( V [ j - s ] >> s ) for k in range ( 1 , s ) : V [ j ] ^= ( ( a >> ( s - 1 - k ) ) & 1 ) * V [ j - k ] X = long ( 0 ) for j in range ( 1 , N ) : X ^= V [ index_of_least_significant_zero_bit ( j - 1 ) ] result [ j ] [ i ] = float ( X / math . pow ( 2 , scale ) ) return result