def plot_looped_data(directory):
file_list = get_data_paths(directory)
print(len(file_list))
voltage_list = list()
current_list = list()
try:
for file in sorted(file_list, key=file_sort):
print(file)
for_voltage = list()
rev_voltage = list()
for_current = list()
rev_current = list()
forward, reverse = get_looped_cv_data(file)
for reading_for, reading_rev in zip(forward, reverse):
for_voltage.append(reading_for[0])
rev_voltage.append(reading_rev[0])
for_current.append(reading_for[1])
rev_current.append(reading_rev[1])
forward_np = np.array(forward)
reverse_np = np.array(reverse)
voltage = np.concatenate((for_voltage, rev_voltage[::-1]), axis=0)
current = np.concatenate((for_current, rev_current[::-1]), axis=0)
voltage_list.append(voltage)
current_list.append(current)
except ValueError:
print('could not be read')
return voltage_list, current_list
def main():
plt.style.use(['seaborn-white', 'seaborn-notebook'])
directory = "/Users/st659/Google Drive/Meth Blue Glucose 12-10-16"
paths = get_data_paths(directory)
print(paths)
sub_bw_anti_3, bw_anti_3, legend1 = calculate_graph_data(paths[3:6])
sub_bw_noanti_3, bw_noanti_3, legend2 = calculate_graph_data(paths[6:9])
sub_pk_anti_3, pk_anti_3, legend3 = calculate_graph_data(paths[10:12])
sub_pk_noanti_3, pk_noanti_3, legend4 = calculate_graph_data(paths[12:15])
bw_mean = np.array([bw_anti_3[1], bw_noanti_3[1]])
pk_mean = np.array([pk_anti_3[1], pk_noanti_3[1]])
total_mean_matrix = np.array(
[bw_anti_3[1], bw_noanti_3[1], pk_noanti_3[1], pk_anti_3[1]])
mean_var = np.var(total_mean_matrix, axis=0)
bw_var = np.var(bw_mean, axis=0)
pk_var = np.var(pk_mean, axis=0)
print(len(mean_var))
figure_var = plt.figure()
ax_var = figure_var.add_subplot(111)
ax_var.plot(bw_noanti_3[0], bw_var, label='BW')
ax_var.plot(bw_noanti_3[0], pk_var, label='PK')
plt.legend(loc='upper right')
figure1 = plt.figure()
ax1 = figure1.add_subplot(211)
ax1.errorbar(sub_bw_anti_3[0],
sub_bw_anti_3[1],
sub_bw_anti_3[2],
label=legend1)
ax1.errorbar(sub_bw_noanti_3[0],
sub_bw_noanti_3[1],
sub_bw_noanti_3[2],
label=legend2)
ax1.set_ylabel('Current (mA)')
ax1.set_xlabel('Voltage (V)')
plt.legend(loc='upper left')
ax2 = figure1.add_subplot(212)
ax2.errorbar(sub_pk_anti_3[0],
sub_pk_anti_3[1],
sub_pk_anti_3[2],
label=legend3)
ax2.errorbar(sub_pk_noanti_3[0],
sub_pk_noanti_3[1],
sub_pk_noanti_3[2],
label=legend4)
ax2.set_ylabel('Current (mA)')
ax2.set_xlabel('Voltage (V)')
plt.legend(loc='upper left')
plt.show()
def cv_difference(directory):
paths = get_data_paths(directory)
sub_bw_anti, bw_anti, bw_anti_max_volt, legend1 = calculate_graph_data(
paths[3:6])
sub_bw_noanti, bw_noanti, bw_noanti_max_volt, legend2 = calculate_graph_data(
paths[6:9])
sub_pk_anti, pk_anti, pk_anti_max_volt, legend3 = calculate_graph_data(
paths[10:12])
sub_pk_noanti, pk_noanti, pk_noanti_max_volt, legend4 = calculate_graph_data(
paths[12:15])
diff_bw = np.subtract(sub_bw_anti[1], sub_bw_noanti[1])
diff_bw_std = np.sqrt(
np.add(np.square(sub_bw_anti[2]), np.square(sub_bw_noanti[2])))
diff_pk = np.subtract(sub_pk_anti[1], sub_pk_noanti[1])
diff_pk_std = np.sqrt(
np.add(np.square(sub_pk_anti[2]), np.square(sub_pk_noanti[2])))
return [sub_bw_anti[0], diff_bw, diff_bw_std, diff_pk, diff_pk_std]
