def plot_peak_intensities(self, title=None):
plot = iPlot.Plot()
plot.line(self.delays / PRE.p, self.peak_intensities)
plot.show(xlabel='Delay (ps)',
ylabel='Peak Intensity (a.u.)',
title=title,
grid=True)
return self
def plotRaw(wavelengths, rawIntensities, title=None, name=None):
plot = iPlot.Plot()
plot.line(wavelengths, rawIntensities, format_='k')
plot.show(xlabel='Wavelength (nm)',
ylabel='Intensity (a.u.)',
grid=True,
title=title,
name=name)
def plotPopulation(js, populations, title=None, name=None):
plot = iPlot.Plot()
plot.bar(js, populations, width=0.8)
plot.show(xlabel='J State',
ylabel='Population (a.u.)',
grid=True,
title=title,
name=name)
def plot_peak_wavelengths(self, title=None):
plot = iPlot.Plot()
plot.line(self.delays / PRE.p,
self.peak_wavelengths / PRE.n,
format_='o-')
plot.show(xlabel='Delay (ps)',
ylabel='Peak Wavelength (nm)',
title=title)
return self
def fwhmVsVerticalPosition(data):
x, y = [], []
for info in data.values():
if info.fiberConfig == '1' and info.fpDistance == 0:
x.append(info.verticalPosition)
y.append(info.fwhm)
print(info)
p2 = iPlot.Plot()
p2.line(x[::-1], y, format_='.', markerSize=8)
p2.show(xlabel='Vertical Position', ylabel='FWHM (THz)', grid=True)
def depthVsVerticalPosition(data):
x, y = [], []
for info in data.values():
if info.fiberConfig == '1' and info.fpDistance == 0:
x.append(info.verticalPosition)
y.append(info.depth)
print(info)
plot = iPlot.Plot()
plot.line(x[::-1], y, format_='.', markerSize=8)
plot.show(xlabel='Vertical Position', ylabel='Depth (0-1)', grid=True)
def cmap_raw(self, title=None):
plot = iPlot.Plot()
extent = [
self.delays[0] / PRE.p, self.delays[-1] / PRE.p,
self.wavelengths[0] / PRE.n, self.wavelengths[-1] / PRE.n
]
plot.cmap(self.intensities,
label='Intensity (a.u.)',
extent=extent,
flip=True)
plot.show(xlabel='Delay (ps)', ylabel='Wavelength (nm)', title=title)
return self
def cmap_raw(self):
plot = iPlot.Plot()
extent = [
self.delays[0] / PRE.p, self.delays[-1] / PRE.p,
self.wavelengths[0] / PRE.n, self.wavelengths[-1] / PRE.n
]
plot.cmap(self.intensities_rel,
label='Intensity Difference (a.u.)',
extent=extent,
flip=True)
plot.show(xlabel='Delay (ps)', ylabel='Wavelength (nm)')
return self
def plotArms(frequencies,
intensities,
blueSlice,
redSlice,
title=None,
name=None):
plot = iPlot.Plot()
plot.line(frequencies[redSlice], intensities[redSlice], format_='tab:red')
plot.line(frequencies[blueSlice],
intensities[blueSlice],
format_='tab:blue')
plot.show(xlabel='Centrifuge Frequency (THz)',
ylabel='Intensity (a.u.)',
grid=True,
title=title,
name=name)
def plotRaman(frequencies, intensities, bounds, js, title=None, name=None):
labelPositions = [(a + b) / 2 for a, b in zip(bounds, bounds[1:])]
plot = iPlot.Plot()
plot.line(frequencies, intensities, format_='k')
plot.line(bounds, np.full_like(bounds, 0), format_='|g', markerSize=10)
plot.annotate(js,
labelPositions,
np.zeros_like(js),
offset=(0.6, -9),
rotation=90,
fontSize=6)
plot.show(xlabel='Centrifuge Frequency (THz)',
ylabel='Intensity (a.u.)',
grid=True,
title=title,
name=name)
def fwhmVsFiberCount(data, doFit=True):
x, y = [], []
for info in data.values():
