# test strayfield class import strayfield import numpy as np import matplotlib.pyplot as plt # magnetism mu0 = 4*np.pi*1e-7 Ms1 = 1.44 / mu0 *1.006# N52 grade (to get closer to the values of tayler) Ms1 = 1.44 / mu0 # N52 grade Ms2 = 1.37 / mu0 # the slighlty more coercive N48SH graders # magnetizations M1_x = np.array([Ms1,0,0]) M1_y = np.array([0, Ms1,0]) M2_x = np.array([Ms2,0,0]) M2_y = np.array([0, Ms2,0]) # sample geometry i_mm = 25.4 a = 0.5 * i_mm b = a c = 2 * i_mm sample_elong = [a, b, c] gap_x = 0.3 * i_mm # generate positions and magnetizations given N block_2 = [] block_4 = [] block_8 = [] block_24 = [] col1 = 'r' col2 = 'b' pos_x = 0 pos_y = 0 pos_z = 0 # populate, see fig1 of JMR277 of Tayler for ii in range(24): # the central ones that are in any design if ii < 2: off_x = (gap_x+a)/2 act_pos = [pos_x-off_x + ii*2*off_x, pos_y, pos_z] block_2.append((M1_x, act_pos, col1)) block_4.append((M1_x, act_pos, col1)) block_8.append((M1_x, act_pos, col1)) block_24.append((M1_x, act_pos, col1)) continue # the left right outer ones if ii < 4: off_y = b act_pos = [pos_x, pos_y-off_y + np.mod(ii,2)*2*off_y, pos_z] block_4.append((-M1_x, act_pos, col1)) block_8.append((-M1_x, act_pos, col1)) block_24.append((-M2_x, act_pos, col2)) continue # the remaining ones of the 8 block if ii < 8: off_x = a off_y = b id_x = np.mod(ii,2) id_y = np.mod(ii,4)>>1 act_pos = [pos_x-off_x + id_x*2*off_x, pos_y-off_y + id_y*2*off_y, pos_z] sign = (-1)**(id_x+id_y) block_8.append((sign*M1_y, act_pos, col1)) block_24.append((sign*M2_y, act_pos, col2)) continue # now the rest of block_24 if ii < 12: # the four pointing up off_x = 2*a off_y = b id_x = np.mod(ii,2) id_y = np.mod(ii,4)>>1 act_pos = [pos_x-off_x + id_x*2*off_x, pos_y-off_y + id_y*2*off_y, pos_z] block_24.append((M1_x, act_pos, col1)) continue if ii < 16: # the four at the outer edges off_x = 2*a off_y = 2*b id_x = np.mod(ii,2) id_y = np.mod(ii,4)>>1 act_pos = [pos_x-off_x + id_x*2*off_x, pos_y-off_y + id_y*2*off_y, pos_z] sign = (-1)**(id_x+id_y) block_24.append((sign*M2_y, act_pos, col2)) continue if ii < 20: # four more off_x = a off_y = 2*b id_x = np.mod(ii,2) id_y = np.mod(ii,4)>>1 act_pos = [pos_x-off_x + id_x*2*off_x, pos_y-off_y + id_y*2*off_y, pos_z] sign = (-1)**(id_x+id_y) block_24.append((sign*M2_y, act_pos, col2)) continue if ii < 22: # the two weak ones off_x = 0 off_y = 2*b id_y = np.mod(ii,2) act_pos = [pos_x, pos_y-off_y + id_y*2*off_y, pos_z] block_24.append((-M2_x, act_pos, col2)) continue if ii < 24: # the two strong ones off_x = (gap_x+a)/2+a id_x = np.mod(ii,2) act_pos = [pos_x-off_x + id_x*2*off_x, pos_y, pos_z] block_24.append((M1_x, act_pos, col1)) continue # target specification target_elong = [ 0, 7/8*a, c] target_zero = [ 0, 0, 0] target_discr = [ 0.5, 0.5, 0.5] stray = strayfield.strayfield(); for ii, block in enumerate(block_24): stray.add_sample(block[0], sample_elong, block[1], ['el{:}'.format(ii)], col=block[2]) stray.set_target(target_elong, target_zero, target_discr); stray.plot_sample_and_target() plt.gca().view_init(elev=-91, azim=0) plt.gcf() stray.calculate() #%% get