from Meth_blue_06_09 import get_data_paths, calculate_graph_data
import matplotlib.pyplot as plt
import os
directory1 = '/Users/st659/Google Drive/Resazurin Growth 12-1-17'
directory2 = '/Users/st659/Google Drive/Resazurin Growth 11-1-17'
directory3 = '/Users/st659/Google Drive/Resazurin Growth 5-1-17'
plt.style.use(['seaborn-white', 'seaborn-notebook'])
paths1 = get_data_paths(directory1)
paths2 = get_data_paths(directory2)
paths3 = get_data_paths(directory3)
blank = paths1[:2]
mg4_paths = paths1[3:]
mg5_paths = paths2[2:]
mg6_paths = paths3[2:]
print(mg6_paths)
print(mg5_paths)
print(mg4_paths)
paths_list = [blank, mg4_paths, mg6_paths]
fig2 = plt.figure()
legends = ['Blank', 'E.coli MG1655 $10^{4}$ cfu/ml', 'E.coli MG1655 $10^{6}$ cfu/ml']
ax2 = fig2.add_subplot(111)
from Meth_blue_06_09 import get_data_paths, calculate_graph_data
import matplotlib.pyplot as plt
import os
from EIS_Reader import EISReader
cv_directory = '/Users/st659/Google Drive/ITO Diazonium 24-2-17/CV'
eis_directory = '/Users/st659/Google Drive/ITO Diazonium 24-2-17/EIS'
cv_paths = get_data_paths(cv_directory)
eis_paths = get_data_paths(eis_directory)
plt.style.use(['seaborn-white', 'seaborn-notebook'])
fig = plt.figure()
ax = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
ax3 = ax2.twinx()
for cv_path, eis_path in zip(cv_paths, eis_paths):
sub_data_2, data, legend = calculate_graph_data(cv_path)
eis_reader = EISReader(eis_path)
ax2.loglog(eis_reader.eis.frequency, eis_reader.eis.magnitude)
ax3.semilogx(eis_reader.eis.frequency,
eis_reader.eis.phase,
linestyle='--')
print(eis_reader.eis.frequency)
legend_str = cv_path.split('/')[-1]
print(legend_str)
leg = legend_str.split('.')[0]
leg = leg.split('_')[1]
ax.plot(sub_data_2[0], sub_data_2[1], label=leg)
def main():
directory = "/Users/st659/Google Drive/Meth Blue 12-09"
paths = get_data_paths(directory)
plt.style.use(['seaborn-white', 'seaborn-notebook'])
print(paths)
# sub_bw_anti_3, bw_anti_3, = calculate_graph_data(paths[0:3])
# sub_bw_noanti_3, bw_noanti_3 = calculate_graph_data(paths[3:6])
# sub_pk_anti_3, pk_anti_3 = calculate_graph_data(paths[6:9])
# sub_pk_noanti_3, pk_noanti_3 = calculate_graph_data(paths[9:12])
#
# figure1 = plt.figure()
# ax1 = figure1.add_subplot(111)
# ax1.errorbar(sub_bw_anti_3[0], sub_bw_anti_3[1], sub_bw_anti_3[2])
# ax1.errorbar(sub_bw_noanti_3[0], sub_bw_noanti_3[1], sub_bw_noanti_3[2])
# ax1.errorbar(sub_pk_anti_3[0], sub_pk_anti_3[1], sub_pk_anti_3[2])
# ax1.errorbar(sub_pk_noanti_3[0], sub_pk_noanti_3[1], sub_pk_noanti_3[2])
#
# plt.xlabel('Voltage vs reference (V)')
# plt.ylabel('Current (mA)')
# plt.xlim([-0.3, 0])
# plt.ylim([-0.02, 0.01])
# plt.legend(('BW25113 0$\mu g/ml$ Ampicillin', 'BW25133 50$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 0$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 50$\mu g/ml$ Ampicillin'),loc='lower right', fontsize = '10')
# plt.title(r'Antibiotic Susceptibility of $10^{3}$ Bacteria after 5 hours incubation')
# sub_bw_anti_4, bw_anti_4, l= calculate_graph_data(paths[12:15])
# sub_bw_noanti_4, bw_noanti_4, l = calculate_graph_data(paths[15:18])
# sub_pk_anti_4, pk_anti_4, l = calculate_graph_data(paths[18:21])
# sub_pk_noanti_4, pk_noanti_4, l = calculate_graph_data(paths[21:24])
#
# figure2 = plt.figure()
# ax2 = figure2.add_subplot(111)
# ax2.errorbar(sub_bw_anti_4[0], sub_bw_anti_4[1], sub_bw_anti_4[2])
# ax2.errorbar(sub_bw_noanti_4[0], sub_bw_noanti_4[1], sub_bw_noanti_4[2])
# ax2.errorbar(sub_pk_anti_4[0], sub_pk_anti_4[1], sub_pk_anti_4[2])
# ax2.errorbar(sub_pk_noanti_4[0], sub_pk_noanti_4[1], sub_pk_noanti_4[2])
#
# plt.xlabel('Voltage vs reference (V)')
# plt.ylabel('Current (mA)')
# plt.xlim([-0.3, 0])
# plt.ylim([-0.02, 0.01])
# plt.legend(('BW25113 50$\mu g/ml$ Ampicillin', 'BW25133 0$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 50$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 0$\mu g/ml$ Ampicillin'),loc='lower right', fontsize = '10')
# plt.title(r'Antibiotic Susceptibility of $10^{4}$ CFU/ml after 5 hours incubation')
# #plt.savefig(os.path.join(directory,'susceptibility 10_4.png'), dpi=1200)
#
# diff = np.subtract(sub_bw_anti_4[1], sub_bw_noanti_4[1])
# diff_std = np.sqrt(np.add(np.square(sub_bw_anti_4[2]), np.square(sub_bw_noanti_4[2])))
# diff2 = np.subtract(sub_pk_anti_4[1], sub_pk_noanti_4[1])
# diff2_std = np.sqrt(np.add(np.square(sub_pk_anti_4[2]), np.square(sub_pk_noanti_4[2])))
#
# figure2 = plt.figure()
# ax3 = figure2.add_subplot(211)
# ax3.errorbar(sub_bw_anti_4[0], diff, diff_std, label='BW', color='b')
# ax3.set_ylabel('$\Delta$ Current (mA)')
#
# plt.legend(loc = 'upper left')
# ax4 = figure2.add_subplot(212)
# ax4.errorbar(sub_bw_anti_4[0], diff2, diff2_std, label='PK', color='g')
# ax4.set_ylabel('$\Delta$ Current (mA)')
# ax4.set_xlabel('Voltage (V)')
# plt.legend(loc = 'upper left')
#
#
#
#
# sub_bw_anti_5, bw_anti_5, l = calculate_graph_data(paths[24:27])
# sub_bw_noanti_5, bw_noanti_5, l = calculate_graph_data(paths[27:30])
# sub_pk_anti_5, pk_anti_5, l = calculate_graph_data(paths[30:33])
# sub_pk_noanti_5, pk_noanti_5, l = calculate_graph_data(paths[33:36])
#
# mean_matrix = np.array([bw_anti_5[1], bw_noanti_5[1], pk_noanti_5[1], pk_anti_5[1]])
# mean_var = np.var(mean_matrix, axis=0)
# print(len(mean_var))
#
# figure_var = plt.figure()
# ax_var = figure_var.add_subplot(111)
# ax_var.plot(bw_noanti_5[0], mean_var)
# plt.show()
# diff = np.subtract(sub_bw_anti_5[1], sub_bw_noanti_5[1])
# diff_std = np.sqrt(np.add(np.square(sub_bw_anti_5[2]), np.square(sub_bw_noanti_5[2])))
# diff2 = np.subtract(sub_pk_anti_5[1], sub_pk_noanti_5[1])
# diff2_std = np.sqrt(np.add(np.square(sub_pk_anti_5[2]), np.square(sub_pk_noanti_5[2])))
#
# figure3 = plt.figure()
# ax5 = figure3.add_subplot(211)
# ax5.errorbar(sub_bw_anti_4[0], diff, diff_std, label='BW', color='b')
# ax5.set_ylabel('$\Delta$ Current (mA)')
#
# plt.legend(loc = 'upper left')
# ax6 = figure3.add_subplot(212)
# ax6.errorbar(sub_bw_anti_4[0], diff2, diff2_std, label='PK', color='g')
# ax6.set_ylabel('$\Delta$ Current (mA)')
# ax6.set_xlabel('Voltage (V)')
# plt.legend(loc = 'upper left')
#
# figure3 = plt.figure()
# ax3 = figure3.add_subplot(111)
# ax3.errorbar(sub_bw_anti_5[0], sub_bw_anti_5[1], sub_bw_anti_5[2])
# ax3.errorbar(sub_bw_noanti_5[0], sub_bw_noanti_5[1], sub_bw_noanti_5[2])
# ax3.errorbar(sub_pk_anti_5[0], sub_pk_anti_5[1], sub_pk_anti_5[2])
