def spinning(): ## test of optical damage decreased by spinning
os.chdir('/home/chris/Documents/DataWeiss/150209')
figure()
a = ['1_sample not moving.SPE',
'2_sample not moving.SPE',
'3_sample not moving 5 min irradiation.SPE',
'4_sample not moving 5 min irradiation.SPE',
'5_spinning.SPE',
'6_spinning.SPE',
'7_spinning 2 min.SPE',
'8_spinning 3 min.SPE',
'9_spinning 4 min.SPE',
'10_spinning 5 min.SPE',
'11_spinning 10 min.SPE', '12_stopped spinning 0 min.SPE', '13_ 1min later.SPE', '14_ 2min later.SPE', '15_ 3min later.SPE', '16_ 4min later.SPE', '17_long scan.SPE', '18_red dots.SPE', '19.SPE']
areas = list()
for i in a[0:17]:
r = RamanSpectrum(i)
print r.name
areas.append(r.calc_area((180,220)))
plot([0,0.5,5,5.5],areas[0:4]/areas[0],'s-')
plot([0,1,2,3,4,5,10],areas[4:11]/areas[4],'s-')
plot([0,1,2,3,4],areas[11:16]/areas[11],'s-')
legend(['not spun','while spinning','stopped spinning'])
return areas
def N2(): ## test of optical damage decreased by spinning
os.chdir('/home/chris/Documents/DataWeiss/150210')
figure()
print os.listdir('.')
a = [ '1_under N2 0 min.SPE', '1_under N2 1 min.SPE', '3_under N2 2 min.SPE',
'4_under N2 3 min.SPE', '5_under N2 4 min.SPE', '6_under N2 5 min.SPE',
'7_under N2 6 min.SPE', '8_under N2 7 min.SPE', '9_under N2 8min.SPE',
'10_under N2 9min.SPE', '11_under N2 10min.SPE', '12_ spinning under N2 0 min.SPE',
'13_ spinning under N2 1min.SPE', '14_ spinning under N2 2min.SPE', '15_ spinning under N2 3min.SPE',
'16_ spinning under N2 4min.SPE', '17_ spinning under N2 5min.SPE',
'18_ spinning under N2 6min.SPE', '19_ spinning under N2 7min.SPE',
'20_ spinning under N2 8min.SPE', '21_ spinning under N2 9min.SPE',
'22 spinning under N2 10min.SPE', '23_after dark time.SPE',
'24_after dark time 1min.SPE', '25_ spinning in air 0 min.SPE',
'26_ spinning in air 1 min.SPE', '27_ spinning in air 2 min.SPE',
'28_ spinning in air3 min.SPE', '29_ spinning in air 4min.SPE',
'30_ spinning in air 5min.SPE', '31_ spinning in air 6 min.SPE',
'32_ spinning in air 7 min.SPE', '33_ spinning in air 8 min.SPE',
'34_ spinning in air 9 min.SPE','34_ spinning in air 10min.SPE',
'35_after 10 min dark.SPE', '36_after 10 min dark plus 1min.SPE',
'37.SPE', '38_ 30 SEC.SPE', '39_ 60s.SPE',
'40_90 s.SPE', '41_120s.SPE', '42_150s.SPE']
areas = list()
for i in a:
r = RamanSpectrum(i)
areas.append(r.calc_area((180,220)))
N2only = areas[0:11]
N2spin = areas[11:24]
airspin = areas[24:37]
airstill = areas[37:]
N2only/=N2only[0]
N2spin/=N2spin[0]
airspin/=airspin[0]
airstill/=airstill[0]
plot(N2only,'s-')
plot([0,1,2,3,4,5,6,7,8,9,10,20,21],N2spin,'s-')
plot([0,1,2,3,4,5,6,7,8,9,10,20,21],airspin,'s-')
plot(arange(0,3,0.5),airstill,'s-')
fill_between((10,20),(0,0),(1,1),color = 'y')
annotate('dark', (15,0.4),horizontalalignment = 'center', fontsize=24)
legend(['n2 only','n2 + spinning','air + spinning','air only'])
xlabel('Time (min)')
ylabel('Phonon Mode Intensity (a.u.)')