the central field for all the designs target_ref_elong = [0, 1e-3, 0] target_ref_discr = [1e-4, 1e-4, 1e-4] for act_block in [block_2, block_4, block_8, block_24]: stray_mx = strayfield.strayfield(); for ii, block in enumerate(act_block): stray_mx.add_sample(block[0], sample_elong, block[1], ['el{:}'.format(ii)], col=block[2]) # stray_mx.set_target(target_elong, target_zero, target_discr); stray_mx.set_target(target_ref_elong, target_zero, target_ref_discr); stray_mx.calculate() B_abs = np.sqrt(stray_mx.Bstray[:,0]**2+stray_mx.Bstray[:,1]**2+stray_mx.Bstray[:,2]**2) print('Bx = {}, Babs = {}'.format(stray_mx.Bstray[:,0].max(), B_abs.max()) ) #%% visualize cmin = np.nanmin(stray.Bstray) cmax = np.nanmax(stray.Bstray) cvec = np.arange(int(np.floor(cmin)),int(np.ceil(cmax)),10) # logarithmic spaced color vector #cvec = np.logspace(0,np.log10(cmax),10) #n_id = np.where(cvec<=abs(cmin))[0] #cvec = np.append(np.append(np.flipud(-cvec[n_id]),0),cvec) # custom color vectors.. #cvec = np.linspace(10,40,16) #cvec = np.linspace(35,65,16) clabelsize = 4 # for plot exports clabelsize = 12 data = stray.Bstray[:,:,0] #data=np.transpose(data2) plt.figure(21) plt.clf() CS = plt.contour(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data , cmap=plt.get_cmap('winter')) plt.clabel(CS, inline=1, fontsize=clabelsize) plt.pcolor(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data, vmin=np.nanmin(data), vmax=np.nanmax(data), shading='auto') plt.colorbar() plt.tight_layout() plt.xlabel('$x$ [mm]') plt.ylabel('$y$ [mm]') plt.figure(22) # fig1 = plt.figure(figsize = (5, 15)) plt.clf() plt.subplot(311) data = stray.Bstray[:,:,0] #data=np.transpose(data2) CS = plt.contour(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data , cmap=plt.get_cmap('winter')) plt.clabel(CS, inline=1, fontsize=clabelsize) plt.pcolor(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data, vmin=np.nanmin(data), vmax=np.nanmax(data), shading='auto') plt.colorbar() plt.tight_layout() #plt.xlabel('$x$ [$\mu$m]') plt.ylabel('$y$ [mm]') plt.title('$B_\mathrm{stray}$ [T]') plt.subplot(312) data = stray.Bstray[:,:,1] #data=np.transpose(data2) CS = plt.contour(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data , cmap=plt.get_cmap('winter')) plt.clabel(CS, inline=1, fontsize=clabelsize) plt.pcolor(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data, vmin=np.nanmin(data), vmax=np.nanmax(data), shading='auto') plt.colorbar() plt.tight_layout() #plt.xlabel('$x$ [$\mu$m]') plt.ylabel('$y$ [mm]') plt.subplot(313) data = stray.Bstray[:,:,2] #data=np.transpose(data2) CS = plt.contour(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data , cmap=plt.get_cmap('winter')) plt.clabel(CS, inline=1, fontsize=clabelsize) plt.pcolor(stray.tc[stray.nzro_ids[1]], stray.tc[stray.nzro_ids[0]], data, vmin=np.nanmin(data), vmax=np.nanmax(data), shading='auto') plt.colorbar() plt.tight_layout() plt.xlabel('$x$ [mm]') plt.ylabel('$y$ [mm]')