# ax3.errorbar(sub_pk_noanti_5[0], sub_pk_noanti_5[1], sub_pk_noanti_5[2])
#
# plt.xlabel('Voltage vs reference (V)')
# plt.ylabel('Current (mA)')
# plt.xlim([-0.3, 0])
# plt.ylim([-0.02, 0.01])
# plt.legend(('BW25113 50$\mu g/ml$ Ampicillin', 'BW25133 00$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 50$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 0$\mu g/ml$ Ampicillin'),loc='lower right', fontsize = '10')
# plt.title(r'Antibiotic Susceptibility of $10^{5}$ CFU/ml after 5 hours incubation')
# #plt.savefig(os.path.join(directory,'susceptibility 10_5.png'), dpi=1200)
#
sub_bw_anti_6, bw_anti_6, leg= calculate_graph_data(paths[36:39])
sub_bw_noanti_6, bw_noanti_6, leg = calculate_graph_data(paths[39:42])
sub_pk_anti_6, pk_anti_6, leg = calculate_graph_data(paths[42:45])
sub_pk_noanti_6, pk_noanti_6, leg = calculate_graph_data(paths[45:48])
figure4 = plt.figure()
ax4 = figure4.add_subplot(111)
ax4.errorbar(sub_bw_anti_6[0], sub_bw_anti_6[1], sub_bw_anti_6[2])
ax4.errorbar(sub_bw_noanti_6[0], sub_bw_noanti_6[1], sub_bw_noanti_6[2])
ax4.errorbar(sub_pk_anti_6[0], sub_pk_anti_6[1], sub_pk_anti_6[2])
ax4.errorbar(sub_pk_noanti_6[0], sub_pk_noanti_6[1], sub_pk_noanti_6[2])
plt.xlabel('Voltage vs reference (V)')
plt.ylabel('Current (mA)')
plt.xlim([-0.3, 0])
plt.ylim([-0.02, 0.01])
plt.legend(('BW25113 50$\mu g/ml$ Ampicillin', 'BW25133 0$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 50$\mu g/ml$ Ampicillin', 'BW25113 with PKD3 0$\mu g/ml$ Ampicillin'),loc='lower right', fontsize = '10')
plt.title(r'Antibiotic Susceptibility of $10^{6}$ CFU/ml after 5 hours incubation')
plt.savefig(os.path.join(directory,'susceptibility 10_6 300dpi.png'), dpi=300)
from Meth_blue_06_09 import get_data_paths, calculate_graph_data
import matplotlib.pyplot as plt
import os
directory = '/Users/st659/Google Drive/ITO Resazurin 17-5-17/Resazurin/Gold'
directory2 = '/Users/st659/Google Drive/ITO Resazurin 17-5-17/MB/SHU'
paths = get_data_paths(directory)
paths_2 = get_data_paths(directory2)
blank = paths[:2]
mg = paths[2:]
mg_pseudo = paths_2[2:]
plt.style.use(['seaborn-white', 'seaborn-notebook'])
data_list = list()
data_list_2 = list()
# fig = plt.figure()
fig2 = plt.figure()
# ax = fig.add_subplot(111)
ax = fig2.add_subplot(111)
#ax2 = fig2.add_subplot(122)
# for path in paths_list:
for pb_path in paths:
print(pb_path)
no, pb, legend = calculate_graph_data(pb_path)
#esfe, shu, seg = calculate_graph_data(shu_path)
from Meth_blue_06_09 import get_data_paths, calculate_graph_data
from EIS_Reader import EISReader
import matplotlib.pyplot as plt
import os
directory = '/Users/st659/Google Drive/ITO Diazonium'
paths = get_data_paths(directory)
plt.style.use(['seaborn-white', 'seaborn-notebook'])
fig = plt.figure()
ax = fig.add_subplot(111)
print(len(paths))
for path in paths:
sub_data_2, data, legend = calculate_graph_data(path)
legend_str = path.split('/')[-1]
print(legend_str)
leg = legend_str.split('.')[0]
print(legend)
ax.plot(sub_data_2[0], sub_data_2[1], label=leg)
plt.title('Electrografting of Diazonium Salts to ITO')
plt.ylabel('Current (mA)')
plt.xlabel('Voltage (V)')
plt.legend(loc='upper left')
plt.savefig(os.path.join(directory, 'ITO_Diaz-22-2-17.png'), dpi=300)
plt.show()