return areas
def processxymap():
os.chdir('/home/chris/Documents/DataWeiss/150114')
averagespectrum = RamanSpectrum('10_maybemap_1.txt')
phononarea = array([])
fluorescenceat1600=array([])
fullspectrum = ndarray((1000,))
for f in os.listdir('.'):
if '10_maybemap' in f:
if 'SPE' in f:
continue
elif f == 'maybemap_1.txt':
continue
elif f == 'maybemap.txt':
continue
else:
r = RamanSpectrum(f)
phononarea = append(phononarea,r.calc_area((200,230)))
fluorescenceat1600 = append(fluorescenceat1600,r.values[-1]-min(r.values))
averagespectrum+=r
averagespectrum = _smooth(averagespectrum)
figure()
subplot(221)
hist(fluorescenceat1600,bins=range(0,200,20))
hist(phononarea,bins=range(0,200,20),color='r')
xticks(range(0,200,20))
subplot(223)
averagespectrum.plot()
return phononarea
def March1():
fluorfilelist = ["160301/160301fluor/160301_01.txt", "160301/160301fluor/160301_02.txt"] ### PPA capped ### oleate
filenames = array(
[
"1pH5",
"2pH5",
"3pH5",
"4pH5",
"1pH7",
"2pH7",
"3pH7",
"4pH7",
"1pH8",
"2pH8",
"3pH8",
"4pH8",
"1pH9",
"2pH9",
"3pH5",
"4pH9",
"1pH11",
"2pH11",
"3pH11",
"4pH11",
]
)
uvvis = loadtxt("160301/160301.csv", delimiter=",", unpack=True, skiprows=1, usecols=(0, 5, 6, 8))
uvvis[1:] -= transpose([uvvis[1:, 0]])
x448nm = np.where(uvvis[0] == 448)[0][0]
x473nm = np.where(uvvis[0] == 473)[0][0]
print x473nm
uvvis[3] -= uvvis[3, x448nm]
for i in uvvis[1:]:
plot(uvvis[0], i)
figure()
absorbances_dots = uvvis[1:3, x473nm]
plot(absorbances_dots)
figure()
absorbance_anth = uvvis[-1, x473nm]
fluorescencedots = array([])
nliq = 1.333
nE = 1.359
s = RamanSpectrum("160301/160301fluor/160301_03.txt")
indy = 10 ** 7 / (10 ** 7 / 473 - s.index)
rhodB = RamanSpectrum(pandas.Series(s.values, indy))
rhodBarea = rhodB.calc_area((500, 700))
rhodB *= 0.65 * (1 - 10 ** (-absorbance_anth)) * nE ** 2 / nE ** 2 / rhodBarea / (1 - 10 ** (-absorbance_anth))
print rhodB.calc_area((500, 700))
# rhodB.plot()
## PPA capped dots
s = RamanSpectrum(fluorfilelist[0])
indy = 10 ** 7 / (10 ** 7 / 473 - s.index)
s = RamanSpectrum(pandas.Series(s.values, indy))
s *= 0.65 * (1 - 10 ** (-absorbance_anth)) * nliq ** 2 / nE ** 2 / rhodBarea / (1 - 10 ** (-absorbances_dots[0]))
s.plot()
print "PPA capped CdSe dots QY:", s.calc_area((490, 650))
#### oleate dots
s = RamanSpectrum(fluorfilelist[1])
indy = 10 ** 7 / (10 ** 7 / 473 - s.index)
s = RamanSpectrum(pandas.Series(s.values, indy))
s *= 0.65 * (1 - 10 ** (-absorbance_anth)) * 1.375 ** 2 / nE ** 2 / rhodBarea / (1 - 10 ** (-absorbances_dots[1]))
s.plot()
print "oleate capped CdSe dots QY:", s.calc_area((490, 650))
return 0
def MBTSeries():
"""methylbenzenethiol exchanged CdSe quantum dots on June12"""
clf()
ax1 = gca()
chdefarea=array([])
thiolarea=array([])
native= RamanSpectrum('/home/chris/Dropbox/DataWeiss/150612/150612_01_CdSe.txt') ###### Native ligand only
native[:]/=2
#native=removespikes(native)
native.autobaseline((911,1196,1385,1515,1800),join='start',specialoption='points',order=7)
native.autobaseline((600,690,826,861,911),specialoption='points', order = 5,join='end')
eightyfour= RamanSpectrum('/home/chris/Dropbox/DataWeiss/150623/150623_7.txt') ###### 84 eq
