os.chdir('/home/thaa191/data2') import kicklib os.chdir('/home/thaa191/data2/2018') folder = ['201805081332'] lengths = np.linspace(50, 250, 9) all_data = [] for i in range(0, len(folder)): num = 0 for j in os.listdir(folder[i]): if (j.endswith('.mat')): num = num + 1 print('Found ' + str(num) + ' mat files in ' + str(folder[i])) if (num == 0): kicklib.getallpics(str(folder[i]), 9) for j in os.listdir(folder[i]): if (j.endswith('.mat')): num = num + 1 print('Found ' + str(num) + ' mat files in ' + str(folder[i])) for j in range(0, num): #print('Loading /Data_'+str(j)+'.mat') data = sio.loadmat(str(folder[i]) + '/Data_' + str(j) + '.mat') try: all_data[j] += data['a1'] / 3 except IndexError: all_data.append(data['a1'] / 3) all_image_points = [] all_channel_points = []
return artist.__module__ == "matplotlib.text" Get_Points= True barrier_pos = np.linspace(0,150,16) #folder = ['201805181551','201805181638','201805181647'] folder = ['201805181700','201805181709','201805181717'] all_data = [] for i in range(0,len(folder)): num = 0 for j in os.listdir(folder[i]): if(j.endswith('.mat')): num = num+1 print('Found '+ str(num)+' mat files in '+str(folder[i])) if(num==0): kicklib.getallpics(str(folder[i]),len(barrier_pos)) for j in os.listdir(folder[i]): if(j.endswith('.mat')): num = num+1 print('Found '+ str(num)+' mat files in '+str(folder[i])) if(Get_Points): for j in range(0,num): #print('Loading /Data_'+str(j)+'.mat') data = sio.loadmat(str(folder[i])+'/Data_'+str(j)+'.mat') try: all_data[j] += data['a1']/3 except IndexError: all_data.append(data['a1']/3) print("Select image boundry points") plt.imshow(data['a1'])
def def_Imabanlce(folder, fill_factor, width, time, points_image, points_channel, Get_Points, plot_images, plot_profiles, plot_imbal): all_data = [] for i in range(0, len(folder)): num = 0 for j in os.listdir(folder[i]): if (j.endswith('.mat')): num = num + 1 print('Found ' + str(num) + ' mat files in ' + str(folder[i])) if (num == 0): kicklib.getallpics(str(folder[i]), len(time)) for j in os.listdir(folder[i]): if (j.endswith('.mat')): num = num + 1 print('Found ' + str(num) + ' mat files in ' + str(folder[i])) if (Get_Points): for j in range(0, num): #print('Loading /Data_'+str(j)+'.mat') data = sio.loadmat(str(folder[i]) + '/Data_' + str(j) + '.mat') try: all_data[j] += data['a1'] / 3 except IndexError: all_data.append(data['a1'] / 3) print("Select image boundry points") plt.imshow(data['a1']) points = plt.ginput(2, 0) plt.close() points = (np.floor(points)).astype(int) x_points = [points[0][0], points[1][0]] y_points = [points[0][1], points[1][1]] points_image = [x_points, y_points] for j in range(0, num): all_data[j] = all_data[j][y_points[0]:y_points[1], x_points[0]:x_points[1]] print("Select channel boundary points") plt.imshow(all_data[len(all_data) - 1]) points_cut = plt.ginput(2, 0) plt.close() points_cut = (np.floor(points_cut)).astype(int) points_channel = [points_cut[0][0], points_cut[1][0]] Get_Points = False print(np.shape(all_data[0]), points_channel) else: x_points = points_image[0] y_points = points_image[1] for j in range(0, num): #print('Loading /Data_'+str(j)+'.mat') data = sio.loadmat(str(folder[i]) + '/Data_' + str(j) + '.mat') try: all_data[j] += data['a1'][y_points[0]:y_points[1], x_points[0]:x_points[1]] / 3 except IndexError: all_data.append(data['a1'][y_points[0]:y_points[1], x_points[0]:x_points[1]] / 3) print("Calculating imbalances") all_imbal = [] uncert = [] #c = (2e-6**2)/(1.938e-13) for i in range(0, len(all_data)): single = np.sum(all_data[i], 0) N1 = np.sum(single[points_channel[0]:], 0) N2 = np.sum(single[0:points_channel[1]], 0) imbal = (N1 - N2) / (N1 + N2) errComb = np.sqrt(N1 + N2) imbal = (N1 - N2) / (N1 + N2) relImbal = np.sqrt((errComb / (N1 + N2))**2 + (errComb / (N1 - N2))**2) all_imbal.append(imbal) uncert.append(imbal * relImbal) #plt.figure() #plt.plot(all_imbal) print("Saving imbalances") hbar = 1.0545718e-34 g_nonl = 4 * np.pi * (hbar**2) * (5.45e-9) / (1.44316060e-25) omega_z = 800 * 2 * np.pi alpha = ((g_nonl * (0.5 * 1.44316060e-25 * (omega_z**2))**(0.5)) / (np.pi * (21e-6**2) * (4 / 3)))**(2 / 3) capacitance = (0.75 / alpha) * ( (0.5 * np.sum(np.sum(all_data[0], 1), 0))**(1 / 3)) print("The capacitance is: " + str(capacitance)) os.chdir('/home/thaa191/Programing/Dumbbells/Width_Disorder_data/Width_' + str(width)) #save_data = {'imbalance':np.array(all_imbal),'width':width,'time':time} sio.savemat( 'Fill_' + str(int(fill_factor * 100)) + '.mat', { 'imbalance': all_imbal, 'Fill Factor': fill_factor, 'error': uncert, 'time': time, 'capacitance': capacitance, 'all_data': all_data }) os.chdir('/home/thaa191/Programing/Dumbbells/Width_Disorder_data/Width_' + str(width) + '/Images') pic_row = int(np.ceil(len(time) / 5)) if (plot_images): fig_img = plt.figure() for i in range(0, len(all_data)): ax = plt.subplot(5, pic_row, i + 1) ax.imshow(all_data[i]) ax.set_title(time[i]) ax.xaxis.set_visible(False) ax.yaxis.set_visible(False) plt.tight_layout() fig_img.savefig("Image_Plot_FillFactor_" + str(int(fill_factor * 100)) + ".png") plt.close() if (plot_profiles): fig_profiles = plt.figure() for i in range(0, len(all_data)): ax = plt.subplot(5, pic_row, i + 1) single = np.sum(all_data[i], 0) ax.plot(single) ax.axvline(points_channel[0]) ax.axvline(points_channel[1]) ax.set_title(time[i]) plt.tight_layout() fig_profiles.savefig("Profile_Plot_FillFactor_" + str(int(fill_factor * 100)) + ".png") plt.close() if (plot_imbal): fig_imbal = plt.figure() plt.plot(time, all_imbal) plt.tight_layout() fig_imbal.savefig("Imbal_Plot_FillFactor_" + str(int(fill_factor * 100)) + ".png") plt.close() os.chdir('/home/thaa191/data2/2018') return points_image, points_channel
def def_Imabanlce(folder,roughness,length,time,points_image, points_channel, Get_Points, plot_images,plot_imbal): all_data = [] for i in range(0,len(folder)): num = 0 for j in os.listdir(folder[i]): if(j.endswith('.mat')): num = num+1 print('Found '+ str(num)+' mat files in '+str(folder[i])) if(num==0): kicklib.getallpics(str(folder[i]),len(time)) for j in os.listdir(folder[i]): if(j.endswith('.mat')): num = num+1 print('Found '+ str(num)+' mat files in '+str(folder[i])) if(Get_Points): for j in range(0,num): #print('Loading /Data_'+str(j)+'.mat') data = sio.loadmat(str(folder[i])+'/Data_'+str(j)+'.mat') try: all_data[j] += data['a1']/3 except IndexError: all_data.append(data['a1']/3) print("Select