def Oct17():
a= loadtxt('/home/chris/Dropbox/DataWeiss/151017/thioldots.csv', delimiter = ',', unpack = True, skiprows=1, usecols = (0,6,3,1,2,4,5))
for i in range(1,7):
r = polyfit(a[0,0:100],a[i,0:100],1)
a[i]-=rs.polyeval(r,a[0])
peak = uv.findpeak(a[0],a[i],(410,420))
#print peak
diameter = -0.000000066521*peak[0]**3+0.00019557*peak[0]**2-0.092352*peak[0]+13.29
#print 'diam', diameter
epsilon = 21536*diameter**2.3
# print 'eps', epsilon
print 'CONC', 5*peak[1]/epsilon
plot(a[0],a[i])
legend(['4.2','6.0',',6.4','7.7','9.7','11.5'])
print 'THIOL EXCHANGE'
a= loadtxt('/home/chris/Dropbox/DataWeiss/151017/thiolcapped doits.csv', delimiter = ',', unpack = True, skiprows=1, usecols = (0,1))
r = polyfit(a[0,0:100],a[1,0:100],1)
a[1]-=rs.polyeval(r,a[0])
peak = uv.findpeak(a[0],a[1],(410,420))
#print peak
diameter = -0.000000066521*peak[0]**3+0.00019557*peak[0]**2-0.092352*peak[0]+13.29
#print 'diam', diameter
epsilon = 21536*diameter**2.3
# print 'eps', epsilon
print 'CONC', 5*peak[1]/epsilon
a= loadtxt('/home/chris/Dropbox/DataWeiss/151017/thioldots.csv', delimiter = ',', unpack = True, skiprows=1, usecols = (0,3,1,2,4,5,6))
for i in range(1,7):
r = polyfit(a[0,0:100],a[i,0:100],1)
a[i]-=rs.polyeval(r,a[0])
peak = uv.findpeak(a[0],a[i],(410,420))
#print peak
diameter = -0.000000066521*peak[0]**3+0.00019557*peak[0]**2-0.092352*peak[0]+13.29
#print 'diam', diameter
epsilon = 21536*diameter**2.3
# print 'eps', epsilon
print 'CONC', 5*peak[1]/epsilon
plot(a[0],a[i])
legend(['200','400',',800','2000','3200','4000'])
return 0
def March5_etching():
"""Time dependent etching of PPA capped QDs from immediately after the PPA exchange"""
a = loadtxt(
"160305/160305_stability measurement.csv",
delimiter=",",
skiprows=2,
usecols=(0,) + tuple(range(11, 75, 2)),
unpack=True,
)
times = array([0, 30, 60, 90, 120, 165, 195, 215])
peakxs = array([])
peakys = array([])
halfwidths = array([])
a[1:] -= transpose([a[1:, 0]])
a[1:] = a[range(1, 33, 4) + range(2, 33, 4) + range(3, 33, 4) + range(4, 33, 4)]
figure()
for i in a[1:]:
(x, y) = UVVistools.findpeak(a[0], i, (401, 418))
peakxs = np.append(peakxs, x)
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
peakys = np.append(peakys, y - i[z])
halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0], i), (401, 418), _plot=False))
plot(a[0], i)
peakys = peakys.reshape((4, -1))
peakxs = peakxs.reshape((4, -1))
halfwidths = halfwidths.reshape((4, -1))
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
#
for i in range(4):
ax1.plot(times, peakys[i] * halfwidths[i])
ax2.plot(times, peakxs[i], "o-")
ax3.plot(times, peakys[i], "o-")
ax4.plot(times, halfwidths[i], "o-")
#
ax1.set_ylabel("first exicton areas (relative)")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
return 0
def Oct30PPATitrationUVVis():
a = loadtxt('/home/chris/Dropbox/DataWeiss/151030/151030PPAtitration.csv', delimiter = ',', unpack=True, skiprows=1)
for i in range(1,11):
a[i]-=a[i,0]
peak = uv.findpeak(a[0],a[i],(410,420))
print peak
plot(a[0],a[i])
diameter = -0.000000066521*peak[0]**3+0.00019557*peak[0]**2-0.092352*peak[0]+13.29