eightyfour[:]/=2
#eightyfour=removespikes(eightyfour)
eightyfour.autobaseline((764,838),order = 0,join='start')
eightyfour.autobaseline((838,2000),order = 1,join='start')
eightyfour.autobaseline((600,690,826,861,900,1196,1385,1515,1657),specialoption='points',order=7)
# eightyfour.smooth()
sixhundredforty= RamanSpectrum('/home/chris/Dropbox/DataWeiss/150617/150617_01.txt') ###### 640 eq MBT
#sixhundredforty=removespikes(sixhundredforty)
sixhundredforty.autobaseline((803,861),order=1, join='start')
sixhundredforty.autobaseline((861,1254),order = 2, join='start')
sixhundredforty.autobaseline((1254,1515),order = 4, join = 'start')
sixhundredforty.autobaseline((1515,2000),order = 3, join = 'start')
sixhundredforty.autobaseline((555,613,764,1141,1321,1565,1652),specialoption='points',order=6)
#sixhundredforty.smooth()
thirtytwo=RamanSpectrum('/home/chris/Dropbox/DataWeiss/150623/150623_10.txt') ###### 32 equivalents
#thirtytwo=removespikes(thirtytwo)
thirtytwo.autobaseline((300,862),order = 1,join='start')
thirtytwo.autobaseline((786,862),order = 0,join='start')
thirtytwo.autobaseline((862,1425),order = 2,join='start')
thirtytwo.autobaseline((1425,1439),order = 1,join='start')
thirtytwo.autobaseline((1439,2000),order = 2,join='start')
x = RamanSpectrum('/home/chris/Dropbox/DataWeiss/150623/150623_12.txt')
#x= removespikes(x)
x.autobaseline((740,1441),order = 1)
thirtytwo=add_RamanSpectra(thirtytwo,x)
thirtytwo.autobaseline((740,764,1052,1141,1321,1425,1441),specialoption='points',order=2)
# thirtytwo.smooth()
oneseventynine=RamanSpectrum('/home/chris/Dropbox/DataWeiss/150623/150623_16.txt') ###### 179 equivalents
# oneseventynine=removespikes(oneseventynine)
oneseventynine.autobaseline((300,793),order = 1,join='start')
oneseventynine.autobaseline((793,862),order = 1,join='start')
oneseventynine.autobaseline((862,1460),order = 1,join='start')
oneseventynine.autobaseline((1460,1486),order = 1,join='start')
oneseventynine.autobaseline((1486,2000),order = 1,join='start')
oneseventynine.autobaseline((740,764,1052,1141,1321,1425,1441,1700),specialoption='points',order=2)
#oneseventynine.smooth()
mbt = CdMethylTPRef.copy()
mbt[:]/=10
lw = 2
thirtytwo[:]+=200
eightyfour[:]+=700
oneseventynine[:]+=1000
sixhundredforty[:]+=1550
mbt[:]+=1950
chtwistarea=array([native.calc_area((1285,1332)),thirtytwo.calc_area((1285,1332)),eightyfour.calc_area((1285,1332)),oneseventynine.calc_area((1285,1332)),sixhundredforty.calc_area((1285,1332)),mbt.calc_area((1285,1332))])
chdefarea=array([native.calc_area((1413,1475)),thirtytwo.calc_area((1413,1475)),eightyfour.calc_area((1413,1475)),oneseventynine.calc_area((1413,1475)),sixhundredforty.calc_area((1413,1475)),mbt.calc_area((1413,1475))])
thiolarea1=array([native.calc_area((1587,1611)),thirtytwo.calc_area((1587,1611)),eightyfour.calc_area((1587,1611)),oneseventynine.calc_area((1587,1611)),sixhundredforty.calc_area((1587,1611)),mbt.calc_area((1587,1611))])
fits1 = list()
fits2 = list()
a = [thirtytwo, eightyfour, oneseventynine, sixhundredforty, mbt]
a.reverse()
for i in a:
i.plot(linewidth=lw,axes=ax1)
native.plot(linewidth = lw,axes=ax1)
ax1.set_ylabel('Intensity (a.u.)')
