import majoranaJJ.operators.sparse.qmsops as spop #sparse operators import majoranaJJ.lattice.nbrs as nb #neighbor arrays import majoranaJJ.lattice.shapes as shps #lattice shapes import majoranaJJ.modules.plots as plots #plotting functions R = 20 coor = shps.halfdisk(R) NN = nb.NN_Arr(coor) NNb = nb.Bound_Arr(coor) idx = 0 plots.lattice(idx, coor, NN = NN) plots.lattice(idx, coor, NNb = NNb)
coor = shps.halfdisk(R) print("size: ", coor.shape[0]) print("") ########################################### #Using old method, scaled by N^2 due to a loop within a loop start = time.time() NN_old = nb2.NN_Arr(coor) end = time.time() print("Time to create Nbr_Arr with original method = {} [s]".format(end - start)) print(NN_old[0:5, :]) idx = 0 plots.lattice(idx, coor, NN=NN_old) print(" ") ########################################### start = time.time() NN_new = nb.NN_Arr(coor) end = time.time() print("Time to create Nbr_Arr with revised method = {} [s]".format(end - start)) print(NN_new[0:5, :]) idx = 0 plots.lattice(idx, coor, NN=NN_new) print(" ")