#print 'diam', diameter
epsilon = 21536*diameter**2.3
# print 'eps', epsilon
print 'CONC', 5*peak[1]/epsilon
legend(['vial0','vial1','vial2','vial3','vial4','vial5','vial6','vial7','vial8','vial9', 'vial10',])
ylabel('Absorbance')
xlabel('wavelength (nm)')
return 0
def Oct13():
a= loadtxt('/home/chris/Dropbox/DataWeiss/151013/NMR samples.csv', delimiter = ',', unpack = True, skiprows=1)
for i in range(1,6):
r = polyfit(a[0,0:100],a[i,0:100],1)
a[i]-=rs.polyeval(r,a[0])
peak = uv.findpeak(a[0],a[i],(410,420))
print peak
diameter = -0.000000066521*peak[0]**3+0.00019557*peak[0]**2-0.092352*peak[0]+13.29
print 'diam', diameter
epsilon = 21536*diameter**2.3
print 'eps', epsilon
print 'conc', 5*peak[1]/epsilon
plot(a[0],a[i])
legend(['10.5','9.5','9.3','8.6','6.8'])
return 0
def March3():
"""Titration of CdS dots PPA capped. Using PPA as acid"""
a = loadtxt(
"160303/160303_titrationpart-allparts.csv",
delimiter=",",
skiprows=2,
usecols=(0,) + tuple(range(1, 78, 2)),
unpack=True,
)
b = loadtxt("160303/TitrationAdditionsAndpHs.csv", delimiter=",", skiprows=1, unpack=True)
pHs = b[5]
volumes = b[9]
peakxs = array([])
peakys = array([])
halfwidths = array([])
a[1:] *= transpose([volumes / volumes[0]])
a[1:] -= transpose([a[1:, 0]])
figure()
for i in a[1:]:
# plot(a[0],i)
# (x,y) = UVVistools.findpeak(a[0],i,(410,420))
# peakxs = np.append(peakxs,x)
# peakys = np.append(peakys,y-i[45])
# halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0],i),(410,420)))
(x, y) = UVVistools.findpeak(a[0], i, (401, 420))
peakxs = np.append(peakxs, x)
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
peakys = np.append(peakys, y - i[z])
halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0], i), (401, 420), _plot=False))
plot(a[0], i)
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax1.plot(pHs)
ax2.plot(peakxs, "o-")
ax3.plot(peakys, "o-")
ax4.plot(halfwidths, "o-")
ax1.set_ylabel("pH")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax2.plot(pHs, peakxs, "o-")
ax3.plot(pHs, peakys, "o-")
ax4.plot(pHs, halfwidths, "o-")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
figure()
for i in a[1:16]:
plot(a[0], i)
return 0
def March10titration():
"""pH Titration of CdS dots PPA capped. Samples kept in the dark during the experiment"""
b = loadtxt("160310/160310_TitrationAdditionsAndpHs.csv", delimiter=",", skiprows=1, unpack=True)
pHs = b[0]
volumes = b[1]
volumes /= volumes[0]
volfix = volumes / np.roll(volumes, 1)
a = loadtxt(
"160310/160310_PPATitration.csv",
delimiter=",",
skiprows=2,
usecols=(2,) + tuple(range(3, 3 + 2 * len(pHs), 2)),
unpack=True,
)
peakxs = array([])
peakys = array([])
peakx2 = array([])
peakx3 = array([])
secondexciton = array([])
thirdexciton = array([])
halfwidths = array([])
baselines = array([])
hw1 = array([])
hw2 = array([])
hw3 = array([])
a[1:] *= transpose([volfix])
a[1:] -= transpose([a[1:, 0]])
figure()
for i in a[1:]:
(x, y) = UVVistools.findpeak(a[0], i, (410, 425))
wguess = 200
Aguess = 0.4
guess = [
Aguess,
x,
wguess,
Aguess,
x - 38,