if all([info.fiberConfig.isdigit(), info.fpDistance == 0, info.verticalPosition == 0]):
x.append(int(info.fiberConfig))
y.append(info.fwhm)
print(info)
p = iPlot.Plot()
p.line(x, y, format_='.', markerSize=8)
if doFit:
parameters, errors, chi2 = iProcess.fit(iProcess.Function.line, x, y, np.full((len(x)), 0.01))
print(f'\nχ²: {chi2:.1E}\n'
f'slope: {parameters[0]:.3f} ± {errors[0]:.0E} THz\n'
f'y-intercept: {parameters[1]:.3f} ± {errors[1]:.0E} THz')
xFit = np.array([min(x), max(x)])
p.line(xFit, iProcess.Function.line(xFit, *parameters), format_='--')
p.show(xlabel='Fiber Count', ylabel='FWHM (THz)', legend=['Data', 'Fit'] if doFit else None, grid=True)
def plotCfg(wavelengths,
intensities,
blueSlice,
redSlice,
cfgMetrics,
title=None,
name=None):
plot = iPlot.Plot()
plot.line(wavelengths[redSlice], intensities[redSlice], format_='tab:red')
plot.line(wavelengths[blueSlice],
intensities[blueSlice],
format_='tab:blue')
parameters = cfgMetrics.centerWavelength, 0, 1, cfgMetrics.blueFwhm, 1, cfgMetrics.redFwhm
plot.line(wavelengths,
halfGaussians(wavelengths, *parameters),
format_='--k')
plot.show(xlabel='Wavelength (nm)',
ylabel='Intensity (a.u.)',
grid=True,
title=title,
name=name)
def transitionHwhmVsFpDistance(data, doFit=True):
x, y = [], []
for info in data.values():
if info.fiberConfig.isdigit() and info.verticalPosition == 0:
x.append(info.fpDistance)
y.append(info.transitionHwhm)
print(info)
plot = iPlot.Plot()
plot.line(x, y, format_='.')
if doFit:
def gaussBeam(z, A, zR):
return A * np.sqrt(1 + (z / zR) ** 2)
parameters, errors, chi2 = iProcess.fit(gaussBeam, x, y, np.full((len(x)), 0.01), guess=[0.065, 1])
print(f'\nχ²: {chi2:.1E}\n'
f'A: {parameters[0]:.3f} ± {errors[0]:.0E} THz\n'
f'zR: {parameters[1]:.2f} ± {errors[1]:.0E} mm')
xFit = np.linspace(min(x), max(x), 100)
plot.line(xFit, gaussBeam(xFit, *parameters), format_='--')
plot.show(xlabel='FP Distance (mm)', ylabel='Transition HWHM (THz)', legend=['Data', 'Fit'] if doFit else None, grid=True)
content = file.read()
wavelengths, intensities = [], []
delays = np.arange(0, 201, 2)
for line in content.splitlines():
values = [float(v) for v in line.split('\t')]
wavelengths.append(values.pop(0))
intensities.append(values)
return np.array(intensities), np.array(wavelengths), delays
if __name__ == '__main__':
folder = ASSETS_DIR / '2021-03-20 OCS'
controlNotch = CfgControl(folder / '0.xls')
probeIntensities, wavelengths, delays = extractScan(folder / 'probe.dat')
frequencies = PHYS.c * (1 / PROBE_WAVELENGTH - 1 / wavelengths) / (PRE.n * PRE.T) / 2
extent = [np.min(delays), np.max(delays), np.min(frequencies), np.max(frequencies)]
# controlIntensities = extractScan(folder / f'0.dat')[0] - probeIntensities
for i in range(1, 4):
notch = CfgNotch(folder / f'{i}.xls', control=controlNotch, rescale=True)
print(notch.notchMetrics)
for i in range(4):
intensities, *_ = extractScan(folder / f'{i}.dat')
intensities -= probeIntensities
plot = iPlot.Plot()
plot.cmap(np.log2(np.clip(intensities, 1, 10000)), extent=extent, label='log$_{2}$ (Intensity)', flip=True)
plot.show(xlabel='Delay (ps)', ylabel='Frequency (THz)')