ax1.set_xlabel('Raman shift (cm$^{-1}$')
legend(['solid', '640eq','179', '84eq','32eq','0'])
ax1.set_xlim(500,1800)
ax1.set_ylim(0,10000)
ax2 = figure().add_subplot(111)
for i in [thirtytwo, eightyfour, oneseventynine, sixhundredforty]:
guess = [100,500,500,1065,1080,1085,7, 7,7,0,i[1100]]
r = fitspectrum(i,(1050,1105), 'xGaussian', guess)
for p in r.peaks:
ax1.plot(r.x, p,'k', linewidth = 2)
fits1.append(r.areas[1]/r.areas[2])
ax2.plot([32,84,179,640],fits1,'rs-', label='1')
return None
def indivQY(
UVVisfile,
UVViscolumn,
anthracenecolumn,
fluorescencefile,
anthracenefluorescencefile,
subtractfluorfile=None,
UVVisplot=None,
fluorplot=None,
fluorescencerange=(410, 473),
excitationwavelength=350,
nliq=1.333,
day=0,
label=None,
color="k",
_plot_standard=False,
subtract_smooth_background_for_anthracene=False,
):
print "-------------------------------------"
print "calculating fluorescence yield for", label, "file", fluorescencefile
alphabet = "abcdefghijklmnopqrstuvwxyz"
if len(UVViscolumn) == 1:
numuvviscolumn = alphabet.find(UVViscolumn)
elif len(UVViscolumn) == 2:
numuvviscolumn = alphabet.find(UVViscolumn[0]) * 26 + alphabet.find(UVViscolumn[1])
a = loadtxt(
UVVisfile, delimiter=",", unpack=True, skiprows=1, usecols=(0, numuvviscolumn, alphabet.find(anthracenecolumn))
)
a[1:] -= transpose([a[1:, 0]])
anthracene = RamanSpectrum(pandas.Series(a[2][::-1], a[0][::-1]))
dot = RamanSpectrum(pandas.Series(a[1][::-1], a[0][::-1]))
if subtract_smooth_background_for_anthracene:
anthracene.smoothbaseline((290, 300), (390, 400))
anthracene[:] -= anthracene[389]
anthraceneabsorbance350 = anthracene[excitationwavelength]
absvalues = dot[excitationwavelength]
nE = 1.359
nQ = 1.44
nW = 1.333 ## refractive index water
a = loadtxt(anthracenefluorescencefile, delimiter="\t", unpack=True, skiprows=2, usecols=(0, 3))
a[1] -= a[1, -1]
anthracenefluorescence = RamanSpectrum(pandas.Series(a[1], a[0]))
###Normalizing to value of anthracene at 420 nm The area for the anthracene fluorescence is related to this value by 78.203
# anthracenefluorescencearea = anthracenefluorescence[420]*78.2032212661
# anthracenefluorescencearea = anthracenefluorescence[440]*292.86
anthracenefluorescencearea = anthracenefluorescence[470] * 1257
print "anthracene fluorescence area=", "%.2E" % anthracenefluorescencearea
print anthracenefluorescence.calc_area((355, 550)) / anthracenefluorescence[
470
], "ratio of total anthracene fluorescence area to value at 470"
oneminusTdot = 1 - 10 ** (-absvalues) ##### gives the fraction of photons absorbed by dots
oneminusT_anthracene350 = 1 - 10 ** (-anthraceneabsorbance350)
print "anthracene absorbance at 350 nm:", anthraceneabsorbance350, ". Fraction photons absorbed:", oneminusT_anthracene350
print "dot absorbance at 350 nm:", absvalues, ". Fraction photons absorbed:", oneminusTdot
a = loadtxt(fluorescencefile, delimiter="\t", unpack=True, skiprows=2, usecols=(0, 3))
hi = RamanSpectrum(pandas.Series(a[1], a[0]))
if subtractfluorfile != None:
b = loadtxt(subtractfluorfile, delimiter="\t", unpack=True, skiprows=1, usecols=(0, 3))
fluorbackground = RamanSpectrum(pandas.Series(b[1], b[0]))
hi[:] -= fluorbackground[:]
fluorbackground.plot(ax=fluorplot)
hi.plot(ax=fluorplot)
hi[:] -= min(hi[400:500])
hi[:] *= (
0.27
/ (1 + 0.00145 * 158)
* oneminusT_anthracene350
* nliq ** 2
/ nE ** 2
