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)
