def test_distances_periodic(): coords = np.array([[0.0, 0.0, 0.0], [0.0, 0.9, 0.0], [0.0, 0.2, 0.0]]) coords = np.random.random((1000, 3)) periodic = np.array([1.0, 1.0, 1.0]) cutoff = 0.1 # Consistency checks print "Simple" t = time.time() dist_simple = distance_matrix(coords, coords, cutoff, method="simple", periodic=periodic) print -t + time.time() print "Cell-lists" t = time.time() dist_clist = distance_matrix(coords, coords, cutoff, method="cell-lists", periodic=periodic) print -t + time.time() #print dist_simple #print dist_clist # errors = (dist_simple != dist_clist.todense()).nonzero() # iderr = (errors[0][0, 0], errors[1][0,0]) # print iderr # print coords[iderr[0]], coords[iderr[1]] # print dist_simple[iderr] # print dist_clist[iderr] assert np.allclose(dist_simple, dist_clist.todense())
def test_distances(coords, coords_b, cutoff): # Consistency checks print "Simple" t = time.time() dist_simple = distance_matrix(coords, coords_b, cutoff, method="simple") print -t + time.time() print "Cell-lists" t = time.time() dist_clist = distance_matrix(coords, coords_b, cutoff, method="cell-lists") print -t + time.time() print dist_simple print dist_clist.todense() assert np.allclose(dist_simple, dist_clist.todense())
def test_distances_periodic(): coords = np.array([[0.0, 0.0, 0.0], [0.0, 0.9, 0.0], [0.0, 0.2, 0.0]]) coords = np.random.random((1000, 3)) periodic = np.array([1.0, 1.0, 1.0]) cutoff = 0.1 # Consistency checks print "Simple" t = time.time() dist_simple = distance_matrix(coords, coords, cutoff, method="simple", periodic=periodic) print -t + time.time() print "Cell-lists" t = time.time() dist_clist = distance_matrix(coords, coords, cutoff, method="cell-lists", periodic=periodic) print -t + time.time() assert np.allclose(dist_simple, dist_clist.todense())