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