wguess,
Aguess,
x - 68,
wguess,
1,
304,
wguess,
-0.001,
0,
] # -1e-3,0]#1e-10,1e-8,
guess = [Aguess, Aguess, 1, 10, x, x - 38, x - 68, 320, wguess, wguess, wguess, 5000]
xfit = a[0][350:500]
yfit = i[350:500]
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
fitres = fitspectrum(RamanSpectrum(pandas.Series(yfit, xfit)), (333, 450), "xGaussianNoBase", guess)
peakys = np.append(peakys, fitres.params[0][3]) # -i[z])
peakxs = np.append(peakxs, fitres.params[0][7])
peakx2 = np.append(peakx2, fitres.params[0][6])
peakx3 = np.append(peakx3, fitres.params[0][5])
halfwidths = np.append(halfwidths, fitres.areas[3]) # UVVistools.HWHM((a[0],i),(410,425),_plot=False))
hw1 = np.append(hw1, sqrt(fitres.params[0][11]))
hw2 = np.append(hw2, sqrt(fitres.params[0][10]))
hw3 = np.append(hw3, sqrt(fitres.params[0][9]))
secondexciton = np.append(secondexciton, fitres.areas[2])
thirdexciton = np.append(thirdexciton, fitres.areas[1])
x1 = argmin(abs(x + 50 - a[0]))
x2 = x1 - 50
slope = -numpy.polynomial.polynomial.polyfit(a[0, x2:x1], i[x2:x1], 1)[1]
print slope
baselines = append(baselines, slope)
plot(a[0], i, "--y")
plot(fitres.x, fitres.peaks[3] + fitres.peaks[0], "k")
plot(fitres.x, fitres.peaks[2] + fitres.peaks[0], "r")
plot(fitres.x, fitres.peaks[1] + fitres.peaks[0], "b")
#
# fig = figure()
# ax1 =fig.add_subplot(411)
# ax2 =fig.add_subplot(412)
# ax3 =fig.add_subplot(413)
# ax4 =fig.add_subplot(414)
#
# ax1.plot(pHs)
#
# ax2.plot(peakxs,'o-')
# ax2.plot(peakx2,'o-')
# ax2.plot(peakx3,'o-')
#
# ax3.plot(halfwidths,'o-')
# ax3.plot(secondexciton,'o-')
# ax3.plot(thirdexciton,'o-')
#
# ax4.plot(hw1,'o-')
# ax4.plot(hw2,'o-')
# ax4.plot(hw2,'o-')
#
#
# ax1.set_ylabel('pH')
# ax2.set_ylabel('peak center (nm)')
# ax3.set_ylabel('noramlized peak areas')
# ax4.set_ylabel('HWHM')
figure()
plot(pHs, baselines)
fig = figure()
ax2 = fig.add_subplot(311)
ax3 = fig.add_subplot(312)
ax4 = fig.add_subplot(313)
ax2.plot(pHs, peakxs, "o-")
ax2.plot(pHs, peakx2, "o-")
ax2.plot(pHs, peakx3, "o-")
ax3.plot(pHs, halfwidths / halfwidths[0], "o-")
ax3.plot(pHs, secondexciton / secondexciton[0], "o-")
ax3.plot(pHs, thirdexciton / thirdexciton[0], "o-")
ax4.plot(pHs, hw1, "o-")
ax4.plot(pHs, hw2, "o-")
ax4.plot(pHs, hw3, "o-")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("normalized peak area")
ax4.set_ylabel("peak hwhm")
ax4.legend(["first", "second", "third"])
figure()
plot(pHs, peakxs, "o-")
return 0
def March9_fit():
"""pH Titration of CdS dots PPA capped. Samples kept in the dark during the experiment"""
b = loadtxt("160309/160309_TitrationAdditionsAndpHs.csv", delimiter=",", skiprows=1, unpack=True)
pHs = b[0]
volumes = b[1]
volumes[8:] -= 0.002
volfix = volumes / np.roll(volumes, 1)
volfix[0] = 1
volfix[8] = 1.003
print volfix
a = loadtxt(
"160309/160309titration.csv",
delimiter=",",
skiprows=2,
usecols=(2,) + tuple(range(3, 3 + 2 * len(pHs), 2)),
unpack=True,
)
peakxs = array([])
peakys = array([])
peakx2 = array([])
peakx3 = array([])
secondexciton = array([])
thirdexciton = array([])
halfwidths = array([])