/ anthracenefluorescencearea
/ oneminusTdot
)
dotfluorescencearea = hi.calc_area(fluorescencerange, fill=False)
## quantum yield of dots using 0.27 as QY for anthracene with o2 quenching corrrection
print "fluorescence (bande edg) yield of dot", dotfluorescencearea
if UVVisplot is not None:
if _plot_standard:
anthracene.plot(ax=UVVisplot) # plot(a[0],anthracene)
dot.plot(ax=UVVisplot, label=label)
if fluorplot is not None:
hi.plot(ax=fluorplot, label=label)
if _plot_standard:
anthracenefluorescence.plot(ax=fluorplot, label=label)
return dotfluorescencearea
def indivCdSeQY(
UVVisfile,
UVViscolumn,
rhodaminecolumn,
fluorescencefile,
rhodaminefluorescencefile,
excitationwavelength=None,
standardfluorescencerange=None,
baselineabsorbanceat=None,
UVVisplot=None,
fluorplot=None,
fluorescencerange=(500, 600),
nliq=1.333,
day=0,
label=None,
color="k",
):
print "-------------------------------------"
print "calculating fluorescence yield for", label, "file", fluorescencefile
alphabet = "abcdefghijklmnopqrstuvwxyz"
if len(UVViscolumn) == 1:
numuvviscolumn = alphabet.find(UVViscolumn)
elif len(UVViscolumn) == 2:
# print 'longer',alphabet.find(UVViscolumn[0]),alphabet.find(UVViscolumn[1])
numuvviscolumn = (alphabet.find(UVViscolumn[0]) + 1) * 26 + alphabet.find(UVViscolumn[1])
a = loadtxt(
UVVisfile, delimiter=",", unpack=True, skiprows=1, usecols=(0, numuvviscolumn, alphabet.find(rhodaminecolumn))
)
a[1:] -= transpose([a[1:, 0]])
rhodamine = RamanSpectrum(pandas.Series(a[2][::-1], a[0][::-1]))
dot = RamanSpectrum(pandas.Series(a[1][::-1], a[0][::-1]))
if baselineabsorbanceat != None:
dot -= dot[baselineabsorbanceat]
rhodamine[:] -= rhodamine[700]
rhodamineabsorbance350 = rhodamine[excitationwavelength] # (rhodamine[374]-anthracene[389])*0.6735#
absvalues = dot[excitationwavelength]
nE = 1.359
nQ = 1.44
nW = 1.333 ## refractive index water
a = loadtxt(rhodaminefluorescencefile, delimiter="\t", unpack=True, skiprows=1, usecols=(0, 3))
a[1] -= a[1, -1]
standardfluorescence = RamanSpectrum(pandas.Series(a[1], a[0]))
###Normalizing to area of rhodamine B
# pdb.set_trace()
standardfluorescencearea = standardfluorescence.calc_area(standardfluorescencerange)
print "standard fluorescence area=", "%.2E" % standardfluorescencearea
oneminusTdot = 1 - 10 ** (-absvalues) ##### gives the fraction of photons absorbed by dots
oneminusT_rhodamine350 = 1 - 10 ** (
-rhodamineabsorbance350
) ##### gives the fraction of photons absorbed by standard
print "rhodamine absorbance at", excitationwavelength, "nm:", rhodamineabsorbance350, ". Fraction photons absorbed:", oneminusT_rhodamine350
print "dot absorbance at ", excitationwavelength, " nm:", absvalues, ". Fraction photons absorbed:", oneminusTdot
a = loadtxt(fluorescencefile, delimiter="\t", unpack=True, skiprows=1, usecols=(0, 3))
hi = RamanSpectrum(pandas.Series(a[1], a[0]))
hi[:] -= min(hi)
hi[:] *= 0.65 * oneminusT_rhodamine350 * nliq ** 2 / nE ** 2 / standardfluorescencearea / oneminusTdot
dotfluorescencearea = hi.calc_area(fluorescencerange, fill=False)
print "fluorescence (bande edge) yield of dot", dotfluorescencearea
if UVVisplot is not None:
# rhodamine.plot(ax=UVVisplot))
dot.plot(ax=UVVisplot, label=label)
if fluorplot is not None:
hi.plot(ax=fluorplot, label=label)
# standardfluorescence.plot(ax = fluorplot,label=label)
return dotfluorescencearea