image boundry points") plt.imshow(data['a1']) points = plt.ginput(2,0) plt.close() points = (np.floor(points)).astype(int) x_points = [ points[0][0], points[1][0] ] y_points = [ points[0][1], points[1][1] ] points_image = [x_points,y_points] for j in range(0,num): all_data[j] = all_data[j][y_points[0]:y_points[1],x_points[0]:x_points[1]] print("Select 1st reservoir boundary points") plt.imshow(all_data[len(all_data)-1]) points = plt.ginput(2,0) plt.close() points = (np.floor(points)).astype(int) x_points_1 = [ points[0][0], points[1][0] ] y_points_1 = [ points[0][1], points[1][1] ] print("Select 2nd reservoir boundary points") plt.imshow(all_data[len(all_data)-1]) points = plt.ginput(2,0) plt.close() points = (np.floor(points)).astype(int) x_points_2 = [ points[0][0], points[1][0] ] y_points_2 = [ points[0][1], points[1][1] ] Get_Points = False else: x_points = points_image[0] y_points = points_image[1] for j in range(0,num): #print('Loading /Data_'+str(j)+'.mat') data = sio.loadmat(str(folder[i])+'/Data_'+str(j)+'.mat') try: all_data[j] += data['a1'][y_points[0]:y_points[1],x_points[0]:x_points[1]]/3 except IndexError: all_data.append(data['a1'][y_points[0]:y_points[1],x_points[0]:x_points[1]]/3) print("Calculating imbalances") all_imbal = [] uncert = [] #c = (2e-6**2)/(1.938e-13) for i in range(0,len(all_data)): single = all_data[i][y_points_1[0]:y_points_1[1],x_points_1[0]:x_points_1[1]] N1 = np.sum(np.sum(single,1),0) single = all_data[i][y_points_2[0]:y_points_2[1],x_points_2[0]:x_points_2[1]] N2 = np.sum(np.sum(single,1),0) errComb = np.sqrt(N1+N2) imbal = (N1-N2)/(N1+N2) relImbal = np.sqrt((errComb/(N1+N2))**2+(errComb/(N1-N2))**2) all_imbal.append(imbal) uncert.append(imbal*relImbal) #plt.figure() #plt.plot(all_imbal) print("Saving imbalances") os.chdir('/home/thaa191/Programing/Dumbbells/Rough_Reservoir/') #save_data = {'imbalance':np.array(all_imbal),'length':length,'time':time} sio.savemat('Roughness_'+str(roughness)+'.mat',{'imbalance':all_imbal,'error':uncert,'Roughness':roughness,'time':time, 'length':length}) os.chdir('/home/thaa191/Programing/Dumbbells/Rough_Reservoir/Images') pic_row = int(np.ceil(len(time)/5)) if(plot_images): fig_img = plt.figure() for i in range(0,len(all_data)): ax = plt.subplot(5,pic_row,i+1) ax.imshow(all_data[i]) ax.set_title(time[i]) ax.xaxis.set_visible(False) ax.yaxis.set_visible(False) plt.tight_layout() fig_img.savefig("Image_Plot_Roughness_"+str(roughness)+".png") plt.close() if(plot_imbal): fig_imbal = plt.figure() ax = plt.subplot() ax.errorbar(time, all_imbal, yerr=uncert, fmt='o') ax.set_ylim(-0.4,1.05) plt.tight_layout() fig_imbal.savefig("Imbal_Plot_Roughness_"+str(roughness)+".png") plt.close() thesis_plot = True if thesis_plot: fig_img = plt.figure(figsize=(2, 4), dpi=80) img_index = [0,14,24] plot_titles = ['(a)','(b)','(c)','(d)','(e)','(f)'] for i in range(0,len(img_index)): ax = plt.subplot(3,1,i+1) ax.imshow(all_data[img_index[i]]) ax.set_title(plot_titles[i]) ax.xaxis.set_visible(False) ax.yaxis.set_visible(False) plt.tight_layout() #fig_img.savefig("Select_Image_Plot_width_"+length+".eps") #plt.close() os.chdir('/home/thaa191/data2/2018') return points_image,points_channel