hw1 = array([])
hw2 = array([])
hw3 = array([])
a[1:] *= transpose([volfix])
a[1:] -= transpose([a[1:, 0]])
#
figure()
for i in a[1:]:
(x, y) = UVVistools.findpeak(a[0], i, (410, 425))
wguess = 200
Aguess = 0.4
guess = [
Aguess,
x,
wguess,
Aguess,
x - 38,
wguess,
Aguess,
x - 68,
wguess,
1,
304,
wguess,
-0.001,
0,
] # -1e-3,0]#1e-10,1e-8,
guess = [Aguess, Aguess, 1, 10, x, x - 38, x - 68, 320, wguess, wguess, wguess, 5000]
xfit = a[0][350:500]
yfit = i[350:500]
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
fitres = fitspectrum(RamanSpectrum(pandas.Series(yfit, xfit)), (333, 450), "xGaussianNoBase", guess)
peakys = np.append(peakys, fitres.params[0][3]) # -i[z])
peakxs = np.append(peakxs, fitres.params[0][7])
peakx2 = np.append(peakx2, fitres.params[0][6])
peakx3 = np.append(peakx3, fitres.params[0][5])
halfwidths = np.append(halfwidths, fitres.areas[3]) # UVVistools.HWHM((a[0],i),(410,425),_plot=False))
hw1 = np.append(hw1, sqrt(fitres.params[0][11]))
hw2 = np.append(hw2, sqrt(fitres.params[0][10]))
hw3 = np.append(hw3, sqrt(fitres.params[0][9]))
secondexciton = np.append(secondexciton, fitres.areas[2])
thirdexciton = np.append(thirdexciton, fitres.areas[1])
plot(a[0], i, "--y")
plot(fitres.x, fitres.peaks[3] + fitres.peaks[0], "k")
plot(fitres.x, fitres.peaks[2] + fitres.peaks[0], "r")
plot(fitres.x, fitres.peaks[1] + fitres.peaks[0], "b")
for x in [3, 27, 39]:
halfwidths[x:] /= halfwidths[x]
secondexciton[x:] /= secondexciton[x]
thirdexciton[x:] /= thirdexciton[x]
fig = figure()
ax1 = fig.add_subplot(141)
ax2 = fig.add_subplot(142)
ax3 = fig.add_subplot(143)
ax4 = fig.add_subplot(144)
ax1.plot(pHs)
ax2.plot(peakxs, "o-")
ax2.plot(peakx2, "o-")
ax2.plot(peakx3, "o-")
ax3.plot(halfwidths, "o-")
ax3.plot(secondexciton, "o-")
ax3.plot(thirdexciton, "o-")
ax4.plot(hw1, "o-")
ax4.plot(hw2, "o-")
ax4.plot(hw2, "o-")
ax1.set_ylabel("pH")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("noramlized peak areas")
ax4.set_ylabel("HWHM")
fig = figure()
ax2 = fig.add_subplot(131)
ax3 = fig.add_subplot(132)
ax4 = fig.add_subplot(133)
ax2.plot(pHs, peakxs, "o-")
ax2.plot(pHs, peakx2, "o-")
ax2.plot(pHs, peakx3, "o-")
ax3.plot(pHs, halfwidths / halfwidths[0], "o-")
ax3.plot(pHs, secondexciton / secondexciton[0], "o-")
ax3.plot(pHs, thirdexciton / thirdexciton[0], "o-")
ax4.plot(pHs, hw1, "o-")
ax4.plot(pHs, hw2, "o-")
ax4.plot(pHs, hw3, "o-")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("normalized peak area")
ax4.set_ylabel("peak hwhm")
ax4.legend(["first", "second", "third"])
figure()
plot(pHs, peakxs, "o-")
return 0
def March9titration():
"""pH Titration of CdS dots PPA capped. Samples kept in the dark during the experiment"""
b = loadtxt("160309/160309_TitrationAdditionsAndpHs.csv", delimiter=",", skiprows=1, unpack=True)
pHs = b[0]
volumes = b[1]
volumes[8:] -= 0.002
volfix = volumes / np.roll(volumes, 1)
volfix[0] = 1
volfix[8] = 1.003
print volfix
a = loadtxt(
"160309/160309titration.csv",
delimiter=",",
skiprows=2,
usecols=(2,) + tuple(range(3, 3 + 2 * len(pHs), 2)),
unpack=True,
)
peakxs = array([])
