Function test_SymLogNorm

lib/matplotlib/tests/test_colors.py:729–759

Test SymLogNorm behavior

()

def test_SymLogNorm():
    """
    Test SymLogNorm behavior
    """
    norm = mcolors.SymLogNorm(3, vmax=5, linscale=1.2, base=np.e)
    vals = np.array([-30, -1, 2, 6], dtype=float)
    normed_vals = norm(vals)
    expected = [0., 0.53980074, 0.826991, 1.02758204]
    assert_array_almost_equal(normed_vals, expected)
    _inverse_tester(norm, vals)
    _scalar_tester(norm, vals)
    _mask_tester(norm, vals)

    # Ensure that specifying vmin returns the same result as above
    norm = mcolors.SymLogNorm(3, vmin=-30, vmax=5, linscale=1.2, base=np.e)
    normed_vals = norm(vals)
    assert_array_almost_equal(normed_vals, expected)

    # test something more easily checked.
    norm = mcolors.SymLogNorm(1, vmin=-np.e**3, vmax=np.e**3, base=np.e)
    nn = norm([-np.e**3, -np.e**2, -np.e**1, -1,
              0, 1, np.e**1, np.e**2, np.e**3])
    xx = np.array([0., 0.109123, 0.218246, 0.32737, 0.5, 0.67263,
                   0.781754, 0.890877, 1.])
    assert_array_almost_equal(nn, xx)
    norm = mcolors.SymLogNorm(1, vmin=-10**3, vmax=10**3, base=10)
    nn = norm([-10**3, -10**2, -10**1, -1,
              0, 1, 10**1, 10**2, 10**3])
    xx = np.array([0., 0.121622, 0.243243, 0.364865, 0.5, 0.635135,
                   0.756757, 0.878378, 1.])
    assert_array_almost_equal(nn, xx)


def test_SymLogNorm_colorbar():