def test_closest_peak(): prev = np.array([1, -.9, 0]) prev = prev/np.sqrt(np.dot(prev, prev)) cp = _closest_peak(peak_points, prev, .5) assert_array_equal(cp, peak_points[0]) cp = _closest_peak(peak_points, -prev, .5) assert_array_equal(cp, -peak_points[0]) assert_raises(StopIteration, _closest_peak, peak_points, prev, .75)
def test_closest_peak(): prev = np.array([1, -.9, 0]) prev = prev / np.sqrt(np.dot(prev, prev)) cp = _closest_peak(peak_points, prev, .5) assert_array_equal(cp, peak_points[0]) cp = _closest_peak(peak_points, -prev, .5) assert_array_equal(cp, -peak_points[0]) assert_raises(StopIteration, _closest_peak, peak_points, prev, .75)
def test_closest_peak(): peak_values = np.array([1, .9, .8, .7, .6, .2, .1]) peak_points = np.array([[1., 0., 0.], [0., .9, .1], [0., 1., 0.], [.9, .1, 0.], [0., 0., 1.], [1., 1., 0.], [0., 1., 1.]]) norms = np.sqrt((peak_points * peak_points).sum(-1)) peak_points = peak_points / norms[:, None] prev = np.array([1, -.9, 0]) prev = prev / np.sqrt(np.dot(prev, prev)) cp = _closest_peak(peak_points, prev, .5) assert_array_equal(cp, peak_points[0]) cp = _closest_peak(peak_points, -prev, .5) assert_array_equal(cp, -peak_points[0]) assert_raises(StopIteration, _closest_peak, peak_points, prev, .75)
def test_closest_peak(): peak_values = np.array([1, .9, .8, .7, .6, .2, .1]) peak_points = np.array([[1., 0., 0.], [0., .9, .1], [0., 1., 0.], [.9, .1, 0.], [0., 0., 1.], [1., 1., 0.], [0., 1., 1.]]) norms = np.sqrt((peak_points*peak_points).sum(-1)) peak_points = peak_points/norms[:, None] prev = np.array([1, -.9, 0]) prev = prev/np.sqrt(np.dot(prev, prev)) cp = _closest_peak(peak_points, prev, .5) assert_array_equal(cp, peak_points[0]) cp = _closest_peak(peak_points, -prev, .5) assert_array_equal(cp, -peak_points[0]) assert_raises(StopIteration, _closest_peak, peak_points, prev, .75)