peakys = array([])
secondexciton = array([])
thirdexciton = array([])
halfwidths = array([])
a[1:] *= transpose([volfix])
a[1:] -= transpose([a[1:, 0]])
figure()
for i in a[1:]:
(x, y) = UVVistools.findpeak(a[0], i, (410, 425))
peakxs = np.append(peakxs, x)
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
peakys = np.append(peakys, y - i[z])
secondexciton = np.append(secondexciton, i[z + 38])
thirdexciton = np.append(thirdexciton, i[z + 68])
halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0], i), (410, 425), _plot=False))
plot(a[0], i)
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax1.plot(pHs)
ax2.plot(peakxs, "o-")
ax3.plot(peakys, "o-")
ax3.plot(secondexciton, "o-")
ax3.plot(thirdexciton, "o-")
ax4.plot(halfwidths, "o-")
ax1.set_ylabel("pH")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax1.plot(pHs, peakys * halfwidths)
ax2.plot(pHs, peakxs, "o-")
ax3.plot(pHs, peakys, "o-")
ax3.plot(pHs, secondexciton, "o-")
ax3.plot(pHs, thirdexciton, "o-")
ax4.plot(pHs, halfwidths, "o-")
figure()
plot(pHs, peakxs, "o-")
plot(pHs[-10:], peakxs[-10:], "ro-")
ax1.set_ylabel("first exicton areas (relative)")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
figure()
for i in a[4:16:1]:
d = UVVistools.findpeak(a[0], i, (410, 425))[0]
plot(a[0] - d, i)
figure()
KOHmol = b[8]
plot(halfwidths, peakxs)
return 0
def March7_etching():
"""Time dependent etching of PPA capped QDs from immediately after the PPA exchange. March 7"""
a = loadtxt(
"160307/160307_CdSPPA-Stability.csv",
delimiter=",",
skiprows=2,
usecols=(0,) + tuple(range(3, 79, 2)),
unpack=True,
)
times = array([0, 30, 60, 90, 120, 180, 240, 300, 345, 405])
peakxs = array([])
peakys = array([])
halfwidths = array([])
a[1:] -= transpose([a[1:, 0]])
b = a[
array(
[
0,
1,
5,
7,
11,
15,
19,
23,
27,
31,
35, ### dark N2
1,
4,
8,
12,
16,
20,
24,
28,
32,
36, ### dark air
1,
6,
9,
13,
17,
21,
25,
29,
33,
37, ### light air
# 2,3,10,14,18,22,26,30,34, ### Cd-added
1,
5,
7,
11,
15,
19,
26,
30,
34,
38,
]
)
] ### light N2]
figure()
for i in b[1:]:
(x, y) = UVVistools.findpeak(a[0], i, (390, 418))
peakxs = np.append(peakxs, x)
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
peakys = np.append(peakys, y - i[z])
halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0], i), (390, 418), _plot=False))
plot(a[0], i)
peakys = peakys.reshape((4, -1))
peakxs = peakxs.reshape((4, -1))
halfwidths = halfwidths.reshape((4, -1))
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
#
for i in range(3):
ax1.plot(times, peakys[i] * halfwidths[i])
ax2.plot(times, peakxs[i], "o-")
ax3.plot(times, peakys[i], "o-")
ax4.plot(times, halfwidths[i], "o-")
ax1.plot([0, 60, 120, 165, 225], peakys[3, 5:] * halfwidths[3, 5:])
ax2.plot([0, 60, 120, 165, 225], peakxs[3, 5:], "o-")
ax3.plot([0, 60, 120, 165, 225], peakys[3, 5:], "o-")
ax4.plot([0, 60, 120, 165, 225], halfwidths[3, 5:], "o-")
#
ax1.set_ylabel("first exicton areas (relative)")
ax1.legend(["dark N2", "dark air", "light air", "light N2"])
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
