How to use the pynets.core.thresholding.threshold_absolute function in pynets

def test_threshold_absolute(x, thr, cp):
        s = thresholding.threshold_absolute(x, thr, copy=cp)
        s_test = [val for arr in s for val in arr if val >= thr] # search for value > thr
        assert round(np.sum(s), 10) == round(np.sum(s_test), 10)

def test_thr2prob(x, thr):
        s = thresholding.threshold_absolute(thresholding.normalize(x), thr)
        s[0][0] = 0.0000001
        t = thresholding.thr2prob(s)
        assert float(len(t[np.logical_and(t < 0.001, t > 0)])) == float(0.0)

def test_density(x, thr):
        d_known = thresholding.est_density(thresholding.threshold_absolute(x, thr, copy=True))
        x = thresholding.density_thresholding(x, d_known)
        d_test = thresholding.est_density(x)
        assert np.equal(np.round(d_known, 1), np.round(d_test, 1))

Thresholded connectivity matrix

    References
    ----------
    .. Adapted from Adapted from bctpy
    """
    from pynets.core import thresholding
    np.fill_diagonal(conn_matrix, 0)

    work_thr = 0
    i = 1
    density = nx.density(nx.from_numpy_matrix(conn_matrix))
    if float(thr) < float(density):
        while float(i) < max_iters and float(work_thr) < float(1):
            work_thr = float(work_thr) + float(interval)
            density = nx.density(nx.from_numpy_matrix(thresholding.threshold_absolute(conn_matrix, work_thr)))
            print("%s%d%s%.2f%s%.2f%s" % ('Iteration ', i, ' -- with Thresh: ', float(work_thr), ' and Density: ',
                                          float(density), '...'))
            if float(thr) >= float(density):
                conn_matrix = thresholding.threshold_absolute(conn_matrix, work_thr)
                break
            i = i + 1
    else:
        print('Density of raw matrix is already greater than or equal to the target density requested')

    return conn_matrix