figure()
for i in b[31:]:
d = UVVistools.findpeak(a[0], i, (401, 418))[0]
plot(a[0] - d, i)
return 0
def March5():
"""Stability of CdS dots PPA capped. """
a = loadtxt(
"160305/160305_stability measurement.csv",
delimiter=",",
skiprows=2,
usecols=(0,) + tuple(range(75, 110, 2)),
unpack=True,
)
b = loadtxt("160305/160305_TitrationAdditionsAndpHs.csv", delimiter=",", skiprows=1, unpack=True)
pHs = b[5]
volumes = b[9]
volumes -= 0.0002
peakxs = array([])
peakys = array([])
halfwidths = array([])
a[1:] *= transpose([volumes / volumes[0]])
a[1:] -= transpose([a[1:, 0]])
figure()
for i in a[1:]:
(x, y) = UVVistools.findpeak(a[0], i, (401, 418))
peakxs = np.append(peakxs, x)
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
peakys = np.append(peakys, y - i[z])
halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0], i), (401, 418), _plot=False))
plot(a[0], i)
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax1.plot(pHs)
ax2.plot(peakxs, "o-")
ax3.plot(peakys, "o-")
ax4.plot(halfwidths, "o-")
ax1.set_ylabel("pH")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax1.plot(pHs, peakys * halfwidths)
ax2.plot(pHs, peakxs, "o-")
ax3.plot(pHs, peakys, "o-")
ax4.plot(pHs, halfwidths, "o-")
ax1.set_ylabel("first exicton areas (relative)")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
figure()
for i in a[29:48:2]:
plot(a[0], i)
return 0
def March4():
"""Titration of CdS dots PPA capped. Using PPA as acid. Second attempt"""
a = loadtxt(
"160304/160304_PPACdSTitrationAll.csv",
delimiter=",",
skiprows=2,
usecols=(0,) + tuple(range(3, 106, 2)),
unpack=True,
)
b = loadtxt("160304/160304_TitrationAdditionsAndpHs.csv", delimiter=",", skiprows=1, unpack=True)
pHs = b[5]
volumes = b[9]
peakxs = array([])
peakys = array([])
halfwidths = array([])
a[1:] *= transpose([volumes / volumes[0]])
a[1:] -= transpose([a[1:, 0]])
figure()
for i in a[1:]:
# plot(a[0],i)
# (x,y) = UVVistools.findpeak(a[0],i,(401,418))
# peakxs = np.append(peakxs,x)
# peakys = np.append(peakys,y-i[345])
# halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0],i),(401,418),_plot=True))
(x, y) = UVVistools.findpeak(a[0], i, (401, 418))
peakxs = np.append(peakxs, x)
z = argmin(abs(x + 50 - a[0]))
i -= i[z]
peakys = np.append(peakys, y - i[z])
halfwidths = np.append(halfwidths, UVVistools.HWHM((a[0], i), (401, 418), _plot=False))
plot(a[0], i)
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax1.plot(pHs)
ax2.plot(peakxs, "o-")
ax3.plot(peakys, "o-")
ax4.plot(halfwidths, "o-")
ax1.set_ylabel("pH")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
fig = figure()
ax1 = fig.add_subplot(411)
ax2 = fig.add_subplot(412)
ax3 = fig.add_subplot(413)
ax4 = fig.add_subplot(414)
ax1.plot(pHs, peakys * halfwidths)
ax2.plot(pHs, peakxs, "o-")
ax3.plot(pHs, peakys, "o-")
ax4.plot(pHs, halfwidths, "o-")
ax1.set_ylabel("first exicton areas (relative)")
ax2.set_ylabel("peak center (nm)")
ax3.set_ylabel("peak absorbance")
ax4.set_ylabel("HWHM")
figure()
for i in a[29:48:2]:
d = UVVistools.findpeak(a[0], i, (401, 418))[0]
plot(a[0] - d, i)
return 0
